diff --git a/404.html b/404.html
index 998f279e3..3fe0fc86c 100644
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     <a class="navbar-brand me-2" href="https://msberends.github.io/AMR/index.html">AMR (for R)</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9061</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9063</small>
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@@ -47,147 +43,47 @@
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 <li class="nav-item dropdown">
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-    <a class="dropdown-item" href="https://msberends.github.io/AMR/articles/MDR.html">
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-      Determine Multi-Drug Resistance (MDR)
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-    <a class="dropdown-item" href="https://msberends.github.io/AMR/articles/WHONET.html">
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-    <a class="dropdown-item" href="https://msberends.github.io/AMR/articles/EUCAST.html">
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-how-to" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-question-circle"></span> How to</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to">
+<li><a class="dropdown-item" href="https://msberends.github.io/AMR/articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="https://msberends.github.io/AMR/reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="https://msberends.github.io/AMR/articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="https://msberends.github.io/AMR/articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="https://msberends.github.io/AMR/reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="https://msberends.github.io/AMR/articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="https://msberends.github.io/AMR/articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="https://msberends.github.io/AMR/articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="https://msberends.github.io/AMR/articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="https://msberends.github.io/AMR/reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="https://msberends.github.io/AMR/reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="https://msberends.github.io/AMR/reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul>
 </li>
 <li class="nav-item dropdown">
-  <a href="https://msberends.github.io/AMR/#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--with-other-pkgs">
-    <span class="fa fa-layer-group"></span>
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-    With other pkgs
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--with-other-pkgs">
-    <a class="dropdown-item" href="https://msberends.github.io/AMR/articles/other_pkg.html">
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-      AMR &amp; dplyr/tidyverse
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-    <a class="dropdown-item" href="https://msberends.github.io/AMR/articles/other_pkg.html">
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-      AMR &amp; data.table
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-    <a class="dropdown-item" href="https://msberends.github.io/AMR/articles/other_pkg.html">
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-      AMR &amp; tidymodels
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-    <a class="dropdown-item" href="https://msberends.github.io/AMR/articles/other_pkg.html">
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-      AMR &amp; base R
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-  </div>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="https://msberends.github.io/AMR/reference/index.html">
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-  <a class="nav-link" href="https://msberends.github.io/AMR/authors.html">
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs">
+<li><a class="dropdown-item" href="https://msberends.github.io/AMR/articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="https://msberends.github.io/AMR/articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="https://msberends.github.io/AMR/articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="https://msberends.github.io/AMR/articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul>
 </li>
+<li class="nav-item"><a class="nav-link" href="https://msberends.github.io/AMR/reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="https://msberends.github.io/AMR/authors.html"><span class="fa fa-users"></span> Authors</a></li>
       </ul>
-<form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="search.json" id="search-input" placeholder="Search for" autocomplete="off">
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+<li class="nav-item"><a class="nav-link" href="https://msberends.github.io/AMR/news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul>
 </div>
 
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 </nav><div class="container template-title-body">
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@@ -207,9 +103,9 @@ Content not found. Please use links in the navbar.
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-         style="font-variant:normal;font-weight:700;font-stretch:condensed;font-size:19.1091px;font-family:'Helvetica Neue';writing-mode:lr-tb;fill:#2d3f50;fill-opacity:1;fill-rule:nonzero;stroke:none"
-         x="0 10.62466 20.179209 25.835503 30.421688 44.906384 49.492569 58.340084 64.703415 73.875778 83.430328 88.016518 97.207993 101.79417 106.38036 117.00502 125.85253 134.33698 138.92316 147.40759 153.06389 162.25537 171.80992 180.65742 189.50494 194.09113 199.74742 210.37209 224.51282 235.13748 240.79376 245.37996 256.34857 265.54004 271.19635 280.38782 284.26697 294.89163 304.44617 313.63766 318.22385 326.70828 335.19272 339.7789 348.26334 352.84952 357.43573 366.99026 371.57645"
-         y="0"
-         id="tspan1053">Antimicrobial Resistance (AMR) Data Analysis in R</tspan></text><text
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-       transform="matrix(1.3333333,0,0,1.599968,169.0488,74.044933)"><tspan
-         style="font-variant:normal;font-weight:300;font-stretch:normal;font-size:8.3335px;font-family:'Helvetica Neue';writing-mode:lr-tb;fill:#1d1d1b;fill-opacity:1;fill-rule:nonzero;stroke:none"
-         x="0 6.1751237 10.50021 14.9753 19.300386 21.925438 26.250525 28.717241 33.042328 37.050739"
-         y="0"
-         id="tspan1054">Generates </tspan><tspan
-         style="font-variant:normal;font-weight:700;font-stretch:condensed;font-size:8.3335px;font-family:'Helvetica Neue';writing-mode:lr-tb;fill:#1d1d1b;fill-opacity:1;fill-rule:nonzero;stroke:none"
-         x="39.367455 43.375866 47.542618 50.009335 52.009373 56.176125 58.176163 62.176243 66.342995 69.11805 73.126465 79.443253"
-         y="0"
-         id="tspan1055">antibiograms</tspan><tspan
-         style="font-variant:normal;font-weight:300;font-stretch:normal;font-size:8.3335px;font-family:'Helvetica Neue';writing-mode:lr-tb;fill:#1d1d1b;fill-opacity:1;fill-rule:nonzero;stroke:none"
-         x="83.143326 85.460045 89.626793 91.943504 94.410225 97.035271 101.36036 106.14379 107.68549 110.15221 111.6939 116.32732 120.80241 125.1275 126.6692 128.98592 131.30263 135.62772 140.26114 147.20294 151.98637 153.52808 158.00316 162.32825 167.11168 169.42839 171.7451 175.75351 179.61192 184.08702 188.87044 191.34467 195.97809 202.91989 204.46159 208.78668 211.10339 213.4201 217.74519 222.22028 227.00371 229.32042 233.64551 237.50392 241.82901 246.30409 248.6208 256.17929 258.02933 263.27942 269.14621"
-         y="0"
-         id="tspan1056"> – traditional, combined, syndromic, and even WISCA</tspan><tspan
-         style="font-variant:normal;font-weight:300;font-stretch:normal;font-size:8.3335px;font-family:'Helvetica Neue';writing-mode:lr-tb;fill:#1d1d1b;fill-opacity:1;fill-rule:nonzero;stroke:none"
-         x="0 5.2501049 7.7251544 12.358581 16.216991 17.758688 22.542118 26.867205 30.875618 33.192329 35.659046 40.134136 44.459221"
-         y="15.0003"
-         id="tspan1057">Provides the </tspan><tspan
-         style="font-variant:normal;font-weight:700;font-stretch:condensed;font-size:8.3335px;font-family:'Helvetica Neue';writing-mode:lr-tb;fill:#1d1d1b;fill-opacity:1;fill-rule:nonzero;stroke:none"
-         x="46.775936 49.242653 53.409401 55.409443 57.409481 59.409523 65.726311 67.726357 71.584763 74.359818 78.359901 82.526649 84.526688 88.526772 90.52681 94.526894 98.693642 100.69368 104.55209 108.5605 110.56055 112.56059 115.0273 119.03571 122.88579 126.88587 131.05263 135.0527 141.36949"
-         y="15.0003"
-         id="tspan1058">full microbiological taxonomy</tspan><tspan
-         style="font-variant:normal;font-weight:300;font-stretch:normal;font-size:8.3335px;font-family:'Helvetica Neue';writing-mode:lr-tb;fill:#1d1d1b;fill-opacity:1;fill-rule:nonzero;stroke:none"
-         x="145.06956 147.38628 151.71136 156.18646 160.96988 163.28661 168.07002 172.39511 174.86183 179.18692 181.50363 186.13705 190.61215"
-         y="15.0003"
-         id="tspan1059"> and data on </tspan><tspan
-         style="font-variant:normal;font-weight:700;font-stretch:condensed;font-size:8.3335px;font-family:'Helvetica Neue';writing-mode:lr-tb;fill:#1d1d1b;fill-opacity:1;fill-rule:nonzero;stroke:none"
-         x="192.92886 196.93727 198.93732 200.93735 202.93739 206.9458 211.11255 213.57927 215.57932 221.8961 223.89615 227.75456 230.52962 234.52969 238.69644 240.69649 244.7049 246.70494 248.70497 252.87172 255.64677 259.81354 263.98029"
-         y="15.0003"
-         id="tspan1060">all antimicrobial drugs</tspan><tspan
-         style="font-variant:normal;font-weight:300;font-stretch:normal;font-size:8.3335px;font-family:'Helvetica Neue';writing-mode:lr-tb;fill:#1d1d1b;fill-opacity:1;fill-rule:nonzero;stroke:none"
-         x="0 5.2501049 10.033534 14.816963 16.35866 17.900358 22.225445 26.233858 28.550571 32.875656 34.417355 35.959053 38.275764 40.749981 45.075069 49.400154 53.725243 58.200329"
-         y="30.000601"
-         id="tspan1061">Applies all recent</tspan><tspan
-         style="font-variant:normal;font-weight:700;font-stretch:condensed;font-size:8.3335px;font-family:'Helvetica Neue';writing-mode:lr-tb;fill:#1d1d1b;fill-opacity:1;fill-rule:nonzero;stroke:none"
-         x="60.667046 62.667088 67.142174 71.000587 75.325676 77.475716 79.475754 83.484169 87.650917 91.817673 93.817711 97.826126 102.30955 106.78464 111.41806 115.74315 119.74323 121.74327 125.43501 127.43505 129.43509 133.60184 135.60188 139.4603 143.4687 145.46875 147.46878 151.63553 154.41058 158.269 162.2774 166.44417 170.61092 174.61099 176.61104 180.77779 183.24449"
-         y="30.000601"
-         id="tspan1062"> CLSI and EUCAST clinical breakpoints</tspan><tspan
-         style="font-variant:normal;font-weight:300;font-stretch:normal;font-size:8.3335px;font-family:'Helvetica Neue';writing-mode:lr-tb;fill:#1d1d1b;fill-opacity:1;fill-rule:nonzero;stroke:none"
-         x="186.94456 189.26129 191.41966 196.05309 198.67815 200.99486 207.83665 209.68669 215.55348 219.56189 221.8786 226.20369 230.67879 235.4622 237.77892 242.56235 244.10405 248.11246 252.27921 254.59593 258.45435 263.08777 267.56287 271.88794"
-         y="30.000601"
-         id="tspan1063"> for MICs and disk zones</tspan><tspan
-         style="font-variant:normal;font-weight:300;font-stretch:normal;font-size:8.3335px;font-family:'Helvetica Neue';writing-mode:lr-tb;fill:#1d1d1b;fill-opacity:1;fill-rule:nonzero;stroke:none"
-         x="0 5.8667841 10.50021 13.125262 15.600312 19.925398 24.250484 26.717201 30.725615 33.042328 35.200703 39.834129 42.459183 44.775894 49.559326 54.034412 58.817844 60.359539 61.901237 66.226326 70.551414 73.018127 77.343216 79.659927 81.201622 85.210037 89.84346 91.385162 95.710251 98.176964 102.50205 106.51046 108.82718"
-         y="45.0009"
-         id="tspan1064">Corrects for duplicate isolates, </tspan><tspan
-         style="font-variant:normal;font-weight:700;font-stretch:condensed;font-size:8.3335px;font-family:'Helvetica Neue';writing-mode:lr-tb;fill:#1d1d1b;fill-opacity:1;fill-rule:nonzero;stroke:none"
-         x="111.14389 115.0023 119.01071 121.01075 124.86916 129.03592 131.03595 135.04437 137.51108 141.36949 145.06956 147.06961 151.07802 155.24477 159.41151 161.41156 165.57831 168.35336 172.21178 176.37852 178.37857 182.23698 184.70369 188.40376 190.09464 194.72806 200.89485"
-         y="45.0009"
-         id="tspan1065">calculates and predicts AMR</tspan><tspan
-         style="font-variant:normal;font-weight:300;font-stretch:normal;font-size:8.3335px;font-family:'Helvetica Neue';writing-mode:lr-tb;fill:#1d1d1b;fill-opacity:1;fill-rule:nonzero;stroke:none"
-         x="205.52827 207.84499 212.62842 216.95351 219.57855 221.89526 226.22035 230.69545 233.16217 234.70386 239.48729 241.02899 245.66241 248.12914 249.67082 253.99591 256.31262 260.63773 262.17941 266.50449 270.51291"
-         y="45.0009"
-         id="tspan1066"> per antibiotic class</tspan><tspan
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-         y="60.001202"
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-         x="139.4278 141.74451 144.06122 149.31133 153.78641 158.56984 164.43661 168.91171 173.2368 180.1786 182.49532"
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-         x="206.71246 211.03755 215.51265 220.29607"
-         y="60.001202"
-         id="tspan1073">and </tspan><tspan
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-         y="60.001202"
-         id="tspan1074">SNOMED CT</tspan><tspan
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-         y="85.001701"
-         id="tspan1080">, highly suitable for places with </tspan><tspan
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index f0b115396..8af97ca3f 100644
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-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antibiotic Drug
-    </a>
-    <a class="dropdown-item" href="reference/av_property.html">
-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antiviral Drug
-    </a>
-  </div>
-</li>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-how-to" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-question-circle"></span> How to</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to"><li><a class="dropdown-item" href="articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul></li>
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--with-other-pkgs">
-    <span class="fa fa-layer-group"></span>
-     
-    With other pkgs
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--with-other-pkgs">
-    <a class="dropdown-item" href="articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; dplyr/tidyverse
-    </a>
-    <a class="dropdown-item" href="articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; data.table
-    </a>
-    <a class="dropdown-item" href="articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; tidymodels
-    </a>
-    <a class="dropdown-item" href="articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; base R
-    </a>
-  </div>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="reference/index.html">
-    <span class="fa fa-book-open"></span>
-     
-    Manual
-  </a>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="authors.html">
-    <span class="fa fa-users"></span>
-     
-    Authors
-  </a>
-</li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
-  <a class="nav-link" href="news/index.html">
-    <span class="far fa far fa-newspaper"></span>
-     
-    Changelog
-  </a>
-</li>
-<li class="nav-item">
-  <a class="external-link nav-link" href="https://github.com/msberends/AMR">
-    <span class="fab fa fab fa-github"></span>
-     
-    Source Code
-  </a>
-</li>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="authors.html"><span class="fa fa-users"></span> Authors</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-title-body">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="logo.svg" class="logo" alt=""><h1>License</h1>
-      
+
     </div>
 
 <pre>GNU GENERAL PUBLIC LICENSE
@@ -421,9 +315,9 @@ END OF TERMS AND CONDITIONS
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/articles/AMR.html b/articles/AMR.html
index dcf038b53..d952caa9d 100644
--- a/articles/AMR.html
+++ b/articles/AMR.html
@@ -5,7 +5,6 @@
 <meta charset="utf-8">
 <meta http-equiv="X-UA-Compatible" content="IE=edge">
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
-<meta name="description" content="AMR">
 <title>How to conduct AMR data analysis • AMR (for R)</title>
 <!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
 <link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
@@ -17,31 +16,22 @@
 <link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet">
 <script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet">
 <link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet">
-<!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous">
-<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous">
-<!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
+<link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet">
+<link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet">
+<script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
 <script src="../extra.js"></script><meta property="og:title" content="How to conduct AMR data analysis">
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 </head>
 <body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
-    
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary" data-bs-theme="dark"><div class="container">
-    
+
+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9061</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9063</small>
+
 
-    
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
       <span class="navbar-toggler-icon"></span>
     </button>
@@ -49,141 +39,41 @@
     <div id="navbar" class="collapse navbar-collapse ms-3">
       <ul class="navbar-nav me-auto">
 <li class="active nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--how-to">
-    <span class="fa fa-question-circle"></span>
-     
-    How to
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--how-to">
-    <a class="dropdown-item" href="../articles/AMR.html">
-      <span class="fa fa-directions"></span>
-       
-      Conduct AMR Analysis
-    </a>
-    <a class="dropdown-item" href="../reference/antibiogram.html">
-      <span class="fa fa-file-prescription"></span>
-       
-      Generate Antibiogram (Trad./Syndromic/WISCA)
-    </a>
-    <a class="dropdown-item" href="../articles/resistance_predict.html">
-      <span class="fa fa-dice"></span>
-       
-      Predict Antimicrobial Resistance
-    </a>
-    <a class="dropdown-item" href="../articles/datasets.html">
-      <span class="fa fa-database"></span>
-       
-      Download Data Sets for Own Use
-    </a>
-    <a class="dropdown-item" href="../reference/AMR-options.html">
-      <span class="fa fa-gear"></span>
-       
-      Set User- Or Team-specific Package Settings
-    </a>
-    <a class="dropdown-item" href="../articles/PCA.html">
-      <span class="fa fa-compress"></span>
-       
-      Conduct Principal Component Analysis for AMR
-    </a>
-    <a class="dropdown-item" href="../articles/MDR.html">
-      <span class="fa fa-skull-crossbones"></span>
-       
-      Determine Multi-Drug Resistance (MDR)
-    </a>
-    <a class="dropdown-item" href="../articles/WHONET.html">
-      <span class="fa fa-globe-americas"></span>
-       
-      Work with WHONET Data
-    </a>
-    <a class="dropdown-item" href="../articles/EUCAST.html">
-      <span class="fa fa-exchange-alt"></span>
-       
-      Apply Eucast Rules
-    </a>
-    <a class="dropdown-item" href="../reference/mo_property.html">
-      <span class="fa fa-bug"></span>
-       
-      Get Taxonomy of a Microorganism
-    </a>
-    <a class="dropdown-item" href="../reference/ab_property.html">
-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antibiotic Drug
-    </a>
-    <a class="dropdown-item" href="../reference/av_property.html">
-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antiviral Drug
-    </a>
-  </div>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-how-to" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-question-circle"></span> How to</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to">
+<li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul>
 </li>
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--with-other-pkgs">
-    <span class="fa fa-layer-group"></span>
-     
-    With other pkgs
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--with-other-pkgs">
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; dplyr/tidyverse
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; data.table
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; tidymodels
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; base R
-    </a>
-  </div>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../reference/index.html">
-    <span class="fa fa-book-open"></span>
-     
-    Manual
-  </a>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../authors.html">
-    <span class="fa fa-users"></span>
-     
-    Authors
-  </a>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs">
+<li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul>
 </li>
+<li class="nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
       </ul>
-<form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off">
-</form>
-
-      <ul class="navbar-nav">
-<li class="nav-item">
-  <a class="nav-link" href="../news/index.html">
-    <span class="far fa far fa-newspaper"></span>
-     
-    Changelog
-  </a>
-</li>
-<li class="nav-item">
-  <a class="external-link nav-link" href="https://github.com/msberends/AMR">
-    <span class="fab fa fab fa-github"></span>
-     
-    Source Code
-  </a>
-</li>
+<ul class="navbar-nav">
+<li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul>
 </div>
 
-    
+
   </div>
 </nav><div class="container template-article">
 
@@ -195,7 +85,7 @@
       <img src="../logo.svg" class="logo" alt=""><h1>How to conduct AMR data analysis</h1>
             
       
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/AMR.Rmd" class="external-link"><code>vignettes/AMR.Rmd</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/AMR.Rmd" class="external-link"><code>vignettes/AMR.Rmd</code></a></small>
       <div class="d-none name"><code>AMR.Rmd</code></div>
     </div>
 
@@ -205,7 +95,7 @@
 website update since they are based on randomly created values and the
 page was written in <a href="https://rmarkdown.rstudio.com/" class="external-link">R
 Markdown</a>. However, the methodology remains unchanged. This page was
-generated on 23 June 2024.</p>
+generated on 16 July 2024.</p>
 <div class="section level2">
 <h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
 </h2>
@@ -261,21 +151,21 @@ make the structure of your data generally look like this:</p>
 </tr></thead>
 <tbody>
 <tr class="odd">
-<td align="center">2024-06-23</td>
+<td align="center">2024-07-16</td>
 <td align="center">abcd</td>
 <td align="center">Escherichia coli</td>
 <td align="center">S</td>
 <td align="center">S</td>
 </tr>
 <tr class="even">
-<td align="center">2024-06-23</td>
+<td align="center">2024-07-16</td>
 <td align="center">abcd</td>
 <td align="center">Escherichia coli</td>
 <td align="center">S</td>
 <td align="center">R</td>
 </tr>
 <tr class="odd">
-<td align="center">2024-06-23</td>
+<td align="center">2024-07-16</td>
 <td align="center">efgh</td>
 <td align="center">Escherichia coli</td>
 <td align="center">R</td>
@@ -318,9 +208,8 @@ have extracted from their laboratory systems:</p>
 <span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> M3         A        2015-10-25 E. coli       R     S     S     S    </span></span>
 <span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> J3         A        2019-06-19 E. coli       S     S     S     S    </span></span>
 <span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> G6         A        2015-04-27 S. aureus     S     S     S     S    </span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,990 more rows</span></span></span></code></pre></div>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,990 more rows</span></span></span>
+<span></span>
 <span><span class="co"># we will use 'our_data' as the data set name for this tutorial</span></span>
 <span><span class="va">our_data</span> <span class="op">&lt;-</span> <span class="va">example_isolates_unclean</span></span></code></pre></div>
 <p>For AMR data analysis, we would like the microorganism column to
@@ -333,24 +222,21 @@ cleaned as SIR values as well.</p>
 <p>With <code><a href="../reference/as.mo.html">as.mo()</a></code>, users can transform arbitrary
 microorganism names or codes to current taxonomy. The <code>AMR</code>
 package contains up-to-date taxonomic data. To be specific, currently
-included data were retrieved on 11 Dec 2022.</p>
+included data were retrieved on 24 Jun 2024.</p>
 <p>The codes of the AMR packages that come from <code><a href="../reference/as.mo.html">as.mo()</a></code> are
 short, but still human readable. More importantly, <code><a href="../reference/as.mo.html">as.mo()</a></code>
 supports all kinds of input:</p>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"Klebsiella pneumoniae"</span><span class="op">)</span></span>
 <span><span class="co">#&gt; Class 'mo'</span></span>
-<span><span class="co">#&gt; [1] B_KLBSL_PNMN</span></span></code></pre></div>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
+<span><span class="co">#&gt; [1] B_KLBSL_PNMN</span></span>
+<span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
 <span><span class="co">#&gt; Class 'mo'</span></span>
-<span><span class="co">#&gt; [1] B_KLBSL_PNMN</span></span></code></pre></div>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"KLEPNE"</span><span class="op">)</span></span>
+<span><span class="co">#&gt; [1] B_KLBSL_PNMN</span></span>
+<span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"KLEPNE"</span><span class="op">)</span></span>
 <span><span class="co">#&gt; Class 'mo'</span></span>
-<span><span class="co">#&gt; [1] B_KLBSL_PNMN</span></span></code></pre></div>
-<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"KLPN"</span><span class="op">)</span></span>
+<span><span class="co">#&gt; [1] B_KLBSL_PNMN</span></span>
+<span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"KLPN"</span><span class="op">)</span></span>
 <span><span class="co">#&gt; Class 'mo'</span></span>
 <span><span class="co">#&gt; [1] B_KLBSL_PNMN</span></span></code></pre></div>
 <p>The first character in above codes denote their taxonomic kingdom,
@@ -360,58 +246,53 @@ retrieve taxonomic properties, such as the name, genus, species, family,
 order, and even Gram-stain. They all start with <code>mo_</code> and
 they use <code><a href="../reference/as.mo.html">as.mo()</a></code> internally, so that still any arbitrary
 user input can be used:</p>
-<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/mo_property.html">mo_family</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
-<span><span class="co">#&gt; [1] "Enterobacteriaceae"</span></span></code></pre></div>
-<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
-<span><span class="co">#&gt; [1] "Klebsiella"</span></span></code></pre></div>
-<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="../reference/mo_property.html">mo_species</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
-<span><span class="co">#&gt; [1] "pneumoniae"</span></span></code></pre></div>
-<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
+<span><span class="co">#&gt; [1] "Enterobacteriaceae"</span></span>
+<span><span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
+<span><span class="co">#&gt; [1] "Klebsiella"</span></span>
+<span><span class="fu"><a href="../reference/mo_property.html">mo_species</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
+<span><span class="co">#&gt; [1] "pneumoniae"</span></span>
+<span></span>
 <span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="st">"Klebsiella pneumoniae"</span><span class="op">)</span></span>
-<span><span class="co">#&gt; [1] "Gram-negative"</span></span></code></pre></div>
-<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
+<span><span class="co">#&gt; [1] "Gram-negative"</span></span>
+<span></span>
 <span><span class="fu"><a href="../reference/mo_property.html">mo_ref</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
-<span><span class="co">#&gt; [1] "Trevisan, 1887"</span></span></code></pre></div>
-<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
+<span><span class="co">#&gt; [1] "Trevisan, 1887"</span></span>
+<span></span>
 <span><span class="fu"><a href="../reference/mo_property.html">mo_snomed</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
 <span><span class="co">#&gt; [[1]]</span></span>
 <span><span class="co">#&gt; [1] "1098101000112102" "446870005"        "1098201000112108" "409801009"       </span></span>
 <span><span class="co">#&gt; [5] "56415008"         "714315002"        "713926009"</span></span></code></pre></div>
 <p>Now we can thus clean our data:</p>
-<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">our_data</span><span class="op">$</span><span class="va">bacteria</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="va">our_data</span><span class="op">$</span><span class="va">bacteria</span>, info <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span>
 <span><span class="co">#&gt; ℹ Microorganism translation was uncertain for four microorganisms. Run</span></span>
 <span><span class="co">#&gt;   mo_uncertainties() to review these uncertainties, or use</span></span>
 <span><span class="co">#&gt;   add_custom_microorganisms() to add custom entries.</span></span></code></pre></div>
 <p>Apparently, there was some uncertainty about the translation to
 taxonomic codes. Let’s check this:</p>
-<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/as.mo.html">mo_uncertainties</a></span><span class="op">(</span><span class="op">)</span></span>
 <span><span class="co">#&gt; Matching scores are based on the resemblance between the input and the full</span></span>
 <span><span class="co">#&gt; taxonomic name, and the pathogenicity in humans. See ?mo_matching_score.</span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; --------------------------------------------------------------------------------</span></span>
 <span><span class="co">#&gt; "E. coli" -&gt; Escherichia coli (B_ESCHR_COLI, 0.688)</span></span>
-<span><span class="co">#&gt; Also matched: Enterobacter cowanii (0.600), Eubacterium combesii</span></span>
+<span><span class="co">#&gt; Also matched: Escherichia coli coli (0.643), Escherichia coli</span></span>
+<span><span class="co">#&gt;               expressing (0.611), Enterobacter cowanii (0.600), Eubacterium combesii</span></span>
 <span><span class="co">#&gt;               (0.600), Eggerthia catenaformis (0.591), Eubacterium callanderi</span></span>
 <span><span class="co">#&gt;               (0.591), Enterocloster citroniae (0.587), Eubacterium cylindroides</span></span>
-<span><span class="co">#&gt;               (0.583), Enterococcus casseliflavus (0.577), Enterobacter cloacae</span></span>
-<span><span class="co">#&gt;               cloacae (0.571), Enterobacter cloacae complex (0.571), and Ehrlichia</span></span>
-<span><span class="co">#&gt;               canis (0.567)</span></span>
+<span><span class="co">#&gt;               (0.583), Enterococcus casseliflavus (0.577), and Enterobacter cloacae</span></span>
+<span><span class="co">#&gt;               cloacae (0.571)</span></span>
 <span><span class="co">#&gt; --------------------------------------------------------------------------------</span></span>
 <span><span class="co">#&gt; "K. pneumoniae" -&gt; Klebsiella pneumoniae (B_KLBSL_PNMN, 0.786)</span></span>
 <span><span class="co">#&gt; Also matched: Klebsiella pneumoniae ozaenae (0.707), Klebsiella</span></span>
 <span><span class="co">#&gt;               pneumoniae pneumoniae (0.688), Klebsiella pneumoniae rhinoscleromatis</span></span>
 <span><span class="co">#&gt;               (0.658), Klebsiella pasteurii (0.500), Klebsiella planticola (0.500),</span></span>
-<span><span class="co">#&gt;               Kingella potus (0.400), Kosakonia pseudosacchari (0.361), Kaistella</span></span>
-<span><span class="co">#&gt;               palustris (0.333), Kocuria palustris (0.333), and Kocuria pelophila</span></span>
-<span><span class="co">#&gt;               (0.333)</span></span>
+<span><span class="co">#&gt;               Kingella potus (0.400), Kluyveromyces pseudotropicale (0.386),</span></span>
+<span><span class="co">#&gt;               Kluyveromyces pseudotropicalis (0.363), Kosakonia pseudosacchari</span></span>
+<span><span class="co">#&gt;               (0.361), and Kluyveromyces pseudotropicalis pseudotropicalis (0.361)</span></span>
 <span><span class="co">#&gt; --------------------------------------------------------------------------------</span></span>
 <span><span class="co">#&gt; "S. aureus" -&gt; Staphylococcus aureus (B_STPHY_AURS, 0.690)</span></span>
 <span><span class="co">#&gt; Also matched: Staphylococcus aureus aureus (0.643), Staphylococcus</span></span>
@@ -448,7 +329,7 @@ diffusion values, read more about that on the <code><a href="../reference/as.sir
 page.</p>
 <p>For now, we will just clean the SIR columns in our data using
 dplyr:</p>
-<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># method 1, be explicit about the columns:</span></span>
 <span><span class="va">our_data</span> <span class="op">&lt;-</span> <span class="va">our_data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
 <span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_at</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html" class="external-link">vars</a></span><span class="op">(</span><span class="va">AMX</span><span class="op">:</span><span class="va">GEN</span><span class="op">)</span>, <span class="va">as.sir</span><span class="op">)</span></span>
@@ -516,7 +397,7 @@ analysis, but the default phenotype-based method is in any case the
 method to properly correct for most duplicate isolates. Read more about
 the methods on the <code><a href="../reference/first_isolate.html">first_isolate()</a></code> page.</p>
 <p>The outcome of the function can easily be added to our data:</p>
-<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">our_data</span> <span class="op">&lt;-</span> <span class="va">our_data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
 <span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>first <span class="op">=</span> <span class="fu"><a href="../reference/first_isolate.html">first_isolate</a></span><span class="op">(</span>info <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span><span class="op">)</span></span>
 <span><span class="co">#&gt; ℹ Determining first isolates using an episode length of 365 days</span></span>
@@ -530,16 +411,16 @@ the methods on the <code><a href="../reference/first_isolate.html">first_isolate
 <p>So only 90% is suitable for resistance analysis! We can now filter on
 it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter()</a></code> function, also from the
 <code>dplyr</code> package:</p>
-<div class="sourceCode" id="cb18"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">our_data_1st</span> <span class="op">&lt;-</span> <span class="va">our_data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
 <span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">first</span> <span class="op">==</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div>
 <p>For future use, the above two syntaxes can be shortened:</p>
-<div class="sourceCode" id="cb19"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">our_data_1st</span> <span class="op">&lt;-</span> <span class="va">our_data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
 <span>  <span class="fu"><a href="../reference/first_isolate.html">filter_first_isolate</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
 <p>So we end up with 2 712 isolates for analysis. Now our data looks
 like:</p>
-<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">our_data_1st</span></span>
 <span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 2,712 × 9</span></span></span>
 <span><span class="co">#&gt;    patient_id hospital date       bacteria     AMX   AMC   CIP   GEN   first</span></span>
@@ -564,7 +445,7 @@ like:</p>
 <p>The base R <code><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary()</a></code> function gives a good first
 impression, as it comes with support for the new <code>mo</code> and
 <code>sir</code> classes that we now have in our data set:</p>
-<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">our_data_1st</span><span class="op">)</span></span>
 <span><span class="co">#&gt;   patient_id          hospital              date           </span></span>
 <span><span class="co">#&gt;  Length:2712        Length:2712        Min.   :2011-01-01  </span></span>
@@ -586,9 +467,8 @@ impression, as it comes with support for the new <code>mo</code> and
 <span><span class="co">#&gt;  %SDD : 0.0% (n=0)      %SDD : 0.0% (n=0)                    </span></span>
 <span><span class="co">#&gt;  %I   : 6.6% (n=178)    %I   : 3.1% (n=85)                   </span></span>
 <span><span class="co">#&gt;  %R   :42.0% (n=1138)   %R   :37.3% (n=1011)                 </span></span>
-<span><span class="co">#&gt;  %NI  : 0.0% (n=0)      %NI  : 0.0% (n=0)</span></span></code></pre></div>
-<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
+<span><span class="co">#&gt;  %NI  : 0.0% (n=0)      %NI  : 0.0% (n=0)</span></span>
+<span></span>
 <span><span class="fu"><a href="https://pillar.r-lib.org/reference/glimpse.html" class="external-link">glimpse</a></span><span class="op">(</span><span class="va">our_data_1st</span><span class="op">)</span></span>
 <span><span class="co">#&gt; Rows: 2,712</span></span>
 <span><span class="co">#&gt; Columns: 9</span></span>
@@ -600,9 +480,8 @@ impression, as it comes with support for the new <code>mo</code> and
 <span><span class="co">#&gt; $ AMC        <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> I, I, I, S, S, S, S, S, S, S, S, S, I, S, S, S, S, R, S, S,…</span></span>
 <span><span class="co">#&gt; $ CIP        <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> S, S, S, S, R, S, S, S, S, S, S, S, S, S, S, S, S, S, S, S,…</span></span>
 <span><span class="co">#&gt; $ GEN        <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> S, S, S, S, S, S, S, S, S, S, R, S, S, S, S, S, S, S, S, S,…</span></span>
-<span><span class="co">#&gt; $ first      <span style="color: #949494; font-style: italic;">&lt;lgl&gt;</span> TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,…</span></span></code></pre></div>
-<div class="sourceCode" id="cb23"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
+<span><span class="co">#&gt; $ first      <span style="color: #949494; font-style: italic;">&lt;lgl&gt;</span> TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,…</span></span>
+<span></span>
 <span><span class="co"># number of unique values per column:</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">sapply</a></span><span class="op">(</span><span class="va">our_data_1st</span>, <span class="va">n_distinct</span><span class="op">)</span></span>
 <span><span class="co">#&gt; patient_id   hospital       date   bacteria        AMX        AMC        CIP </span></span>
@@ -615,7 +494,7 @@ impression, as it comes with support for the new <code>mo</code> and
 <p>To just get an idea how the species are distributed, create a
 frequency table with <code><a href="../reference/count.html">count()</a></code> based on the name of the
 microorganisms:</p>
-<div class="sourceCode" id="cb24"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">our_data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
 <span>  <span class="fu"><a href="../reference/count.html">count</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">bacteria</span><span class="op">)</span>, sort <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span>
 <span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 4 × 2</span></span></span>
@@ -624,9 +503,8 @@ microorganisms:</p>
 <span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> Escherichia coli          <span style="text-decoration: underline;">1</span>518</span></span>
 <span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> Staphylococcus aureus      730</span></span>
 <span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> Streptococcus pneumoniae   426</span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> Klebsiella pneumoniae      326</span></span></code></pre></div>
-<div class="sourceCode" id="cb25"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> Klebsiella pneumoniae      326</span></span>
+<span></span>
 <span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
 <span>  <span class="fu"><a href="../reference/count.html">count</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">bacteria</span><span class="op">)</span>, sort <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span>
 <span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 4 × 2</span></span></span>
@@ -643,7 +521,7 @@ microorganisms:</p>
 <p>Using so-called antibiotic class selectors, you can select or filter
 columns based on the antibiotic class that your antibiotic results are
 in:</p>
-<div class="sourceCode" id="cb26"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
 <span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">date</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span></span>
 <span><span class="co">#&gt; ℹ For aminoglycosides() using column 'GEN' (gentamicin)</span></span>
@@ -660,9 +538,8 @@ in:</p>
 <span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> 2015-04-27 S    </span></span>
 <span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> 2011-06-21 S    </span></span>
 <span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> 2014-09-05 S    </span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,702 more rows</span></span></span></code></pre></div>
-<div class="sourceCode" id="cb27"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,702 more rows</span></span></span>
+<span></span>
 <span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
 <span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">bacteria</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">betalactams</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span></span>
 <span><span class="co">#&gt; ℹ For betalactams() using columns 'AMX' (amoxicillin) and 'AMC'</span></span>
@@ -680,9 +557,8 @@ in:</p>
 <span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> B_STPHY_AURS S     S    </span></span>
 <span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> B_ESCHR_COLI S     S    </span></span>
 <span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> B_ESCHR_COLI S     S    </span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,702 more rows</span></span></span></code></pre></div>
-<div class="sourceCode" id="cb28"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,702 more rows</span></span></span>
+<span></span>
 <span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
 <span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">bacteria</span>, <span class="fu"><a href="https://tidyselect.r-lib.org/reference/where.html" class="external-link">where</a></span><span class="op">(</span><span class="va">is.sir</span><span class="op">)</span><span class="op">)</span></span>
 <span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 2,712 × 5</span></span></span>
@@ -698,9 +574,8 @@ in:</p>
 <span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> B_STPHY_AURS S     S     S     S    </span></span>
 <span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> B_ESCHR_COLI S     S     S     S    </span></span>
 <span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> B_ESCHR_COLI S     S     S     S    </span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,702 more rows</span></span></span></code></pre></div>
-<div class="sourceCode" id="cb29"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,702 more rows</span></span></span>
+<span></span>
 <span><span class="co"># filtering using AB selectors is also possible:</span></span>
 <span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
 <span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/any.html" class="external-link">any</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span><span class="op">)</span></span>
@@ -718,9 +593,8 @@ in:</p>
 <span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> P5         A        2019-03-09 B_STPHY_AURS S     S     S     R     TRUE </span></span>
 <span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> Q8         A        2019-08-10 B_STPHY_AURS S     S     S     R     TRUE </span></span>
 <span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> K5         A        2013-03-15 B_STRPT_PNMN S     S     S     R     TRUE </span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 1,001 more rows</span></span></span></code></pre></div>
-<div class="sourceCode" id="cb30"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 1,001 more rows</span></span></span>
+<span></span>
 <span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
 <span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/all.html" class="external-link">all</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">betalactams</a></span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span><span class="op">)</span></span>
 <span><span class="co">#&gt; ℹ For betalactams() using columns 'AMX' (amoxicillin) and 'AMC'</span></span>
@@ -738,9 +612,8 @@ in:</p>
 <span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> Q2         A        2019-09-22 B_ESCHR_COLI R     R     S     S     TRUE </span></span>
 <span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> X7         A        2011-03-20 B_ESCHR_COLI R     R     S     R     TRUE </span></span>
 <span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> V1         A        2018-08-07 B_STPHY_AURS R     R     S     S     TRUE </span></span>
-<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 473 more rows</span></span></span></code></pre></div>
-<div class="sourceCode" id="cb31"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 473 more rows</span></span></span>
+<span></span>
 <span><span class="co"># even works in base R (since R 3.0):</span></span>
 <span><span class="va">our_data_1st</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/all.html" class="external-link">all</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">betalactams</a></span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span>, <span class="op">]</span></span>
 <span><span class="co">#&gt; ℹ For betalactams() using columns 'AMX' (amoxicillin) and 'AMC'</span></span>
@@ -793,7 +666,7 @@ failure</li>
 function to create any of the above antibiogram types. For starters,
 this is what the included <code>example_isolates</code> data set looks
 like:</p>
-<div class="sourceCode" id="cb32"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">example_isolates</span></span>
 <span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 2,000 × 46</span></span></span>
 <span><span class="co">#&gt;    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX  </span></span>
@@ -822,7 +695,7 @@ like:</p>
 should be used. The <code>antibiotics</code> argument in the
 <code><a href="../reference/antibiogram.html">antibiogram()</a></code> function supports any (combination) of the
 previously mentioned antibiotic class selectors:</p>
-<div class="sourceCode" id="cb33"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/antibiogram.html">antibiogram</a></span><span class="op">(</span><span class="va">example_isolates</span>,</span>
 <span>            antibiotics <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span>
 <span><span class="co">#&gt; ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB'</span></span>
@@ -949,7 +822,7 @@ Chinese, Czech, Danish, Dutch, Finnish, French, German, Greek, Italian,
 Japanese, Norwegian, Polish, Portuguese, Romanian, Russian, Spanish,
 Swedish, Turkish, or Ukrainian. In this next example, we force the
 language to be Spanish using the <code>language</code> argument:</p>
-<div class="sourceCode" id="cb34"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/antibiogram.html">antibiogram</a></span><span class="op">(</span><span class="va">example_isolates</span>,</span>
 <span>            mo_transform <span class="op">=</span> <span class="st">"gramstain"</span>,</span>
 <span>            antibiotics <span class="op">=</span> <span class="fu"><a href="../reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>,</span>
@@ -995,7 +868,7 @@ language to be Spanish using the <code>language</code> argument:</p>
 </h4>
 <p>To create a combined antibiogram, use antibiotic codes or names with
 a plus <code>+</code> character like this:</p>
-<div class="sourceCode" id="cb35"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb18"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/antibiogram.html">antibiogram</a></span><span class="op">(</span><span class="va">example_isolates</span>,</span>
 <span>            antibiotics <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"TZP"</span>, <span class="st">"TZP+TOB"</span>, <span class="st">"TZP+GEN"</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
 <table class="table">
@@ -1077,7 +950,7 @@ a plus <code>+</code> character like this:</p>
 <p>To create a syndromic antibiogram, the <code>syndromic_group</code>
 argument must be used. This can be any column in the data, or e.g. an
 <code><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse()</a></code> with calculations based on certain columns:</p>
-<div class="sourceCode" id="cb36"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb19"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/antibiogram.html">antibiogram</a></span><span class="op">(</span><span class="va">example_isolates</span>,</span>
 <span>            antibiotics <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span>,</span>
 <span>            syndromic_group <span class="op">=</span> <span class="st">"ward"</span><span class="op">)</span></span>
@@ -1271,7 +1144,7 @@ Antibiogram) in which cases are predefined based on clinical or
 demographic characteristics (e.g., endocarditis in 75+ females). This
 next example is a simplification without clinical characteristics, but
 just gives an idea of how a WISCA can be created:</p>
-<div class="sourceCode" id="cb37"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">wisca</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/antibiogram.html">antibiogram</a></span><span class="op">(</span><span class="va">example_isolates</span>,</span>
 <span>                     antibiotics <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"AMC"</span>, <span class="st">"AMC+CIP"</span>, <span class="st">"TZP"</span>, <span class="st">"TZP+TOB"</span><span class="op">)</span>,</span>
 <span>                     mo_transform <span class="op">=</span> <span class="st">"gramstain"</span>,</span>
@@ -1339,7 +1212,7 @@ just gives an idea of how a WISCA can be created:</p>
 <p>Antibiograms can be plotted using <code><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot()</a></code> from the
 <code>ggplot2</code> packages, since this <code>AMR</code> package
 provides an extension to that function:</p>
-<div class="sourceCode" id="cb38"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span><span class="va">wisca</span><span class="op">)</span></span></code></pre></div>
 <p><img src="AMR_files/figure-html/unnamed-chunk-10-1.png" width="720"></p>
 <p>To calculate antimicrobial resistance in a more sensible way, also by
@@ -1368,12 +1241,12 @@ proportion of R (<code><a href="../reference/proportion.html">proportion_R()</a>
 I (<code><a href="../reference/proportion.html">proportion_SI()</a></code>, equal to
 <code><a href="../reference/proportion.html">susceptibility()</a></code>). These functions can be used on their
 own:</p>
-<div class="sourceCode" id="cb39"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="../reference/proportion.html">resistance</a></span><span class="op">(</span><span class="va">AMX</span><span class="op">)</span></span>
 <span><span class="co">#&gt; [1] 0.4288348</span></span></code></pre></div>
 <p>Or can be used in conjunction with <code><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by()</a></code> and
 <code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise()</a></code>, both from the <code>dplyr</code> package:</p>
-<div class="sourceCode" id="cb40"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb23"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
 <span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
 <span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span>amoxicillin <span class="op">=</span> <span class="fu"><a href="../reference/proportion.html">resistance</a></span><span class="op">(</span><span class="va">AMX</span><span class="op">)</span><span class="op">)</span></span>
@@ -1387,7 +1260,7 @@ own:</p>
 <p><em>Author: Dr. Matthijs Berends, 26th Feb 2023</em></p>
 </div>
 </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside>
 </div>
 
@@ -1404,9 +1277,9 @@ own:</p>
     </footer>
 </div>
 
-  
 
-  
+
+
 
   </body>
 </html>
diff --git a/articles/EUCAST.html b/articles/EUCAST.html
index a91e85c0a..cedc26d85 100644
--- a/articles/EUCAST.html
+++ b/articles/EUCAST.html
@@ -5,7 +5,6 @@
 <meta charset="utf-8">
 <meta http-equiv="X-UA-Compatible" content="IE=edge">
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
-<meta name="description" content="AMR">
 <title>How to apply EUCAST rules • AMR (for R)</title>
 <!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
 <link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
@@ -17,31 +16,22 @@
 <link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet">
 <script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet">
 <link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet">
-<!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous">
-<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous">
-<!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
+<link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet">
+<link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet">
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+
     <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9061</small>
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@@ -49,141 +39,41 @@
     <div id="navbar" class="collapse navbar-collapse ms-3">
       <ul class="navbar-nav me-auto">
 <li class="active nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--how-to">
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-      Generate Antibiogram (Trad./Syndromic/WISCA)
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-      Predict Antimicrobial Resistance
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-how-to" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-question-circle"></span> How to</button>
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+<li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
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+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
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+    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul>
 </li>
 <li class="nav-item dropdown">
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs">
+<li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
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+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul>
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+<li class="nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
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+<ul class="navbar-nav">
+<li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
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       </ul>
 </div>
 
-    
+
   </div>
 </nav><div class="container template-article">
 
@@ -195,7 +85,7 @@
       <img src="../logo.svg" class="logo" alt=""><h1>How to apply EUCAST rules</h1>
             
       
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/EUCAST.Rmd" class="external-link"><code>vignettes/EUCAST.Rmd</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/EUCAST.Rmd" class="external-link"><code>vignettes/EUCAST.Rmd</code></a></small>
       <div class="d-none name"><code>EUCAST.Rmd</code></div>
     </div>
 
@@ -248,9 +138,8 @@ be applied using <code><a href="../reference/eucast_rules.html">eucast_rules()</
 <span><span class="va">oops</span></span>
 <span><span class="co">#&gt;            mo ampicillin</span></span>
 <span><span class="co">#&gt; 1  Klebsiella          S</span></span>
-<span><span class="co">#&gt; 2 Escherichia          S</span></span></code></pre></div>
-<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
+<span><span class="co">#&gt; 2 Escherichia          S</span></span>
+<span></span>
 <span><span class="fu"><a href="../reference/eucast_rules.html">eucast_rules</a></span><span class="op">(</span><span class="va">oops</span>, info <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span>
 <span><span class="co">#&gt;            mo ampicillin</span></span>
 <span><span class="co">#&gt; 1  Klebsiella          R</span></span>
@@ -259,14 +148,13 @@ be applied using <code><a href="../reference/eucast_rules.html">eucast_rules()</
 <code><a href="../reference/mo_property.html">mo_is_intrinsic_resistant()</a></code> that uses the same guideline,
 but allows to check for one or more specific microorganisms or
 antibiotics:</p>
-<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span></span>
 <span>  <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Klebsiella"</span>, <span class="st">"Escherichia"</span><span class="op">)</span>,</span>
 <span>  <span class="st">"ampicillin"</span></span>
 <span><span class="op">)</span></span>
-<span><span class="co">#&gt; [1]  TRUE FALSE</span></span></code></pre></div>
-<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
+<span><span class="co">#&gt; [1]  TRUE FALSE</span></span>
+<span></span>
 <span><span class="fu"><a href="../reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span></span>
 <span>  <span class="st">"Klebsiella"</span>,</span>
 <span>  <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"ampicillin"</span>, <span class="st">"kanamycin"</span><span class="op">)</span></span>
@@ -277,7 +165,7 @@ used for filling in known resistance and susceptibility based on results
 of other antimicrobials drugs. This process is called <em>interpretive
 reading</em>, is basically a form of imputation, and is part of the
 <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function as well:</p>
-<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span></span>
 <span>  mo <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span></span>
 <span>    <span class="st">"Staphylococcus aureus"</span>,</span>
@@ -295,7 +183,7 @@ reading</em>, is basically a form of imputation, and is part of the
 <span>  FOX <span class="op">=</span> <span class="st">"S"</span>, <span class="co"># Cefoxitin</span></span>
 <span>  stringsAsFactors <span class="op">=</span> <span class="cn">FALSE</span></span>
 <span><span class="op">)</span></span></code></pre></div>
-<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">data</span></span></code></pre></div>
 <table class="table">
 <thead><tr class="header">
@@ -361,7 +249,7 @@ reading</em>, is basically a form of imputation, and is part of the
 </tr>
 </tbody>
 </table>
-<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
+<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="../reference/eucast_rules.html">eucast_rules</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
 <table class="table">
 <thead><tr class="header">
@@ -428,7 +316,7 @@ reading</em>, is basically a form of imputation, and is part of the
 </tbody>
 </table>
 </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside>
 </div>
 
@@ -445,9 +333,9 @@ reading</em>, is basically a form of imputation, and is part of the
     </footer>
 </div>
 
-  
 
-  
+
+
 
   </body>
 </html>
diff --git a/articles/MDR.html b/articles/MDR.html
index 0af6ef6d4..cde992d7b 100644
--- a/articles/MDR.html
+++ b/articles/MDR.html
@@ -5,7 +5,6 @@
 <meta charset="utf-8">
 <meta http-equiv="X-UA-Compatible" content="IE=edge">
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
-<meta name="description" content="AMR">
 <title>How to determine multi-drug resistance (MDR) • AMR (for R)</title>
 <!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
 <link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
@@ -17,31 +16,22 @@
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 <script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet">
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-<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous">
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+<link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet">
+<link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet">
+<script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
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-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9061</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9063</small>
+
 
-    
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
       <span class="navbar-toggler-icon"></span>
     </button>
@@ -49,141 +39,41 @@
     <div id="navbar" class="collapse navbar-collapse ms-3">
       <ul class="navbar-nav me-auto">
 <li class="active nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--how-to">
-    <span class="fa fa-question-circle"></span>
-     
-    How to
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--how-to">
-    <a class="dropdown-item" href="../articles/AMR.html">
-      <span class="fa fa-directions"></span>
-       
-      Conduct AMR Analysis
-    </a>
-    <a class="dropdown-item" href="../reference/antibiogram.html">
-      <span class="fa fa-file-prescription"></span>
-       
-      Generate Antibiogram (Trad./Syndromic/WISCA)
-    </a>
-    <a class="dropdown-item" href="../articles/resistance_predict.html">
-      <span class="fa fa-dice"></span>
-       
-      Predict Antimicrobial Resistance
-    </a>
-    <a class="dropdown-item" href="../articles/datasets.html">
-      <span class="fa fa-database"></span>
-       
-      Download Data Sets for Own Use
-    </a>
-    <a class="dropdown-item" href="../reference/AMR-options.html">
-      <span class="fa fa-gear"></span>
-       
-      Set User- Or Team-specific Package Settings
-    </a>
-    <a class="dropdown-item" href="../articles/PCA.html">
-      <span class="fa fa-compress"></span>
-       
-      Conduct Principal Component Analysis for AMR
-    </a>
-    <a class="dropdown-item" href="../articles/MDR.html">
-      <span class="fa fa-skull-crossbones"></span>
-       
-      Determine Multi-Drug Resistance (MDR)
-    </a>
-    <a class="dropdown-item" href="../articles/WHONET.html">
-      <span class="fa fa-globe-americas"></span>
-       
-      Work with WHONET Data
-    </a>
-    <a class="dropdown-item" href="../articles/EUCAST.html">
-      <span class="fa fa-exchange-alt"></span>
-       
-      Apply Eucast Rules
-    </a>
-    <a class="dropdown-item" href="../reference/mo_property.html">
-      <span class="fa fa-bug"></span>
-       
-      Get Taxonomy of a Microorganism
-    </a>
-    <a class="dropdown-item" href="../reference/ab_property.html">
-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antibiotic Drug
-    </a>
-    <a class="dropdown-item" href="../reference/av_property.html">
-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antiviral Drug
-    </a>
-  </div>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-how-to" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-question-circle"></span> How to</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to">
+<li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul>
 </li>
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--with-other-pkgs">
-    <span class="fa fa-layer-group"></span>
-     
-    With other pkgs
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--with-other-pkgs">
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; dplyr/tidyverse
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; data.table
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; tidymodels
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; base R
-    </a>
-  </div>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../reference/index.html">
-    <span class="fa fa-book-open"></span>
-     
-    Manual
-  </a>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../authors.html">
-    <span class="fa fa-users"></span>
-     
-    Authors
-  </a>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs">
+<li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul>
 </li>
+<li class="nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
       </ul>
-<form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off">
-</form>
-
-      <ul class="navbar-nav">
-<li class="nav-item">
-  <a class="nav-link" href="../news/index.html">
-    <span class="far fa far fa-newspaper"></span>
-     
-    Changelog
-  </a>
-</li>
-<li class="nav-item">
-  <a class="external-link nav-link" href="https://github.com/msberends/AMR">
-    <span class="fab fa fab fa-github"></span>
-     
-    Source Code
-  </a>
-</li>
+<ul class="navbar-nav">
+<li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul>
 </div>
 
-    
+
   </div>
 </nav><div class="container template-article">
 
@@ -195,7 +85,7 @@
       <img src="../logo.svg" class="logo" alt=""><h1>How to determine multi-drug resistance (MDR)</h1>
             
       
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/MDR.Rmd" class="external-link"><code>vignettes/MDR.Rmd</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/MDR.Rmd" class="external-link"><code>vignettes/MDR.Rmd</code></a></small>
       <div class="d-none name"><code>MDR.Rmd</code></div>
     </div>
 
@@ -495,7 +385,7 @@ Unique: 5</p>
 </tbody>
 </table>
 </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside>
 </div>
 
@@ -512,9 +402,9 @@ Unique: 5</p>
     </footer>
 </div>
 
-  
 
-  
+
+
 
   </body>
 </html>
diff --git a/articles/PCA.html b/articles/PCA.html
index 46eb80ee6..e4b044782 100644
--- a/articles/PCA.html
+++ b/articles/PCA.html
@@ -5,7 +5,6 @@
 <meta charset="utf-8">
 <meta http-equiv="X-UA-Compatible" content="IE=edge">
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
-<meta name="description" content="AMR">
 <title>How to conduct principal component analysis (PCA) for AMR • AMR (for R)</title>
 <!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
 <link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
@@ -17,31 +16,22 @@
 <link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet">
 <script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet">
 <link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet">
-<!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous">
-<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous">
-<!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
+<link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet">
+<link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet">
+<script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
 <script src="../extra.js"></script><meta property="og:title" content="How to conduct principal component analysis (PCA) for AMR">
-<meta property="og:description" content="AMR">
-<meta property="og:image" content="https://msberends.github.io/AMR/logo.svg">
-<meta name="twitter:card" content="summary_large_image">
-<meta name="twitter:creator" content="@msberends">
-<meta name="twitter:site" content="@msberends">
-<!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
-<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
-<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
-<![endif]-->
 </head>
 <body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
-    
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary" data-bs-theme="dark"><div class="container">
-    
+
+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9061</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9063</small>
+
 
-    
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
       <span class="navbar-toggler-icon"></span>
     </button>
@@ -49,141 +39,41 @@
     <div id="navbar" class="collapse navbar-collapse ms-3">
       <ul class="navbar-nav me-auto">
 <li class="active nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--how-to">
-    <span class="fa fa-question-circle"></span>
-     
-    How to
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--how-to">
-    <a class="dropdown-item" href="../articles/AMR.html">
-      <span class="fa fa-directions"></span>
-       
-      Conduct AMR Analysis
-    </a>
-    <a class="dropdown-item" href="../reference/antibiogram.html">
-      <span class="fa fa-file-prescription"></span>
-       
-      Generate Antibiogram (Trad./Syndromic/WISCA)
-    </a>
-    <a class="dropdown-item" href="../articles/resistance_predict.html">
-      <span class="fa fa-dice"></span>
-       
-      Predict Antimicrobial Resistance
-    </a>
-    <a class="dropdown-item" href="../articles/datasets.html">
-      <span class="fa fa-database"></span>
-       
-      Download Data Sets for Own Use
-    </a>
-    <a class="dropdown-item" href="../reference/AMR-options.html">
-      <span class="fa fa-gear"></span>
-       
-      Set User- Or Team-specific Package Settings
-    </a>
-    <a class="dropdown-item" href="../articles/PCA.html">
-      <span class="fa fa-compress"></span>
-       
-      Conduct Principal Component Analysis for AMR
-    </a>
-    <a class="dropdown-item" href="../articles/MDR.html">
-      <span class="fa fa-skull-crossbones"></span>
-       
-      Determine Multi-Drug Resistance (MDR)
-    </a>
-    <a class="dropdown-item" href="../articles/WHONET.html">
-      <span class="fa fa-globe-americas"></span>
-       
-      Work with WHONET Data
-    </a>
-    <a class="dropdown-item" href="../articles/EUCAST.html">
-      <span class="fa fa-exchange-alt"></span>
-       
-      Apply Eucast Rules
-    </a>
-    <a class="dropdown-item" href="../reference/mo_property.html">
-      <span class="fa fa-bug"></span>
-       
-      Get Taxonomy of a Microorganism
-    </a>
-    <a class="dropdown-item" href="../reference/ab_property.html">
-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antibiotic Drug
-    </a>
-    <a class="dropdown-item" href="../reference/av_property.html">
-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antiviral Drug
-    </a>
-  </div>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-how-to" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-question-circle"></span> How to</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to">
+<li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul>
 </li>
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--with-other-pkgs">
-    <span class="fa fa-layer-group"></span>
-     
-    With other pkgs
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--with-other-pkgs">
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; dplyr/tidyverse
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; data.table
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; tidymodels
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; base R
-    </a>
-  </div>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../reference/index.html">
-    <span class="fa fa-book-open"></span>
-     
-    Manual
-  </a>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../authors.html">
-    <span class="fa fa-users"></span>
-     
-    Authors
-  </a>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs">
+<li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul>
 </li>
+<li class="nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
       </ul>
-<form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off">
-</form>
-
-      <ul class="navbar-nav">
-<li class="nav-item">
-  <a class="nav-link" href="../news/index.html">
-    <span class="far fa far fa-newspaper"></span>
-     
-    Changelog
-  </a>
-</li>
-<li class="nav-item">
-  <a class="external-link nav-link" href="https://github.com/msberends/AMR">
-    <span class="fab fa fab fa-github"></span>
-     
-    Source Code
-  </a>
-</li>
+<ul class="navbar-nav">
+<li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul>
 </div>
 
-    
+
   </div>
 </nav><div class="container template-article">
 
@@ -195,7 +85,7 @@
       <img src="../logo.svg" class="logo" alt=""><h1>How to conduct principal component analysis (PCA) for AMR</h1>
             
       
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/PCA.Rmd" class="external-link"><code>vignettes/PCA.Rmd</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/PCA.Rmd" class="external-link"><code>vignettes/PCA.Rmd</code></a></small>
       <div class="d-none name"><code>PCA.Rmd</code></div>
     </div>
 
@@ -337,7 +227,7 @@ automatically adds the right labels and even groups:</p>
 <span>  <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span>title <span class="op">=</span> <span class="st">"An AMR/PCA biplot!"</span><span class="op">)</span></span></code></pre></div>
 <p><img src="PCA_files/figure-html/unnamed-chunk-7-1.png" width="750"></p>
 </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside>
 </div>
 
@@ -354,9 +244,9 @@ automatically adds the right labels and even groups:</p>
     </footer>
 </div>
 
-  
 
-  
+
+
 
   </body>
 </html>
diff --git a/articles/WHONET.html b/articles/WHONET.html
index d842e2eb2..f43d983db 100644
--- a/articles/WHONET.html
+++ b/articles/WHONET.html
@@ -5,7 +5,6 @@
 <meta charset="utf-8">
 <meta http-equiv="X-UA-Compatible" content="IE=edge">
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
-<meta name="description" content="AMR">
 <title>How to work with WHONET data • AMR (for R)</title>
 <!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
 <link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
@@ -17,31 +16,22 @@
 <link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet">
 <script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet">
 <link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet">
-<!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous">
-<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous">
-<!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
+<link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet">
+<link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet">
+<script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
 <script src="../extra.js"></script><meta property="og:title" content="How to work with WHONET data">
-<meta property="og:description" content="AMR">
-<meta property="og:image" content="https://msberends.github.io/AMR/logo.svg">
-<meta name="twitter:card" content="summary_large_image">
-<meta name="twitter:creator" content="@msberends">
-<meta name="twitter:site" content="@msberends">
-<!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
-<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
-<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
-<![endif]-->
 </head>
 <body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
-    
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary" data-bs-theme="dark"><div class="container">
-    
+
+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9061</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9063</small>
+
 
-    
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
       <span class="navbar-toggler-icon"></span>
     </button>
@@ -49,141 +39,41 @@
     <div id="navbar" class="collapse navbar-collapse ms-3">
       <ul class="navbar-nav me-auto">
 <li class="active nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--how-to">
-    <span class="fa fa-question-circle"></span>
-     
-    How to
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--how-to">
-    <a class="dropdown-item" href="../articles/AMR.html">
-      <span class="fa fa-directions"></span>
-       
-      Conduct AMR Analysis
-    </a>
-    <a class="dropdown-item" href="../reference/antibiogram.html">
-      <span class="fa fa-file-prescription"></span>
-       
-      Generate Antibiogram (Trad./Syndromic/WISCA)
-    </a>
-    <a class="dropdown-item" href="../articles/resistance_predict.html">
-      <span class="fa fa-dice"></span>
-       
-      Predict Antimicrobial Resistance
-    </a>
-    <a class="dropdown-item" href="../articles/datasets.html">
-      <span class="fa fa-database"></span>
-       
-      Download Data Sets for Own Use
-    </a>
-    <a class="dropdown-item" href="../reference/AMR-options.html">
-      <span class="fa fa-gear"></span>
-       
-      Set User- Or Team-specific Package Settings
-    </a>
-    <a class="dropdown-item" href="../articles/PCA.html">
-      <span class="fa fa-compress"></span>
-       
-      Conduct Principal Component Analysis for AMR
-    </a>
-    <a class="dropdown-item" href="../articles/MDR.html">
-      <span class="fa fa-skull-crossbones"></span>
-       
-      Determine Multi-Drug Resistance (MDR)
-    </a>
-    <a class="dropdown-item" href="../articles/WHONET.html">
-      <span class="fa fa-globe-americas"></span>
-       
-      Work with WHONET Data
-    </a>
-    <a class="dropdown-item" href="../articles/EUCAST.html">
-      <span class="fa fa-exchange-alt"></span>
-       
-      Apply Eucast Rules
-    </a>
-    <a class="dropdown-item" href="../reference/mo_property.html">
-      <span class="fa fa-bug"></span>
-       
-      Get Taxonomy of a Microorganism
-    </a>
-    <a class="dropdown-item" href="../reference/ab_property.html">
-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antibiotic Drug
-    </a>
-    <a class="dropdown-item" href="../reference/av_property.html">
-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antiviral Drug
-    </a>
-  </div>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-how-to" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-question-circle"></span> How to</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to">
+<li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul>
 </li>
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--with-other-pkgs">
-    <span class="fa fa-layer-group"></span>
-     
-    With other pkgs
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--with-other-pkgs">
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; dplyr/tidyverse
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; data.table
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; tidymodels
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; base R
-    </a>
-  </div>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../reference/index.html">
-    <span class="fa fa-book-open"></span>
-     
-    Manual
-  </a>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../authors.html">
-    <span class="fa fa-users"></span>
-     
-    Authors
-  </a>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs">
+<li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul>
 </li>
+<li class="nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
       </ul>
-<form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off">
-</form>
-
-      <ul class="navbar-nav">
-<li class="nav-item">
-  <a class="nav-link" href="../news/index.html">
-    <span class="far fa far fa-newspaper"></span>
-     
-    Changelog
-  </a>
-</li>
-<li class="nav-item">
-  <a class="external-link nav-link" href="https://github.com/msberends/AMR">
-    <span class="fab fa fab fa-github"></span>
-     
-    Source Code
-  </a>
-</li>
+<ul class="navbar-nav">
+<li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul>
 </div>
 
-    
+
   </div>
 </nav><div class="container template-article">
 
@@ -195,7 +85,7 @@
       <img src="../logo.svg" class="logo" alt=""><h1>How to work with WHONET data</h1>
             
       
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/WHONET.Rmd" class="external-link"><code>vignettes/WHONET.Rmd</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/WHONET.Rmd" class="external-link"><code>vignettes/WHONET.Rmd</code></a></small>
       <div class="d-none name"><code>WHONET.Rmd</code></div>
     </div>
 
@@ -427,7 +317,7 @@ using the included <code><a href="../reference/ggplot_sir.html">ggplot_sir()</a>
 <span>  <span class="fu"><a href="../reference/ggplot_sir.html">ggplot_sir</a></span><span class="op">(</span>translate_ab <span class="op">=</span> <span class="st">"ab"</span>, facet <span class="op">=</span> <span class="st">"Country"</span>, datalabels <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div>
 <p><img src="WHONET_files/figure-html/unnamed-chunk-7-1.png" width="720"></p>
 </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside>
 </div>
 
@@ -444,9 +334,9 @@ using the included <code><a href="../reference/ggplot_sir.html">ggplot_sir()</a>
     </footer>
 </div>
 
-  
 
-  
+
+
 
   </body>
 </html>
diff --git a/articles/datasets.html b/articles/datasets.html
index 0ce5343fd..f922d4d80 100644
--- a/articles/datasets.html
+++ b/articles/datasets.html
@@ -5,7 +5,6 @@
 <meta charset="utf-8">
 <meta http-equiv="X-UA-Compatible" content="IE=edge">
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
-<meta name="description" content="AMR">
 <title>Data sets for download / own use • AMR (for R)</title>
 <!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
 <link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
@@ -17,31 +16,22 @@
 <link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet">
 <script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet">
 <link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet">
-<!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous">
-<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous">
-<!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
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-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9061</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9063</small>
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+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
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+    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
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+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul>
 </li>
 <li class="nav-item dropdown">
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-    <span class="fa fa-users"></span>
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs">
+<li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul>
 </li>
+<li class="nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
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-<form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off">
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+<ul class="navbar-nav">
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       </ul>
 </div>
 
-    
+
   </div>
 </nav><div class="container template-article">
 
@@ -194,9 +84,9 @@
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Data sets for download / own use</h1>
             
-            <h4 data-toc-skip class="date">23 June 2024</h4>
+            <h4 data-toc-skip class="date">16 July 2024</h4>
       
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/datasets.Rmd" class="external-link"><code>vignettes/datasets.Rmd</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/datasets.Rmd" class="external-link"><code>vignettes/datasets.Rmd</code></a></small>
       <div class="d-none name"><code>datasets.Rmd</code></div>
     </div>
 
@@ -215,43 +105,44 @@ of the data sets look like.</p>
 <h2 id="microorganisms-full-microbial-taxonomy">
 <code>microorganisms</code>: Full Microbial Taxonomy<a class="anchor" aria-label="anchor" href="#microorganisms-full-microbial-taxonomy"></a>
 </h2>
-<p>A data set with 52 171 rows and 23 columns, containing the following
+<p>A data set with 70 547 rows and 26 columns, containing the following
 column names:<br><em>mo</em>, <em>fullname</em>, <em>status</em>, <em>kingdom</em>,
 <em>phylum</em>, <em>class</em>, <em>order</em>, <em>family</em>,
 <em>genus</em>, <em>species</em>, <em>subspecies</em>, <em>rank</em>,
 <em>ref</em>, <em>oxygen_tolerance</em>, <em>source</em>, <em>lpsn</em>,
-<em>lpsn_parent</em>, <em>lpsn_renamed_to</em>, <em>gbif</em>,
+<em>lpsn_parent</em>, <em>lpsn_renamed_to</em>, <em>mycobank</em>,
+<em>mycobank_parent</em>, <em>mycobank_renamed_to</em>, <em>gbif</em>,
 <em>gbif_parent</em>, <em>gbif_renamed_to</em>, <em>prevalence</em>, and
 <em>snomed</em>.</p>
 <p>This data set is in R available as <code>microorganisms</code>, after
 you load the <code>AMR</code> package.</p>
-<p>It was last updated on 14 July 2023 08:49:06 UTC. Find more info
+<p>It was last updated on 16 July 2024 12:51:57 UTC. Find more info
 about the structure of this data set <a href="https://msberends.github.io/AMR/reference/microorganisms.html">here</a>.</p>
 <p><strong>Direct download links:</strong></p>
 <ul>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.rds" class="external-link">original
-R Data Structure (RDS) file</a> (1.2 MB)<br>
+R Data Structure (RDS) file</a> (1.6 MB)<br>
 </li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.txt" class="external-link">tab-separated
-text file</a> (11.7 MB)<br>
+text file</a> (15.9 MB)<br>
 </li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.xlsx" class="external-link">Microsoft
-Excel workbook</a> (5.2 MB)<br>
+Excel workbook</a> (7.8 MB)<br>
 </li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.feather" class="external-link">Apache
-Feather file</a> (5.5 MB)<br>
+Feather file</a> (19 MB)<br>
 </li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.parquet" class="external-link">Apache
-Parquet file</a> (2.6 MB)<br>
+Parquet file</a> (0 kB)<br>
 </li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.xpt" class="external-link">SAS
-transport (XPT) file</a> (48.6 MB)<br>
+transport (XPT) file</a> (69.5 MB)<br>
 </li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.sav" class="external-link">IBM
-SPSS Statistics data file</a> (17.8 MB)<br>
+SPSS Statistics data file</a> (24.5 MB)<br>
 </li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.dta" class="external-link">Stata
-DTA file</a> (48.6 MB)</li>
+DTA file</a> (69.5 MB)</li>
 </ul>
 <p><strong>NOTE: The exported files for SAS, SPSS and Stata contain only
 the first 50 SNOMED codes per record, as their file size would otherwise
@@ -263,16 +154,16 @@ all SNOMED codes as comma separated values.</p>
 <div class="section level3">
 <h3 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a>
 </h3>
-<p>This data set contains the full microbial taxonomy of five kingdoms
+<p>This data set contains the full microbial taxonomy of six kingdoms
 from the List of Prokaryotic names with Standing in Nomenclature (LPSN)
 and the Global Biodiversity Information Facility (GBIF):</p>
 <ul>
 <li>Parte, AC <em>et al.</em> (2020). <strong>List of Prokaryotic names
 with Standing in Nomenclature (LPSN) moves to the DSMZ.</strong>
 International Journal of Systematic and Evolutionary Microbiology, 70,
-5607-5612; . Accessed from <a href="https://lpsn.dsmz.de" class="external-link uri">https://lpsn.dsmz.de</a> on December 11th, 2022.</li>
+5607-5612; . Accessed from <a href="https://lpsn.dsmz.de" class="external-link uri">https://lpsn.dsmz.de</a> on June 24th, 2024.</li>
 <li>GBIF Secretariat (2023). GBIF Backbone Taxonomy. Checklist dataset .
-Accessed from <a href="https://www.gbif.org" class="external-link uri">https://www.gbif.org</a> on January 8th, 2024.</li>
+Accessed from <a href="https://www.gbif.org" class="external-link uri">https://www.gbif.org</a> on June 24th, 2024.</li>
 <li>Public Health Information Network Vocabulary Access and Distribution
 System (PHIN VADS). US Edition of SNOMED CT from 1 September 2020. Value
 Set Name ‘Microorganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: <a href="https://phinvads.cdc.gov" class="external-link uri">https://phinvads.cdc.gov</a>
@@ -295,52 +186,55 @@ Set Name ‘Microorganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: <a hre
 </tr>
 <tr class="even">
 <td align="center">Animalia</td>
-<td align="center">1 379</td>
+<td align="center">1 713</td>
 </tr>
 <tr class="odd">
 <td align="center">Archaea</td>
-<td align="center">1 314</td>
+<td align="center">1 418</td>
 </tr>
 <tr class="even">
 <td align="center">Bacteria</td>
-<td align="center">36 501</td>
+<td align="center">39 238</td>
 </tr>
 <tr class="odd">
-<td align="center">Fungi</td>
-<td align="center">7 905</td>
+<td align="center">Chromista</td>
+<td align="center">164</td>
 </tr>
 <tr class="even">
-<td align="center">Protozoa</td>
-<td align="center">5 071</td>
+<td align="center">Fungi</td>
+<td align="center">19 878</td>
 </tr>
 </tbody>
 </table>
 <p>Example rows when filtering on genus <em>Escherichia</em>:</p>
-<table class="table">
+<table style="width:100%;" class="table">
 <colgroup>
-<col width="3%">
-<col width="7%">
-<col width="2%">
-<col width="2%">
 <col width="4%">
-<col width="5%">
-<col width="4%">
-<col width="5%">
-<col width="3%">
-<col width="4%">
-<col width="3%">
-<col width="2%">
 <col width="6%">
-<col width="7%">
 <col width="2%">
 <col width="2%">
 <col width="3%">
 <col width="4%">
+<col width="4%">
+<col width="4%">
+<col width="2%">
+<col width="3%">
+<col width="2%">
+<col width="2%">
+<col width="5%">
+<col width="6%">
+<col width="1%">
+<col width="1%">
+<col width="2%">
+<col width="3%">
 <col width="2%">
 <col width="3%">
 <col width="4%">
+<col width="2%">
+<col width="2%">
 <col width="3%">
-<col width="11%">
+<col width="2%">
+<col width="10%">
 </colgroup>
 <thead><tr class="header">
 <th align="center">mo</th>
@@ -361,6 +255,9 @@ Set Name ‘Microorganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: <a hre
 <th align="center">lpsn</th>
 <th align="center">lpsn_parent</th>
 <th align="center">lpsn_renamed_to</th>
+<th align="center">mycobank</th>
+<th align="center">mycobank_parent</th>
+<th align="center">mycobank_renamed_to</th>
 <th align="center">gbif</th>
 <th align="center">gbif_parent</th>
 <th align="center">gbif_renamed_to</th>
@@ -387,7 +284,10 @@ Set Name ‘Microorganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: <a hre
 <td align="center">515602</td>
 <td align="center">482</td>
 <td align="center"></td>
-<td align="center">3221780</td>
+<td align="center"></td>
+<td align="center"></td>
+<td align="center"></td>
+<td align="center"></td>
 <td align="center">11158430</td>
 <td align="center"></td>
 <td align="center">1.0</td>
@@ -407,7 +307,7 @@ Set Name ‘Microorganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: <a hre
 <td align="center"></td>
 <td align="center">species</td>
 <td align="center">Leclerc, 1962</td>
-<td align="center">aerobe</td>
+<td align="center">likely facultative anaerobe</td>
 <td align="center">LPSN</td>
 <td align="center">776052</td>
 <td align="center">515602</td>
@@ -415,6 +315,9 @@ Set Name ‘Microorganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: <a hre
 <td align="center"></td>
 <td align="center"></td>
 <td align="center"></td>
+<td align="center"></td>
+<td align="center"></td>
+<td align="center"></td>
 <td align="center">1.0</td>
 <td align="center"></td>
 </tr>
@@ -432,13 +335,16 @@ Set Name ‘Microorganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: <a hre
 <td align="center"></td>
 <td align="center">species</td>
 <td align="center">Huys et al., 2003</td>
-<td align="center">aerobe</td>
+<td align="center">facultative anaerobe</td>
 <td align="center">LPSN</td>
 <td align="center">776053</td>
 <td align="center">515602</td>
 <td align="center"></td>
+<td align="center"></td>
+<td align="center"></td>
+<td align="center"></td>
 <td align="center">5427575</td>
-<td align="center">3221780</td>
+<td align="center"></td>
 <td align="center"></td>
 <td align="center">1.0</td>
 <td align="center">419388003</td>
@@ -465,6 +371,9 @@ Set Name ‘Microorganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: <a hre
 <td align="center"></td>
 <td align="center"></td>
 <td align="center"></td>
+<td align="center"></td>
+<td align="center"></td>
+<td align="center"></td>
 <td align="center">1.5</td>
 <td align="center"></td>
 </tr>
@@ -487,15 +396,18 @@ Set Name ‘Microorganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: <a hre
 <td align="center">776057</td>
 <td align="center">515602</td>
 <td align="center"></td>
+<td align="center"></td>
+<td align="center"></td>
+<td align="center"></td>
 <td align="center">11286021</td>
-<td align="center">3221780</td>
+<td align="center"></td>
 <td align="center"></td>
 <td align="center">1.0</td>
 <td align="center">1095001000112106, 715307006, 737528008, …</td>
 </tr>
 <tr class="even">
-<td align="center">B_ESCHR_DYSN</td>
-<td align="center">Escherichia dysenteriae</td>
+<td align="center">B_ESCHR_COLI_COLI</td>
+<td align="center">Escherichia coli coli</td>
 <td align="center">accepted</td>
 <td align="center">Bacteria</td>
 <td align="center">Pseudomonadota</td>
@@ -503,19 +415,22 @@ Set Name ‘Microorganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: <a hre
 <td align="center">Enterobacterales</td>
 <td align="center">Enterobacteriaceae</td>
 <td align="center">Escherichia</td>
-<td align="center">dysenteriae</td>
+<td align="center">coli</td>
+<td align="center">coli</td>
+<td align="center">subspecies</td>
 <td align="center"></td>
-<td align="center">species</td>
 <td align="center"></td>
-<td align="center">likely facultative anaerobe</td>
 <td align="center">GBIF</td>
 <td align="center"></td>
 <td align="center"></td>
 <td align="center"></td>
-<td align="center">10862979</td>
-<td align="center">3221780</td>
 <td align="center"></td>
-<td align="center">1.5</td>
+<td align="center"></td>
+<td align="center"></td>
+<td align="center">12233256</td>
+<td align="center"></td>
+<td align="center"></td>
+<td align="center">1.0</td>
 <td align="center"></td>
 </tr>
 </tbody>
@@ -912,7 +827,7 @@ column names:<br><em>guideline</em>, <em>type</em>, <em>host</em>, <em>method</e
 <em>breakpoint_R</em>, <em>uti</em>, and <em>is_SDD</em>.</p>
 <p>This data set is in R available as <code>clinical_breakpoints</code>,
 after you load the <code>AMR</code> package.</p>
-<p>It was last updated on 19 June 2024 13:08:23 UTC. Find more info
+<p>It was last updated on 16 July 2024 12:51:57 UTC. Find more info
 about the structure of this data set <a href="https://msberends.github.io/AMR/reference/clinical_breakpoints.html">here</a>.</p>
 <p><strong>Direct download links:</strong></p>
 <ul>
@@ -923,7 +838,7 @@ R Data Structure (RDS) file</a> (70 kB)<br>
 text file</a> (3.1 MB)<br>
 </li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/clinical_breakpoints.xlsx" class="external-link">Microsoft
-Excel workbook</a> (1.7 MB)<br>
+Excel workbook</a> (2 MB)<br>
 </li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/clinical_breakpoints.feather" class="external-link">Apache
 Feather file</a> (4.9 MB)<br>
@@ -1125,37 +1040,37 @@ use.</p>
 <code>intrinsic_resistant</code>: Intrinsic Bacterial
 Resistance<a class="anchor" aria-label="anchor" href="#intrinsic_resistant-intrinsic-bacterial-resistance"></a>
 </h2>
-<p>A data set with 134 634 rows and 2 columns, containing the following
+<p>A data set with 340 804 rows and 2 columns, containing the following
 column names:<br><em>mo</em> and <em>ab</em>.</p>
 <p>This data set is in R available as <code>intrinsic_resistant</code>,
 after you load the <code>AMR</code> package.</p>
-<p>It was last updated on 16 December 2022 15:10:43 UTC. Find more info
+<p>It was last updated on 16 July 2024 12:51:57 UTC. Find more info
 about the structure of this data set <a href="https://msberends.github.io/AMR/reference/intrinsic_resistant.html">here</a>.</p>
 <p><strong>Direct download links:</strong></p>
 <ul>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.rds" class="external-link">original
-R Data Structure (RDS) file</a> (78 kB)<br>
+R Data Structure (RDS) file</a> (0.1 MB)<br>
 </li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.txt" class="external-link">tab-separated
-text file</a> (5.1 MB)<br>
+text file</a> (12.4 MB)<br>
 </li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.xlsx" class="external-link">Microsoft
-Excel workbook</a> (1.3 MB)<br>
+Excel workbook</a> (3.4 MB)<br>
 </li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.feather" class="external-link">Apache
-Feather file</a> (1.2 MB)<br>
+Feather file</a> (13.1 MB)<br>
 </li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.parquet" class="external-link">Apache
-Parquet file</a> (0.2 MB)<br>
+Parquet file</a> (0 kB)<br>
 </li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.xpt" class="external-link">SAS
-transport (XPT) file</a> (9.5 MB)<br>
+transport (XPT) file</a> (28.3 MB)<br>
 </li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.sav" class="external-link">IBM
-SPSS Statistics data file</a> (7.4 MB)<br>
+SPSS Statistics data file</a> (18.4 MB)<br>
 </li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.dta" class="external-link">Stata
-DTA file</a> (9.5 MB)</li>
+DTA file</a> (28.3 MB)</li>
 </ul>
 <div class="section level3">
 <h3 id="source-4">Source<a class="anchor" aria-label="anchor" href="#source-4"></a>
@@ -2188,7 +2103,7 @@ which are used in the <code>clinical_breakpoints</code> data set.</p>
 column names:<br><em>code</em> and <em>mo</em>.</p>
 <p>This data set is in R available as <code>microorganisms.codes</code>,
 after you load the <code>AMR</code> package.</p>
-<p>It was last updated on 16 June 2024 09:28:56 UTC. Find more info
+<p>It was last updated on 16 July 2024 12:51:57 UTC. Find more info
 about the structure of this data set <a href="https://msberends.github.io/AMR/reference/microorganisms.codes.html">here</a>.</p>
 <p><strong>Direct download links:</strong></p>
 <ul>
@@ -2199,7 +2114,7 @@ R Data Structure (RDS) file</a> (22 kB)<br>
 text file</a> (0.1 MB)<br>
 </li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.codes.xlsx" class="external-link">Microsoft
-Excel workbook</a> (91 kB)<br>
+Excel workbook</a> (82 kB)<br>
 </li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.codes.feather" class="external-link">Apache
 Feather file</a> (0.1 MB)<br>
@@ -2259,7 +2174,7 @@ laboratory systems and <a href="https://whonet.org" class="external-link">WHONET
 </table>
 </div>
 </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside>
 </div>
 
@@ -2276,9 +2191,9 @@ laboratory systems and <a href="https://whonet.org" class="external-link">WHONET
     </footer>
 </div>
 
-  
 
-  
+
+
 
   </body>
 </html>
diff --git a/articles/index.html b/articles/index.html
index fba7b419a..87951a8a1 100644
--- a/articles/index.html
+++ b/articles/index.html
@@ -1,155 +1,49 @@
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Articles • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Articles"><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"></head><body>
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+  </ul></li>
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--with-other-pkgs">
-    <span class="fa fa-layer-group"></span>
-     
-    With other pkgs
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--with-other-pkgs">
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; dplyr/tidyverse
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; data.table
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; tidymodels
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; base R
-    </a>
-  </div>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../reference/index.html">
-    <span class="fa fa-book-open"></span>
-     
-    Manual
-  </a>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../authors.html">
-    <span class="fa fa-users"></span>
-     
-    Authors
-  </a>
-</li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
-  <a class="nav-link" href="../news/index.html">
-    <span class="far fa far fa-newspaper"></span>
-     
-    Changelog
-  </a>
-</li>
-<li class="nav-item">
-  <a class="external-link nav-link" href="https://github.com/msberends/AMR">
-    <span class="fab fa fab fa-github"></span>
-     
-    Source Code
-  </a>
-</li>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-article-index">
 <div class="row">
@@ -193,9 +87,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/articles/other_pkg.html b/articles/other_pkg.html
index e6c0d6f61..8a60e3f83 100644
--- a/articles/other_pkg.html
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@@ -5,7 +5,6 @@
 <meta charset="utf-8">
 <meta http-equiv="X-UA-Compatible" content="IE=edge">
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
-<meta name="description" content="AMR">
 <title>Using AMR with other packages: AMR &amp; dplyr/tidyverse • AMR (for R)</title>
 <!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
 <link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
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 <link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet">
-<!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous">
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+<link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet">
+<link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet">
+<script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
 <script src="../extra.js"></script><meta property="og:title" content="Using AMR with other packages: AMR &amp; dplyr/tidyverse">
-<meta property="og:description" content="AMR">
-<meta property="og:image" content="https://msberends.github.io/AMR/logo.svg">
-<meta name="twitter:card" content="summary_large_image">
-<meta name="twitter:creator" content="@msberends">
-<meta name="twitter:site" content="@msberends">
-<!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
-<![endif]-->
 </head>
 <body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
-    
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary" data-bs-theme="dark"><div class="container">
-    
+
+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9061</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9063</small>
+
 
-    
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
       <span class="navbar-toggler-icon"></span>
     </button>
@@ -49,141 +39,41 @@
     <div id="navbar" class="collapse navbar-collapse ms-3">
       <ul class="navbar-nav me-auto">
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--how-to">
-    <span class="fa fa-question-circle"></span>
-     
-    How to
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--how-to">
-    <a class="dropdown-item" href="../articles/AMR.html">
-      <span class="fa fa-directions"></span>
-       
-      Conduct AMR Analysis
-    </a>
-    <a class="dropdown-item" href="../reference/antibiogram.html">
-      <span class="fa fa-file-prescription"></span>
-       
-      Generate Antibiogram (Trad./Syndromic/WISCA)
-    </a>
-    <a class="dropdown-item" href="../articles/resistance_predict.html">
-      <span class="fa fa-dice"></span>
-       
-      Predict Antimicrobial Resistance
-    </a>
-    <a class="dropdown-item" href="../articles/datasets.html">
-      <span class="fa fa-database"></span>
-       
-      Download Data Sets for Own Use
-    </a>
-    <a class="dropdown-item" href="../reference/AMR-options.html">
-      <span class="fa fa-gear"></span>
-       
-      Set User- Or Team-specific Package Settings
-    </a>
-    <a class="dropdown-item" href="../articles/PCA.html">
-      <span class="fa fa-compress"></span>
-       
-      Conduct Principal Component Analysis for AMR
-    </a>
-    <a class="dropdown-item" href="../articles/MDR.html">
-      <span class="fa fa-skull-crossbones"></span>
-       
-      Determine Multi-Drug Resistance (MDR)
-    </a>
-    <a class="dropdown-item" href="../articles/WHONET.html">
-      <span class="fa fa-globe-americas"></span>
-       
-      Work with WHONET Data
-    </a>
-    <a class="dropdown-item" href="../articles/EUCAST.html">
-      <span class="fa fa-exchange-alt"></span>
-       
-      Apply Eucast Rules
-    </a>
-    <a class="dropdown-item" href="../reference/mo_property.html">
-      <span class="fa fa-bug"></span>
-       
-      Get Taxonomy of a Microorganism
-    </a>
-    <a class="dropdown-item" href="../reference/ab_property.html">
-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antibiotic Drug
-    </a>
-    <a class="dropdown-item" href="../reference/av_property.html">
-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antiviral Drug
-    </a>
-  </div>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-how-to" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-question-circle"></span> How to</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to">
+<li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul>
 </li>
 <li class="active nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--with-other-pkgs">
-    <span class="fa fa-layer-group"></span>
-     
-    With other pkgs
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--with-other-pkgs">
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; dplyr/tidyverse
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; data.table
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; tidymodels
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; base R
-    </a>
-  </div>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../reference/index.html">
-    <span class="fa fa-book-open"></span>
-     
-    Manual
-  </a>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../authors.html">
-    <span class="fa fa-users"></span>
-     
-    Authors
-  </a>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs">
+<li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul>
 </li>
+<li class="nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
       </ul>
-<form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off">
-</form>
-
-      <ul class="navbar-nav">
-<li class="nav-item">
-  <a class="nav-link" href="../news/index.html">
-    <span class="far fa far fa-newspaper"></span>
-     
-    Changelog
-  </a>
-</li>
-<li class="nav-item">
-  <a class="external-link nav-link" href="https://github.com/msberends/AMR">
-    <span class="fab fa fab fa-github"></span>
-     
-    Source Code
-  </a>
-</li>
+<ul class="navbar-nav">
+<li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul>
 </div>
 
-    
+
   </div>
 </nav><div class="container template-article">
 
@@ -195,7 +85,7 @@
       <img src="../logo.svg" class="logo" alt=""><h1>Using AMR with other packages: AMR &amp; dplyr/tidyverse</h1>
             
       
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/other_pkg.Rmd" class="external-link"><code>vignettes/other_pkg.Rmd</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/other_pkg.Rmd" class="external-link"><code>vignettes/other_pkg.Rmd</code></a></small>
       <div class="d-none name"><code>other_pkg.Rmd</code></div>
     </div>
 
@@ -220,9 +110,9 @@ used to working in <code>dplyr</code> or other tidyverse packages.</p>
     </footer>
 </div>
 
-  
 
-  
+
+
 
   </body>
 </html>
diff --git a/articles/resistance_predict.html b/articles/resistance_predict.html
index b63a91401..d4690cea1 100644
--- a/articles/resistance_predict.html
+++ b/articles/resistance_predict.html
@@ -5,7 +5,6 @@
 <meta charset="utf-8">
 <meta http-equiv="X-UA-Compatible" content="IE=edge">
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
-<meta name="description" content="AMR">
 <title>How to predict antimicrobial resistance • AMR (for R)</title>
 <!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
 <link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
@@ -17,31 +16,22 @@
 <link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet">
 <script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet">
 <link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet">
-<!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous">
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+
     <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9061</small>
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@@ -49,141 +39,41 @@
     <div id="navbar" class="collapse navbar-collapse ms-3">
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 <li class="active nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--how-to">
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-      Generate Antibiogram (Trad./Syndromic/WISCA)
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-      Predict Antimicrobial Resistance
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-      <span class="fa fa-database"></span>
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-      Download Data Sets for Own Use
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-      <span class="fa fa-capsules"></span>
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-      Get Properties of an Antiviral Drug
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-  </div>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-how-to" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-question-circle"></span> How to</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to">
+<li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul>
 </li>
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--with-other-pkgs">
-    <span class="fa fa-layer-group"></span>
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-  <div class="dropdown-menu" aria-labelledby="dropdown--with-other-pkgs">
-    <a class="dropdown-item" href="../articles/other_pkg.html">
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-      AMR &amp; data.table
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-      AMR &amp; tidymodels
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
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-      AMR &amp; base R
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-<li class="nav-item">
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-  <a class="nav-link" href="../authors.html">
-    <span class="fa fa-users"></span>
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs">
+<li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul>
 </li>
+<li class="nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
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-    <span class="fab fa fab fa-github"></span>
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+<ul class="navbar-nav">
+<li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
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       </ul>
 </div>
 
-    
+
   </div>
 </nav><div class="container template-article">
 
@@ -195,7 +85,7 @@
       <img src="../logo.svg" class="logo" alt=""><h1>How to predict antimicrobial resistance</h1>
             
       
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/resistance_predict.Rmd" class="external-link"><code>vignettes/resistance_predict.Rmd</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/resistance_predict.Rmd" class="external-link"><code>vignettes/resistance_predict.Rmd</code></a></small>
       <div class="d-none name"><code>resistance_predict.Rmd</code></div>
     </div>
 
@@ -362,16 +252,15 @@ model might be more appropriate:</p>
 <span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">model</span><span class="op">)</span><span class="op">$</span><span class="va">family</span></span>
 <span><span class="co">#&gt; </span></span>
 <span><span class="co">#&gt; Family: binomial </span></span>
-<span><span class="co">#&gt; Link function: logit</span></span></code></pre></div>
-<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span></span>
+<span><span class="co">#&gt; Link function: logit</span></span>
+<span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">model</span><span class="op">)</span><span class="op">$</span><span class="va">coefficients</span></span>
 <span><span class="co">#&gt;                  Estimate  Std. Error   z value     Pr(&gt;|z|)</span></span>
 <span><span class="co">#&gt; (Intercept) -200.67944891 46.17315349 -4.346237 1.384932e-05</span></span>
 <span><span class="co">#&gt; year           0.09883005  0.02295317  4.305725 1.664395e-05</span></span></code></pre></div>
 </div>
 </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside>
 </div>
 
@@ -388,9 +277,9 @@ model might be more appropriate:</p>
     </footer>
 </div>
 
-  
 
-  
+
+
 
   </body>
 </html>
diff --git a/articles/welcome_to_AMR.html b/articles/welcome_to_AMR.html
index 5106400c6..74e1e4d73 100644
--- a/articles/welcome_to_AMR.html
+++ b/articles/welcome_to_AMR.html
@@ -5,7 +5,6 @@
 <meta charset="utf-8">
 <meta http-equiv="X-UA-Compatible" content="IE=edge">
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
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 <link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
@@ -17,31 +16,22 @@
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 <script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet">
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-<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous">
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+<link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet">
+<link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet">
+<script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
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-    
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary" data-bs-theme="dark"><div class="container">
-    
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+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9061</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9063</small>
+
 
-    
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@@ -49,141 +39,41 @@
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-    How to
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--how-to">
-    <a class="dropdown-item" href="../articles/AMR.html">
-      <span class="fa fa-directions"></span>
-       
-      Conduct AMR Analysis
-    </a>
-    <a class="dropdown-item" href="../reference/antibiogram.html">
-      <span class="fa fa-file-prescription"></span>
-       
-      Generate Antibiogram (Trad./Syndromic/WISCA)
-    </a>
-    <a class="dropdown-item" href="../articles/resistance_predict.html">
-      <span class="fa fa-dice"></span>
-       
-      Predict Antimicrobial Resistance
-    </a>
-    <a class="dropdown-item" href="../articles/datasets.html">
-      <span class="fa fa-database"></span>
-       
-      Download Data Sets for Own Use
-    </a>
-    <a class="dropdown-item" href="../reference/AMR-options.html">
-      <span class="fa fa-gear"></span>
-       
-      Set User- Or Team-specific Package Settings
-    </a>
-    <a class="dropdown-item" href="../articles/PCA.html">
-      <span class="fa fa-compress"></span>
-       
-      Conduct Principal Component Analysis for AMR
-    </a>
-    <a class="dropdown-item" href="../articles/MDR.html">
-      <span class="fa fa-skull-crossbones"></span>
-       
-      Determine Multi-Drug Resistance (MDR)
-    </a>
-    <a class="dropdown-item" href="../articles/WHONET.html">
-      <span class="fa fa-globe-americas"></span>
-       
-      Work with WHONET Data
-    </a>
-    <a class="dropdown-item" href="../articles/EUCAST.html">
-      <span class="fa fa-exchange-alt"></span>
-       
-      Apply Eucast Rules
-    </a>
-    <a class="dropdown-item" href="../reference/mo_property.html">
-      <span class="fa fa-bug"></span>
-       
-      Get Taxonomy of a Microorganism
-    </a>
-    <a class="dropdown-item" href="../reference/ab_property.html">
-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antibiotic Drug
-    </a>
-    <a class="dropdown-item" href="../reference/av_property.html">
-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antiviral Drug
-    </a>
-  </div>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-how-to" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-question-circle"></span> How to</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to">
+<li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul>
 </li>
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--with-other-pkgs">
-    <span class="fa fa-layer-group"></span>
-     
-    With other pkgs
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--with-other-pkgs">
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; dplyr/tidyverse
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; data.table
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; tidymodels
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; base R
-    </a>
-  </div>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../reference/index.html">
-    <span class="fa fa-book-open"></span>
-     
-    Manual
-  </a>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../authors.html">
-    <span class="fa fa-users"></span>
-     
-    Authors
-  </a>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs">
+<li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul>
 </li>
+<li class="nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
       </ul>
-<form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off">
-</form>
-
-      <ul class="navbar-nav">
-<li class="nav-item">
-  <a class="nav-link" href="../news/index.html">
-    <span class="far fa far fa-newspaper"></span>
-     
-    Changelog
-  </a>
-</li>
-<li class="nav-item">
-  <a class="external-link nav-link" href="https://github.com/msberends/AMR">
-    <span class="fab fa fab fa-github"></span>
-     
-    Source Code
-  </a>
-</li>
+<ul class="navbar-nav">
+<li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul>
 </div>
 
-    
+
   </div>
 </nav><div class="container template-article">
 
@@ -195,7 +85,7 @@
       <img src="../logo.svg" class="logo" alt=""><h1>Welcome to the `AMR` package</h1>
             
       
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/welcome_to_AMR.Rmd" class="external-link"><code>vignettes/welcome_to_AMR.Rmd</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/welcome_to_AMR.Rmd" class="external-link"><code>vignettes/welcome_to_AMR.Rmd</code></a></small>
       <div class="d-none name"><code>welcome_to_AMR.Rmd</code></div>
     </div>
 
@@ -222,7 +112,7 @@ this a successful and durable project!</p>
 10.18637/jss.v104.i03</a>) and formed the basis of two PhD theses (<a href="https://doi.org/10.33612/diss.177417131" class="external-link">DOI
 10.33612/diss.177417131</a> and <a href="https://doi.org/10.33612/diss.192486375" class="external-link">DOI
 10.33612/diss.192486375</a>).</p>
-<p>After installing this package, R knows ~52 000 distinct microbial
+<p>After installing this package, R knows ~71 000 distinct microbial
 species and all ~600 antibiotic, antimycotic and antiviral drugs by name
 and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED
 CT), and knows all about valid SIR and MIC values. The integral
@@ -313,9 +203,9 @@ included with the package. </small></p>
     </footer>
 </div>
 
-  
 
-  
+
+
 
   </body>
 </html>
diff --git a/authors.html b/authors.html
index 47158e3da..019a480b8 100644
--- a/authors.html
+++ b/authors.html
@@ -1,155 +1,49 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Authors and Citation • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png"><script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="pkgdown.js"></script><link href="extra.css" rel="stylesheet"><script src="extra.js"></script><meta property="og:title" content="Authors and Citation"><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<![endif]--></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Authors and Citation • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png"><script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><link href="deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="deps/headroom-0.11.0/headroom.min.js"></script><script src="deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="deps/search-1.0.0/fuse.min.js"></script><script src="deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="pkgdown.js"></script><link href="extra.css" rel="stylesheet"><script src="extra.js"></script><meta property="og:title" content="Authors and Citation"><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"></head><body>
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-    
 
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+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="index.html">AMR (for R)</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9061</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9063</small>
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-      <span class="fa fa-directions"></span>
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-      Conduct AMR Analysis
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-    <a class="dropdown-item" href="reference/antibiogram.html">
-      <span class="fa fa-file-prescription"></span>
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-      Generate Antibiogram (Trad./Syndromic/WISCA)
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-    <a class="dropdown-item" href="articles/resistance_predict.html">
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-      Predict Antimicrobial Resistance
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-      Get Properties of an Antibiotic Drug
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-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antiviral Drug
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to"><li><a class="dropdown-item" href="articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul></li>
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-      AMR &amp; tidymodels
-    </a>
-    <a class="dropdown-item" href="articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; base R
-    </a>
-  </div>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="reference/index.html">
-    <span class="fa fa-book-open"></span>
-     
-    Manual
-  </a>
-</li>
-<li class="active nav-item">
-  <a class="nav-link" href="authors.html">
-    <span class="fa fa-users"></span>
-     
-    Authors
-  </a>
-</li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
-  <a class="nav-link" href="news/index.html">
-    <span class="far fa far fa-newspaper"></span>
-     
-    Changelog
-  </a>
-</li>
-<li class="nav-item">
-  <a class="external-link nav-link" href="https://github.com/msberends/AMR">
-    <span class="fab fa fab fa-github"></span>
-     
-    Source Code
-  </a>
-</li>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="active nav-item"><a class="nav-link" href="authors.html"><span class="fa fa-users"></span> Authors</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-citation-authors">
 <div class="row">
@@ -157,9 +51,9 @@
       <img src="logo.svg" class="logo" alt=""><h1>Authors and Citation</h1>
     </div>
 
-    <div class="section level2 citation">
+    <div class="section level2">
       <h2>Authors</h2>
-      
+
       <ul class="list-unstyled"><li>
           <p><strong>Matthijs S. Berends</strong>. Author, maintainer. <a href="https://orcid.org/0000-0001-7620-1800" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
           </p>
@@ -169,7 +63,7 @@
           </p>
         </li>
         <li>
-          <p><strong>Erwin E. A. Hassing</strong>. Author, contributor. 
+          <p><strong>Erwin E. A. Hassing</strong>. Author, contributor.
           </p>
         </li>
         <li>
@@ -181,7 +75,7 @@
           </p>
         </li>
         <li>
-          <p><strong>Judith M. Fonville</strong>. Contributor. 
+          <p><strong>Judith M. Fonville</strong>. Contributor.
           </p>
         </li>
         <li>
@@ -193,7 +87,7 @@
           </p>
         </li>
         <li>
-          <p><strong>Eric H. L. C. M. Hazenberg</strong>. Contributor. 
+          <p><strong>Eric H. L. C. M. Hazenberg</strong>. Contributor.
           </p>
         </li>
         <li>
@@ -209,15 +103,15 @@
           </p>
         </li>
         <li>
-          <p><strong>Bart C. Meijer</strong>. Contributor. 
+          <p><strong>Bart C. Meijer</strong>. Contributor.
           </p>
         </li>
         <li>
-          <p><strong>Dmytro Mykhailenko</strong>. Contributor. 
+          <p><strong>Dmytro Mykhailenko</strong>. Contributor.
           </p>
         </li>
         <li>
-          <p><strong>Anton Mymrikov</strong>. Contributor. 
+          <p><strong>Anton Mymrikov</strong>. Contributor.
           </p>
         </li>
         <li>
@@ -229,11 +123,11 @@
           </p>
         </li>
         <li>
-          <p><strong>Matthew Saab</strong>. Contributor. 
+          <p><strong>Matthew Saab</strong>. Contributor.
           </p>
         </li>
         <li>
-          <p><strong>Jonas Salm</strong>. Contributor. 
+          <p><strong>Jonas Salm</strong>. Contributor.
           </p>
         </li>
         <li>
@@ -241,7 +135,7 @@
           </p>
         </li>
         <li>
-          <p><strong>Rogier P. Schade</strong>. Contributor. 
+          <p><strong>Rogier P. Schade</strong>. Contributor.
           </p>
         </li>
         <li>
@@ -262,14 +156,14 @@
         </li>
       </ul></div>
 
-    <div class="section level2 citation">
+    <div class="section level2">
       <h2 id="citation">Citation</h2>
-      <p><small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/inst/CITATION" class="external-link"><code>inst/CITATION</code></a></small></p>
+      <p><small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/inst/CITATION" class="external-link"><code>inst/CITATION</code></a></small></p>
 
       <p>Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C (2022).
 “AMR: An R Package for Working with Antimicrobial Resistance Data.”
 <em>Journal of Statistical Software</em>, <b>104</b>(3), 1–31.
-<a href="https://doi.org/10.18637/jss.v104.i03" class="external-link">doi:10.18637/jss.v104.i03</a>. 
+<a href="https://doi.org/10.18637/jss.v104.i03" class="external-link">doi:10.18637/jss.v104.i03</a>.
 </p>
       <pre>@Article{,
   title = {{AMR}: An {R} Package for Working with Antimicrobial Resistance Data},
@@ -282,7 +176,8 @@
   doi = {10.18637/jss.v104.i03},
 }</pre>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -296,9 +191,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/countries.png b/countries.png
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diff --git a/countries_large.png b/countries_large.png
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diff --git a/deps/bootstrap-5.3.1/bootstrap.min.css b/deps/bootstrap-5.3.1/bootstrap.min.css
index f944782c7..f5af0dfc2 100644
--- a/deps/bootstrap-5.3.1/bootstrap.min.css
+++ b/deps/bootstrap-5.3.1/bootstrap.min.css
@@ -2,4 +2,4 @@
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reduce){.btn{transition:none}}.btn:hover{color:var(--bs-btn-hover-color);background-color:var(--bs-btn-hover-bg);border-color:var(--bs-btn-hover-border-color)}.btn-check+.btn:hover{color:var(--bs-btn-color);background-color:var(--bs-btn-bg);border-color:var(--bs-btn-border-color)}.btn:focus-visible{color:var(--bs-btn-hover-color);background-color:var(--bs-btn-hover-bg);border-color:var(--bs-btn-hover-border-color);outline:0;box-shadow:var(--bs-btn-focus-box-shadow)}.btn-check:focus-visible+.btn{border-color:var(--bs-btn-hover-border-color);outline:0;box-shadow:var(--bs-btn-focus-box-shadow)}.btn-check:checked+.btn,:not(.btn-check)+.btn:active,.btn:first-child:active,.btn.active,.btn.show{color:var(--bs-btn-active-color);background-color:var(--bs-btn-active-bg);border-color:var(--bs-btn-active-border-color)}.btn-check:checked+.btn:focus-visible,:not(.btn-check)+.btn:active:focus-visible,.btn:first-child:active:focus-visible,.btn.active:focus-visible,.btn.show:focus-visible{box-shadow:var(--bs-btn-focus-box-shadow)}.btn:disabled,.btn.disabled,fieldset:disabled 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#fff;--bs-btn-active-bg: #13967d;--bs-btn-active-border-color: #128d75;--bs-btn-active-shadow: inset 0 3px 5px rgba(0,0,0,0.125);--bs-btn-disabled-color: #fff;--bs-btn-disabled-bg: #18bc9c;--bs-btn-disabled-border-color: #18bc9c}.btn-info{--bs-btn-color: #fff;--bs-btn-bg: #3498db;--bs-btn-border-color: #3498db;--bs-btn-hover-color: #fff;--bs-btn-hover-bg: #2c81ba;--bs-btn-hover-border-color: #2a7aaf;--bs-btn-focus-shadow-rgb: 82,167,224;--bs-btn-active-color: #fff;--bs-btn-active-bg: #2a7aaf;--bs-btn-active-border-color: #2772a4;--bs-btn-active-shadow: inset 0 3px 5px rgba(0,0,0,0.125);--bs-btn-disabled-color: #fff;--bs-btn-disabled-bg: #3498db;--bs-btn-disabled-border-color: #3498db}.btn-warning{--bs-btn-color: #fff;--bs-btn-bg: #f39c12;--bs-btn-border-color: #f39c12;--bs-btn-hover-color: #fff;--bs-btn-hover-bg: #cf850f;--bs-btn-hover-border-color: #c27d0e;--bs-btn-focus-shadow-rgb: 245,171,54;--bs-btn-active-color: #fff;--bs-btn-active-bg: #c27d0e;--bs-btn-active-border-color: 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#95a5a6;--bs-btn-disabled-bg: transparent;--bs-btn-disabled-border-color: #95a5a6;--bs-btn-bg: transparent;--bs-gradient: none}.btn-outline-success{--bs-btn-color: #18bc9c;--bs-btn-border-color: #18bc9c;--bs-btn-hover-color: #fff;--bs-btn-hover-bg: #18bc9c;--bs-btn-hover-border-color: #18bc9c;--bs-btn-focus-shadow-rgb: 24,188,156;--bs-btn-active-color: #fff;--bs-btn-active-bg: #18bc9c;--bs-btn-active-border-color: #18bc9c;--bs-btn-active-shadow: inset 0 3px 5px rgba(0,0,0,0.125);--bs-btn-disabled-color: #18bc9c;--bs-btn-disabled-bg: transparent;--bs-btn-disabled-border-color: #18bc9c;--bs-btn-bg: transparent;--bs-gradient: none}.btn-outline-info{--bs-btn-color: #3498db;--bs-btn-border-color: #3498db;--bs-btn-hover-color: #fff;--bs-btn-hover-bg: #3498db;--bs-btn-hover-border-color: #3498db;--bs-btn-focus-shadow-rgb: 52,152,219;--bs-btn-active-color: #fff;--bs-btn-active-bg: #3498db;--bs-btn-active-border-color: #3498db;--bs-btn-active-shadow: inset 0 3px 5px 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inset 0 3px 5px rgba(0,0,0,0.125);--bs-btn-disabled-color: #e74c3c;--bs-btn-disabled-bg: transparent;--bs-btn-disabled-border-color: #e74c3c;--bs-btn-bg: transparent;--bs-gradient: none}.btn-outline-light{--bs-btn-color: #ecf0f1;--bs-btn-border-color: #ecf0f1;--bs-btn-hover-color: #000;--bs-btn-hover-bg: #ecf0f1;--bs-btn-hover-border-color: #ecf0f1;--bs-btn-focus-shadow-rgb: 236,240,241;--bs-btn-active-color: #000;--bs-btn-active-bg: #ecf0f1;--bs-btn-active-border-color: #ecf0f1;--bs-btn-active-shadow: inset 0 3px 5px rgba(0,0,0,0.125);--bs-btn-disabled-color: #ecf0f1;--bs-btn-disabled-bg: transparent;--bs-btn-disabled-border-color: #ecf0f1;--bs-btn-bg: transparent;--bs-gradient: none}.btn-outline-dark{--bs-btn-color: #7b8a8b;--bs-btn-border-color: #7b8a8b;--bs-btn-hover-color: #fff;--bs-btn-hover-bg: #7b8a8b;--bs-btn-hover-border-color: #7b8a8b;--bs-btn-focus-shadow-rgb: 123,138,139;--bs-btn-active-color: #fff;--bs-btn-active-bg: #7b8a8b;--bs-btn-active-border-color: #7b8a8b;--bs-btn-active-shadow: inset 0 3px 5px rgba(0,0,0,0.125);--bs-btn-disabled-color: #7b8a8b;--bs-btn-disabled-bg: transparent;--bs-btn-disabled-border-color: #7b8a8b;--bs-btn-bg: transparent;--bs-gradient: none}.btn-link{--bs-btn-font-weight: 400;--bs-btn-color: var(--bs-link-color);--bs-btn-bg: transparent;--bs-btn-border-color: transparent;--bs-btn-hover-color: var(--bs-link-hover-color);--bs-btn-hover-border-color: transparent;--bs-btn-active-color: var(--bs-link-hover-color);--bs-btn-active-border-color: transparent;--bs-btn-disabled-color: #95a5a6;--bs-btn-disabled-border-color: transparent;--bs-btn-box-shadow: 0 0 0 #000;--bs-btn-focus-shadow-rgb: 59,198,171;text-decoration:underline;-webkit-text-decoration:underline;-moz-text-decoration:underline;-ms-text-decoration:underline;-o-text-decoration:underline}.btn-link:focus-visible{color:var(--bs-btn-color)}.btn-link:hover{color:var(--bs-btn-hover-color)}.btn-lg,.btn-group-lg>.btn{--bs-btn-padding-y: .5rem;--bs-btn-padding-x: 1rem;--bs-btn-font-size:1.25rem;--bs-btn-border-radius: var(--bs-border-radius-lg)}.btn-sm,.btn-group-sm>.btn{--bs-btn-padding-y: .25rem;--bs-btn-padding-x: .5rem;--bs-btn-font-size:.875rem;--bs-btn-border-radius: var(--bs-border-radius-sm)}.fade{transition:opacity 0.15s linear}@media (prefers-reduced-motion: reduce){.fade{transition:none}}.fade:not(.show){opacity:0}.collapse:not(.show){display:none}.collapsing{height:0;overflow:hidden;transition:height 0.35s ease}@media (prefers-reduced-motion: reduce){.collapsing{transition:none}}.collapsing.collapse-horizontal{width:0;height:auto;transition:width 0.35s ease}@media (prefers-reduced-motion: reduce){.collapsing.collapse-horizontal{transition:none}}.dropup,.dropend,.dropdown,.dropstart,.dropup-center,.dropdown-center{position:relative}.dropdown-toggle{white-space:nowrap}.dropdown-toggle::after{display:inline-block;margin-left:.255em;vertical-align:.255em;content:"";border-top:.3em solid;border-right:.3em solid transparent;border-bottom:0;border-left:.3em solid transparent}.dropdown-toggle:empty::after{margin-left:0}.dropdown-menu{--bs-dropdown-zindex: 1000;--bs-dropdown-min-width: 10rem;--bs-dropdown-padding-x: 0;--bs-dropdown-padding-y: .5rem;--bs-dropdown-spacer: .125rem;--bs-dropdown-font-size:1rem;--bs-dropdown-color: var(--bs-body-color);--bs-dropdown-bg: var(--bs-body-bg);--bs-dropdown-border-color: var(--bs-border-color-translucent);--bs-dropdown-border-radius: var(--bs-border-radius);--bs-dropdown-border-width: var(--bs-border-width);--bs-dropdown-inner-border-radius: calc(var(--bs-border-radius) - var(--bs-border-width));--bs-dropdown-divider-bg: var(--bs-border-color-translucent);--bs-dropdown-divider-margin-y: .5rem;--bs-dropdown-box-shadow: 0 0.5rem 1rem rgba(0,0,0,0.15);--bs-dropdown-link-color: #7b8a8b;--bs-dropdown-link-hover-color: #fff;--bs-dropdown-link-hover-bg: #2c3e50;--bs-dropdown-link-active-color: #fff;--bs-dropdown-link-active-bg: #2c3e50;--bs-dropdown-link-disabled-color: var(--bs-tertiary-color);--bs-dropdown-item-padding-x: 1rem;--bs-dropdown-item-padding-y: .25rem;--bs-dropdown-header-color: #95a5a6;--bs-dropdown-header-padding-x: 1rem;--bs-dropdown-header-padding-y: .5rem;position:absolute;z-index:var(--bs-dropdown-zindex);display:none;min-width:var(--bs-dropdown-min-width);padding:var(--bs-dropdown-padding-y) var(--bs-dropdown-padding-x);margin:0;font-size:var(--bs-dropdown-font-size);color:var(--bs-dropdown-color);text-align:left;list-style:none;background-color:var(--bs-dropdown-bg);background-clip:padding-box;border:var(--bs-dropdown-border-width) solid var(--bs-dropdown-border-color);border-radius:var(--bs-dropdown-border-radius)}.dropdown-menu[data-bs-popper]{top:100%;left:0;margin-top:var(--bs-dropdown-spacer)}.dropdown-menu-start{--bs-position: start}.dropdown-menu-start[data-bs-popper]{right:auto;left:0}.dropdown-menu-end{--bs-position: end}.dropdown-menu-end[data-bs-popper]{right:0;left:auto}@media (min-width: 576px){.dropdown-menu-sm-start{--bs-position: start}.dropdown-menu-sm-start[data-bs-popper]{right:auto;left:0}.dropdown-menu-sm-end{--bs-position: end}.dropdown-menu-sm-end[data-bs-popper]{right:0;left:auto}}@media (min-width: 768px){.dropdown-menu-md-start{--bs-position: start}.dropdown-menu-md-start[data-bs-popper]{right:auto;left:0}.dropdown-menu-md-end{--bs-position: end}.dropdown-menu-md-end[data-bs-popper]{right:0;left:auto}}@media (min-width: 992px){.dropdown-menu-lg-start{--bs-position: start}.dropdown-menu-lg-start[data-bs-popper]{right:auto;left:0}.dropdown-menu-lg-end{--bs-position: end}.dropdown-menu-lg-end[data-bs-popper]{right:0;left:auto}}@media (min-width: 1200px){.dropdown-menu-xl-start{--bs-position: start}.dropdown-menu-xl-start[data-bs-popper]{right:auto;left:0}.dropdown-menu-xl-end{--bs-position: end}.dropdown-menu-xl-end[data-bs-popper]{right:0;left:auto}}@media (min-width: 1400px){.dropdown-menu-xxl-start{--bs-position: start}.dropdown-menu-xxl-start[data-bs-popper]{right:auto;left:0}.dropdown-menu-xxl-end{--bs-position: end}.dropdown-menu-xxl-end[data-bs-popper]{right:0;left:auto}}.dropup .dropdown-menu[data-bs-popper]{top:auto;bottom:100%;margin-top:0;margin-bottom:var(--bs-dropdown-spacer)}.dropup .dropdown-toggle::after{display:inline-block;margin-left:.255em;vertical-align:.255em;content:"";border-top:0;border-right:.3em solid transparent;border-bottom:.3em solid;border-left:.3em solid transparent}.dropup .dropdown-toggle:empty::after{margin-left:0}.dropend .dropdown-menu[data-bs-popper]{top:0;right:auto;left:100%;margin-top:0;margin-left:var(--bs-dropdown-spacer)}.dropend .dropdown-toggle::after{display:inline-block;margin-left:.255em;vertical-align:.255em;content:"";border-top:.3em solid transparent;border-right:0;border-bottom:.3em solid transparent;border-left:.3em solid}.dropend .dropdown-toggle:empty::after{margin-left:0}.dropend .dropdown-toggle::after{vertical-align:0}.dropstart .dropdown-menu[data-bs-popper]{top:0;right:100%;left:auto;margin-top:0;margin-right:var(--bs-dropdown-spacer)}.dropstart .dropdown-toggle::after{display:inline-block;margin-left:.255em;vertical-align:.255em;content:""}.dropstart .dropdown-toggle::after{display:none}.dropstart .dropdown-toggle::before{display:inline-block;margin-right:.255em;vertical-align:.255em;content:"";border-top:.3em solid transparent;border-right:.3em solid;border-bottom:.3em solid transparent}.dropstart .dropdown-toggle:empty::after{margin-left:0}.dropstart .dropdown-toggle::before{vertical-align:0}.dropdown-divider{height:0;margin:var(--bs-dropdown-divider-margin-y) 0;overflow:hidden;border-top:1px solid var(--bs-dropdown-divider-bg);opacity:1}.dropdown-item{display:block;width:100%;padding:var(--bs-dropdown-item-padding-y) 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var(--bs-dropdown-header-padding-x);margin-bottom:0;font-size:.875rem;color:var(--bs-dropdown-header-color);white-space:nowrap}.dropdown-item-text{display:block;padding:var(--bs-dropdown-item-padding-y) var(--bs-dropdown-item-padding-x);color:var(--bs-dropdown-link-color)}.dropdown-menu-dark{--bs-dropdown-color: #dee2e6;--bs-dropdown-bg: #343a40;--bs-dropdown-border-color: var(--bs-border-color-translucent);--bs-dropdown-box-shadow: ;--bs-dropdown-link-color: #dee2e6;--bs-dropdown-link-hover-color: #fff;--bs-dropdown-divider-bg: var(--bs-border-color-translucent);--bs-dropdown-link-hover-bg: rgba(255,255,255,0.15);--bs-dropdown-link-active-color: #fff;--bs-dropdown-link-active-bg: #2c3e50;--bs-dropdown-link-disabled-color: #b4bcc2;--bs-dropdown-header-color: #b4bcc2}.btn-group,.btn-group-vertical{position:relative;display:inline-flex;vertical-align:middle}.btn-group>.btn,.btn-group-vertical>.btn{position:relative;flex:1 1 auto;-webkit-flex:1 1 auto}.btn-group>.btn-check:checked+.btn,.btn-group>.btn-check:focus+.btn,.btn-group>.btn:hover,.btn-group>.btn:focus,.btn-group>.btn:active,.btn-group>.btn.active,.btn-group-vertical>.btn-check:checked+.btn,.btn-group-vertical>.btn-check:focus+.btn,.btn-group-vertical>.btn:hover,.btn-group-vertical>.btn:focus,.btn-group-vertical>.btn:active,.btn-group-vertical>.btn.active{z-index:1}.btn-toolbar{display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;justify-content:flex-start;-webkit-justify-content:flex-start}.btn-toolbar .input-group{width:auto}.btn-group{border-radius:var(--bs-border-radius)}.btn-group>:not(.btn-check:first-child)+.btn,.btn-group>.btn-group:not(:first-child){margin-left:calc(var(--bs-border-width) * -1)}.btn-group>.btn:not(:last-child):not(.dropdown-toggle),.btn-group>.btn.dropdown-toggle-split:first-child,.btn-group>.btn-group:not(:last-child)>.btn{border-top-right-radius:0;border-bottom-right-radius:0}.btn-group>.btn:nth-child(n + 3),.btn-group>:not(.btn-check)+.btn,.btn-group>.btn-group:not(:first-child)>.btn{border-top-left-radius:0;border-bottom-left-radius:0}.dropdown-toggle-split{padding-right:.5625rem;padding-left:.5625rem}.dropdown-toggle-split::after,.dropup .dropdown-toggle-split::after,.dropend .dropdown-toggle-split::after{margin-left:0}.dropstart .dropdown-toggle-split::before{margin-right:0}.btn-sm+.dropdown-toggle-split,.btn-group-sm>.btn+.dropdown-toggle-split{padding-right:.375rem;padding-left:.375rem}.btn-lg+.dropdown-toggle-split,.btn-group-lg>.btn+.dropdown-toggle-split{padding-right:.75rem;padding-left:.75rem}.btn-group-vertical{flex-direction:column;-webkit-flex-direction:column;align-items:flex-start;-webkit-align-items:flex-start;justify-content:center;-webkit-justify-content:center}.btn-group-vertical>.btn,.btn-group-vertical>.btn-group{width:100%}.btn-group-vertical>.btn:not(:first-child),.btn-group-vertical>.btn-group:not(:first-child){margin-top:calc(var(--bs-border-width) * -1)}.btn-group-vertical>.btn:not(:last-child):not(.dropdown-toggle),.btn-group-vertical>.btn-group:not(:last-child)>.btn{border-bottom-right-radius:0;border-bottom-left-radius:0}.btn-group-vertical>.btn~.btn,.btn-group-vertical>.btn-group:not(:first-child)>.btn{border-top-left-radius:0;border-top-right-radius:0}.nav{--bs-nav-link-padding-x: 2rem;--bs-nav-link-padding-y: .5rem;--bs-nav-link-font-weight: ;--bs-nav-link-color: var(--bs-link-color);--bs-nav-link-hover-color: var(--bs-link-hover-color);--bs-nav-link-disabled-color: #95a5a6;display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;padding-left:0;margin-bottom:0;list-style:none}.nav-link{display:block;padding:var(--bs-nav-link-padding-y) var(--bs-nav-link-padding-x);font-size:var(--bs-nav-link-font-size);font-weight:var(--bs-nav-link-font-weight);color:var(--bs-nav-link-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background:none;border:0;transition:color 0.15s ease-in-out,background-color 0.15s ease-in-out,border-color 0.15s ease-in-out}@media (prefers-reduced-motion: reduce){.nav-link{transition:none}}.nav-link:hover,.nav-link:focus{color:var(--bs-nav-link-hover-color)}.nav-link:focus-visible{outline:0;box-shadow:0 0 0 .25rem rgba(44,62,80,0.25)}.nav-link.disabled,.nav-link:disabled{color:var(--bs-nav-link-disabled-color);pointer-events:none;cursor:default}.nav-tabs{--bs-nav-tabs-border-width: var(--bs-border-width);--bs-nav-tabs-border-color: #ecf0f1;--bs-nav-tabs-border-radius: var(--bs-border-radius);--bs-nav-tabs-link-hover-border-color: var(--bs-secondary-bg) var(--bs-secondary-bg) #ecf0f1;--bs-nav-tabs-link-active-color: var(--bs-emphasis-color);--bs-nav-tabs-link-active-bg: var(--bs-body-bg);--bs-nav-tabs-link-active-border-color: var(--bs-border-color) var(--bs-border-color) var(--bs-body-bg);border-bottom:var(--bs-nav-tabs-border-width) solid var(--bs-nav-tabs-border-color)}.nav-tabs .nav-link{margin-bottom:calc(-1 * var(--bs-nav-tabs-border-width));border:var(--bs-nav-tabs-border-width) solid transparent;border-top-left-radius:var(--bs-nav-tabs-border-radius);border-top-right-radius:var(--bs-nav-tabs-border-radius)}.nav-tabs .nav-link:hover,.nav-tabs .nav-link:focus{isolation:isolate;border-color:var(--bs-nav-tabs-link-hover-border-color)}.nav-tabs .nav-link.active,.nav-tabs .nav-item.show .nav-link{color:var(--bs-nav-tabs-link-active-color);background-color:var(--bs-nav-tabs-link-active-bg);border-color:var(--bs-nav-tabs-link-active-border-color)}.nav-tabs .dropdown-menu{margin-top:calc(-1 * var(--bs-nav-tabs-border-width));border-top-left-radius:0;border-top-right-radius:0}.nav-pills{--bs-nav-pills-border-radius: var(--bs-border-radius);--bs-nav-pills-link-active-color: #fff;--bs-nav-pills-link-active-bg: #2c3e50}.nav-pills .nav-link{border-radius:var(--bs-nav-pills-border-radius)}.nav-pills .nav-link.active,.nav-pills .show>.nav-link{color:var(--bs-nav-pills-link-active-color);background-color:var(--bs-nav-pills-link-active-bg)}.nav-underline{--bs-nav-underline-gap: 1rem;--bs-nav-underline-border-width: .125rem;--bs-nav-underline-link-active-color: var(--bs-emphasis-color);gap:var(--bs-nav-underline-gap)}.nav-underline .nav-link{padding-right:0;padding-left:0;border-bottom:var(--bs-nav-underline-border-width) solid transparent}.nav-underline .nav-link:hover,.nav-underline .nav-link:focus{border-bottom-color:currentcolor}.nav-underline .nav-link.active,.nav-underline 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var(--bs-navbar-hover-color);--bs-nav-link-disabled-color: var(--bs-navbar-disabled-color);display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;padding-left:0;margin-bottom:0;list-style:none}.navbar-nav .nav-link.active,.navbar-nav .nav-link.show{color:var(--bs-navbar-active-color)}.navbar-nav .dropdown-menu{position:static}.navbar-text{padding-top:.5rem;padding-bottom:.5rem;color:var(--bs-navbar-color)}.navbar-text a,.navbar-text a:hover,.navbar-text a:focus{color:var(--bs-navbar-active-color)}.navbar-collapse{flex-basis:100%;-webkit-flex-basis:100%;flex-grow:1;-webkit-flex-grow:1;align-items:center;-webkit-align-items:center}.navbar-toggler{padding:var(--bs-navbar-toggler-padding-y) var(--bs-navbar-toggler-padding-x);font-size:var(--bs-navbar-toggler-font-size);line-height:1;color:var(--bs-navbar-color);background-color:transparent;border:var(--bs-border-width) solid 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.navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand-md .navbar-nav .dropdown-menu{position:absolute}.navbar-expand-md .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand-md .navbar-nav-scroll{overflow:visible}.navbar-expand-md .navbar-collapse{display:flex !important;display:-webkit-flex !important;flex-basis:auto;-webkit-flex-basis:auto}.navbar-expand-md .navbar-toggler{display:none}.navbar-expand-md .offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:transparent !important;border:0 !important;transform:none !important;transition:none}.navbar-expand-md .offcanvas .offcanvas-header{display:none}.navbar-expand-md .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}}@media (min-width: 992px){.navbar-expand-lg{flex-wrap:nowrap;-webkit-flex-wrap:nowrap;justify-content:flex-start;-webkit-justify-content:flex-start}.navbar-expand-lg .navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand-lg .navbar-nav .dropdown-menu{position:absolute}.navbar-expand-lg .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand-lg .navbar-nav-scroll{overflow:visible}.navbar-expand-lg .navbar-collapse{display:flex !important;display:-webkit-flex !important;flex-basis:auto;-webkit-flex-basis:auto}.navbar-expand-lg .navbar-toggler{display:none}.navbar-expand-lg .offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:transparent !important;border:0 !important;transform:none !important;transition:none}.navbar-expand-lg .offcanvas .offcanvas-header{display:none}.navbar-expand-lg .offcanvas 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!important;transform:none !important;transition:none}.navbar-expand-xl .offcanvas .offcanvas-header{display:none}.navbar-expand-xl .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}}@media (min-width: 1400px){.navbar-expand-xxl{flex-wrap:nowrap;-webkit-flex-wrap:nowrap;justify-content:flex-start;-webkit-justify-content:flex-start}.navbar-expand-xxl .navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand-xxl .navbar-nav .dropdown-menu{position:absolute}.navbar-expand-xxl .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand-xxl .navbar-nav-scroll{overflow:visible}.navbar-expand-xxl .navbar-collapse{display:flex !important;display:-webkit-flex !important;flex-basis:auto;-webkit-flex-basis:auto}.navbar-expand-xxl .navbar-toggler{display:none}.navbar-expand-xxl .offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:transparent !important;border:0 !important;transform:none !important;transition:none}.navbar-expand-xxl .offcanvas .offcanvas-header{display:none}.navbar-expand-xxl .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}}.navbar-expand{flex-wrap:nowrap;-webkit-flex-wrap:nowrap;justify-content:flex-start;-webkit-justify-content:flex-start}.navbar-expand .navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand .navbar-nav .dropdown-menu{position:absolute}.navbar-expand .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand .navbar-nav-scroll{overflow:visible}.navbar-expand .navbar-collapse{display:flex !important;display:-webkit-flex !important;flex-basis:auto;-webkit-flex-basis:auto}.navbar-expand .navbar-toggler{display:none}.navbar-expand .offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:transparent !important;border:0 !important;transform:none !important;transition:none}.navbar-expand .offcanvas .offcanvas-header{display:none}.navbar-expand .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}.navbar-dark,.navbar[data-bs-theme="dark"]{--bs-navbar-color: #fff;--bs-navbar-hover-color: #2c3e50;--bs-navbar-disabled-color: rgba(255,255,255,0.25);--bs-navbar-active-color: #2c3e50;--bs-navbar-brand-color: #fff;--bs-navbar-brand-hover-color: #fff;--bs-navbar-toggler-border-color: rgba(255,255,255,0.1);--bs-navbar-toggler-icon-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'%3e%3cpath stroke='rgba%28255,255,255,0.75%29' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/%3e%3c/svg%3e")}[data-bs-theme="dark"] .navbar-toggler-icon{--bs-navbar-toggler-icon-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'%3e%3cpath stroke='rgba%28255,255,255,0.75%29' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/%3e%3c/svg%3e")}.card{--bs-card-spacer-y: 1rem;--bs-card-spacer-x: 1rem;--bs-card-title-spacer-y: .5rem;--bs-card-title-color: ;--bs-card-subtitle-color: ;--bs-card-border-width: var(--bs-border-width);--bs-card-border-color: var(--bs-border-color-translucent);--bs-card-border-radius: var(--bs-border-radius);--bs-card-box-shadow: ;--bs-card-inner-border-radius: calc(var(--bs-border-radius) - (var(--bs-border-width)));--bs-card-cap-padding-y: .5rem;--bs-card-cap-padding-x: 1rem;--bs-card-cap-bg: rgba(var(--bs-body-color-rgb), 0.03);--bs-card-cap-color: ;--bs-card-height: ;--bs-card-color: ;--bs-card-bg: var(--bs-body-bg);--bs-card-img-overlay-padding: 1rem;--bs-card-group-margin: .75rem;position:relative;display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;min-width:0;height:var(--bs-card-height);color:var(--bs-body-color);word-wrap:break-word;background-color:var(--bs-card-bg);background-clip:border-box;border:var(--bs-card-border-width) solid var(--bs-card-border-color);border-radius:var(--bs-card-border-radius)}.card>hr{margin-right:0;margin-left:0}.card>.list-group{border-top:inherit;border-bottom:inherit}.card>.list-group:first-child{border-top-width:0;border-top-left-radius:var(--bs-card-inner-border-radius);border-top-right-radius:var(--bs-card-inner-border-radius)}.card>.list-group:last-child{border-bottom-width:0;border-bottom-right-radius:var(--bs-card-inner-border-radius);border-bottom-left-radius:var(--bs-card-inner-border-radius)}.card>.card-header+.list-group,.card>.list-group+.card-footer{border-top:0}.card-body{flex:1 1 auto;-webkit-flex:1 1 auto;padding:var(--bs-card-spacer-y) var(--bs-card-spacer-x);color:var(--bs-card-color)}.card-title{margin-bottom:var(--bs-card-title-spacer-y);color:var(--bs-card-title-color)}.card-subtitle{margin-top:calc(-.5 * var(--bs-card-title-spacer-y));margin-bottom:0;color:var(--bs-card-subtitle-color)}.card-text:last-child{margin-bottom:0}.card-link+.card-link{margin-left:var(--bs-card-spacer-x)}.card-header{padding:var(--bs-card-cap-padding-y) var(--bs-card-cap-padding-x);margin-bottom:0;color:var(--bs-card-cap-color);background-color:var(--bs-card-cap-bg);border-bottom:var(--bs-card-border-width) solid var(--bs-card-border-color)}.card-header:first-child{border-radius:var(--bs-card-inner-border-radius) var(--bs-card-inner-border-radius) 0 0}.card-footer{padding:var(--bs-card-cap-padding-y) var(--bs-card-cap-padding-x);color:var(--bs-card-cap-color);background-color:var(--bs-card-cap-bg);border-top:var(--bs-card-border-width) solid var(--bs-card-border-color)}.card-footer:last-child{border-radius:0 0 var(--bs-card-inner-border-radius) var(--bs-card-inner-border-radius)}.card-header-tabs{margin-right:calc(-.5 * var(--bs-card-cap-padding-x));margin-bottom:calc(-1 * 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wrap;-webkit-flex-flow:row wrap}.card-group>.card{flex:1 0 0%;-webkit-flex:1 0 0%;margin-bottom:0}.card-group>.card+.card{margin-left:0;border-left:0}.card-group>.card:not(:last-child){border-top-right-radius:0;border-bottom-right-radius:0}.card-group>.card:not(:last-child) .card-img-top,.card-group>.card:not(:last-child) .card-header{border-top-right-radius:0}.card-group>.card:not(:last-child) .card-img-bottom,.card-group>.card:not(:last-child) .card-footer{border-bottom-right-radius:0}.card-group>.card:not(:first-child){border-top-left-radius:0;border-bottom-left-radius:0}.card-group>.card:not(:first-child) .card-img-top,.card-group>.card:not(:first-child) .card-header{border-top-left-radius:0}.card-group>.card:not(:first-child) .card-img-bottom,.card-group>.card:not(:first-child) .card-footer{border-bottom-left-radius:0}}.accordion{--bs-accordion-color: var(--bs-body-color);--bs-accordion-bg: var(--bs-body-bg);--bs-accordion-transition: color 0.15s ease-in-out,background-color 0.15s ease-in-out,border-color 0.15s ease-in-out,box-shadow 0.15s ease-in-out,border-radius 0.15s ease;--bs-accordion-border-color: var(--bs-border-color);--bs-accordion-border-width: var(--bs-border-width);--bs-accordion-border-radius: var(--bs-border-radius);--bs-accordion-inner-border-radius: calc(var(--bs-border-radius) - (var(--bs-border-width)));--bs-accordion-btn-padding-x: 1.25rem;--bs-accordion-btn-padding-y: 1rem;--bs-accordion-btn-color: var(--bs-body-color);--bs-accordion-btn-bg: var(--bs-accordion-bg);--bs-accordion-btn-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23212529'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-icon-width: 1.25rem;--bs-accordion-btn-icon-transform: rotate(-180deg);--bs-accordion-btn-icon-transition: transform 0.2s ease-in-out;--bs-accordion-btn-active-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23121920'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-focus-border-color: #969fa8;--bs-accordion-btn-focus-box-shadow: 0 0 0 .25rem rgba(44,62,80,0.25);--bs-accordion-body-padding-x: 1.25rem;--bs-accordion-body-padding-y: 1rem;--bs-accordion-active-color: var(--bs-primary-text-emphasis);--bs-accordion-active-bg: var(--bs-primary-bg-subtle)}.accordion-button{position:relative;display:flex;display:-webkit-flex;align-items:center;-webkit-align-items:center;width:100%;padding:var(--bs-accordion-btn-padding-y) var(--bs-accordion-btn-padding-x);font-size:1rem;color:var(--bs-accordion-btn-color);text-align:left;background-color:var(--bs-accordion-btn-bg);border:0;border-radius:0;overflow-anchor:none;transition:var(--bs-accordion-transition)}@media (prefers-reduced-motion: reduce){.accordion-button{transition:none}}.accordion-button:not(.collapsed){color:var(--bs-accordion-active-color);background-color:var(--bs-accordion-active-bg);box-shadow:inset 0 calc(-1 * var(--bs-accordion-border-width)) 0 var(--bs-accordion-border-color)}.accordion-button:not(.collapsed)::after{background-image:var(--bs-accordion-btn-active-icon);transform:var(--bs-accordion-btn-icon-transform)}.accordion-button::after{flex-shrink:0;-webkit-flex-shrink:0;width:var(--bs-accordion-btn-icon-width);height:var(--bs-accordion-btn-icon-width);margin-left:auto;content:"";background-image:var(--bs-accordion-btn-icon);background-repeat:no-repeat;background-size:var(--bs-accordion-btn-icon-width);transition:var(--bs-accordion-btn-icon-transition)}@media (prefers-reduced-motion: reduce){.accordion-button::after{transition:none}}.accordion-button:hover{z-index:2}.accordion-button:focus{z-index:3;border-color:var(--bs-accordion-btn-focus-border-color);outline:0;box-shadow:var(--bs-accordion-btn-focus-box-shadow)}.accordion-header{margin-bottom:0}.accordion-item{color:var(--bs-accordion-color);background-color:var(--bs-accordion-bg);border:var(--bs-accordion-border-width) solid var(--bs-accordion-border-color)}.accordion-item:first-of-type{border-top-left-radius:var(--bs-accordion-border-radius);border-top-right-radius:var(--bs-accordion-border-radius)}.accordion-item:first-of-type .accordion-button{border-top-left-radius:var(--bs-accordion-inner-border-radius);border-top-right-radius:var(--bs-accordion-inner-border-radius)}.accordion-item:not(:first-of-type){border-top:0}.accordion-item:last-of-type{border-bottom-right-radius:var(--bs-accordion-border-radius);border-bottom-left-radius:var(--bs-accordion-border-radius)}.accordion-item:last-of-type .accordion-button.collapsed{border-bottom-right-radius:var(--bs-accordion-inner-border-radius);border-bottom-left-radius:var(--bs-accordion-inner-border-radius)}.accordion-item:last-of-type .accordion-collapse{border-bottom-right-radius:var(--bs-accordion-border-radius);border-bottom-left-radius:var(--bs-accordion-border-radius)}.accordion-body{padding:var(--bs-accordion-body-padding-y) var(--bs-accordion-body-padding-x)}.accordion-flush .accordion-collapse{border-width:0}.accordion-flush .accordion-item{border-right:0;border-left:0;border-radius:0}.accordion-flush .accordion-item:first-child{border-top:0}.accordion-flush .accordion-item:last-child{border-bottom:0}.accordion-flush .accordion-item .accordion-button,.accordion-flush .accordion-item .accordion-button.collapsed{border-radius:0}[data-bs-theme="dark"] .accordion-button::after{--bs-accordion-btn-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23808b96'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-active-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23808b96'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e")}.breadcrumb{--bs-breadcrumb-padding-x: .75rem;--bs-breadcrumb-padding-y: .375rem;--bs-breadcrumb-margin-bottom: 1rem;--bs-breadcrumb-bg: ;--bs-breadcrumb-border-radius: .25rem;--bs-breadcrumb-divider-color: var(--bs-secondary-color);--bs-breadcrumb-item-padding-x: .5rem;--bs-breadcrumb-item-active-color: var(--bs-secondary-color);display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;padding:var(--bs-breadcrumb-padding-y) var(--bs-breadcrumb-padding-x);margin-bottom:var(--bs-breadcrumb-margin-bottom);font-size:var(--bs-breadcrumb-font-size);list-style:none;background-color:var(--bs-breadcrumb-bg);border-radius:var(--bs-breadcrumb-border-radius)}.breadcrumb-item+.breadcrumb-item{padding-left:var(--bs-breadcrumb-item-padding-x)}.breadcrumb-item+.breadcrumb-item::before{float:left;padding-right:var(--bs-breadcrumb-item-padding-x);color:var(--bs-breadcrumb-divider-color);content:var(--bs-breadcrumb-divider, "/") /* rtl: var(--bs-breadcrumb-divider, "/") */}.breadcrumb-item.active{color:var(--bs-breadcrumb-item-active-color)}.pagination{--bs-pagination-padding-x: .75rem;--bs-pagination-padding-y: .375rem;--bs-pagination-font-size:1rem;--bs-pagination-color: #fff;--bs-pagination-bg: #18bc9c;--bs-pagination-border-width: 0;--bs-pagination-border-color: rgba(0,0,0,0);--bs-pagination-border-radius: var(--bs-border-radius);--bs-pagination-hover-color: #fff;--bs-pagination-hover-bg: #0f7864;--bs-pagination-hover-border-color: rgba(0,0,0,0);--bs-pagination-focus-color: var(--bs-link-hover-color);--bs-pagination-focus-bg: var(--bs-secondary-bg);--bs-pagination-focus-box-shadow: 0 0 0 .25rem rgba(44,62,80,0.25);--bs-pagination-active-color: #fff;--bs-pagination-active-bg: #0f7864;--bs-pagination-active-border-color: rgba(0,0,0,0);--bs-pagination-disabled-color: #ecf0f1;--bs-pagination-disabled-bg: #3be6c4;--bs-pagination-disabled-border-color: rgba(0,0,0,0);display:flex;display:-webkit-flex;padding-left:0;list-style:none}.page-link{position:relative;display:block;padding:var(--bs-pagination-padding-y) var(--bs-pagination-padding-x);font-size:var(--bs-pagination-font-size);color:var(--bs-pagination-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background-color:var(--bs-pagination-bg);border:var(--bs-pagination-border-width) solid var(--bs-pagination-border-color);transition:color 0.15s ease-in-out,background-color 0.15s ease-in-out,border-color 0.15s ease-in-out,box-shadow 0.15s ease-in-out}@media (prefers-reduced-motion: reduce){.page-link{transition:none}}.page-link:hover{z-index:2;color:var(--bs-pagination-hover-color);background-color:var(--bs-pagination-hover-bg);border-color:var(--bs-pagination-hover-border-color)}.page-link:focus{z-index:3;color:var(--bs-pagination-focus-color);background-color:var(--bs-pagination-focus-bg);outline:0;box-shadow:var(--bs-pagination-focus-box-shadow)}.page-link.active,.active>.page-link{z-index:3;color:var(--bs-pagination-active-color);background-color:var(--bs-pagination-active-bg);border-color:var(--bs-pagination-active-border-color)}.page-link.disabled,.disabled>.page-link{color:var(--bs-pagination-disabled-color);pointer-events:none;background-color:var(--bs-pagination-disabled-bg);border-color:var(--bs-pagination-disabled-border-color)}.page-item:not(:first-child) .page-link{margin-left:calc(0 * -1)}.page-item:first-child .page-link{border-top-left-radius:var(--bs-pagination-border-radius);border-bottom-left-radius:var(--bs-pagination-border-radius)}.page-item:last-child .page-link{border-top-right-radius:var(--bs-pagination-border-radius);border-bottom-right-radius:var(--bs-pagination-border-radius)}.pagination-lg{--bs-pagination-padding-x: 1.5rem;--bs-pagination-padding-y: .75rem;--bs-pagination-font-size:1.25rem;--bs-pagination-border-radius: var(--bs-border-radius-lg)}.pagination-sm{--bs-pagination-padding-x: .5rem;--bs-pagination-padding-y: .25rem;--bs-pagination-font-size:.875rem;--bs-pagination-border-radius: var(--bs-border-radius-sm)}.badge{--bs-badge-padding-x: .65em;--bs-badge-padding-y: .35em;--bs-badge-font-size:.75em;--bs-badge-font-weight: 700;--bs-badge-color: #fff;--bs-badge-border-radius: var(--bs-border-radius);display:inline-block;padding:var(--bs-badge-padding-y) var(--bs-badge-padding-x);font-size:var(--bs-badge-font-size);font-weight:var(--bs-badge-font-weight);line-height:1;color:var(--bs-badge-color);text-align:center;white-space:nowrap;vertical-align:baseline;border-radius:var(--bs-badge-border-radius)}.badge:empty{display:none}.btn .badge{position:relative;top:-1px}.alert{--bs-alert-bg: transparent;--bs-alert-padding-x: 1rem;--bs-alert-padding-y: 1rem;--bs-alert-margin-bottom: 1rem;--bs-alert-color: inherit;--bs-alert-border-color: transparent;--bs-alert-border: var(--bs-border-width) solid var(--bs-alert-border-color);--bs-alert-border-radius: var(--bs-border-radius);--bs-alert-link-color: inherit;position:relative;padding:var(--bs-alert-padding-y) var(--bs-alert-padding-x);margin-bottom:var(--bs-alert-margin-bottom);color:var(--bs-alert-color);background-color:var(--bs-alert-bg);border:var(--bs-alert-border);border-radius:var(--bs-alert-border-radius)}.alert-heading{color:inherit}.alert-link{font-weight:700;color:var(--bs-alert-link-color)}.alert-dismissible{padding-right:3rem}.alert-dismissible .btn-close{position:absolute;top:0;right:0;z-index:2;padding:1.25rem 1rem}.alert-default{--bs-alert-color: var(--bs-default-text-emphasis);--bs-alert-bg: var(--bs-default-bg-subtle);--bs-alert-border-color: var(--bs-default-border-subtle);--bs-alert-link-color: var(--bs-default-text-emphasis)}.alert-primary{--bs-alert-color: var(--bs-primary-text-emphasis);--bs-alert-bg: var(--bs-primary-bg-subtle);--bs-alert-border-color: var(--bs-primary-border-subtle);--bs-alert-link-color: var(--bs-primary-text-emphasis)}.alert-secondary{--bs-alert-color: var(--bs-secondary-text-emphasis);--bs-alert-bg: var(--bs-secondary-bg-subtle);--bs-alert-border-color: var(--bs-secondary-border-subtle);--bs-alert-link-color: var(--bs-secondary-text-emphasis)}.alert-success{--bs-alert-color: var(--bs-success-text-emphasis);--bs-alert-bg: var(--bs-success-bg-subtle);--bs-alert-border-color: var(--bs-success-border-subtle);--bs-alert-link-color: var(--bs-success-text-emphasis)}.alert-info{--bs-alert-color: var(--bs-info-text-emphasis);--bs-alert-bg: var(--bs-info-bg-subtle);--bs-alert-border-color: var(--bs-info-border-subtle);--bs-alert-link-color: var(--bs-info-text-emphasis)}.alert-warning{--bs-alert-color: var(--bs-warning-text-emphasis);--bs-alert-bg: var(--bs-warning-bg-subtle);--bs-alert-border-color: var(--bs-warning-border-subtle);--bs-alert-link-color: var(--bs-warning-text-emphasis)}.alert-danger{--bs-alert-color: var(--bs-danger-text-emphasis);--bs-alert-bg: var(--bs-danger-bg-subtle);--bs-alert-border-color: var(--bs-danger-border-subtle);--bs-alert-link-color: var(--bs-danger-text-emphasis)}.alert-light{--bs-alert-color: var(--bs-light-text-emphasis);--bs-alert-bg: var(--bs-light-bg-subtle);--bs-alert-border-color: var(--bs-light-border-subtle);--bs-alert-link-color: var(--bs-light-text-emphasis)}.alert-dark{--bs-alert-color: var(--bs-dark-text-emphasis);--bs-alert-bg: var(--bs-dark-bg-subtle);--bs-alert-border-color: var(--bs-dark-border-subtle);--bs-alert-link-color: var(--bs-dark-text-emphasis)}@keyframes progress-bar-stripes{0%{background-position-x:1rem}}.progress,.progress-stacked{--bs-progress-height: 1rem;--bs-progress-font-size:.75rem;--bs-progress-bg: var(--bs-secondary-bg);--bs-progress-border-radius: var(--bs-border-radius);--bs-progress-box-shadow: var(--bs-box-shadow-inset);--bs-progress-bar-color: #fff;--bs-progress-bar-bg: #2c3e50;--bs-progress-bar-transition: width 0.6s ease;display:flex;display:-webkit-flex;height:var(--bs-progress-height);overflow:hidden;font-size:var(--bs-progress-font-size);background-color:var(--bs-progress-bg);border-radius:var(--bs-progress-border-radius)}.progress-bar{display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;justify-content:center;-webkit-justify-content:center;overflow:hidden;color:var(--bs-progress-bar-color);text-align:center;white-space:nowrap;background-color:var(--bs-progress-bar-bg);transition:var(--bs-progress-bar-transition)}@media (prefers-reduced-motion: reduce){.progress-bar{transition:none}}.progress-bar-striped{background-image:linear-gradient(45deg, rgba(255,255,255,0.15) 25%, transparent 25%, transparent 50%, rgba(255,255,255,0.15) 50%, rgba(255,255,255,0.15) 75%, transparent 75%, transparent);background-size:var(--bs-progress-height) var(--bs-progress-height)}.progress-stacked>.progress{overflow:visible}.progress-stacked>.progress>.progress-bar{width:100%}.progress-bar-animated{animation:1s linear infinite progress-bar-stripes}@media (prefers-reduced-motion: reduce){.progress-bar-animated{animation:none}}.list-group{--bs-list-group-color: var(--bs-body-color);--bs-list-group-bg: var(--bs-body-bg);--bs-list-group-border-color: var(--bs-border-color);--bs-list-group-border-width: var(--bs-border-width);--bs-list-group-border-radius: var(--bs-border-radius);--bs-list-group-item-padding-x: 1rem;--bs-list-group-item-padding-y: .5rem;--bs-list-group-action-color: var(--bs-secondary-color);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: #ecf0f1;--bs-list-group-action-active-color: var(--bs-body-color);--bs-list-group-action-active-bg: var(--bs-secondary-bg);--bs-list-group-disabled-color: var(--bs-secondary-color);--bs-list-group-disabled-bg: 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reduce){.btn{transition:none}}.btn:hover{color:var(--bs-btn-hover-color);background-color:var(--bs-btn-hover-bg);border-color:var(--bs-btn-hover-border-color)}.btn-check+.btn:hover{color:var(--bs-btn-color);background-color:var(--bs-btn-bg);border-color:var(--bs-btn-border-color)}.btn:focus-visible{color:var(--bs-btn-hover-color);background-color:var(--bs-btn-hover-bg);border-color:var(--bs-btn-hover-border-color);outline:0;box-shadow:var(--bs-btn-focus-box-shadow)}.btn-check:focus-visible+.btn{border-color:var(--bs-btn-hover-border-color);outline:0;box-shadow:var(--bs-btn-focus-box-shadow)}.btn-check:checked+.btn,:not(.btn-check)+.btn:active,.btn:first-child:active,.btn.active,.btn.show{color:var(--bs-btn-active-color);background-color:var(--bs-btn-active-bg);border-color:var(--bs-btn-active-border-color)}.btn-check:checked+.btn:focus-visible,:not(.btn-check)+.btn:active:focus-visible,.btn:first-child:active:focus-visible,.btn.active:focus-visible,.btn.show:focus-visible{box-shadow:var(--bs-btn-focus-box-shadow)}.btn:disabled,.btn.disabled,fieldset:disabled 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#fff;--bs-btn-active-bg: #13967d;--bs-btn-active-border-color: #128d75;--bs-btn-active-shadow: inset 0 3px 5px rgba(0,0,0,0.125);--bs-btn-disabled-color: #fff;--bs-btn-disabled-bg: #18bc9c;--bs-btn-disabled-border-color: #18bc9c}.btn-info{--bs-btn-color: #fff;--bs-btn-bg: #3498db;--bs-btn-border-color: #3498db;--bs-btn-hover-color: #fff;--bs-btn-hover-bg: #2c81ba;--bs-btn-hover-border-color: #2a7aaf;--bs-btn-focus-shadow-rgb: 82,167,224;--bs-btn-active-color: #fff;--bs-btn-active-bg: #2a7aaf;--bs-btn-active-border-color: #2772a4;--bs-btn-active-shadow: inset 0 3px 5px rgba(0,0,0,0.125);--bs-btn-disabled-color: #fff;--bs-btn-disabled-bg: #3498db;--bs-btn-disabled-border-color: #3498db}.btn-warning{--bs-btn-color: #fff;--bs-btn-bg: #f39c12;--bs-btn-border-color: #f39c12;--bs-btn-hover-color: #fff;--bs-btn-hover-bg: #cf850f;--bs-btn-hover-border-color: #c27d0e;--bs-btn-focus-shadow-rgb: 245,171,54;--bs-btn-active-color: #fff;--bs-btn-active-bg: #c27d0e;--bs-btn-active-border-color: 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#95a5a6;--bs-btn-disabled-bg: transparent;--bs-btn-disabled-border-color: #95a5a6;--bs-btn-bg: transparent;--bs-gradient: none}.btn-outline-success{--bs-btn-color: #18bc9c;--bs-btn-border-color: #18bc9c;--bs-btn-hover-color: #fff;--bs-btn-hover-bg: #18bc9c;--bs-btn-hover-border-color: #18bc9c;--bs-btn-focus-shadow-rgb: 24,188,156;--bs-btn-active-color: #fff;--bs-btn-active-bg: #18bc9c;--bs-btn-active-border-color: #18bc9c;--bs-btn-active-shadow: inset 0 3px 5px rgba(0,0,0,0.125);--bs-btn-disabled-color: #18bc9c;--bs-btn-disabled-bg: transparent;--bs-btn-disabled-border-color: #18bc9c;--bs-btn-bg: transparent;--bs-gradient: none}.btn-outline-info{--bs-btn-color: #3498db;--bs-btn-border-color: #3498db;--bs-btn-hover-color: #fff;--bs-btn-hover-bg: #3498db;--bs-btn-hover-border-color: #3498db;--bs-btn-focus-shadow-rgb: 52,152,219;--bs-btn-active-color: #fff;--bs-btn-active-bg: #3498db;--bs-btn-active-border-color: #3498db;--bs-btn-active-shadow: inset 0 3px 5px 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inset 0 3px 5px rgba(0,0,0,0.125);--bs-btn-disabled-color: #e74c3c;--bs-btn-disabled-bg: transparent;--bs-btn-disabled-border-color: #e74c3c;--bs-btn-bg: transparent;--bs-gradient: none}.btn-outline-light{--bs-btn-color: #ecf0f1;--bs-btn-border-color: #ecf0f1;--bs-btn-hover-color: #000;--bs-btn-hover-bg: #ecf0f1;--bs-btn-hover-border-color: #ecf0f1;--bs-btn-focus-shadow-rgb: 236,240,241;--bs-btn-active-color: #000;--bs-btn-active-bg: #ecf0f1;--bs-btn-active-border-color: #ecf0f1;--bs-btn-active-shadow: inset 0 3px 5px rgba(0,0,0,0.125);--bs-btn-disabled-color: #ecf0f1;--bs-btn-disabled-bg: transparent;--bs-btn-disabled-border-color: #ecf0f1;--bs-btn-bg: transparent;--bs-gradient: none}.btn-outline-dark{--bs-btn-color: #7b8a8b;--bs-btn-border-color: #7b8a8b;--bs-btn-hover-color: #fff;--bs-btn-hover-bg: #7b8a8b;--bs-btn-hover-border-color: #7b8a8b;--bs-btn-focus-shadow-rgb: 123,138,139;--bs-btn-active-color: #fff;--bs-btn-active-bg: #7b8a8b;--bs-btn-active-border-color: #7b8a8b;--bs-btn-active-shadow: inset 0 3px 5px rgba(0,0,0,0.125);--bs-btn-disabled-color: #7b8a8b;--bs-btn-disabled-bg: transparent;--bs-btn-disabled-border-color: #7b8a8b;--bs-btn-bg: transparent;--bs-gradient: none}.btn-link{--bs-btn-font-weight: 400;--bs-btn-color: var(--bs-link-color);--bs-btn-bg: transparent;--bs-btn-border-color: transparent;--bs-btn-hover-color: var(--bs-link-hover-color);--bs-btn-hover-border-color: transparent;--bs-btn-active-color: var(--bs-link-hover-color);--bs-btn-active-border-color: transparent;--bs-btn-disabled-color: #95a5a6;--bs-btn-disabled-border-color: transparent;--bs-btn-box-shadow: 0 0 0 #000;--bs-btn-focus-shadow-rgb: 59,198,171;text-decoration:underline;-webkit-text-decoration:underline;-moz-text-decoration:underline;-ms-text-decoration:underline;-o-text-decoration:underline}.btn-link:focus-visible{color:var(--bs-btn-color)}.btn-link:hover{color:var(--bs-btn-hover-color)}.btn-lg,.btn-group-lg>.btn{--bs-btn-padding-y: .5rem;--bs-btn-padding-x: 1rem;--bs-btn-font-size:1.25rem;--bs-btn-border-radius: var(--bs-border-radius-lg)}.btn-sm,.btn-group-sm>.btn{--bs-btn-padding-y: .25rem;--bs-btn-padding-x: .5rem;--bs-btn-font-size:.875rem;--bs-btn-border-radius: var(--bs-border-radius-sm)}.fade{transition:opacity 0.15s linear}@media (prefers-reduced-motion: reduce){.fade{transition:none}}.fade:not(.show){opacity:0}.collapse:not(.show){display:none}.collapsing{height:0;overflow:hidden;transition:height 0.35s ease}@media (prefers-reduced-motion: reduce){.collapsing{transition:none}}.collapsing.collapse-horizontal{width:0;height:auto;transition:width 0.35s ease}@media (prefers-reduced-motion: reduce){.collapsing.collapse-horizontal{transition:none}}.dropup,.dropend,.dropdown,.dropstart,.dropup-center,.dropdown-center{position:relative}.dropdown-toggle{white-space:nowrap}.dropdown-toggle::after{display:inline-block;margin-left:.255em;vertical-align:.255em;content:"";border-top:.3em solid;border-right:.3em solid transparent;border-bottom:0;border-left:.3em solid transparent}.dropdown-toggle:empty::after{margin-left:0}.dropdown-menu{--bs-dropdown-zindex: 1000;--bs-dropdown-min-width: 10rem;--bs-dropdown-padding-x: 0;--bs-dropdown-padding-y: .5rem;--bs-dropdown-spacer: .125rem;--bs-dropdown-font-size:1rem;--bs-dropdown-color: var(--bs-body-color);--bs-dropdown-bg: var(--bs-body-bg);--bs-dropdown-border-color: var(--bs-border-color-translucent);--bs-dropdown-border-radius: var(--bs-border-radius);--bs-dropdown-border-width: var(--bs-border-width);--bs-dropdown-inner-border-radius: calc(var(--bs-border-radius) - var(--bs-border-width));--bs-dropdown-divider-bg: var(--bs-border-color-translucent);--bs-dropdown-divider-margin-y: .5rem;--bs-dropdown-box-shadow: 0 0.5rem 1rem rgba(0,0,0,0.15);--bs-dropdown-link-color: #7b8a8b;--bs-dropdown-link-hover-color: #fff;--bs-dropdown-link-hover-bg: #2c3e50;--bs-dropdown-link-active-color: #fff;--bs-dropdown-link-active-bg: #2c3e50;--bs-dropdown-link-disabled-color: var(--bs-tertiary-color);--bs-dropdown-item-padding-x: 1rem;--bs-dropdown-item-padding-y: .25rem;--bs-dropdown-header-color: #95a5a6;--bs-dropdown-header-padding-x: 1rem;--bs-dropdown-header-padding-y: .5rem;position:absolute;z-index:var(--bs-dropdown-zindex);display:none;min-width:var(--bs-dropdown-min-width);padding:var(--bs-dropdown-padding-y) var(--bs-dropdown-padding-x);margin:0;font-size:var(--bs-dropdown-font-size);color:var(--bs-dropdown-color);text-align:left;list-style:none;background-color:var(--bs-dropdown-bg);background-clip:padding-box;border:var(--bs-dropdown-border-width) solid var(--bs-dropdown-border-color);border-radius:var(--bs-dropdown-border-radius)}.dropdown-menu[data-bs-popper]{top:100%;left:0;margin-top:var(--bs-dropdown-spacer)}.dropdown-menu-start{--bs-position: start}.dropdown-menu-start[data-bs-popper]{right:auto;left:0}.dropdown-menu-end{--bs-position: end}.dropdown-menu-end[data-bs-popper]{right:0;left:auto}@media (min-width: 576px){.dropdown-menu-sm-start{--bs-position: start}.dropdown-menu-sm-start[data-bs-popper]{right:auto;left:0}.dropdown-menu-sm-end{--bs-position: end}.dropdown-menu-sm-end[data-bs-popper]{right:0;left:auto}}@media (min-width: 768px){.dropdown-menu-md-start{--bs-position: start}.dropdown-menu-md-start[data-bs-popper]{right:auto;left:0}.dropdown-menu-md-end{--bs-position: end}.dropdown-menu-md-end[data-bs-popper]{right:0;left:auto}}@media (min-width: 992px){.dropdown-menu-lg-start{--bs-position: start}.dropdown-menu-lg-start[data-bs-popper]{right:auto;left:0}.dropdown-menu-lg-end{--bs-position: end}.dropdown-menu-lg-end[data-bs-popper]{right:0;left:auto}}@media (min-width: 1200px){.dropdown-menu-xl-start{--bs-position: start}.dropdown-menu-xl-start[data-bs-popper]{right:auto;left:0}.dropdown-menu-xl-end{--bs-position: end}.dropdown-menu-xl-end[data-bs-popper]{right:0;left:auto}}@media (min-width: 1400px){.dropdown-menu-xxl-start{--bs-position: start}.dropdown-menu-xxl-start[data-bs-popper]{right:auto;left:0}.dropdown-menu-xxl-end{--bs-position: end}.dropdown-menu-xxl-end[data-bs-popper]{right:0;left:auto}}.dropup .dropdown-menu[data-bs-popper]{top:auto;bottom:100%;margin-top:0;margin-bottom:var(--bs-dropdown-spacer)}.dropup .dropdown-toggle::after{display:inline-block;margin-left:.255em;vertical-align:.255em;content:"";border-top:0;border-right:.3em solid transparent;border-bottom:.3em solid;border-left:.3em solid transparent}.dropup .dropdown-toggle:empty::after{margin-left:0}.dropend .dropdown-menu[data-bs-popper]{top:0;right:auto;left:100%;margin-top:0;margin-left:var(--bs-dropdown-spacer)}.dropend .dropdown-toggle::after{display:inline-block;margin-left:.255em;vertical-align:.255em;content:"";border-top:.3em solid transparent;border-right:0;border-bottom:.3em solid transparent;border-left:.3em solid}.dropend .dropdown-toggle:empty::after{margin-left:0}.dropend .dropdown-toggle::after{vertical-align:0}.dropstart .dropdown-menu[data-bs-popper]{top:0;right:100%;left:auto;margin-top:0;margin-right:var(--bs-dropdown-spacer)}.dropstart .dropdown-toggle::after{display:inline-block;margin-left:.255em;vertical-align:.255em;content:""}.dropstart .dropdown-toggle::after{display:none}.dropstart .dropdown-toggle::before{display:inline-block;margin-right:.255em;vertical-align:.255em;content:"";border-top:.3em solid transparent;border-right:.3em solid;border-bottom:.3em solid transparent}.dropstart .dropdown-toggle:empty::after{margin-left:0}.dropstart .dropdown-toggle::before{vertical-align:0}.dropdown-divider{height:0;margin:var(--bs-dropdown-divider-margin-y) 0;overflow:hidden;border-top:1px solid var(--bs-dropdown-divider-bg);opacity:1}.dropdown-item{display:block;width:100%;padding:var(--bs-dropdown-item-padding-y) 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var(--bs-dropdown-header-padding-x);margin-bottom:0;font-size:.875rem;color:var(--bs-dropdown-header-color);white-space:nowrap}.dropdown-item-text{display:block;padding:var(--bs-dropdown-item-padding-y) var(--bs-dropdown-item-padding-x);color:var(--bs-dropdown-link-color)}.dropdown-menu-dark{--bs-dropdown-color: #dee2e6;--bs-dropdown-bg: #343a40;--bs-dropdown-border-color: var(--bs-border-color-translucent);--bs-dropdown-box-shadow: ;--bs-dropdown-link-color: #dee2e6;--bs-dropdown-link-hover-color: #fff;--bs-dropdown-divider-bg: var(--bs-border-color-translucent);--bs-dropdown-link-hover-bg: rgba(255,255,255,0.15);--bs-dropdown-link-active-color: #fff;--bs-dropdown-link-active-bg: #2c3e50;--bs-dropdown-link-disabled-color: #b4bcc2;--bs-dropdown-header-color: #b4bcc2}.btn-group,.btn-group-vertical{position:relative;display:inline-flex;vertical-align:middle}.btn-group>.btn,.btn-group-vertical>.btn{position:relative;flex:1 1 auto;-webkit-flex:1 1 auto}.btn-group>.btn-check:checked+.btn,.btn-group>.btn-check:focus+.btn,.btn-group>.btn:hover,.btn-group>.btn:focus,.btn-group>.btn:active,.btn-group>.btn.active,.btn-group-vertical>.btn-check:checked+.btn,.btn-group-vertical>.btn-check:focus+.btn,.btn-group-vertical>.btn:hover,.btn-group-vertical>.btn:focus,.btn-group-vertical>.btn:active,.btn-group-vertical>.btn.active{z-index:1}.btn-toolbar{display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;justify-content:flex-start;-webkit-justify-content:flex-start}.btn-toolbar .input-group{width:auto}.btn-group{border-radius:var(--bs-border-radius)}.btn-group>:not(.btn-check:first-child)+.btn,.btn-group>.btn-group:not(:first-child){margin-left:calc(var(--bs-border-width) * -1)}.btn-group>.btn:not(:last-child):not(.dropdown-toggle),.btn-group>.btn.dropdown-toggle-split:first-child,.btn-group>.btn-group:not(:last-child)>.btn{border-top-right-radius:0;border-bottom-right-radius:0}.btn-group>.btn:nth-child(n + 3),.btn-group>:not(.btn-check)+.btn,.btn-group>.btn-group:not(:first-child)>.btn{border-top-left-radius:0;border-bottom-left-radius:0}.dropdown-toggle-split{padding-right:.5625rem;padding-left:.5625rem}.dropdown-toggle-split::after,.dropup .dropdown-toggle-split::after,.dropend .dropdown-toggle-split::after{margin-left:0}.dropstart .dropdown-toggle-split::before{margin-right:0}.btn-sm+.dropdown-toggle-split,.btn-group-sm>.btn+.dropdown-toggle-split{padding-right:.375rem;padding-left:.375rem}.btn-lg+.dropdown-toggle-split,.btn-group-lg>.btn+.dropdown-toggle-split{padding-right:.75rem;padding-left:.75rem}.btn-group-vertical{flex-direction:column;-webkit-flex-direction:column;align-items:flex-start;-webkit-align-items:flex-start;justify-content:center;-webkit-justify-content:center}.btn-group-vertical>.btn,.btn-group-vertical>.btn-group{width:100%}.btn-group-vertical>.btn:not(:first-child),.btn-group-vertical>.btn-group:not(:first-child){margin-top:calc(var(--bs-border-width) * -1)}.btn-group-vertical>.btn:not(:last-child):not(.dropdown-toggle),.btn-group-vertical>.btn-group:not(:last-child)>.btn{border-bottom-right-radius:0;border-bottom-left-radius:0}.btn-group-vertical>.btn~.btn,.btn-group-vertical>.btn-group:not(:first-child)>.btn{border-top-left-radius:0;border-top-right-radius:0}.nav{--bs-nav-link-padding-x: 2rem;--bs-nav-link-padding-y: .5rem;--bs-nav-link-font-weight: ;--bs-nav-link-color: var(--bs-link-color);--bs-nav-link-hover-color: var(--bs-link-hover-color);--bs-nav-link-disabled-color: #95a5a6;display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;padding-left:0;margin-bottom:0;list-style:none}.nav-link{display:block;padding:var(--bs-nav-link-padding-y) var(--bs-nav-link-padding-x);font-size:var(--bs-nav-link-font-size);font-weight:var(--bs-nav-link-font-weight);color:var(--bs-nav-link-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background:none;border:0;transition:color 0.15s ease-in-out,background-color 0.15s ease-in-out,border-color 0.15s ease-in-out}@media (prefers-reduced-motion: reduce){.nav-link{transition:none}}.nav-link:hover,.nav-link:focus{color:var(--bs-nav-link-hover-color)}.nav-link:focus-visible{outline:0;box-shadow:0 0 0 .25rem rgba(44,62,80,0.25)}.nav-link.disabled,.nav-link:disabled{color:var(--bs-nav-link-disabled-color);pointer-events:none;cursor:default}.nav-tabs{--bs-nav-tabs-border-width: var(--bs-border-width);--bs-nav-tabs-border-color: #ecf0f1;--bs-nav-tabs-border-radius: var(--bs-border-radius);--bs-nav-tabs-link-hover-border-color: var(--bs-secondary-bg) var(--bs-secondary-bg) #ecf0f1;--bs-nav-tabs-link-active-color: var(--bs-emphasis-color);--bs-nav-tabs-link-active-bg: var(--bs-body-bg);--bs-nav-tabs-link-active-border-color: var(--bs-border-color) var(--bs-border-color) var(--bs-body-bg);border-bottom:var(--bs-nav-tabs-border-width) solid var(--bs-nav-tabs-border-color)}.nav-tabs .nav-link{margin-bottom:calc(-1 * var(--bs-nav-tabs-border-width));border:var(--bs-nav-tabs-border-width) solid transparent;border-top-left-radius:var(--bs-nav-tabs-border-radius);border-top-right-radius:var(--bs-nav-tabs-border-radius)}.nav-tabs .nav-link:hover,.nav-tabs .nav-link:focus{isolation:isolate;border-color:var(--bs-nav-tabs-link-hover-border-color)}.nav-tabs .nav-link.active,.nav-tabs .nav-item.show .nav-link{color:var(--bs-nav-tabs-link-active-color);background-color:var(--bs-nav-tabs-link-active-bg);border-color:var(--bs-nav-tabs-link-active-border-color)}.nav-tabs .dropdown-menu{margin-top:calc(-1 * var(--bs-nav-tabs-border-width));border-top-left-radius:0;border-top-right-radius:0}.nav-pills{--bs-nav-pills-border-radius: var(--bs-border-radius);--bs-nav-pills-link-active-color: #fff;--bs-nav-pills-link-active-bg: #2c3e50}.nav-pills .nav-link{border-radius:var(--bs-nav-pills-border-radius)}.nav-pills .nav-link.active,.nav-pills .show>.nav-link{color:var(--bs-nav-pills-link-active-color);background-color:var(--bs-nav-pills-link-active-bg)}.nav-underline{--bs-nav-underline-gap: 1rem;--bs-nav-underline-border-width: .125rem;--bs-nav-underline-link-active-color: var(--bs-emphasis-color);gap:var(--bs-nav-underline-gap)}.nav-underline .nav-link{padding-right:0;padding-left:0;border-bottom:var(--bs-nav-underline-border-width) solid transparent}.nav-underline .nav-link:hover,.nav-underline .nav-link:focus{border-bottom-color:currentcolor}.nav-underline .nav-link.active,.nav-underline 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var(--bs-navbar-hover-color);--bs-nav-link-disabled-color: var(--bs-navbar-disabled-color);display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;padding-left:0;margin-bottom:0;list-style:none}.navbar-nav .nav-link.active,.navbar-nav .nav-link.show{color:var(--bs-navbar-active-color)}.navbar-nav .dropdown-menu{position:static}.navbar-text{padding-top:.5rem;padding-bottom:.5rem;color:var(--bs-navbar-color)}.navbar-text a,.navbar-text a:hover,.navbar-text a:focus{color:var(--bs-navbar-active-color)}.navbar-collapse{flex-basis:100%;-webkit-flex-basis:100%;flex-grow:1;-webkit-flex-grow:1;align-items:center;-webkit-align-items:center}.navbar-toggler{padding:var(--bs-navbar-toggler-padding-y) var(--bs-navbar-toggler-padding-x);font-size:var(--bs-navbar-toggler-font-size);line-height:1;color:var(--bs-navbar-color);background-color:transparent;border:var(--bs-border-width) solid 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.navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand-md .navbar-nav .dropdown-menu{position:absolute}.navbar-expand-md .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand-md .navbar-nav-scroll{overflow:visible}.navbar-expand-md .navbar-collapse{display:flex !important;display:-webkit-flex !important;flex-basis:auto;-webkit-flex-basis:auto}.navbar-expand-md .navbar-toggler{display:none}.navbar-expand-md .offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:transparent !important;border:0 !important;transform:none !important;transition:none}.navbar-expand-md .offcanvas .offcanvas-header{display:none}.navbar-expand-md .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}}@media (min-width: 992px){.navbar-expand-lg{flex-wrap:nowrap;-webkit-flex-wrap:nowrap;justify-content:flex-start;-webkit-justify-content:flex-start}.navbar-expand-lg .navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand-lg .navbar-nav .dropdown-menu{position:absolute}.navbar-expand-lg .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand-lg .navbar-nav-scroll{overflow:visible}.navbar-expand-lg .navbar-collapse{display:flex !important;display:-webkit-flex !important;flex-basis:auto;-webkit-flex-basis:auto}.navbar-expand-lg .navbar-toggler{display:none}.navbar-expand-lg .offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:transparent !important;border:0 !important;transform:none !important;transition:none}.navbar-expand-lg .offcanvas .offcanvas-header{display:none}.navbar-expand-lg .offcanvas 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!important;transform:none !important;transition:none}.navbar-expand-xl .offcanvas .offcanvas-header{display:none}.navbar-expand-xl .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}}@media (min-width: 1400px){.navbar-expand-xxl{flex-wrap:nowrap;-webkit-flex-wrap:nowrap;justify-content:flex-start;-webkit-justify-content:flex-start}.navbar-expand-xxl .navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand-xxl .navbar-nav .dropdown-menu{position:absolute}.navbar-expand-xxl .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand-xxl .navbar-nav-scroll{overflow:visible}.navbar-expand-xxl .navbar-collapse{display:flex !important;display:-webkit-flex !important;flex-basis:auto;-webkit-flex-basis:auto}.navbar-expand-xxl .navbar-toggler{display:none}.navbar-expand-xxl .offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:transparent !important;border:0 !important;transform:none !important;transition:none}.navbar-expand-xxl .offcanvas .offcanvas-header{display:none}.navbar-expand-xxl .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}}.navbar-expand{flex-wrap:nowrap;-webkit-flex-wrap:nowrap;justify-content:flex-start;-webkit-justify-content:flex-start}.navbar-expand .navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand .navbar-nav .dropdown-menu{position:absolute}.navbar-expand .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand .navbar-nav-scroll{overflow:visible}.navbar-expand .navbar-collapse{display:flex !important;display:-webkit-flex !important;flex-basis:auto;-webkit-flex-basis:auto}.navbar-expand .navbar-toggler{display:none}.navbar-expand .offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:transparent !important;border:0 !important;transform:none !important;transition:none}.navbar-expand .offcanvas .offcanvas-header{display:none}.navbar-expand .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}.navbar-dark,.navbar[data-bs-theme="dark"]{--bs-navbar-color: #fff;--bs-navbar-hover-color: #2c3e50;--bs-navbar-disabled-color: rgba(255,255,255,0.25);--bs-navbar-active-color: #2c3e50;--bs-navbar-brand-color: #fff;--bs-navbar-brand-hover-color: #fff;--bs-navbar-toggler-border-color: rgba(255,255,255,0.1);--bs-navbar-toggler-icon-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'%3e%3cpath stroke='rgba%28255,255,255,0.75%29' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/%3e%3c/svg%3e")}[data-bs-theme="dark"] .navbar-toggler-icon{--bs-navbar-toggler-icon-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'%3e%3cpath stroke='rgba%28255,255,255,0.75%29' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/%3e%3c/svg%3e")}.card{--bs-card-spacer-y: 1rem;--bs-card-spacer-x: 1rem;--bs-card-title-spacer-y: .5rem;--bs-card-title-color: ;--bs-card-subtitle-color: ;--bs-card-border-width: var(--bs-border-width);--bs-card-border-color: var(--bs-border-color-translucent);--bs-card-border-radius: var(--bs-border-radius);--bs-card-box-shadow: ;--bs-card-inner-border-radius: calc(var(--bs-border-radius) - (var(--bs-border-width)));--bs-card-cap-padding-y: .5rem;--bs-card-cap-padding-x: 1rem;--bs-card-cap-bg: rgba(var(--bs-body-color-rgb), 0.03);--bs-card-cap-color: ;--bs-card-height: ;--bs-card-color: ;--bs-card-bg: var(--bs-body-bg);--bs-card-img-overlay-padding: 1rem;--bs-card-group-margin: .75rem;position:relative;display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;min-width:0;height:var(--bs-card-height);color:var(--bs-body-color);word-wrap:break-word;background-color:var(--bs-card-bg);background-clip:border-box;border:var(--bs-card-border-width) solid var(--bs-card-border-color);border-radius:var(--bs-card-border-radius)}.card>hr{margin-right:0;margin-left:0}.card>.list-group{border-top:inherit;border-bottom:inherit}.card>.list-group:first-child{border-top-width:0;border-top-left-radius:var(--bs-card-inner-border-radius);border-top-right-radius:var(--bs-card-inner-border-radius)}.card>.list-group:last-child{border-bottom-width:0;border-bottom-right-radius:var(--bs-card-inner-border-radius);border-bottom-left-radius:var(--bs-card-inner-border-radius)}.card>.card-header+.list-group,.card>.list-group+.card-footer{border-top:0}.card-body{flex:1 1 auto;-webkit-flex:1 1 auto;padding:var(--bs-card-spacer-y) var(--bs-card-spacer-x);color:var(--bs-card-color)}.card-title{margin-bottom:var(--bs-card-title-spacer-y);color:var(--bs-card-title-color)}.card-subtitle{margin-top:calc(-.5 * var(--bs-card-title-spacer-y));margin-bottom:0;color:var(--bs-card-subtitle-color)}.card-text:last-child{margin-bottom:0}.card-link+.card-link{margin-left:var(--bs-card-spacer-x)}.card-header{padding:var(--bs-card-cap-padding-y) var(--bs-card-cap-padding-x);margin-bottom:0;color:var(--bs-card-cap-color);background-color:var(--bs-card-cap-bg);border-bottom:var(--bs-card-border-width) solid var(--bs-card-border-color)}.card-header:first-child{border-radius:var(--bs-card-inner-border-radius) var(--bs-card-inner-border-radius) 0 0}.card-footer{padding:var(--bs-card-cap-padding-y) var(--bs-card-cap-padding-x);color:var(--bs-card-cap-color);background-color:var(--bs-card-cap-bg);border-top:var(--bs-card-border-width) solid var(--bs-card-border-color)}.card-footer:last-child{border-radius:0 0 var(--bs-card-inner-border-radius) var(--bs-card-inner-border-radius)}.card-header-tabs{margin-right:calc(-.5 * var(--bs-card-cap-padding-x));margin-bottom:calc(-1 * 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wrap;-webkit-flex-flow:row wrap}.card-group>.card{flex:1 0 0%;-webkit-flex:1 0 0%;margin-bottom:0}.card-group>.card+.card{margin-left:0;border-left:0}.card-group>.card:not(:last-child){border-top-right-radius:0;border-bottom-right-radius:0}.card-group>.card:not(:last-child) .card-img-top,.card-group>.card:not(:last-child) .card-header{border-top-right-radius:0}.card-group>.card:not(:last-child) .card-img-bottom,.card-group>.card:not(:last-child) .card-footer{border-bottom-right-radius:0}.card-group>.card:not(:first-child){border-top-left-radius:0;border-bottom-left-radius:0}.card-group>.card:not(:first-child) .card-img-top,.card-group>.card:not(:first-child) .card-header{border-top-left-radius:0}.card-group>.card:not(:first-child) .card-img-bottom,.card-group>.card:not(:first-child) .card-footer{border-bottom-left-radius:0}}.accordion{--bs-accordion-color: var(--bs-body-color);--bs-accordion-bg: var(--bs-body-bg);--bs-accordion-transition: color 0.15s ease-in-out,background-color 0.15s ease-in-out,border-color 0.15s ease-in-out,box-shadow 0.15s ease-in-out,border-radius 0.15s ease;--bs-accordion-border-color: var(--bs-border-color);--bs-accordion-border-width: var(--bs-border-width);--bs-accordion-border-radius: var(--bs-border-radius);--bs-accordion-inner-border-radius: calc(var(--bs-border-radius) - (var(--bs-border-width)));--bs-accordion-btn-padding-x: 1.25rem;--bs-accordion-btn-padding-y: 1rem;--bs-accordion-btn-color: var(--bs-body-color);--bs-accordion-btn-bg: var(--bs-accordion-bg);--bs-accordion-btn-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23212529'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-icon-width: 1.25rem;--bs-accordion-btn-icon-transform: rotate(-180deg);--bs-accordion-btn-icon-transition: transform 0.2s ease-in-out;--bs-accordion-btn-active-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23121920'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-focus-border-color: #969fa8;--bs-accordion-btn-focus-box-shadow: 0 0 0 .25rem rgba(44,62,80,0.25);--bs-accordion-body-padding-x: 1.25rem;--bs-accordion-body-padding-y: 1rem;--bs-accordion-active-color: var(--bs-primary-text-emphasis);--bs-accordion-active-bg: var(--bs-primary-bg-subtle)}.accordion-button{position:relative;display:flex;display:-webkit-flex;align-items:center;-webkit-align-items:center;width:100%;padding:var(--bs-accordion-btn-padding-y) var(--bs-accordion-btn-padding-x);font-size:1rem;color:var(--bs-accordion-btn-color);text-align:left;background-color:var(--bs-accordion-btn-bg);border:0;border-radius:0;overflow-anchor:none;transition:var(--bs-accordion-transition)}@media (prefers-reduced-motion: reduce){.accordion-button{transition:none}}.accordion-button:not(.collapsed){color:var(--bs-accordion-active-color);background-color:var(--bs-accordion-active-bg);box-shadow:inset 0 calc(-1 * var(--bs-accordion-border-width)) 0 var(--bs-accordion-border-color)}.accordion-button:not(.collapsed)::after{background-image:var(--bs-accordion-btn-active-icon);transform:var(--bs-accordion-btn-icon-transform)}.accordion-button::after{flex-shrink:0;-webkit-flex-shrink:0;width:var(--bs-accordion-btn-icon-width);height:var(--bs-accordion-btn-icon-width);margin-left:auto;content:"";background-image:var(--bs-accordion-btn-icon);background-repeat:no-repeat;background-size:var(--bs-accordion-btn-icon-width);transition:var(--bs-accordion-btn-icon-transition)}@media (prefers-reduced-motion: reduce){.accordion-button::after{transition:none}}.accordion-button:hover{z-index:2}.accordion-button:focus{z-index:3;border-color:var(--bs-accordion-btn-focus-border-color);outline:0;box-shadow:var(--bs-accordion-btn-focus-box-shadow)}.accordion-header{margin-bottom:0}.accordion-item{color:var(--bs-accordion-color);background-color:var(--bs-accordion-bg);border:var(--bs-accordion-border-width) solid var(--bs-accordion-border-color)}.accordion-item:first-of-type{border-top-left-radius:var(--bs-accordion-border-radius);border-top-right-radius:var(--bs-accordion-border-radius)}.accordion-item:first-of-type .accordion-button{border-top-left-radius:var(--bs-accordion-inner-border-radius);border-top-right-radius:var(--bs-accordion-inner-border-radius)}.accordion-item:not(:first-of-type){border-top:0}.accordion-item:last-of-type{border-bottom-right-radius:var(--bs-accordion-border-radius);border-bottom-left-radius:var(--bs-accordion-border-radius)}.accordion-item:last-of-type .accordion-button.collapsed{border-bottom-right-radius:var(--bs-accordion-inner-border-radius);border-bottom-left-radius:var(--bs-accordion-inner-border-radius)}.accordion-item:last-of-type .accordion-collapse{border-bottom-right-radius:var(--bs-accordion-border-radius);border-bottom-left-radius:var(--bs-accordion-border-radius)}.accordion-body{padding:var(--bs-accordion-body-padding-y) var(--bs-accordion-body-padding-x)}.accordion-flush .accordion-collapse{border-width:0}.accordion-flush .accordion-item{border-right:0;border-left:0;border-radius:0}.accordion-flush .accordion-item:first-child{border-top:0}.accordion-flush .accordion-item:last-child{border-bottom:0}.accordion-flush .accordion-item .accordion-button,.accordion-flush .accordion-item .accordion-button.collapsed{border-radius:0}[data-bs-theme="dark"] .accordion-button::after{--bs-accordion-btn-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23808b96'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-active-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23808b96'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e")}.breadcrumb{--bs-breadcrumb-padding-x: .75rem;--bs-breadcrumb-padding-y: .375rem;--bs-breadcrumb-margin-bottom: 1rem;--bs-breadcrumb-bg: ;--bs-breadcrumb-border-radius: .25rem;--bs-breadcrumb-divider-color: var(--bs-secondary-color);--bs-breadcrumb-item-padding-x: .5rem;--bs-breadcrumb-item-active-color: var(--bs-secondary-color);display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;padding:var(--bs-breadcrumb-padding-y) var(--bs-breadcrumb-padding-x);margin-bottom:var(--bs-breadcrumb-margin-bottom);font-size:var(--bs-breadcrumb-font-size);list-style:none;background-color:var(--bs-breadcrumb-bg);border-radius:var(--bs-breadcrumb-border-radius)}.breadcrumb-item+.breadcrumb-item{padding-left:var(--bs-breadcrumb-item-padding-x)}.breadcrumb-item+.breadcrumb-item::before{float:left;padding-right:var(--bs-breadcrumb-item-padding-x);color:var(--bs-breadcrumb-divider-color);content:var(--bs-breadcrumb-divider, "/") /* rtl: var(--bs-breadcrumb-divider, "/") */}.breadcrumb-item.active{color:var(--bs-breadcrumb-item-active-color)}.pagination{--bs-pagination-padding-x: .75rem;--bs-pagination-padding-y: .375rem;--bs-pagination-font-size:1rem;--bs-pagination-color: #fff;--bs-pagination-bg: #18bc9c;--bs-pagination-border-width: 0;--bs-pagination-border-color: rgba(0,0,0,0);--bs-pagination-border-radius: var(--bs-border-radius);--bs-pagination-hover-color: #fff;--bs-pagination-hover-bg: #0f7864;--bs-pagination-hover-border-color: rgba(0,0,0,0);--bs-pagination-focus-color: var(--bs-link-hover-color);--bs-pagination-focus-bg: var(--bs-secondary-bg);--bs-pagination-focus-box-shadow: 0 0 0 .25rem rgba(44,62,80,0.25);--bs-pagination-active-color: #fff;--bs-pagination-active-bg: #0f7864;--bs-pagination-active-border-color: rgba(0,0,0,0);--bs-pagination-disabled-color: #ecf0f1;--bs-pagination-disabled-bg: #3be6c4;--bs-pagination-disabled-border-color: rgba(0,0,0,0);display:flex;display:-webkit-flex;padding-left:0;list-style:none}.page-link{position:relative;display:block;padding:var(--bs-pagination-padding-y) var(--bs-pagination-padding-x);font-size:var(--bs-pagination-font-size);color:var(--bs-pagination-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background-color:var(--bs-pagination-bg);border:var(--bs-pagination-border-width) solid var(--bs-pagination-border-color);transition:color 0.15s ease-in-out,background-color 0.15s ease-in-out,border-color 0.15s ease-in-out,box-shadow 0.15s ease-in-out}@media (prefers-reduced-motion: reduce){.page-link{transition:none}}.page-link:hover{z-index:2;color:var(--bs-pagination-hover-color);background-color:var(--bs-pagination-hover-bg);border-color:var(--bs-pagination-hover-border-color)}.page-link:focus{z-index:3;color:var(--bs-pagination-focus-color);background-color:var(--bs-pagination-focus-bg);outline:0;box-shadow:var(--bs-pagination-focus-box-shadow)}.page-link.active,.active>.page-link{z-index:3;color:var(--bs-pagination-active-color);background-color:var(--bs-pagination-active-bg);border-color:var(--bs-pagination-active-border-color)}.page-link.disabled,.disabled>.page-link{color:var(--bs-pagination-disabled-color);pointer-events:none;background-color:var(--bs-pagination-disabled-bg);border-color:var(--bs-pagination-disabled-border-color)}.page-item:not(:first-child) .page-link{margin-left:calc(0 * -1)}.page-item:first-child .page-link{border-top-left-radius:var(--bs-pagination-border-radius);border-bottom-left-radius:var(--bs-pagination-border-radius)}.page-item:last-child .page-link{border-top-right-radius:var(--bs-pagination-border-radius);border-bottom-right-radius:var(--bs-pagination-border-radius)}.pagination-lg{--bs-pagination-padding-x: 1.5rem;--bs-pagination-padding-y: .75rem;--bs-pagination-font-size:1.25rem;--bs-pagination-border-radius: var(--bs-border-radius-lg)}.pagination-sm{--bs-pagination-padding-x: .5rem;--bs-pagination-padding-y: .25rem;--bs-pagination-font-size:.875rem;--bs-pagination-border-radius: var(--bs-border-radius-sm)}.badge{--bs-badge-padding-x: .65em;--bs-badge-padding-y: .35em;--bs-badge-font-size:.75em;--bs-badge-font-weight: 700;--bs-badge-color: #fff;--bs-badge-border-radius: var(--bs-border-radius);display:inline-block;padding:var(--bs-badge-padding-y) var(--bs-badge-padding-x);font-size:var(--bs-badge-font-size);font-weight:var(--bs-badge-font-weight);line-height:1;color:var(--bs-badge-color);text-align:center;white-space:nowrap;vertical-align:baseline;border-radius:var(--bs-badge-border-radius)}.badge:empty{display:none}.btn .badge{position:relative;top:-1px}.alert{--bs-alert-bg: transparent;--bs-alert-padding-x: 1rem;--bs-alert-padding-y: 1rem;--bs-alert-margin-bottom: 1rem;--bs-alert-color: inherit;--bs-alert-border-color: transparent;--bs-alert-border: var(--bs-border-width) solid var(--bs-alert-border-color);--bs-alert-border-radius: var(--bs-border-radius);--bs-alert-link-color: inherit;position:relative;padding:var(--bs-alert-padding-y) var(--bs-alert-padding-x);margin-bottom:var(--bs-alert-margin-bottom);color:var(--bs-alert-color);background-color:var(--bs-alert-bg);border:var(--bs-alert-border);border-radius:var(--bs-alert-border-radius)}.alert-heading{color:inherit}.alert-link{font-weight:700;color:var(--bs-alert-link-color)}.alert-dismissible{padding-right:3rem}.alert-dismissible .btn-close{position:absolute;top:0;right:0;z-index:2;padding:1.25rem 1rem}.alert-default{--bs-alert-color: var(--bs-default-text-emphasis);--bs-alert-bg: var(--bs-default-bg-subtle);--bs-alert-border-color: var(--bs-default-border-subtle);--bs-alert-link-color: var(--bs-default-text-emphasis)}.alert-primary{--bs-alert-color: var(--bs-primary-text-emphasis);--bs-alert-bg: var(--bs-primary-bg-subtle);--bs-alert-border-color: var(--bs-primary-border-subtle);--bs-alert-link-color: var(--bs-primary-text-emphasis)}.alert-secondary{--bs-alert-color: var(--bs-secondary-text-emphasis);--bs-alert-bg: var(--bs-secondary-bg-subtle);--bs-alert-border-color: var(--bs-secondary-border-subtle);--bs-alert-link-color: var(--bs-secondary-text-emphasis)}.alert-success{--bs-alert-color: var(--bs-success-text-emphasis);--bs-alert-bg: var(--bs-success-bg-subtle);--bs-alert-border-color: var(--bs-success-border-subtle);--bs-alert-link-color: var(--bs-success-text-emphasis)}.alert-info{--bs-alert-color: var(--bs-info-text-emphasis);--bs-alert-bg: var(--bs-info-bg-subtle);--bs-alert-border-color: var(--bs-info-border-subtle);--bs-alert-link-color: var(--bs-info-text-emphasis)}.alert-warning{--bs-alert-color: var(--bs-warning-text-emphasis);--bs-alert-bg: var(--bs-warning-bg-subtle);--bs-alert-border-color: var(--bs-warning-border-subtle);--bs-alert-link-color: var(--bs-warning-text-emphasis)}.alert-danger{--bs-alert-color: var(--bs-danger-text-emphasis);--bs-alert-bg: var(--bs-danger-bg-subtle);--bs-alert-border-color: var(--bs-danger-border-subtle);--bs-alert-link-color: var(--bs-danger-text-emphasis)}.alert-light{--bs-alert-color: var(--bs-light-text-emphasis);--bs-alert-bg: var(--bs-light-bg-subtle);--bs-alert-border-color: var(--bs-light-border-subtle);--bs-alert-link-color: var(--bs-light-text-emphasis)}.alert-dark{--bs-alert-color: var(--bs-dark-text-emphasis);--bs-alert-bg: var(--bs-dark-bg-subtle);--bs-alert-border-color: var(--bs-dark-border-subtle);--bs-alert-link-color: var(--bs-dark-text-emphasis)}@keyframes progress-bar-stripes{0%{background-position-x:1rem}}.progress,.progress-stacked{--bs-progress-height: 1rem;--bs-progress-font-size:.75rem;--bs-progress-bg: var(--bs-secondary-bg);--bs-progress-border-radius: var(--bs-border-radius);--bs-progress-box-shadow: var(--bs-box-shadow-inset);--bs-progress-bar-color: #fff;--bs-progress-bar-bg: #2c3e50;--bs-progress-bar-transition: width 0.6s ease;display:flex;display:-webkit-flex;height:var(--bs-progress-height);overflow:hidden;font-size:var(--bs-progress-font-size);background-color:var(--bs-progress-bg);border-radius:var(--bs-progress-border-radius)}.progress-bar{display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;justify-content:center;-webkit-justify-content:center;overflow:hidden;color:var(--bs-progress-bar-color);text-align:center;white-space:nowrap;background-color:var(--bs-progress-bar-bg);transition:var(--bs-progress-bar-transition)}@media (prefers-reduced-motion: reduce){.progress-bar{transition:none}}.progress-bar-striped{background-image:linear-gradient(45deg, rgba(255,255,255,0.15) 25%, transparent 25%, transparent 50%, rgba(255,255,255,0.15) 50%, rgba(255,255,255,0.15) 75%, transparent 75%, transparent);background-size:var(--bs-progress-height) var(--bs-progress-height)}.progress-stacked>.progress{overflow:visible}.progress-stacked>.progress>.progress-bar{width:100%}.progress-bar-animated{animation:1s linear infinite progress-bar-stripes}@media (prefers-reduced-motion: reduce){.progress-bar-animated{animation:none}}.list-group{--bs-list-group-color: var(--bs-body-color);--bs-list-group-bg: var(--bs-body-bg);--bs-list-group-border-color: var(--bs-border-color);--bs-list-group-border-width: var(--bs-border-width);--bs-list-group-border-radius: var(--bs-border-radius);--bs-list-group-item-padding-x: 1rem;--bs-list-group-item-padding-y: .5rem;--bs-list-group-action-color: var(--bs-secondary-color);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: #ecf0f1;--bs-list-group-action-active-color: var(--bs-body-color);--bs-list-group-action-active-bg: var(--bs-secondary-bg);--bs-list-group-disabled-color: var(--bs-secondary-color);--bs-list-group-disabled-bg: 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new file mode 100644
index 000000000..c628326a8
--- /dev/null
+++ b/deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js
@@ -0,0 +1,5 @@
+/*!
+ * Bootstrap Table of Contents v1.0.1 (http://afeld.github.io/bootstrap-toc/)
+ * Copyright 2015 Aidan Feldman
+ * Licensed under MIT (https://github.com/afeld/bootstrap-toc/blob/gh-pages/LICENSE.md) */
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diff --git a/deps/clipboard.js-2.0.11/clipboard.min.js b/deps/clipboard.js-2.0.11/clipboard.min.js
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index 000000000..1103f811e
--- /dev/null
+++ b/deps/clipboard.js-2.0.11/clipboard.min.js
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+/*!
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+ * https://clipboardjs.com/
+ *
+ * Licensed MIT © Zeno Rocha
+ */
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e,n="SELECT"===t.nodeName?(t.focus(),t.value):"INPUT"===t.nodeName||"TEXTAREA"===t.nodeName?((e=t.hasAttribute("readonly"))||t.setAttribute("readonly",""),t.select(),t.setSelectionRange(0,t.value.length),e||t.removeAttribute("readonly"),t.value):(t.hasAttribute("contenteditable")&&t.focus(),n=window.getSelection(),(e=document.createRange()).selectNodeContents(t),n.removeAllRanges(),n.addRange(e),n.toString());return n}},279:function(t){function e(){}e.prototype={on:function(t,e,n){var o=this.e||(this.e={});return(o[t]||(o[t]=[])).push({fn:e,ctx:n}),this},once:function(t,e,n){var o=this;function r(){o.off(t,r),e.apply(n,arguments)}return r._=e,this.on(t,r,n)},emit:function(t){for(var e=[].slice.call(arguments,1),n=((this.e||(this.e={}))[t]||[]).slice(),o=0,r=n.length;o<r;o++)n[o].fn.apply(n[o].ctx,e);return this},off:function(t,e){var n=this.e||(this.e={}),o=n[t],r=[];if(o&&e)for(var i=0,u=o.length;i<u;i++)o[i].fn!==e&&o[i].fn._!==e&&r.push(o[i]);return r.length?n[t]=r:delete 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\ No newline at end of file
diff --git a/deps/data-deps.txt b/deps/data-deps.txt
index 1bdf35ddf..e9f0b19f2 100644
--- a/deps/data-deps.txt
+++ b/deps/data-deps.txt
@@ -4,3 +4,12 @@
 <script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script>
 <link href="deps/Lato-0.4.9/font.css" rel="stylesheet" />
 <link href="deps/Fira_Code-0.4.9/font.css" rel="stylesheet" />
+<link href="deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet" />
+<link href="deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet" />
+<script src="deps/headroom-0.11.0/headroom.min.js"></script>
+<script src="deps/headroom-0.11.0/jQuery.headroom.min.js"></script>
+<script src="deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script>
+<script src="deps/clipboard.js-2.0.11/clipboard.min.js"></script>
+<script src="deps/search-1.0.0/autocomplete.jquery.min.js"></script>
+<script src="deps/search-1.0.0/fuse.min.js"></script>
+<script src="deps/search-1.0.0/mark.min.js"></script>
diff --git a/deps/font-awesome-6.4.2/css/all.css b/deps/font-awesome-6.4.2/css/all.css
new file mode 100644
index 000000000..bdb6e3ae8
--- /dev/null
+++ b/deps/font-awesome-6.4.2/css/all.css
@@ -0,0 +1,7968 @@
+/*!
+ * Font Awesome Free 6.4.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
+.fa {
+  font-family: var(--fa-style-family, "Font Awesome 6 Free");
+  font-weight: var(--fa-style, 900); }
+
+.fa,
+.fa-classic,
+.fa-sharp,
+.fas,
+.fa-solid,
+.far,
+.fa-regular,
+.fab,
+.fa-brands {
+  -moz-osx-font-smoothing: grayscale;
+  -webkit-font-smoothing: antialiased;
+  display: var(--fa-display, inline-block);
+  font-style: normal;
+  font-variant: normal;
+  line-height: 1;
+  text-rendering: auto; }
+
+.fas,
+.fa-classic,
+.fa-solid,
+.far,
+.fa-regular {
+  font-family: 'Font Awesome 6 Free'; }
+
+.fab,
+.fa-brands {
+  font-family: 'Font Awesome 6 Brands'; }
+
+.fa-1x {
+  font-size: 1em; }
+
+.fa-2x {
+  font-size: 2em; }
+
+.fa-3x {
+  font-size: 3em; }
+
+.fa-4x {
+  font-size: 4em; }
+
+.fa-5x {
+  font-size: 5em; }
+
+.fa-6x {
+  font-size: 6em; }
+
+.fa-7x {
+  font-size: 7em; }
+
+.fa-8x {
+  font-size: 8em; }
+
+.fa-9x {
+  font-size: 9em; }
+
+.fa-10x {
+  font-size: 10em; }
+
+.fa-2xs {
+  font-size: 0.625em;
+  line-height: 0.1em;
+  vertical-align: 0.225em; }
+
+.fa-xs {
+  font-size: 0.75em;
+  line-height: 0.08333em;
+  vertical-align: 0.125em; }
+
+.fa-sm {
+  font-size: 0.875em;
+  line-height: 0.07143em;
+  vertical-align: 0.05357em; }
+
+.fa-lg {
+  font-size: 1.25em;
+  line-height: 0.05em;
+  vertical-align: -0.075em; }
+
+.fa-xl {
+  font-size: 1.5em;
+  line-height: 0.04167em;
+  vertical-align: -0.125em; }
+
+.fa-2xl {
+  font-size: 2em;
+  line-height: 0.03125em;
+  vertical-align: -0.1875em; }
+
+.fa-fw {
+  text-align: center;
+  width: 1.25em; }
+
+.fa-ul {
+  list-style-type: none;
+  margin-left: var(--fa-li-margin, 2.5em);
+  padding-left: 0; }
+  .fa-ul > li {
+    position: relative; }
+
+.fa-li {
+  left: calc(var(--fa-li-width, 2em) * -1);
+  position: absolute;
+  text-align: center;
+  width: var(--fa-li-width, 2em);
+  line-height: inherit; }
+
+.fa-border {
+  border-color: var(--fa-border-color, #eee);
+  border-radius: var(--fa-border-radius, 0.1em);
+  border-style: var(--fa-border-style, solid);
+  border-width: var(--fa-border-width, 0.08em);
+  padding: var(--fa-border-padding, 0.2em 0.25em 0.15em); }
+
+.fa-pull-left {
+  float: left;
+  margin-right: var(--fa-pull-margin, 0.3em); }
+
+.fa-pull-right {
+  float: right;
+  margin-left: var(--fa-pull-margin, 0.3em); }
+
+.fa-beat {
+  -webkit-animation-name: fa-beat;
+          animation-name: fa-beat;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, ease-in-out);
+          animation-timing-function: var(--fa-animation-timing, ease-in-out); }
+
+.fa-bounce {
+  -webkit-animation-name: fa-bounce;
+          animation-name: fa-bounce;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.28, 0.84, 0.42, 1));
+          animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.28, 0.84, 0.42, 1)); }
+
+.fa-fade {
+  -webkit-animation-name: fa-fade;
+          animation-name: fa-fade;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1));
+          animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1)); }
+
+.fa-beat-fade {
+  -webkit-animation-name: fa-beat-fade;
+          animation-name: fa-beat-fade;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1));
+          animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1)); }
+
+.fa-flip {
+  -webkit-animation-name: fa-flip;
+          animation-name: fa-flip;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, ease-in-out);
+          animation-timing-function: var(--fa-animation-timing, ease-in-out); }
+
+.fa-shake {
+  -webkit-animation-name: fa-shake;
+          animation-name: fa-shake;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, linear);
+          animation-timing-function: var(--fa-animation-timing, linear); }
+
+.fa-spin {
+  -webkit-animation-name: fa-spin;
+          animation-name: fa-spin;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 2s);
+          animation-duration: var(--fa-animation-duration, 2s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, linear);
+          animation-timing-function: var(--fa-animation-timing, linear); }
+
+.fa-spin-reverse {
+  --fa-animation-direction: reverse; }
+
+.fa-pulse,
+.fa-spin-pulse {
+  -webkit-animation-name: fa-spin;
+          animation-name: fa-spin;
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, steps(8));
+          animation-timing-function: var(--fa-animation-timing, steps(8)); }
+
+@media (prefers-reduced-motion: reduce) {
+  .fa-beat,
+  .fa-bounce,
+  .fa-fade,
+  .fa-beat-fade,
+  .fa-flip,
+  .fa-pulse,
+  .fa-shake,
+  .fa-spin,
+  .fa-spin-pulse {
+    -webkit-animation-delay: -1ms;
+            animation-delay: -1ms;
+    -webkit-animation-duration: 1ms;
+            animation-duration: 1ms;
+    -webkit-animation-iteration-count: 1;
+            animation-iteration-count: 1;
+    -webkit-transition-delay: 0s;
+            transition-delay: 0s;
+    -webkit-transition-duration: 0s;
+            transition-duration: 0s; } }
+
+@-webkit-keyframes fa-beat {
+  0%, 90% {
+    -webkit-transform: scale(1);
+            transform: scale(1); }
+  45% {
+    -webkit-transform: scale(var(--fa-beat-scale, 1.25));
+            transform: scale(var(--fa-beat-scale, 1.25)); } }
+
+@keyframes fa-beat {
+  0%, 90% {
+    -webkit-transform: scale(1);
+            transform: scale(1); }
+  45% {
+    -webkit-transform: scale(var(--fa-beat-scale, 1.25));
+            transform: scale(var(--fa-beat-scale, 1.25)); } }
+
+@-webkit-keyframes fa-bounce {
+  0% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); }
+  10% {
+    -webkit-transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0);
+            transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0); }
+  30% {
+    -webkit-transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em));
+            transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em)); }
+  50% {
+    -webkit-transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0);
+            transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0); }
+  57% {
+    -webkit-transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em));
+            transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em)); }
+  64% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); }
+  100% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); } }
+
+@keyframes fa-bounce {
+  0% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); }
+  10% {
+    -webkit-transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0);
+            transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0); }
+  30% {
+    -webkit-transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em));
+            transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em)); }
+  50% {
+    -webkit-transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0);
+            transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0); }
+  57% {
+    -webkit-transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em));
+            transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em)); }
+  64% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); }
+  100% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); } }
+
+@-webkit-keyframes fa-fade {
+  50% {
+    opacity: var(--fa-fade-opacity, 0.4); } }
+
+@keyframes fa-fade {
+  50% {
+    opacity: var(--fa-fade-opacity, 0.4); } }
+
+@-webkit-keyframes fa-beat-fade {
+  0%, 100% {
+    opacity: var(--fa-beat-fade-opacity, 0.4);
+    -webkit-transform: scale(1);
+            transform: scale(1); }
+  50% {
+    opacity: 1;
+    -webkit-transform: scale(var(--fa-beat-fade-scale, 1.125));
+            transform: scale(var(--fa-beat-fade-scale, 1.125)); } }
+
+@keyframes fa-beat-fade {
+  0%, 100% {
+    opacity: var(--fa-beat-fade-opacity, 0.4);
+    -webkit-transform: scale(1);
+            transform: scale(1); }
+  50% {
+    opacity: 1;
+    -webkit-transform: scale(var(--fa-beat-fade-scale, 1.125));
+            transform: scale(var(--fa-beat-fade-scale, 1.125)); } }
+
+@-webkit-keyframes fa-flip {
+  50% {
+    -webkit-transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg));
+            transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg)); } }
+
+@keyframes fa-flip {
+  50% {
+    -webkit-transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg));
+            transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg)); } }
+
+@-webkit-keyframes fa-shake {
+  0% {
+    -webkit-transform: rotate(-15deg);
+            transform: rotate(-15deg); }
+  4% {
+    -webkit-transform: rotate(15deg);
+            transform: rotate(15deg); }
+  8%, 24% {
+    -webkit-transform: rotate(-18deg);
+            transform: rotate(-18deg); }
+  12%, 28% {
+    -webkit-transform: rotate(18deg);
+            transform: rotate(18deg); }
+  16% {
+    -webkit-transform: rotate(-22deg);
+            transform: rotate(-22deg); }
+  20% {
+    -webkit-transform: rotate(22deg);
+            transform: rotate(22deg); }
+  32% {
+    -webkit-transform: rotate(-12deg);
+            transform: rotate(-12deg); }
+  36% {
+    -webkit-transform: rotate(12deg);
+            transform: rotate(12deg); }
+  40%, 100% {
+    -webkit-transform: rotate(0deg);
+            transform: rotate(0deg); } }
+
+@keyframes fa-shake {
+  0% {
+    -webkit-transform: rotate(-15deg);
+            transform: rotate(-15deg); }
+  4% {
+    -webkit-transform: rotate(15deg);
+            transform: rotate(15deg); }
+  8%, 24% {
+    -webkit-transform: rotate(-18deg);
+            transform: rotate(-18deg); }
+  12%, 28% {
+    -webkit-transform: rotate(18deg);
+            transform: rotate(18deg); }
+  16% {
+    -webkit-transform: rotate(-22deg);
+            transform: rotate(-22deg); }
+  20% {
+    -webkit-transform: rotate(22deg);
+            transform: rotate(22deg); }
+  32% {
+    -webkit-transform: rotate(-12deg);
+            transform: rotate(-12deg); }
+  36% {
+    -webkit-transform: rotate(12deg);
+            transform: rotate(12deg); }
+  40%, 100% {
+    -webkit-transform: rotate(0deg);
+            transform: rotate(0deg); } }
+
+@-webkit-keyframes fa-spin {
+  0% {
+    -webkit-transform: rotate(0deg);
+            transform: rotate(0deg); }
+  100% {
+    -webkit-transform: rotate(360deg);
+            transform: rotate(360deg); } }
+
+@keyframes fa-spin {
+  0% {
+    -webkit-transform: rotate(0deg);
+            transform: rotate(0deg); }
+  100% {
+    -webkit-transform: rotate(360deg);
+            transform: rotate(360deg); } }
+
+.fa-rotate-90 {
+  -webkit-transform: rotate(90deg);
+          transform: rotate(90deg); }
+
+.fa-rotate-180 {
+  -webkit-transform: rotate(180deg);
+          transform: rotate(180deg); }
+
+.fa-rotate-270 {
+  -webkit-transform: rotate(270deg);
+          transform: rotate(270deg); }
+
+.fa-flip-horizontal {
+  -webkit-transform: scale(-1, 1);
+          transform: scale(-1, 1); }
+
+.fa-flip-vertical {
+  -webkit-transform: scale(1, -1);
+          transform: scale(1, -1); }
+
+.fa-flip-both,
+.fa-flip-horizontal.fa-flip-vertical {
+  -webkit-transform: scale(-1, -1);
+          transform: scale(-1, -1); }
+
+.fa-rotate-by {
+  -webkit-transform: rotate(var(--fa-rotate-angle, none));
+          transform: rotate(var(--fa-rotate-angle, none)); }
+
+.fa-stack {
+  display: inline-block;
+  height: 2em;
+  line-height: 2em;
+  position: relative;
+  vertical-align: middle;
+  width: 2.5em; }
+
+.fa-stack-1x,
+.fa-stack-2x {
+  left: 0;
+  position: absolute;
+  text-align: center;
+  width: 100%;
+  z-index: var(--fa-stack-z-index, auto); }
+
+.fa-stack-1x {
+  line-height: inherit; }
+
+.fa-stack-2x {
+  font-size: 2em; }
+
+.fa-inverse {
+  color: var(--fa-inverse, #fff); }
+
+/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
+readers do not read off random characters that represent icons */
+
+.fa-0::before {
+  content: "\30"; }
+
+.fa-1::before {
+  content: "\31"; }
+
+.fa-2::before {
+  content: "\32"; }
+
+.fa-3::before {
+  content: "\33"; }
+
+.fa-4::before {
+  content: "\34"; }
+
+.fa-5::before {
+  content: "\35"; }
+
+.fa-6::before {
+  content: "\36"; }
+
+.fa-7::before {
+  content: "\37"; }
+
+.fa-8::before {
+  content: "\38"; }
+
+.fa-9::before {
+  content: "\39"; }
+
+.fa-fill-drip::before {
+  content: "\f576"; }
+
+.fa-arrows-to-circle::before {
+  content: "\e4bd"; }
+
+.fa-circle-chevron-right::before {
+  content: "\f138"; }
+
+.fa-chevron-circle-right::before {
+  content: "\f138"; }
+
+.fa-at::before {
+  content: "\40"; }
+
+.fa-trash-can::before {
+  content: "\f2ed"; }
+
+.fa-trash-alt::before {
+  content: "\f2ed"; }
+
+.fa-text-height::before {
+  content: "\f034"; }
+
+.fa-user-xmark::before {
+  content: "\f235"; }
+
+.fa-user-times::before {
+  content: "\f235"; }
+
+.fa-stethoscope::before {
+  content: "\f0f1"; }
+
+.fa-message::before {
+  content: "\f27a"; }
+
+.fa-comment-alt::before {
+  content: "\f27a"; }
+
+.fa-info::before {
+  content: "\f129"; }
+
+.fa-down-left-and-up-right-to-center::before {
+  content: "\f422"; }
+
+.fa-compress-alt::before {
+  content: "\f422"; }
+
+.fa-explosion::before {
+  content: "\e4e9"; }
+
+.fa-file-lines::before {
+  content: "\f15c"; }
+
+.fa-file-alt::before {
+  content: "\f15c"; }
+
+.fa-file-text::before {
+  content: "\f15c"; }
+
+.fa-wave-square::before {
+  content: "\f83e"; }
+
+.fa-ring::before {
+  content: "\f70b"; }
+
+.fa-building-un::before {
+  content: "\e4d9"; }
+
+.fa-dice-three::before {
+  content: "\f527"; }
+
+.fa-calendar-days::before {
+  content: "\f073"; }
+
+.fa-calendar-alt::before {
+  content: "\f073"; }
+
+.fa-anchor-circle-check::before {
+  content: "\e4aa"; }
+
+.fa-building-circle-arrow-right::before {
+  content: "\e4d1"; }
+
+.fa-volleyball::before {
+  content: "\f45f"; }
+
+.fa-volleyball-ball::before {
+  content: "\f45f"; }
+
+.fa-arrows-up-to-line::before {
+  content: "\e4c2"; }
+
+.fa-sort-down::before {
+  content: "\f0dd"; }
+
+.fa-sort-desc::before {
+  content: "\f0dd"; }
+
+.fa-circle-minus::before {
+  content: "\f056"; }
+
+.fa-minus-circle::before {
+  content: "\f056"; }
+
+.fa-door-open::before {
+  content: "\f52b"; }
+
+.fa-right-from-bracket::before {
+  content: "\f2f5"; }
+
+.fa-sign-out-alt::before {
+  content: "\f2f5"; }
+
+.fa-atom::before {
+  content: "\f5d2"; }
+
+.fa-soap::before {
+  content: "\e06e"; }
+
+.fa-icons::before {
+  content: "\f86d"; }
+
+.fa-heart-music-camera-bolt::before {
+  content: "\f86d"; }
+
+.fa-microphone-lines-slash::before {
+  content: "\f539"; }
+
+.fa-microphone-alt-slash::before {
+  content: "\f539"; }
+
+.fa-bridge-circle-check::before {
+  content: "\e4c9"; }
+
+.fa-pump-medical::before {
+  content: "\e06a"; }
+
+.fa-fingerprint::before {
+  content: "\f577"; }
+
+.fa-hand-point-right::before {
+  content: "\f0a4"; }
+
+.fa-magnifying-glass-location::before {
+  content: "\f689"; }
+
+.fa-search-location::before {
+  content: "\f689"; }
+
+.fa-forward-step::before {
+  content: "\f051"; }
+
+.fa-step-forward::before {
+  content: "\f051"; }
+
+.fa-face-smile-beam::before {
+  content: "\f5b8"; }
+
+.fa-smile-beam::before {
+  content: "\f5b8"; }
+
+.fa-flag-checkered::before {
+  content: "\f11e"; }
+
+.fa-football::before {
+  content: "\f44e"; }
+
+.fa-football-ball::before {
+  content: "\f44e"; }
+
+.fa-school-circle-exclamation::before {
+  content: "\e56c"; }
+
+.fa-crop::before {
+  content: "\f125"; }
+
+.fa-angles-down::before {
+  content: "\f103"; }
+
+.fa-angle-double-down::before {
+  content: "\f103"; }
+
+.fa-users-rectangle::before {
+  content: "\e594"; }
+
+.fa-people-roof::before {
+  content: "\e537"; }
+
+.fa-people-line::before {
+  content: "\e534"; }
+
+.fa-beer-mug-empty::before {
+  content: "\f0fc"; }
+
+.fa-beer::before {
+  content: "\f0fc"; }
+
+.fa-diagram-predecessor::before {
+  content: "\e477"; }
+
+.fa-arrow-up-long::before {
+  content: "\f176"; }
+
+.fa-long-arrow-up::before {
+  content: "\f176"; }
+
+.fa-fire-flame-simple::before {
+  content: "\f46a"; }
+
+.fa-burn::before {
+  content: "\f46a"; }
+
+.fa-person::before {
+  content: "\f183"; }
+
+.fa-male::before {
+  content: "\f183"; }
+
+.fa-laptop::before {
+  content: "\f109"; }
+
+.fa-file-csv::before {
+  content: "\f6dd"; }
+
+.fa-menorah::before {
+  content: "\f676"; }
+
+.fa-truck-plane::before {
+  content: "\e58f"; }
+
+.fa-record-vinyl::before {
+  content: "\f8d9"; }
+
+.fa-face-grin-stars::before {
+  content: "\f587"; }
+
+.fa-grin-stars::before {
+  content: "\f587"; }
+
+.fa-bong::before {
+  content: "\f55c"; }
+
+.fa-spaghetti-monster-flying::before {
+  content: "\f67b"; }
+
+.fa-pastafarianism::before {
+  content: "\f67b"; }
+
+.fa-arrow-down-up-across-line::before {
+  content: "\e4af"; }
+
+.fa-spoon::before {
+  content: "\f2e5"; }
+
+.fa-utensil-spoon::before {
+  content: "\f2e5"; }
+
+.fa-jar-wheat::before {
+  content: "\e517"; }
+
+.fa-envelopes-bulk::before {
+  content: "\f674"; }
+
+.fa-mail-bulk::before {
+  content: "\f674"; }
+
+.fa-file-circle-exclamation::before {
+  content: "\e4eb"; }
+
+.fa-circle-h::before {
+  content: "\f47e"; }
+
+.fa-hospital-symbol::before {
+  content: "\f47e"; }
+
+.fa-pager::before {
+  content: "\f815"; }
+
+.fa-address-book::before {
+  content: "\f2b9"; }
+
+.fa-contact-book::before {
+  content: "\f2b9"; }
+
+.fa-strikethrough::before {
+  content: "\f0cc"; }
+
+.fa-k::before {
+  content: "\4b"; }
+
+.fa-landmark-flag::before {
+  content: "\e51c"; }
+
+.fa-pencil::before {
+  content: "\f303"; }
+
+.fa-pencil-alt::before {
+  content: "\f303"; }
+
+.fa-backward::before {
+  content: "\f04a"; }
+
+.fa-caret-right::before {
+  content: "\f0da"; }
+
+.fa-comments::before {
+  content: "\f086"; }
+
+.fa-paste::before {
+  content: "\f0ea"; }
+
+.fa-file-clipboard::before {
+  content: "\f0ea"; }
+
+.fa-code-pull-request::before {
+  content: "\e13c"; }
+
+.fa-clipboard-list::before {
+  content: "\f46d"; }
+
+.fa-truck-ramp-box::before {
+  content: "\f4de"; }
+
+.fa-truck-loading::before {
+  content: "\f4de"; }
+
+.fa-user-check::before {
+  content: "\f4fc"; }
+
+.fa-vial-virus::before {
+  content: "\e597"; }
+
+.fa-sheet-plastic::before {
+  content: "\e571"; }
+
+.fa-blog::before {
+  content: "\f781"; }
+
+.fa-user-ninja::before {
+  content: "\f504"; }
+
+.fa-person-arrow-up-from-line::before {
+  content: "\e539"; }
+
+.fa-scroll-torah::before {
+  content: "\f6a0"; }
+
+.fa-torah::before {
+  content: "\f6a0"; }
+
+.fa-broom-ball::before {
+  content: "\f458"; }
+
+.fa-quidditch::before {
+  content: "\f458"; }
+
+.fa-quidditch-broom-ball::before {
+  content: "\f458"; }
+
+.fa-toggle-off::before {
+  content: "\f204"; }
+
+.fa-box-archive::before {
+  content: "\f187"; }
+
+.fa-archive::before {
+  content: "\f187"; }
+
+.fa-person-drowning::before {
+  content: "\e545"; }
+
+.fa-arrow-down-9-1::before {
+  content: "\f886"; }
+
+.fa-sort-numeric-desc::before {
+  content: "\f886"; }
+
+.fa-sort-numeric-down-alt::before {
+  content: "\f886"; }
+
+.fa-face-grin-tongue-squint::before {
+  content: "\f58a"; }
+
+.fa-grin-tongue-squint::before {
+  content: "\f58a"; }
+
+.fa-spray-can::before {
+  content: "\f5bd"; }
+
+.fa-truck-monster::before {
+  content: "\f63b"; }
+
+.fa-w::before {
+  content: "\57"; }
+
+.fa-earth-africa::before {
+  content: "\f57c"; }
+
+.fa-globe-africa::before {
+  content: "\f57c"; }
+
+.fa-rainbow::before {
+  content: "\f75b"; }
+
+.fa-circle-notch::before {
+  content: "\f1ce"; }
+
+.fa-tablet-screen-button::before {
+  content: "\f3fa"; }
+
+.fa-tablet-alt::before {
+  content: "\f3fa"; }
+
+.fa-paw::before {
+  content: "\f1b0"; }
+
+.fa-cloud::before {
+  content: "\f0c2"; }
+
+.fa-trowel-bricks::before {
+  content: "\e58a"; }
+
+.fa-face-flushed::before {
+  content: "\f579"; }
+
+.fa-flushed::before {
+  content: "\f579"; }
+
+.fa-hospital-user::before {
+  content: "\f80d"; }
+
+.fa-tent-arrow-left-right::before {
+  content: "\e57f"; }
+
+.fa-gavel::before {
+  content: "\f0e3"; }
+
+.fa-legal::before {
+  content: "\f0e3"; }
+
+.fa-binoculars::before {
+  content: "\f1e5"; }
+
+.fa-microphone-slash::before {
+  content: "\f131"; }
+
+.fa-box-tissue::before {
+  content: "\e05b"; }
+
+.fa-motorcycle::before {
+  content: "\f21c"; }
+
+.fa-bell-concierge::before {
+  content: "\f562"; }
+
+.fa-concierge-bell::before {
+  content: "\f562"; }
+
+.fa-pen-ruler::before {
+  content: "\f5ae"; }
+
+.fa-pencil-ruler::before {
+  content: "\f5ae"; }
+
+.fa-people-arrows::before {
+  content: "\e068"; }
+
+.fa-people-arrows-left-right::before {
+  content: "\e068"; }
+
+.fa-mars-and-venus-burst::before {
+  content: "\e523"; }
+
+.fa-square-caret-right::before {
+  content: "\f152"; }
+
+.fa-caret-square-right::before {
+  content: "\f152"; }
+
+.fa-scissors::before {
+  content: "\f0c4"; }
+
+.fa-cut::before {
+  content: "\f0c4"; }
+
+.fa-sun-plant-wilt::before {
+  content: "\e57a"; }
+
+.fa-toilets-portable::before {
+  content: "\e584"; }
+
+.fa-hockey-puck::before {
+  content: "\f453"; }
+
+.fa-table::before {
+  content: "\f0ce"; }
+
+.fa-magnifying-glass-arrow-right::before {
+  content: "\e521"; }
+
+.fa-tachograph-digital::before {
+  content: "\f566"; }
+
+.fa-digital-tachograph::before {
+  content: "\f566"; }
+
+.fa-users-slash::before {
+  content: "\e073"; }
+
+.fa-clover::before {
+  content: "\e139"; }
+
+.fa-reply::before {
+  content: "\f3e5"; }
+
+.fa-mail-reply::before {
+  content: "\f3e5"; }
+
+.fa-star-and-crescent::before {
+  content: "\f699"; }
+
+.fa-house-fire::before {
+  content: "\e50c"; }
+
+.fa-square-minus::before {
+  content: "\f146"; }
+
+.fa-minus-square::before {
+  content: "\f146"; }
+
+.fa-helicopter::before {
+  content: "\f533"; }
+
+.fa-compass::before {
+  content: "\f14e"; }
+
+.fa-square-caret-down::before {
+  content: "\f150"; }
+
+.fa-caret-square-down::before {
+  content: "\f150"; }
+
+.fa-file-circle-question::before {
+  content: "\e4ef"; }
+
+.fa-laptop-code::before {
+  content: "\f5fc"; }
+
+.fa-swatchbook::before {
+  content: "\f5c3"; }
+
+.fa-prescription-bottle::before {
+  content: "\f485"; }
+
+.fa-bars::before {
+  content: "\f0c9"; }
+
+.fa-navicon::before {
+  content: "\f0c9"; }
+
+.fa-people-group::before {
+  content: "\e533"; }
+
+.fa-hourglass-end::before {
+  content: "\f253"; }
+
+.fa-hourglass-3::before {
+  content: "\f253"; }
+
+.fa-heart-crack::before {
+  content: "\f7a9"; }
+
+.fa-heart-broken::before {
+  content: "\f7a9"; }
+
+.fa-square-up-right::before {
+  content: "\f360"; }
+
+.fa-external-link-square-alt::before {
+  content: "\f360"; }
+
+.fa-face-kiss-beam::before {
+  content: "\f597"; }
+
+.fa-kiss-beam::before {
+  content: "\f597"; }
+
+.fa-film::before {
+  content: "\f008"; }
+
+.fa-ruler-horizontal::before {
+  content: "\f547"; }
+
+.fa-people-robbery::before {
+  content: "\e536"; }
+
+.fa-lightbulb::before {
+  content: "\f0eb"; }
+
+.fa-caret-left::before {
+  content: "\f0d9"; }
+
+.fa-circle-exclamation::before {
+  content: "\f06a"; }
+
+.fa-exclamation-circle::before {
+  content: "\f06a"; }
+
+.fa-school-circle-xmark::before {
+  content: "\e56d"; }
+
+.fa-arrow-right-from-bracket::before {
+  content: "\f08b"; }
+
+.fa-sign-out::before {
+  content: "\f08b"; }
+
+.fa-circle-chevron-down::before {
+  content: "\f13a"; }
+
+.fa-chevron-circle-down::before {
+  content: "\f13a"; }
+
+.fa-unlock-keyhole::before {
+  content: "\f13e"; }
+
+.fa-unlock-alt::before {
+  content: "\f13e"; }
+
+.fa-cloud-showers-heavy::before {
+  content: "\f740"; }
+
+.fa-headphones-simple::before {
+  content: "\f58f"; }
+
+.fa-headphones-alt::before {
+  content: "\f58f"; }
+
+.fa-sitemap::before {
+  content: "\f0e8"; }
+
+.fa-circle-dollar-to-slot::before {
+  content: "\f4b9"; }
+
+.fa-donate::before {
+  content: "\f4b9"; }
+
+.fa-memory::before {
+  content: "\f538"; }
+
+.fa-road-spikes::before {
+  content: "\e568"; }
+
+.fa-fire-burner::before {
+  content: "\e4f1"; }
+
+.fa-flag::before {
+  content: "\f024"; }
+
+.fa-hanukiah::before {
+  content: "\f6e6"; }
+
+.fa-feather::before {
+  content: "\f52d"; }
+
+.fa-volume-low::before {
+  content: "\f027"; }
+
+.fa-volume-down::before {
+  content: "\f027"; }
+
+.fa-comment-slash::before {
+  content: "\f4b3"; }
+
+.fa-cloud-sun-rain::before {
+  content: "\f743"; }
+
+.fa-compress::before {
+  content: "\f066"; }
+
+.fa-wheat-awn::before {
+  content: "\e2cd"; }
+
+.fa-wheat-alt::before {
+  content: "\e2cd"; }
+
+.fa-ankh::before {
+  content: "\f644"; }
+
+.fa-hands-holding-child::before {
+  content: "\e4fa"; }
+
+.fa-asterisk::before {
+  content: "\2a"; }
+
+.fa-square-check::before {
+  content: "\f14a"; }
+
+.fa-check-square::before {
+  content: "\f14a"; }
+
+.fa-peseta-sign::before {
+  content: "\e221"; }
+
+.fa-heading::before {
+  content: "\f1dc"; }
+
+.fa-header::before {
+  content: "\f1dc"; }
+
+.fa-ghost::before {
+  content: "\f6e2"; }
+
+.fa-list::before {
+  content: "\f03a"; }
+
+.fa-list-squares::before {
+  content: "\f03a"; }
+
+.fa-square-phone-flip::before {
+  content: "\f87b"; }
+
+.fa-phone-square-alt::before {
+  content: "\f87b"; }
+
+.fa-cart-plus::before {
+  content: "\f217"; }
+
+.fa-gamepad::before {
+  content: "\f11b"; }
+
+.fa-circle-dot::before {
+  content: "\f192"; }
+
+.fa-dot-circle::before {
+  content: "\f192"; }
+
+.fa-face-dizzy::before {
+  content: "\f567"; }
+
+.fa-dizzy::before {
+  content: "\f567"; }
+
+.fa-egg::before {
+  content: "\f7fb"; }
+
+.fa-house-medical-circle-xmark::before {
+  content: "\e513"; }
+
+.fa-campground::before {
+  content: "\f6bb"; }
+
+.fa-folder-plus::before {
+  content: "\f65e"; }
+
+.fa-futbol::before {
+  content: "\f1e3"; }
+
+.fa-futbol-ball::before {
+  content: "\f1e3"; }
+
+.fa-soccer-ball::before {
+  content: "\f1e3"; }
+
+.fa-paintbrush::before {
+  content: "\f1fc"; }
+
+.fa-paint-brush::before {
+  content: "\f1fc"; }
+
+.fa-lock::before {
+  content: "\f023"; }
+
+.fa-gas-pump::before {
+  content: "\f52f"; }
+
+.fa-hot-tub-person::before {
+  content: "\f593"; }
+
+.fa-hot-tub::before {
+  content: "\f593"; }
+
+.fa-map-location::before {
+  content: "\f59f"; }
+
+.fa-map-marked::before {
+  content: "\f59f"; }
+
+.fa-house-flood-water::before {
+  content: "\e50e"; }
+
+.fa-tree::before {
+  content: "\f1bb"; }
+
+.fa-bridge-lock::before {
+  content: "\e4cc"; }
+
+.fa-sack-dollar::before {
+  content: "\f81d"; }
+
+.fa-pen-to-square::before {
+  content: "\f044"; }
+
+.fa-edit::before {
+  content: "\f044"; }
+
+.fa-car-side::before {
+  content: "\f5e4"; }
+
+.fa-share-nodes::before {
+  content: "\f1e0"; }
+
+.fa-share-alt::before {
+  content: "\f1e0"; }
+
+.fa-heart-circle-minus::before {
+  content: "\e4ff"; }
+
+.fa-hourglass-half::before {
+  content: "\f252"; }
+
+.fa-hourglass-2::before {
+  content: "\f252"; }
+
+.fa-microscope::before {
+  content: "\f610"; }
+
+.fa-sink::before {
+  content: "\e06d"; }
+
+.fa-bag-shopping::before {
+  content: "\f290"; }
+
+.fa-shopping-bag::before {
+  content: "\f290"; }
+
+.fa-arrow-down-z-a::before {
+  content: "\f881"; }
+
+.fa-sort-alpha-desc::before {
+  content: "\f881"; }
+
+.fa-sort-alpha-down-alt::before {
+  content: "\f881"; }
+
+.fa-mitten::before {
+  content: "\f7b5"; }
+
+.fa-person-rays::before {
+  content: "\e54d"; }
+
+.fa-users::before {
+  content: "\f0c0"; }
+
+.fa-eye-slash::before {
+  content: "\f070"; }
+
+.fa-flask-vial::before {
+  content: "\e4f3"; }
+
+.fa-hand::before {
+  content: "\f256"; }
+
+.fa-hand-paper::before {
+  content: "\f256"; }
+
+.fa-om::before {
+  content: "\f679"; }
+
+.fa-worm::before {
+  content: "\e599"; }
+
+.fa-house-circle-xmark::before {
+  content: "\e50b"; }
+
+.fa-plug::before {
+  content: "\f1e6"; }
+
+.fa-chevron-up::before {
+  content: "\f077"; }
+
+.fa-hand-spock::before {
+  content: "\f259"; }
+
+.fa-stopwatch::before {
+  content: "\f2f2"; }
+
+.fa-face-kiss::before {
+  content: "\f596"; }
+
+.fa-kiss::before {
+  content: "\f596"; }
+
+.fa-bridge-circle-xmark::before {
+  content: "\e4cb"; }
+
+.fa-face-grin-tongue::before {
+  content: "\f589"; }
+
+.fa-grin-tongue::before {
+  content: "\f589"; }
+
+.fa-chess-bishop::before {
+  content: "\f43a"; }
+
+.fa-face-grin-wink::before {
+  content: "\f58c"; }
+
+.fa-grin-wink::before {
+  content: "\f58c"; }
+
+.fa-ear-deaf::before {
+  content: "\f2a4"; }
+
+.fa-deaf::before {
+  content: "\f2a4"; }
+
+.fa-deafness::before {
+  content: "\f2a4"; }
+
+.fa-hard-of-hearing::before {
+  content: "\f2a4"; }
+
+.fa-road-circle-check::before {
+  content: "\e564"; }
+
+.fa-dice-five::before {
+  content: "\f523"; }
+
+.fa-square-rss::before {
+  content: "\f143"; }
+
+.fa-rss-square::before {
+  content: "\f143"; }
+
+.fa-land-mine-on::before {
+  content: "\e51b"; }
+
+.fa-i-cursor::before {
+  content: "\f246"; }
+
+.fa-stamp::before {
+  content: "\f5bf"; }
+
+.fa-stairs::before {
+  content: "\e289"; }
+
+.fa-i::before {
+  content: "\49"; }
+
+.fa-hryvnia-sign::before {
+  content: "\f6f2"; }
+
+.fa-hryvnia::before {
+  content: "\f6f2"; }
+
+.fa-pills::before {
+  content: "\f484"; }
+
+.fa-face-grin-wide::before {
+  content: "\f581"; }
+
+.fa-grin-alt::before {
+  content: "\f581"; }
+
+.fa-tooth::before {
+  content: "\f5c9"; }
+
+.fa-v::before {
+  content: "\56"; }
+
+.fa-bangladeshi-taka-sign::before {
+  content: "\e2e6"; }
+
+.fa-bicycle::before {
+  content: "\f206"; }
+
+.fa-staff-snake::before {
+  content: "\e579"; }
+
+.fa-rod-asclepius::before {
+  content: "\e579"; }
+
+.fa-rod-snake::before {
+  content: "\e579"; }
+
+.fa-staff-aesculapius::before {
+  content: "\e579"; }
+
+.fa-head-side-cough-slash::before {
+  content: "\e062"; }
+
+.fa-truck-medical::before {
+  content: "\f0f9"; }
+
+.fa-ambulance::before {
+  content: "\f0f9"; }
+
+.fa-wheat-awn-circle-exclamation::before {
+  content: "\e598"; }
+
+.fa-snowman::before {
+  content: "\f7d0"; }
+
+.fa-mortar-pestle::before {
+  content: "\f5a7"; }
+
+.fa-road-barrier::before {
+  content: "\e562"; }
+
+.fa-school::before {
+  content: "\f549"; }
+
+.fa-igloo::before {
+  content: "\f7ae"; }
+
+.fa-joint::before {
+  content: "\f595"; }
+
+.fa-angle-right::before {
+  content: "\f105"; }
+
+.fa-horse::before {
+  content: "\f6f0"; }
+
+.fa-q::before {
+  content: "\51"; }
+
+.fa-g::before {
+  content: "\47"; }
+
+.fa-notes-medical::before {
+  content: "\f481"; }
+
+.fa-temperature-half::before {
+  content: "\f2c9"; }
+
+.fa-temperature-2::before {
+  content: "\f2c9"; }
+
+.fa-thermometer-2::before {
+  content: "\f2c9"; }
+
+.fa-thermometer-half::before {
+  content: "\f2c9"; }
+
+.fa-dong-sign::before {
+  content: "\e169"; }
+
+.fa-capsules::before {
+  content: "\f46b"; }
+
+.fa-poo-storm::before {
+  content: "\f75a"; }
+
+.fa-poo-bolt::before {
+  content: "\f75a"; }
+
+.fa-face-frown-open::before {
+  content: "\f57a"; }
+
+.fa-frown-open::before {
+  content: "\f57a"; }
+
+.fa-hand-point-up::before {
+  content: "\f0a6"; }
+
+.fa-money-bill::before {
+  content: "\f0d6"; }
+
+.fa-bookmark::before {
+  content: "\f02e"; }
+
+.fa-align-justify::before {
+  content: "\f039"; }
+
+.fa-umbrella-beach::before {
+  content: "\f5ca"; }
+
+.fa-helmet-un::before {
+  content: "\e503"; }
+
+.fa-bullseye::before {
+  content: "\f140"; }
+
+.fa-bacon::before {
+  content: "\f7e5"; }
+
+.fa-hand-point-down::before {
+  content: "\f0a7"; }
+
+.fa-arrow-up-from-bracket::before {
+  content: "\e09a"; }
+
+.fa-folder::before {
+  content: "\f07b"; }
+
+.fa-folder-blank::before {
+  content: "\f07b"; }
+
+.fa-file-waveform::before {
+  content: "\f478"; }
+
+.fa-file-medical-alt::before {
+  content: "\f478"; }
+
+.fa-radiation::before {
+  content: "\f7b9"; }
+
+.fa-chart-simple::before {
+  content: "\e473"; }
+
+.fa-mars-stroke::before {
+  content: "\f229"; }
+
+.fa-vial::before {
+  content: "\f492"; }
+
+.fa-gauge::before {
+  content: "\f624"; }
+
+.fa-dashboard::before {
+  content: "\f624"; }
+
+.fa-gauge-med::before {
+  content: "\f624"; }
+
+.fa-tachometer-alt-average::before {
+  content: "\f624"; }
+
+.fa-wand-magic-sparkles::before {
+  content: "\e2ca"; }
+
+.fa-magic-wand-sparkles::before {
+  content: "\e2ca"; }
+
+.fa-e::before {
+  content: "\45"; }
+
+.fa-pen-clip::before {
+  content: "\f305"; }
+
+.fa-pen-alt::before {
+  content: "\f305"; }
+
+.fa-bridge-circle-exclamation::before {
+  content: "\e4ca"; }
+
+.fa-user::before {
+  content: "\f007"; }
+
+.fa-school-circle-check::before {
+  content: "\e56b"; }
+
+.fa-dumpster::before {
+  content: "\f793"; }
+
+.fa-van-shuttle::before {
+  content: "\f5b6"; }
+
+.fa-shuttle-van::before {
+  content: "\f5b6"; }
+
+.fa-building-user::before {
+  content: "\e4da"; }
+
+.fa-square-caret-left::before {
+  content: "\f191"; }
+
+.fa-caret-square-left::before {
+  content: "\f191"; }
+
+.fa-highlighter::before {
+  content: "\f591"; }
+
+.fa-key::before {
+  content: "\f084"; }
+
+.fa-bullhorn::before {
+  content: "\f0a1"; }
+
+.fa-globe::before {
+  content: "\f0ac"; }
+
+.fa-synagogue::before {
+  content: "\f69b"; }
+
+.fa-person-half-dress::before {
+  content: "\e548"; }
+
+.fa-road-bridge::before {
+  content: "\e563"; }
+
+.fa-location-arrow::before {
+  content: "\f124"; }
+
+.fa-c::before {
+  content: "\43"; }
+
+.fa-tablet-button::before {
+  content: "\f10a"; }
+
+.fa-building-lock::before {
+  content: "\e4d6"; }
+
+.fa-pizza-slice::before {
+  content: "\f818"; }
+
+.fa-money-bill-wave::before {
+  content: "\f53a"; }
+
+.fa-chart-area::before {
+  content: "\f1fe"; }
+
+.fa-area-chart::before {
+  content: "\f1fe"; }
+
+.fa-house-flag::before {
+  content: "\e50d"; }
+
+.fa-person-circle-minus::before {
+  content: "\e540"; }
+
+.fa-ban::before {
+  content: "\f05e"; }
+
+.fa-cancel::before {
+  content: "\f05e"; }
+
+.fa-camera-rotate::before {
+  content: "\e0d8"; }
+
+.fa-spray-can-sparkles::before {
+  content: "\f5d0"; }
+
+.fa-air-freshener::before {
+  content: "\f5d0"; }
+
+.fa-star::before {
+  content: "\f005"; }
+
+.fa-repeat::before {
+  content: "\f363"; }
+
+.fa-cross::before {
+  content: "\f654"; }
+
+.fa-box::before {
+  content: "\f466"; }
+
+.fa-venus-mars::before {
+  content: "\f228"; }
+
+.fa-arrow-pointer::before {
+  content: "\f245"; }
+
+.fa-mouse-pointer::before {
+  content: "\f245"; }
+
+.fa-maximize::before {
+  content: "\f31e"; }
+
+.fa-expand-arrows-alt::before {
+  content: "\f31e"; }
+
+.fa-charging-station::before {
+  content: "\f5e7"; }
+
+.fa-shapes::before {
+  content: "\f61f"; }
+
+.fa-triangle-circle-square::before {
+  content: "\f61f"; }
+
+.fa-shuffle::before {
+  content: "\f074"; }
+
+.fa-random::before {
+  content: "\f074"; }
+
+.fa-person-running::before {
+  content: "\f70c"; }
+
+.fa-running::before {
+  content: "\f70c"; }
+
+.fa-mobile-retro::before {
+  content: "\e527"; }
+
+.fa-grip-lines-vertical::before {
+  content: "\f7a5"; }
+
+.fa-spider::before {
+  content: "\f717"; }
+
+.fa-hands-bound::before {
+  content: "\e4f9"; }
+
+.fa-file-invoice-dollar::before {
+  content: "\f571"; }
+
+.fa-plane-circle-exclamation::before {
+  content: "\e556"; }
+
+.fa-x-ray::before {
+  content: "\f497"; }
+
+.fa-spell-check::before {
+  content: "\f891"; }
+
+.fa-slash::before {
+  content: "\f715"; }
+
+.fa-computer-mouse::before {
+  content: "\f8cc"; }
+
+.fa-mouse::before {
+  content: "\f8cc"; }
+
+.fa-arrow-right-to-bracket::before {
+  content: "\f090"; }
+
+.fa-sign-in::before {
+  content: "\f090"; }
+
+.fa-shop-slash::before {
+  content: "\e070"; }
+
+.fa-store-alt-slash::before {
+  content: "\e070"; }
+
+.fa-server::before {
+  content: "\f233"; }
+
+.fa-virus-covid-slash::before {
+  content: "\e4a9"; }
+
+.fa-shop-lock::before {
+  content: "\e4a5"; }
+
+.fa-hourglass-start::before {
+  content: "\f251"; }
+
+.fa-hourglass-1::before {
+  content: "\f251"; }
+
+.fa-blender-phone::before {
+  content: "\f6b6"; }
+
+.fa-building-wheat::before {
+  content: "\e4db"; }
+
+.fa-person-breastfeeding::before {
+  content: "\e53a"; }
+
+.fa-right-to-bracket::before {
+  content: "\f2f6"; }
+
+.fa-sign-in-alt::before {
+  content: "\f2f6"; }
+
+.fa-venus::before {
+  content: "\f221"; }
+
+.fa-passport::before {
+  content: "\f5ab"; }
+
+.fa-heart-pulse::before {
+  content: "\f21e"; }
+
+.fa-heartbeat::before {
+  content: "\f21e"; }
+
+.fa-people-carry-box::before {
+  content: "\f4ce"; }
+
+.fa-people-carry::before {
+  content: "\f4ce"; }
+
+.fa-temperature-high::before {
+  content: "\f769"; }
+
+.fa-microchip::before {
+  content: "\f2db"; }
+
+.fa-crown::before {
+  content: "\f521"; }
+
+.fa-weight-hanging::before {
+  content: "\f5cd"; }
+
+.fa-xmarks-lines::before {
+  content: "\e59a"; }
+
+.fa-file-prescription::before {
+  content: "\f572"; }
+
+.fa-weight-scale::before {
+  content: "\f496"; }
+
+.fa-weight::before {
+  content: "\f496"; }
+
+.fa-user-group::before {
+  content: "\f500"; }
+
+.fa-user-friends::before {
+  content: "\f500"; }
+
+.fa-arrow-up-a-z::before {
+  content: "\f15e"; }
+
+.fa-sort-alpha-up::before {
+  content: "\f15e"; }
+
+.fa-chess-knight::before {
+  content: "\f441"; }
+
+.fa-face-laugh-squint::before {
+  content: "\f59b"; }
+
+.fa-laugh-squint::before {
+  content: "\f59b"; }
+
+.fa-wheelchair::before {
+  content: "\f193"; }
+
+.fa-circle-arrow-up::before {
+  content: "\f0aa"; }
+
+.fa-arrow-circle-up::before {
+  content: "\f0aa"; }
+
+.fa-toggle-on::before {
+  content: "\f205"; }
+
+.fa-person-walking::before {
+  content: "\f554"; }
+
+.fa-walking::before {
+  content: "\f554"; }
+
+.fa-l::before {
+  content: "\4c"; }
+
+.fa-fire::before {
+  content: "\f06d"; }
+
+.fa-bed-pulse::before {
+  content: "\f487"; }
+
+.fa-procedures::before {
+  content: "\f487"; }
+
+.fa-shuttle-space::before {
+  content: "\f197"; }
+
+.fa-space-shuttle::before {
+  content: "\f197"; }
+
+.fa-face-laugh::before {
+  content: "\f599"; }
+
+.fa-laugh::before {
+  content: "\f599"; }
+
+.fa-folder-open::before {
+  content: "\f07c"; }
+
+.fa-heart-circle-plus::before {
+  content: "\e500"; }
+
+.fa-code-fork::before {
+  content: "\e13b"; }
+
+.fa-city::before {
+  content: "\f64f"; }
+
+.fa-microphone-lines::before {
+  content: "\f3c9"; }
+
+.fa-microphone-alt::before {
+  content: "\f3c9"; }
+
+.fa-pepper-hot::before {
+  content: "\f816"; }
+
+.fa-unlock::before {
+  content: "\f09c"; }
+
+.fa-colon-sign::before {
+  content: "\e140"; }
+
+.fa-headset::before {
+  content: "\f590"; }
+
+.fa-store-slash::before {
+  content: "\e071"; }
+
+.fa-road-circle-xmark::before {
+  content: "\e566"; }
+
+.fa-user-minus::before {
+  content: "\f503"; }
+
+.fa-mars-stroke-up::before {
+  content: "\f22a"; }
+
+.fa-mars-stroke-v::before {
+  content: "\f22a"; }
+
+.fa-champagne-glasses::before {
+  content: "\f79f"; }
+
+.fa-glass-cheers::before {
+  content: "\f79f"; }
+
+.fa-clipboard::before {
+  content: "\f328"; }
+
+.fa-house-circle-exclamation::before {
+  content: "\e50a"; }
+
+.fa-file-arrow-up::before {
+  content: "\f574"; }
+
+.fa-file-upload::before {
+  content: "\f574"; }
+
+.fa-wifi::before {
+  content: "\f1eb"; }
+
+.fa-wifi-3::before {
+  content: "\f1eb"; }
+
+.fa-wifi-strong::before {
+  content: "\f1eb"; }
+
+.fa-bath::before {
+  content: "\f2cd"; }
+
+.fa-bathtub::before {
+  content: "\f2cd"; }
+
+.fa-underline::before {
+  content: "\f0cd"; }
+
+.fa-user-pen::before {
+  content: "\f4ff"; }
+
+.fa-user-edit::before {
+  content: "\f4ff"; }
+
+.fa-signature::before {
+  content: "\f5b7"; }
+
+.fa-stroopwafel::before {
+  content: "\f551"; }
+
+.fa-bold::before {
+  content: "\f032"; }
+
+.fa-anchor-lock::before {
+  content: "\e4ad"; }
+
+.fa-building-ngo::before {
+  content: "\e4d7"; }
+
+.fa-manat-sign::before {
+  content: "\e1d5"; }
+
+.fa-not-equal::before {
+  content: "\f53e"; }
+
+.fa-border-top-left::before {
+  content: "\f853"; }
+
+.fa-border-style::before {
+  content: "\f853"; }
+
+.fa-map-location-dot::before {
+  content: "\f5a0"; }
+
+.fa-map-marked-alt::before {
+  content: "\f5a0"; }
+
+.fa-jedi::before {
+  content: "\f669"; }
+
+.fa-square-poll-vertical::before {
+  content: "\f681"; }
+
+.fa-poll::before {
+  content: "\f681"; }
+
+.fa-mug-hot::before {
+  content: "\f7b6"; }
+
+.fa-car-battery::before {
+  content: "\f5df"; }
+
+.fa-battery-car::before {
+  content: "\f5df"; }
+
+.fa-gift::before {
+  content: "\f06b"; }
+
+.fa-dice-two::before {
+  content: "\f528"; }
+
+.fa-chess-queen::before {
+  content: "\f445"; }
+
+.fa-glasses::before {
+  content: "\f530"; }
+
+.fa-chess-board::before {
+  content: "\f43c"; }
+
+.fa-building-circle-check::before {
+  content: "\e4d2"; }
+
+.fa-person-chalkboard::before {
+  content: "\e53d"; }
+
+.fa-mars-stroke-right::before {
+  content: "\f22b"; }
+
+.fa-mars-stroke-h::before {
+  content: "\f22b"; }
+
+.fa-hand-back-fist::before {
+  content: "\f255"; }
+
+.fa-hand-rock::before {
+  content: "\f255"; }
+
+.fa-square-caret-up::before {
+  content: "\f151"; }
+
+.fa-caret-square-up::before {
+  content: "\f151"; }
+
+.fa-cloud-showers-water::before {
+  content: "\e4e4"; }
+
+.fa-chart-bar::before {
+  content: "\f080"; }
+
+.fa-bar-chart::before {
+  content: "\f080"; }
+
+.fa-hands-bubbles::before {
+  content: "\e05e"; }
+
+.fa-hands-wash::before {
+  content: "\e05e"; }
+
+.fa-less-than-equal::before {
+  content: "\f537"; }
+
+.fa-train::before {
+  content: "\f238"; }
+
+.fa-eye-low-vision::before {
+  content: "\f2a8"; }
+
+.fa-low-vision::before {
+  content: "\f2a8"; }
+
+.fa-crow::before {
+  content: "\f520"; }
+
+.fa-sailboat::before {
+  content: "\e445"; }
+
+.fa-window-restore::before {
+  content: "\f2d2"; }
+
+.fa-square-plus::before {
+  content: "\f0fe"; }
+
+.fa-plus-square::before {
+  content: "\f0fe"; }
+
+.fa-torii-gate::before {
+  content: "\f6a1"; }
+
+.fa-frog::before {
+  content: "\f52e"; }
+
+.fa-bucket::before {
+  content: "\e4cf"; }
+
+.fa-image::before {
+  content: "\f03e"; }
+
+.fa-microphone::before {
+  content: "\f130"; }
+
+.fa-cow::before {
+  content: "\f6c8"; }
+
+.fa-caret-up::before {
+  content: "\f0d8"; }
+
+.fa-screwdriver::before {
+  content: "\f54a"; }
+
+.fa-folder-closed::before {
+  content: "\e185"; }
+
+.fa-house-tsunami::before {
+  content: "\e515"; }
+
+.fa-square-nfi::before {
+  content: "\e576"; }
+
+.fa-arrow-up-from-ground-water::before {
+  content: "\e4b5"; }
+
+.fa-martini-glass::before {
+  content: "\f57b"; }
+
+.fa-glass-martini-alt::before {
+  content: "\f57b"; }
+
+.fa-rotate-left::before {
+  content: "\f2ea"; }
+
+.fa-rotate-back::before {
+  content: "\f2ea"; }
+
+.fa-rotate-backward::before {
+  content: "\f2ea"; }
+
+.fa-undo-alt::before {
+  content: "\f2ea"; }
+
+.fa-table-columns::before {
+  content: "\f0db"; }
+
+.fa-columns::before {
+  content: "\f0db"; }
+
+.fa-lemon::before {
+  content: "\f094"; }
+
+.fa-head-side-mask::before {
+  content: "\e063"; }
+
+.fa-handshake::before {
+  content: "\f2b5"; }
+
+.fa-gem::before {
+  content: "\f3a5"; }
+
+.fa-dolly::before {
+  content: "\f472"; }
+
+.fa-dolly-box::before {
+  content: "\f472"; }
+
+.fa-smoking::before {
+  content: "\f48d"; }
+
+.fa-minimize::before {
+  content: "\f78c"; }
+
+.fa-compress-arrows-alt::before {
+  content: "\f78c"; }
+
+.fa-monument::before {
+  content: "\f5a6"; }
+
+.fa-snowplow::before {
+  content: "\f7d2"; }
+
+.fa-angles-right::before {
+  content: "\f101"; }
+
+.fa-angle-double-right::before {
+  content: "\f101"; }
+
+.fa-cannabis::before {
+  content: "\f55f"; }
+
+.fa-circle-play::before {
+  content: "\f144"; }
+
+.fa-play-circle::before {
+  content: "\f144"; }
+
+.fa-tablets::before {
+  content: "\f490"; }
+
+.fa-ethernet::before {
+  content: "\f796"; }
+
+.fa-euro-sign::before {
+  content: "\f153"; }
+
+.fa-eur::before {
+  content: "\f153"; }
+
+.fa-euro::before {
+  content: "\f153"; }
+
+.fa-chair::before {
+  content: "\f6c0"; }
+
+.fa-circle-check::before {
+  content: "\f058"; }
+
+.fa-check-circle::before {
+  content: "\f058"; }
+
+.fa-circle-stop::before {
+  content: "\f28d"; }
+
+.fa-stop-circle::before {
+  content: "\f28d"; }
+
+.fa-compass-drafting::before {
+  content: "\f568"; }
+
+.fa-drafting-compass::before {
+  content: "\f568"; }
+
+.fa-plate-wheat::before {
+  content: "\e55a"; }
+
+.fa-icicles::before {
+  content: "\f7ad"; }
+
+.fa-person-shelter::before {
+  content: "\e54f"; }
+
+.fa-neuter::before {
+  content: "\f22c"; }
+
+.fa-id-badge::before {
+  content: "\f2c1"; }
+
+.fa-marker::before {
+  content: "\f5a1"; }
+
+.fa-face-laugh-beam::before {
+  content: "\f59a"; }
+
+.fa-laugh-beam::before {
+  content: "\f59a"; }
+
+.fa-helicopter-symbol::before {
+  content: "\e502"; }
+
+.fa-universal-access::before {
+  content: "\f29a"; }
+
+.fa-circle-chevron-up::before {
+  content: "\f139"; }
+
+.fa-chevron-circle-up::before {
+  content: "\f139"; }
+
+.fa-lari-sign::before {
+  content: "\e1c8"; }
+
+.fa-volcano::before {
+  content: "\f770"; }
+
+.fa-person-walking-dashed-line-arrow-right::before {
+  content: "\e553"; }
+
+.fa-sterling-sign::before {
+  content: "\f154"; }
+
+.fa-gbp::before {
+  content: "\f154"; }
+
+.fa-pound-sign::before {
+  content: "\f154"; }
+
+.fa-viruses::before {
+  content: "\e076"; }
+
+.fa-square-person-confined::before {
+  content: "\e577"; }
+
+.fa-user-tie::before {
+  content: "\f508"; }
+
+.fa-arrow-down-long::before {
+  content: "\f175"; }
+
+.fa-long-arrow-down::before {
+  content: "\f175"; }
+
+.fa-tent-arrow-down-to-line::before {
+  content: "\e57e"; }
+
+.fa-certificate::before {
+  content: "\f0a3"; }
+
+.fa-reply-all::before {
+  content: "\f122"; }
+
+.fa-mail-reply-all::before {
+  content: "\f122"; }
+
+.fa-suitcase::before {
+  content: "\f0f2"; }
+
+.fa-person-skating::before {
+  content: "\f7c5"; }
+
+.fa-skating::before {
+  content: "\f7c5"; }
+
+.fa-filter-circle-dollar::before {
+  content: "\f662"; }
+
+.fa-funnel-dollar::before {
+  content: "\f662"; }
+
+.fa-camera-retro::before {
+  content: "\f083"; }
+
+.fa-circle-arrow-down::before {
+  content: "\f0ab"; }
+
+.fa-arrow-circle-down::before {
+  content: "\f0ab"; }
+
+.fa-file-import::before {
+  content: "\f56f"; }
+
+.fa-arrow-right-to-file::before {
+  content: "\f56f"; }
+
+.fa-square-arrow-up-right::before {
+  content: "\f14c"; }
+
+.fa-external-link-square::before {
+  content: "\f14c"; }
+
+.fa-box-open::before {
+  content: "\f49e"; }
+
+.fa-scroll::before {
+  content: "\f70e"; }
+
+.fa-spa::before {
+  content: "\f5bb"; }
+
+.fa-location-pin-lock::before {
+  content: "\e51f"; }
+
+.fa-pause::before {
+  content: "\f04c"; }
+
+.fa-hill-avalanche::before {
+  content: "\e507"; }
+
+.fa-temperature-empty::before {
+  content: "\f2cb"; }
+
+.fa-temperature-0::before {
+  content: "\f2cb"; }
+
+.fa-thermometer-0::before {
+  content: "\f2cb"; }
+
+.fa-thermometer-empty::before {
+  content: "\f2cb"; }
+
+.fa-bomb::before {
+  content: "\f1e2"; }
+
+.fa-registered::before {
+  content: "\f25d"; }
+
+.fa-address-card::before {
+  content: "\f2bb"; }
+
+.fa-contact-card::before {
+  content: "\f2bb"; }
+
+.fa-vcard::before {
+  content: "\f2bb"; }
+
+.fa-scale-unbalanced-flip::before {
+  content: "\f516"; }
+
+.fa-balance-scale-right::before {
+  content: "\f516"; }
+
+.fa-subscript::before {
+  content: "\f12c"; }
+
+.fa-diamond-turn-right::before {
+  content: "\f5eb"; }
+
+.fa-directions::before {
+  content: "\f5eb"; }
+
+.fa-burst::before {
+  content: "\e4dc"; }
+
+.fa-house-laptop::before {
+  content: "\e066"; }
+
+.fa-laptop-house::before {
+  content: "\e066"; }
+
+.fa-face-tired::before {
+  content: "\f5c8"; }
+
+.fa-tired::before {
+  content: "\f5c8"; }
+
+.fa-money-bills::before {
+  content: "\e1f3"; }
+
+.fa-smog::before {
+  content: "\f75f"; }
+
+.fa-crutch::before {
+  content: "\f7f7"; }
+
+.fa-cloud-arrow-up::before {
+  content: "\f0ee"; }
+
+.fa-cloud-upload::before {
+  content: "\f0ee"; }
+
+.fa-cloud-upload-alt::before {
+  content: "\f0ee"; }
+
+.fa-palette::before {
+  content: "\f53f"; }
+
+.fa-arrows-turn-right::before {
+  content: "\e4c0"; }
+
+.fa-vest::before {
+  content: "\e085"; }
+
+.fa-ferry::before {
+  content: "\e4ea"; }
+
+.fa-arrows-down-to-people::before {
+  content: "\e4b9"; }
+
+.fa-seedling::before {
+  content: "\f4d8"; }
+
+.fa-sprout::before {
+  content: "\f4d8"; }
+
+.fa-left-right::before {
+  content: "\f337"; }
+
+.fa-arrows-alt-h::before {
+  content: "\f337"; }
+
+.fa-boxes-packing::before {
+  content: "\e4c7"; }
+
+.fa-circle-arrow-left::before {
+  content: "\f0a8"; }
+
+.fa-arrow-circle-left::before {
+  content: "\f0a8"; }
+
+.fa-group-arrows-rotate::before {
+  content: "\e4f6"; }
+
+.fa-bowl-food::before {
+  content: "\e4c6"; }
+
+.fa-candy-cane::before {
+  content: "\f786"; }
+
+.fa-arrow-down-wide-short::before {
+  content: "\f160"; }
+
+.fa-sort-amount-asc::before {
+  content: "\f160"; }
+
+.fa-sort-amount-down::before {
+  content: "\f160"; }
+
+.fa-cloud-bolt::before {
+  content: "\f76c"; }
+
+.fa-thunderstorm::before {
+  content: "\f76c"; }
+
+.fa-text-slash::before {
+  content: "\f87d"; }
+
+.fa-remove-format::before {
+  content: "\f87d"; }
+
+.fa-face-smile-wink::before {
+  content: "\f4da"; }
+
+.fa-smile-wink::before {
+  content: "\f4da"; }
+
+.fa-file-word::before {
+  content: "\f1c2"; }
+
+.fa-file-powerpoint::before {
+  content: "\f1c4"; }
+
+.fa-arrows-left-right::before {
+  content: "\f07e"; }
+
+.fa-arrows-h::before {
+  content: "\f07e"; }
+
+.fa-house-lock::before {
+  content: "\e510"; }
+
+.fa-cloud-arrow-down::before {
+  content: "\f0ed"; }
+
+.fa-cloud-download::before {
+  content: "\f0ed"; }
+
+.fa-cloud-download-alt::before {
+  content: "\f0ed"; }
+
+.fa-children::before {
+  content: "\e4e1"; }
+
+.fa-chalkboard::before {
+  content: "\f51b"; }
+
+.fa-blackboard::before {
+  content: "\f51b"; }
+
+.fa-user-large-slash::before {
+  content: "\f4fa"; }
+
+.fa-user-alt-slash::before {
+  content: "\f4fa"; }
+
+.fa-envelope-open::before {
+  content: "\f2b6"; }
+
+.fa-handshake-simple-slash::before {
+  content: "\e05f"; }
+
+.fa-handshake-alt-slash::before {
+  content: "\e05f"; }
+
+.fa-mattress-pillow::before {
+  content: "\e525"; }
+
+.fa-guarani-sign::before {
+  content: "\e19a"; }
+
+.fa-arrows-rotate::before {
+  content: "\f021"; }
+
+.fa-refresh::before {
+  content: "\f021"; }
+
+.fa-sync::before {
+  content: "\f021"; }
+
+.fa-fire-extinguisher::before {
+  content: "\f134"; }
+
+.fa-cruzeiro-sign::before {
+  content: "\e152"; }
+
+.fa-greater-than-equal::before {
+  content: "\f532"; }
+
+.fa-shield-halved::before {
+  content: "\f3ed"; }
+
+.fa-shield-alt::before {
+  content: "\f3ed"; }
+
+.fa-book-atlas::before {
+  content: "\f558"; }
+
+.fa-atlas::before {
+  content: "\f558"; }
+
+.fa-virus::before {
+  content: "\e074"; }
+
+.fa-envelope-circle-check::before {
+  content: "\e4e8"; }
+
+.fa-layer-group::before {
+  content: "\f5fd"; }
+
+.fa-arrows-to-dot::before {
+  content: "\e4be"; }
+
+.fa-archway::before {
+  content: "\f557"; }
+
+.fa-heart-circle-check::before {
+  content: "\e4fd"; }
+
+.fa-house-chimney-crack::before {
+  content: "\f6f1"; }
+
+.fa-house-damage::before {
+  content: "\f6f1"; }
+
+.fa-file-zipper::before {
+  content: "\f1c6"; }
+
+.fa-file-archive::before {
+  content: "\f1c6"; }
+
+.fa-square::before {
+  content: "\f0c8"; }
+
+.fa-martini-glass-empty::before {
+  content: "\f000"; }
+
+.fa-glass-martini::before {
+  content: "\f000"; }
+
+.fa-couch::before {
+  content: "\f4b8"; }
+
+.fa-cedi-sign::before {
+  content: "\e0df"; }
+
+.fa-italic::before {
+  content: "\f033"; }
+
+.fa-church::before {
+  content: "\f51d"; }
+
+.fa-comments-dollar::before {
+  content: "\f653"; }
+
+.fa-democrat::before {
+  content: "\f747"; }
+
+.fa-z::before {
+  content: "\5a"; }
+
+.fa-person-skiing::before {
+  content: "\f7c9"; }
+
+.fa-skiing::before {
+  content: "\f7c9"; }
+
+.fa-road-lock::before {
+  content: "\e567"; }
+
+.fa-a::before {
+  content: "\41"; }
+
+.fa-temperature-arrow-down::before {
+  content: "\e03f"; }
+
+.fa-temperature-down::before {
+  content: "\e03f"; }
+
+.fa-feather-pointed::before {
+  content: "\f56b"; }
+
+.fa-feather-alt::before {
+  content: "\f56b"; }
+
+.fa-p::before {
+  content: "\50"; }
+
+.fa-snowflake::before {
+  content: "\f2dc"; }
+
+.fa-newspaper::before {
+  content: "\f1ea"; }
+
+.fa-rectangle-ad::before {
+  content: "\f641"; }
+
+.fa-ad::before {
+  content: "\f641"; }
+
+.fa-circle-arrow-right::before {
+  content: "\f0a9"; }
+
+.fa-arrow-circle-right::before {
+  content: "\f0a9"; }
+
+.fa-filter-circle-xmark::before {
+  content: "\e17b"; }
+
+.fa-locust::before {
+  content: "\e520"; }
+
+.fa-sort::before {
+  content: "\f0dc"; }
+
+.fa-unsorted::before {
+  content: "\f0dc"; }
+
+.fa-list-ol::before {
+  content: "\f0cb"; }
+
+.fa-list-1-2::before {
+  content: "\f0cb"; }
+
+.fa-list-numeric::before {
+  content: "\f0cb"; }
+
+.fa-person-dress-burst::before {
+  content: "\e544"; }
+
+.fa-money-check-dollar::before {
+  content: "\f53d"; }
+
+.fa-money-check-alt::before {
+  content: "\f53d"; }
+
+.fa-vector-square::before {
+  content: "\f5cb"; }
+
+.fa-bread-slice::before {
+  content: "\f7ec"; }
+
+.fa-language::before {
+  content: "\f1ab"; }
+
+.fa-face-kiss-wink-heart::before {
+  content: "\f598"; }
+
+.fa-kiss-wink-heart::before {
+  content: "\f598"; }
+
+.fa-filter::before {
+  content: "\f0b0"; }
+
+.fa-question::before {
+  content: "\3f"; }
+
+.fa-file-signature::before {
+  content: "\f573"; }
+
+.fa-up-down-left-right::before {
+  content: "\f0b2"; }
+
+.fa-arrows-alt::before {
+  content: "\f0b2"; }
+
+.fa-house-chimney-user::before {
+  content: "\e065"; }
+
+.fa-hand-holding-heart::before {
+  content: "\f4be"; }
+
+.fa-puzzle-piece::before {
+  content: "\f12e"; }
+
+.fa-money-check::before {
+  content: "\f53c"; }
+
+.fa-star-half-stroke::before {
+  content: "\f5c0"; }
+
+.fa-star-half-alt::before {
+  content: "\f5c0"; }
+
+.fa-code::before {
+  content: "\f121"; }
+
+.fa-whiskey-glass::before {
+  content: "\f7a0"; }
+
+.fa-glass-whiskey::before {
+  content: "\f7a0"; }
+
+.fa-building-circle-exclamation::before {
+  content: "\e4d3"; }
+
+.fa-magnifying-glass-chart::before {
+  content: "\e522"; }
+
+.fa-arrow-up-right-from-square::before {
+  content: "\f08e"; }
+
+.fa-external-link::before {
+  content: "\f08e"; }
+
+.fa-cubes-stacked::before {
+  content: "\e4e6"; }
+
+.fa-won-sign::before {
+  content: "\f159"; }
+
+.fa-krw::before {
+  content: "\f159"; }
+
+.fa-won::before {
+  content: "\f159"; }
+
+.fa-virus-covid::before {
+  content: "\e4a8"; }
+
+.fa-austral-sign::before {
+  content: "\e0a9"; }
+
+.fa-f::before {
+  content: "\46"; }
+
+.fa-leaf::before {
+  content: "\f06c"; }
+
+.fa-road::before {
+  content: "\f018"; }
+
+.fa-taxi::before {
+  content: "\f1ba"; }
+
+.fa-cab::before {
+  content: "\f1ba"; }
+
+.fa-person-circle-plus::before {
+  content: "\e541"; }
+
+.fa-chart-pie::before {
+  content: "\f200"; }
+
+.fa-pie-chart::before {
+  content: "\f200"; }
+
+.fa-bolt-lightning::before {
+  content: "\e0b7"; }
+
+.fa-sack-xmark::before {
+  content: "\e56a"; }
+
+.fa-file-excel::before {
+  content: "\f1c3"; }
+
+.fa-file-contract::before {
+  content: "\f56c"; }
+
+.fa-fish-fins::before {
+  content: "\e4f2"; }
+
+.fa-building-flag::before {
+  content: "\e4d5"; }
+
+.fa-face-grin-beam::before {
+  content: "\f582"; }
+
+.fa-grin-beam::before {
+  content: "\f582"; }
+
+.fa-object-ungroup::before {
+  content: "\f248"; }
+
+.fa-poop::before {
+  content: "\f619"; }
+
+.fa-location-pin::before {
+  content: "\f041"; }
+
+.fa-map-marker::before {
+  content: "\f041"; }
+
+.fa-kaaba::before {
+  content: "\f66b"; }
+
+.fa-toilet-paper::before {
+  content: "\f71e"; }
+
+.fa-helmet-safety::before {
+  content: "\f807"; }
+
+.fa-hard-hat::before {
+  content: "\f807"; }
+
+.fa-hat-hard::before {
+  content: "\f807"; }
+
+.fa-eject::before {
+  content: "\f052"; }
+
+.fa-circle-right::before {
+  content: "\f35a"; }
+
+.fa-arrow-alt-circle-right::before {
+  content: "\f35a"; }
+
+.fa-plane-circle-check::before {
+  content: "\e555"; }
+
+.fa-face-rolling-eyes::before {
+  content: "\f5a5"; }
+
+.fa-meh-rolling-eyes::before {
+  content: "\f5a5"; }
+
+.fa-object-group::before {
+  content: "\f247"; }
+
+.fa-chart-line::before {
+  content: "\f201"; }
+
+.fa-line-chart::before {
+  content: "\f201"; }
+
+.fa-mask-ventilator::before {
+  content: "\e524"; }
+
+.fa-arrow-right::before {
+  content: "\f061"; }
+
+.fa-signs-post::before {
+  content: "\f277"; }
+
+.fa-map-signs::before {
+  content: "\f277"; }
+
+.fa-cash-register::before {
+  content: "\f788"; }
+
+.fa-person-circle-question::before {
+  content: "\e542"; }
+
+.fa-h::before {
+  content: "\48"; }
+
+.fa-tarp::before {
+  content: "\e57b"; }
+
+.fa-screwdriver-wrench::before {
+  content: "\f7d9"; }
+
+.fa-tools::before {
+  content: "\f7d9"; }
+
+.fa-arrows-to-eye::before {
+  content: "\e4bf"; }
+
+.fa-plug-circle-bolt::before {
+  content: "\e55b"; }
+
+.fa-heart::before {
+  content: "\f004"; }
+
+.fa-mars-and-venus::before {
+  content: "\f224"; }
+
+.fa-house-user::before {
+  content: "\e1b0"; }
+
+.fa-home-user::before {
+  content: "\e1b0"; }
+
+.fa-dumpster-fire::before {
+  content: "\f794"; }
+
+.fa-house-crack::before {
+  content: "\e3b1"; }
+
+.fa-martini-glass-citrus::before {
+  content: "\f561"; }
+
+.fa-cocktail::before {
+  content: "\f561"; }
+
+.fa-face-surprise::before {
+  content: "\f5c2"; }
+
+.fa-surprise::before {
+  content: "\f5c2"; }
+
+.fa-bottle-water::before {
+  content: "\e4c5"; }
+
+.fa-circle-pause::before {
+  content: "\f28b"; }
+
+.fa-pause-circle::before {
+  content: "\f28b"; }
+
+.fa-toilet-paper-slash::before {
+  content: "\e072"; }
+
+.fa-apple-whole::before {
+  content: "\f5d1"; }
+
+.fa-apple-alt::before {
+  content: "\f5d1"; }
+
+.fa-kitchen-set::before {
+  content: "\e51a"; }
+
+.fa-r::before {
+  content: "\52"; }
+
+.fa-temperature-quarter::before {
+  content: "\f2ca"; }
+
+.fa-temperature-1::before {
+  content: "\f2ca"; }
+
+.fa-thermometer-1::before {
+  content: "\f2ca"; }
+
+.fa-thermometer-quarter::before {
+  content: "\f2ca"; }
+
+.fa-cube::before {
+  content: "\f1b2"; }
+
+.fa-bitcoin-sign::before {
+  content: "\e0b4"; }
+
+.fa-shield-dog::before {
+  content: "\e573"; }
+
+.fa-solar-panel::before {
+  content: "\f5ba"; }
+
+.fa-lock-open::before {
+  content: "\f3c1"; }
+
+.fa-elevator::before {
+  content: "\e16d"; }
+
+.fa-money-bill-transfer::before {
+  content: "\e528"; }
+
+.fa-money-bill-trend-up::before {
+  content: "\e529"; }
+
+.fa-house-flood-water-circle-arrow-right::before {
+  content: "\e50f"; }
+
+.fa-square-poll-horizontal::before {
+  content: "\f682"; }
+
+.fa-poll-h::before {
+  content: "\f682"; }
+
+.fa-circle::before {
+  content: "\f111"; }
+
+.fa-backward-fast::before {
+  content: "\f049"; }
+
+.fa-fast-backward::before {
+  content: "\f049"; }
+
+.fa-recycle::before {
+  content: "\f1b8"; }
+
+.fa-user-astronaut::before {
+  content: "\f4fb"; }
+
+.fa-plane-slash::before {
+  content: "\e069"; }
+
+.fa-trademark::before {
+  content: "\f25c"; }
+
+.fa-basketball::before {
+  content: "\f434"; }
+
+.fa-basketball-ball::before {
+  content: "\f434"; }
+
+.fa-satellite-dish::before {
+  content: "\f7c0"; }
+
+.fa-circle-up::before {
+  content: "\f35b"; }
+
+.fa-arrow-alt-circle-up::before {
+  content: "\f35b"; }
+
+.fa-mobile-screen-button::before {
+  content: "\f3cd"; }
+
+.fa-mobile-alt::before {
+  content: "\f3cd"; }
+
+.fa-volume-high::before {
+  content: "\f028"; }
+
+.fa-volume-up::before {
+  content: "\f028"; }
+
+.fa-users-rays::before {
+  content: "\e593"; }
+
+.fa-wallet::before {
+  content: "\f555"; }
+
+.fa-clipboard-check::before {
+  content: "\f46c"; }
+
+.fa-file-audio::before {
+  content: "\f1c7"; }
+
+.fa-burger::before {
+  content: "\f805"; }
+
+.fa-hamburger::before {
+  content: "\f805"; }
+
+.fa-wrench::before {
+  content: "\f0ad"; }
+
+.fa-bugs::before {
+  content: "\e4d0"; }
+
+.fa-rupee-sign::before {
+  content: "\f156"; }
+
+.fa-rupee::before {
+  content: "\f156"; }
+
+.fa-file-image::before {
+  content: "\f1c5"; }
+
+.fa-circle-question::before {
+  content: "\f059"; }
+
+.fa-question-circle::before {
+  content: "\f059"; }
+
+.fa-plane-departure::before {
+  content: "\f5b0"; }
+
+.fa-handshake-slash::before {
+  content: "\e060"; }
+
+.fa-book-bookmark::before {
+  content: "\e0bb"; }
+
+.fa-code-branch::before {
+  content: "\f126"; }
+
+.fa-hat-cowboy::before {
+  content: "\f8c0"; }
+
+.fa-bridge::before {
+  content: "\e4c8"; }
+
+.fa-phone-flip::before {
+  content: "\f879"; }
+
+.fa-phone-alt::before {
+  content: "\f879"; }
+
+.fa-truck-front::before {
+  content: "\e2b7"; }
+
+.fa-cat::before {
+  content: "\f6be"; }
+
+.fa-anchor-circle-exclamation::before {
+  content: "\e4ab"; }
+
+.fa-truck-field::before {
+  content: "\e58d"; }
+
+.fa-route::before {
+  content: "\f4d7"; }
+
+.fa-clipboard-question::before {
+  content: "\e4e3"; }
+
+.fa-panorama::before {
+  content: "\e209"; }
+
+.fa-comment-medical::before {
+  content: "\f7f5"; }
+
+.fa-teeth-open::before {
+  content: "\f62f"; }
+
+.fa-file-circle-minus::before {
+  content: "\e4ed"; }
+
+.fa-tags::before {
+  content: "\f02c"; }
+
+.fa-wine-glass::before {
+  content: "\f4e3"; }
+
+.fa-forward-fast::before {
+  content: "\f050"; }
+
+.fa-fast-forward::before {
+  content: "\f050"; }
+
+.fa-face-meh-blank::before {
+  content: "\f5a4"; }
+
+.fa-meh-blank::before {
+  content: "\f5a4"; }
+
+.fa-square-parking::before {
+  content: "\f540"; }
+
+.fa-parking::before {
+  content: "\f540"; }
+
+.fa-house-signal::before {
+  content: "\e012"; }
+
+.fa-bars-progress::before {
+  content: "\f828"; }
+
+.fa-tasks-alt::before {
+  content: "\f828"; }
+
+.fa-faucet-drip::before {
+  content: "\e006"; }
+
+.fa-cart-flatbed::before {
+  content: "\f474"; }
+
+.fa-dolly-flatbed::before {
+  content: "\f474"; }
+
+.fa-ban-smoking::before {
+  content: "\f54d"; }
+
+.fa-smoking-ban::before {
+  content: "\f54d"; }
+
+.fa-terminal::before {
+  content: "\f120"; }
+
+.fa-mobile-button::before {
+  content: "\f10b"; }
+
+.fa-house-medical-flag::before {
+  content: "\e514"; }
+
+.fa-basket-shopping::before {
+  content: "\f291"; }
+
+.fa-shopping-basket::before {
+  content: "\f291"; }
+
+.fa-tape::before {
+  content: "\f4db"; }
+
+.fa-bus-simple::before {
+  content: "\f55e"; }
+
+.fa-bus-alt::before {
+  content: "\f55e"; }
+
+.fa-eye::before {
+  content: "\f06e"; }
+
+.fa-face-sad-cry::before {
+  content: "\f5b3"; }
+
+.fa-sad-cry::before {
+  content: "\f5b3"; }
+
+.fa-audio-description::before {
+  content: "\f29e"; }
+
+.fa-person-military-to-person::before {
+  content: "\e54c"; }
+
+.fa-file-shield::before {
+  content: "\e4f0"; }
+
+.fa-user-slash::before {
+  content: "\f506"; }
+
+.fa-pen::before {
+  content: "\f304"; }
+
+.fa-tower-observation::before {
+  content: "\e586"; }
+
+.fa-file-code::before {
+  content: "\f1c9"; }
+
+.fa-signal::before {
+  content: "\f012"; }
+
+.fa-signal-5::before {
+  content: "\f012"; }
+
+.fa-signal-perfect::before {
+  content: "\f012"; }
+
+.fa-bus::before {
+  content: "\f207"; }
+
+.fa-heart-circle-xmark::before {
+  content: "\e501"; }
+
+.fa-house-chimney::before {
+  content: "\e3af"; }
+
+.fa-home-lg::before {
+  content: "\e3af"; }
+
+.fa-window-maximize::before {
+  content: "\f2d0"; }
+
+.fa-face-frown::before {
+  content: "\f119"; }
+
+.fa-frown::before {
+  content: "\f119"; }
+
+.fa-prescription::before {
+  content: "\f5b1"; }
+
+.fa-shop::before {
+  content: "\f54f"; }
+
+.fa-store-alt::before {
+  content: "\f54f"; }
+
+.fa-floppy-disk::before {
+  content: "\f0c7"; }
+
+.fa-save::before {
+  content: "\f0c7"; }
+
+.fa-vihara::before {
+  content: "\f6a7"; }
+
+.fa-scale-unbalanced::before {
+  content: "\f515"; }
+
+.fa-balance-scale-left::before {
+  content: "\f515"; }
+
+.fa-sort-up::before {
+  content: "\f0de"; }
+
+.fa-sort-asc::before {
+  content: "\f0de"; }
+
+.fa-comment-dots::before {
+  content: "\f4ad"; }
+
+.fa-commenting::before {
+  content: "\f4ad"; }
+
+.fa-plant-wilt::before {
+  content: "\e5aa"; }
+
+.fa-diamond::before {
+  content: "\f219"; }
+
+.fa-face-grin-squint::before {
+  content: "\f585"; }
+
+.fa-grin-squint::before {
+  content: "\f585"; }
+
+.fa-hand-holding-dollar::before {
+  content: "\f4c0"; }
+
+.fa-hand-holding-usd::before {
+  content: "\f4c0"; }
+
+.fa-bacterium::before {
+  content: "\e05a"; }
+
+.fa-hand-pointer::before {
+  content: "\f25a"; }
+
+.fa-drum-steelpan::before {
+  content: "\f56a"; }
+
+.fa-hand-scissors::before {
+  content: "\f257"; }
+
+.fa-hands-praying::before {
+  content: "\f684"; }
+
+.fa-praying-hands::before {
+  content: "\f684"; }
+
+.fa-arrow-rotate-right::before {
+  content: "\f01e"; }
+
+.fa-arrow-right-rotate::before {
+  content: "\f01e"; }
+
+.fa-arrow-rotate-forward::before {
+  content: "\f01e"; }
+
+.fa-redo::before {
+  content: "\f01e"; }
+
+.fa-biohazard::before {
+  content: "\f780"; }
+
+.fa-location-crosshairs::before {
+  content: "\f601"; }
+
+.fa-location::before {
+  content: "\f601"; }
+
+.fa-mars-double::before {
+  content: "\f227"; }
+
+.fa-child-dress::before {
+  content: "\e59c"; }
+
+.fa-users-between-lines::before {
+  content: "\e591"; }
+
+.fa-lungs-virus::before {
+  content: "\e067"; }
+
+.fa-face-grin-tears::before {
+  content: "\f588"; }
+
+.fa-grin-tears::before {
+  content: "\f588"; }
+
+.fa-phone::before {
+  content: "\f095"; }
+
+.fa-calendar-xmark::before {
+  content: "\f273"; }
+
+.fa-calendar-times::before {
+  content: "\f273"; }
+
+.fa-child-reaching::before {
+  content: "\e59d"; }
+
+.fa-head-side-virus::before {
+  content: "\e064"; }
+
+.fa-user-gear::before {
+  content: "\f4fe"; }
+
+.fa-user-cog::before {
+  content: "\f4fe"; }
+
+.fa-arrow-up-1-9::before {
+  content: "\f163"; }
+
+.fa-sort-numeric-up::before {
+  content: "\f163"; }
+
+.fa-door-closed::before {
+  content: "\f52a"; }
+
+.fa-shield-virus::before {
+  content: "\e06c"; }
+
+.fa-dice-six::before {
+  content: "\f526"; }
+
+.fa-mosquito-net::before {
+  content: "\e52c"; }
+
+.fa-bridge-water::before {
+  content: "\e4ce"; }
+
+.fa-person-booth::before {
+  content: "\f756"; }
+
+.fa-text-width::before {
+  content: "\f035"; }
+
+.fa-hat-wizard::before {
+  content: "\f6e8"; }
+
+.fa-pen-fancy::before {
+  content: "\f5ac"; }
+
+.fa-person-digging::before {
+  content: "\f85e"; }
+
+.fa-digging::before {
+  content: "\f85e"; }
+
+.fa-trash::before {
+  content: "\f1f8"; }
+
+.fa-gauge-simple::before {
+  content: "\f629"; }
+
+.fa-gauge-simple-med::before {
+  content: "\f629"; }
+
+.fa-tachometer-average::before {
+  content: "\f629"; }
+
+.fa-book-medical::before {
+  content: "\f7e6"; }
+
+.fa-poo::before {
+  content: "\f2fe"; }
+
+.fa-quote-right::before {
+  content: "\f10e"; }
+
+.fa-quote-right-alt::before {
+  content: "\f10e"; }
+
+.fa-shirt::before {
+  content: "\f553"; }
+
+.fa-t-shirt::before {
+  content: "\f553"; }
+
+.fa-tshirt::before {
+  content: "\f553"; }
+
+.fa-cubes::before {
+  content: "\f1b3"; }
+
+.fa-divide::before {
+  content: "\f529"; }
+
+.fa-tenge-sign::before {
+  content: "\f7d7"; }
+
+.fa-tenge::before {
+  content: "\f7d7"; }
+
+.fa-headphones::before {
+  content: "\f025"; }
+
+.fa-hands-holding::before {
+  content: "\f4c2"; }
+
+.fa-hands-clapping::before {
+  content: "\e1a8"; }
+
+.fa-republican::before {
+  content: "\f75e"; }
+
+.fa-arrow-left::before {
+  content: "\f060"; }
+
+.fa-person-circle-xmark::before {
+  content: "\e543"; }
+
+.fa-ruler::before {
+  content: "\f545"; }
+
+.fa-align-left::before {
+  content: "\f036"; }
+
+.fa-dice-d6::before {
+  content: "\f6d1"; }
+
+.fa-restroom::before {
+  content: "\f7bd"; }
+
+.fa-j::before {
+  content: "\4a"; }
+
+.fa-users-viewfinder::before {
+  content: "\e595"; }
+
+.fa-file-video::before {
+  content: "\f1c8"; }
+
+.fa-up-right-from-square::before {
+  content: "\f35d"; }
+
+.fa-external-link-alt::before {
+  content: "\f35d"; }
+
+.fa-table-cells::before {
+  content: "\f00a"; }
+
+.fa-th::before {
+  content: "\f00a"; }
+
+.fa-file-pdf::before {
+  content: "\f1c1"; }
+
+.fa-book-bible::before {
+  content: "\f647"; }
+
+.fa-bible::before {
+  content: "\f647"; }
+
+.fa-o::before {
+  content: "\4f"; }
+
+.fa-suitcase-medical::before {
+  content: "\f0fa"; }
+
+.fa-medkit::before {
+  content: "\f0fa"; }
+
+.fa-user-secret::before {
+  content: "\f21b"; }
+
+.fa-otter::before {
+  content: "\f700"; }
+
+.fa-person-dress::before {
+  content: "\f182"; }
+
+.fa-female::before {
+  content: "\f182"; }
+
+.fa-comment-dollar::before {
+  content: "\f651"; }
+
+.fa-business-time::before {
+  content: "\f64a"; }
+
+.fa-briefcase-clock::before {
+  content: "\f64a"; }
+
+.fa-table-cells-large::before {
+  content: "\f009"; }
+
+.fa-th-large::before {
+  content: "\f009"; }
+
+.fa-book-tanakh::before {
+  content: "\f827"; }
+
+.fa-tanakh::before {
+  content: "\f827"; }
+
+.fa-phone-volume::before {
+  content: "\f2a0"; }
+
+.fa-volume-control-phone::before {
+  content: "\f2a0"; }
+
+.fa-hat-cowboy-side::before {
+  content: "\f8c1"; }
+
+.fa-clipboard-user::before {
+  content: "\f7f3"; }
+
+.fa-child::before {
+  content: "\f1ae"; }
+
+.fa-lira-sign::before {
+  content: "\f195"; }
+
+.fa-satellite::before {
+  content: "\f7bf"; }
+
+.fa-plane-lock::before {
+  content: "\e558"; }
+
+.fa-tag::before {
+  content: "\f02b"; }
+
+.fa-comment::before {
+  content: "\f075"; }
+
+.fa-cake-candles::before {
+  content: "\f1fd"; }
+
+.fa-birthday-cake::before {
+  content: "\f1fd"; }
+
+.fa-cake::before {
+  content: "\f1fd"; }
+
+.fa-envelope::before {
+  content: "\f0e0"; }
+
+.fa-angles-up::before {
+  content: "\f102"; }
+
+.fa-angle-double-up::before {
+  content: "\f102"; }
+
+.fa-paperclip::before {
+  content: "\f0c6"; }
+
+.fa-arrow-right-to-city::before {
+  content: "\e4b3"; }
+
+.fa-ribbon::before {
+  content: "\f4d6"; }
+
+.fa-lungs::before {
+  content: "\f604"; }
+
+.fa-arrow-up-9-1::before {
+  content: "\f887"; }
+
+.fa-sort-numeric-up-alt::before {
+  content: "\f887"; }
+
+.fa-litecoin-sign::before {
+  content: "\e1d3"; }
+
+.fa-border-none::before {
+  content: "\f850"; }
+
+.fa-circle-nodes::before {
+  content: "\e4e2"; }
+
+.fa-parachute-box::before {
+  content: "\f4cd"; }
+
+.fa-indent::before {
+  content: "\f03c"; }
+
+.fa-truck-field-un::before {
+  content: "\e58e"; }
+
+.fa-hourglass::before {
+  content: "\f254"; }
+
+.fa-hourglass-empty::before {
+  content: "\f254"; }
+
+.fa-mountain::before {
+  content: "\f6fc"; }
+
+.fa-user-doctor::before {
+  content: "\f0f0"; }
+
+.fa-user-md::before {
+  content: "\f0f0"; }
+
+.fa-circle-info::before {
+  content: "\f05a"; }
+
+.fa-info-circle::before {
+  content: "\f05a"; }
+
+.fa-cloud-meatball::before {
+  content: "\f73b"; }
+
+.fa-camera::before {
+  content: "\f030"; }
+
+.fa-camera-alt::before {
+  content: "\f030"; }
+
+.fa-square-virus::before {
+  content: "\e578"; }
+
+.fa-meteor::before {
+  content: "\f753"; }
+
+.fa-car-on::before {
+  content: "\e4dd"; }
+
+.fa-sleigh::before {
+  content: "\f7cc"; }
+
+.fa-arrow-down-1-9::before {
+  content: "\f162"; }
+
+.fa-sort-numeric-asc::before {
+  content: "\f162"; }
+
+.fa-sort-numeric-down::before {
+  content: "\f162"; }
+
+.fa-hand-holding-droplet::before {
+  content: "\f4c1"; }
+
+.fa-hand-holding-water::before {
+  content: "\f4c1"; }
+
+.fa-water::before {
+  content: "\f773"; }
+
+.fa-calendar-check::before {
+  content: "\f274"; }
+
+.fa-braille::before {
+  content: "\f2a1"; }
+
+.fa-prescription-bottle-medical::before {
+  content: "\f486"; }
+
+.fa-prescription-bottle-alt::before {
+  content: "\f486"; }
+
+.fa-landmark::before {
+  content: "\f66f"; }
+
+.fa-truck::before {
+  content: "\f0d1"; }
+
+.fa-crosshairs::before {
+  content: "\f05b"; }
+
+.fa-person-cane::before {
+  content: "\e53c"; }
+
+.fa-tent::before {
+  content: "\e57d"; }
+
+.fa-vest-patches::before {
+  content: "\e086"; }
+
+.fa-check-double::before {
+  content: "\f560"; }
+
+.fa-arrow-down-a-z::before {
+  content: "\f15d"; }
+
+.fa-sort-alpha-asc::before {
+  content: "\f15d"; }
+
+.fa-sort-alpha-down::before {
+  content: "\f15d"; }
+
+.fa-money-bill-wheat::before {
+  content: "\e52a"; }
+
+.fa-cookie::before {
+  content: "\f563"; }
+
+.fa-arrow-rotate-left::before {
+  content: "\f0e2"; }
+
+.fa-arrow-left-rotate::before {
+  content: "\f0e2"; }
+
+.fa-arrow-rotate-back::before {
+  content: "\f0e2"; }
+
+.fa-arrow-rotate-backward::before {
+  content: "\f0e2"; }
+
+.fa-undo::before {
+  content: "\f0e2"; }
+
+.fa-hard-drive::before {
+  content: "\f0a0"; }
+
+.fa-hdd::before {
+  content: "\f0a0"; }
+
+.fa-face-grin-squint-tears::before {
+  content: "\f586"; }
+
+.fa-grin-squint-tears::before {
+  content: "\f586"; }
+
+.fa-dumbbell::before {
+  content: "\f44b"; }
+
+.fa-rectangle-list::before {
+  content: "\f022"; }
+
+.fa-list-alt::before {
+  content: "\f022"; }
+
+.fa-tarp-droplet::before {
+  content: "\e57c"; }
+
+.fa-house-medical-circle-check::before {
+  content: "\e511"; }
+
+.fa-person-skiing-nordic::before {
+  content: "\f7ca"; }
+
+.fa-skiing-nordic::before {
+  content: "\f7ca"; }
+
+.fa-calendar-plus::before {
+  content: "\f271"; }
+
+.fa-plane-arrival::before {
+  content: "\f5af"; }
+
+.fa-circle-left::before {
+  content: "\f359"; }
+
+.fa-arrow-alt-circle-left::before {
+  content: "\f359"; }
+
+.fa-train-subway::before {
+  content: "\f239"; }
+
+.fa-subway::before {
+  content: "\f239"; }
+
+.fa-chart-gantt::before {
+  content: "\e0e4"; }
+
+.fa-indian-rupee-sign::before {
+  content: "\e1bc"; }
+
+.fa-indian-rupee::before {
+  content: "\e1bc"; }
+
+.fa-inr::before {
+  content: "\e1bc"; }
+
+.fa-crop-simple::before {
+  content: "\f565"; }
+
+.fa-crop-alt::before {
+  content: "\f565"; }
+
+.fa-money-bill-1::before {
+  content: "\f3d1"; }
+
+.fa-money-bill-alt::before {
+  content: "\f3d1"; }
+
+.fa-left-long::before {
+  content: "\f30a"; }
+
+.fa-long-arrow-alt-left::before {
+  content: "\f30a"; }
+
+.fa-dna::before {
+  content: "\f471"; }
+
+.fa-virus-slash::before {
+  content: "\e075"; }
+
+.fa-minus::before {
+  content: "\f068"; }
+
+.fa-subtract::before {
+  content: "\f068"; }
+
+.fa-chess::before {
+  content: "\f439"; }
+
+.fa-arrow-left-long::before {
+  content: "\f177"; }
+
+.fa-long-arrow-left::before {
+  content: "\f177"; }
+
+.fa-plug-circle-check::before {
+  content: "\e55c"; }
+
+.fa-street-view::before {
+  content: "\f21d"; }
+
+.fa-franc-sign::before {
+  content: "\e18f"; }
+
+.fa-volume-off::before {
+  content: "\f026"; }
+
+.fa-hands-asl-interpreting::before {
+  content: "\f2a3"; }
+
+.fa-american-sign-language-interpreting::before {
+  content: "\f2a3"; }
+
+.fa-asl-interpreting::before {
+  content: "\f2a3"; }
+
+.fa-hands-american-sign-language-interpreting::before {
+  content: "\f2a3"; }
+
+.fa-gear::before {
+  content: "\f013"; }
+
+.fa-cog::before {
+  content: "\f013"; }
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+  content: "\f5c7"; }
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+  content: "\f5c7"; }
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+  content: "\f678"; }
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+.fa-mosquito::before {
+  content: "\e52b"; }
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+.fa-star-of-david::before {
+  content: "\f69a"; }
+
+.fa-person-military-rifle::before {
+  content: "\e54b"; }
+
+.fa-cart-shopping::before {
+  content: "\f07a"; }
+
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+  content: "\f07a"; }
+
+.fa-vials::before {
+  content: "\f493"; }
+
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+  content: "\e55f"; }
+
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+  content: "\f67f"; }
+
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+  content: "\f58e"; }
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+  content: "\f148"; }
+
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+  content: "\f148"; }
+
+.fa-u::before {
+  content: "\55"; }
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+  content: "\f698"; }
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+  content: "\f698"; }
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+  content: "\f017"; }
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+  content: "\f017"; }
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+  content: "\f048"; }
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+.fa-step-backward::before {
+  content: "\f048"; }
+
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+  content: "\f482"; }
+
+.fa-faucet::before {
+  content: "\e005"; }
+
+.fa-baseball-bat-ball::before {
+  content: "\f432"; }
+
+.fa-s::before {
+  content: "\53"; }
+
+.fa-timeline::before {
+  content: "\e29c"; }
+
+.fa-keyboard::before {
+  content: "\f11c"; }
+
+.fa-caret-down::before {
+  content: "\f0d7"; }
+
+.fa-house-chimney-medical::before {
+  content: "\f7f2"; }
+
+.fa-clinic-medical::before {
+  content: "\f7f2"; }
+
+.fa-temperature-three-quarters::before {
+  content: "\f2c8"; }
+
+.fa-temperature-3::before {
+  content: "\f2c8"; }
+
+.fa-thermometer-3::before {
+  content: "\f2c8"; }
+
+.fa-thermometer-three-quarters::before {
+  content: "\f2c8"; }
+
+.fa-mobile-screen::before {
+  content: "\f3cf"; }
+
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+  content: "\f3cf"; }
+
+.fa-plane-up::before {
+  content: "\e22d"; }
+
+.fa-piggy-bank::before {
+  content: "\f4d3"; }
+
+.fa-battery-half::before {
+  content: "\f242"; }
+
+.fa-battery-3::before {
+  content: "\f242"; }
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+.fa-mountain-city::before {
+  content: "\e52e"; }
+
+.fa-coins::before {
+  content: "\f51e"; }
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+.fa-khanda::before {
+  content: "\f66d"; }
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+  content: "\f1de"; }
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+  content: "\f1de"; }
+
+.fa-folder-tree::before {
+  content: "\f802"; }
+
+.fa-network-wired::before {
+  content: "\f6ff"; }
+
+.fa-map-pin::before {
+  content: "\f276"; }
+
+.fa-hamsa::before {
+  content: "\f665"; }
+
+.fa-cent-sign::before {
+  content: "\e3f5"; }
+
+.fa-flask::before {
+  content: "\f0c3"; }
+
+.fa-person-pregnant::before {
+  content: "\e31e"; }
+
+.fa-wand-sparkles::before {
+  content: "\f72b"; }
+
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+  content: "\f142"; }
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+  content: "\f142"; }
+
+.fa-ticket::before {
+  content: "\f145"; }
+
+.fa-power-off::before {
+  content: "\f011"; }
+
+.fa-right-long::before {
+  content: "\f30b"; }
+
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+  content: "\f30b"; }
+
+.fa-flag-usa::before {
+  content: "\f74d"; }
+
+.fa-laptop-file::before {
+  content: "\e51d"; }
+
+.fa-tty::before {
+  content: "\f1e4"; }
+
+.fa-teletype::before {
+  content: "\f1e4"; }
+
+.fa-diagram-next::before {
+  content: "\e476"; }
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+.fa-person-rifle::before {
+  content: "\e54e"; }
+
+.fa-house-medical-circle-exclamation::before {
+  content: "\e512"; }
+
+.fa-closed-captioning::before {
+  content: "\f20a"; }
+
+.fa-person-hiking::before {
+  content: "\f6ec"; }
+
+.fa-hiking::before {
+  content: "\f6ec"; }
+
+.fa-venus-double::before {
+  content: "\f226"; }
+
+.fa-images::before {
+  content: "\f302"; }
+
+.fa-calculator::before {
+  content: "\f1ec"; }
+
+.fa-people-pulling::before {
+  content: "\e535"; }
+
+.fa-n::before {
+  content: "\4e"; }
+
+.fa-cable-car::before {
+  content: "\f7da"; }
+
+.fa-tram::before {
+  content: "\f7da"; }
+
+.fa-cloud-rain::before {
+  content: "\f73d"; }
+
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+  content: "\e4d4"; }
+
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+  content: "\f21a"; }
+
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+  content: "\e4b8"; }
+
+.fa-download::before {
+  content: "\f019"; }
+
+.fa-face-grin::before {
+  content: "\f580"; }
+
+.fa-grin::before {
+  content: "\f580"; }
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+  content: "\f55a"; }
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+  content: "\f55a"; }
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+.fa-eye-dropper::before {
+  content: "\f1fb"; }
+
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+  content: "\f1fb"; }
+
+.fa-eyedropper::before {
+  content: "\f1fb"; }
+
+.fa-file-circle-check::before {
+  content: "\e5a0"; }
+
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+  content: "\f04e"; }
+
+.fa-mobile::before {
+  content: "\f3ce"; }
+
+.fa-mobile-android::before {
+  content: "\f3ce"; }
+
+.fa-mobile-phone::before {
+  content: "\f3ce"; }
+
+.fa-face-meh::before {
+  content: "\f11a"; }
+
+.fa-meh::before {
+  content: "\f11a"; }
+
+.fa-align-center::before {
+  content: "\f037"; }
+
+.fa-book-skull::before {
+  content: "\f6b7"; }
+
+.fa-book-dead::before {
+  content: "\f6b7"; }
+
+.fa-id-card::before {
+  content: "\f2c2"; }
+
+.fa-drivers-license::before {
+  content: "\f2c2"; }
+
+.fa-outdent::before {
+  content: "\f03b"; }
+
+.fa-dedent::before {
+  content: "\f03b"; }
+
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+  content: "\e4fe"; }
+
+.fa-house::before {
+  content: "\f015"; }
+
+.fa-home::before {
+  content: "\f015"; }
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+.fa-home-alt::before {
+  content: "\f015"; }
+
+.fa-home-lg-alt::before {
+  content: "\f015"; }
+
+.fa-calendar-week::before {
+  content: "\f784"; }
+
+.fa-laptop-medical::before {
+  content: "\f812"; }
+
+.fa-b::before {
+  content: "\42"; }
+
+.fa-file-medical::before {
+  content: "\f477"; }
+
+.fa-dice-one::before {
+  content: "\f525"; }
+
+.fa-kiwi-bird::before {
+  content: "\f535"; }
+
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+  content: "\f0ec"; }
+
+.fa-exchange::before {
+  content: "\f0ec"; }
+
+.fa-rotate-right::before {
+  content: "\f2f9"; }
+
+.fa-redo-alt::before {
+  content: "\f2f9"; }
+
+.fa-rotate-forward::before {
+  content: "\f2f9"; }
+
+.fa-utensils::before {
+  content: "\f2e7"; }
+
+.fa-cutlery::before {
+  content: "\f2e7"; }
+
+.fa-arrow-up-wide-short::before {
+  content: "\f161"; }
+
+.fa-sort-amount-up::before {
+  content: "\f161"; }
+
+.fa-mill-sign::before {
+  content: "\e1ed"; }
+
+.fa-bowl-rice::before {
+  content: "\e2eb"; }
+
+.fa-skull::before {
+  content: "\f54c"; }
+
+.fa-tower-broadcast::before {
+  content: "\f519"; }
+
+.fa-broadcast-tower::before {
+  content: "\f519"; }
+
+.fa-truck-pickup::before {
+  content: "\f63c"; }
+
+.fa-up-long::before {
+  content: "\f30c"; }
+
+.fa-long-arrow-alt-up::before {
+  content: "\f30c"; }
+
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+  content: "\f04d"; }
+
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+  content: "\f387"; }
+
+.fa-upload::before {
+  content: "\f093"; }
+
+.fa-hurricane::before {
+  content: "\f751"; }
+
+.fa-mound::before {
+  content: "\e52d"; }
+
+.fa-toilet-portable::before {
+  content: "\e583"; }
+
+.fa-compact-disc::before {
+  content: "\f51f"; }
+
+.fa-file-arrow-down::before {
+  content: "\f56d"; }
+
+.fa-file-download::before {
+  content: "\f56d"; }
+
+.fa-caravan::before {
+  content: "\f8ff"; }
+
+.fa-shield-cat::before {
+  content: "\e572"; }
+
+.fa-bolt::before {
+  content: "\f0e7"; }
+
+.fa-zap::before {
+  content: "\f0e7"; }
+
+.fa-glass-water::before {
+  content: "\e4f4"; }
+
+.fa-oil-well::before {
+  content: "\e532"; }
+
+.fa-vault::before {
+  content: "\e2c5"; }
+
+.fa-mars::before {
+  content: "\f222"; }
+
+.fa-toilet::before {
+  content: "\f7d8"; }
+
+.fa-plane-circle-xmark::before {
+  content: "\e557"; }
+
+.fa-yen-sign::before {
+  content: "\f157"; }
+
+.fa-cny::before {
+  content: "\f157"; }
+
+.fa-jpy::before {
+  content: "\f157"; }
+
+.fa-rmb::before {
+  content: "\f157"; }
+
+.fa-yen::before {
+  content: "\f157"; }
+
+.fa-ruble-sign::before {
+  content: "\f158"; }
+
+.fa-rouble::before {
+  content: "\f158"; }
+
+.fa-rub::before {
+  content: "\f158"; }
+
+.fa-ruble::before {
+  content: "\f158"; }
+
+.fa-sun::before {
+  content: "\f185"; }
+
+.fa-guitar::before {
+  content: "\f7a6"; }
+
+.fa-face-laugh-wink::before {
+  content: "\f59c"; }
+
+.fa-laugh-wink::before {
+  content: "\f59c"; }
+
+.fa-horse-head::before {
+  content: "\f7ab"; }
+
+.fa-bore-hole::before {
+  content: "\e4c3"; }
+
+.fa-industry::before {
+  content: "\f275"; }
+
+.fa-circle-down::before {
+  content: "\f358"; }
+
+.fa-arrow-alt-circle-down::before {
+  content: "\f358"; }
+
+.fa-arrows-turn-to-dots::before {
+  content: "\e4c1"; }
+
+.fa-florin-sign::before {
+  content: "\e184"; }
+
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+  content: "\f884"; }
+
+.fa-sort-amount-desc::before {
+  content: "\f884"; }
+
+.fa-sort-amount-down-alt::before {
+  content: "\f884"; }
+
+.fa-less-than::before {
+  content: "\3c"; }
+
+.fa-angle-down::before {
+  content: "\f107"; }
+
+.fa-car-tunnel::before {
+  content: "\e4de"; }
+
+.fa-head-side-cough::before {
+  content: "\e061"; }
+
+.fa-grip-lines::before {
+  content: "\f7a4"; }
+
+.fa-thumbs-down::before {
+  content: "\f165"; }
+
+.fa-user-lock::before {
+  content: "\f502"; }
+
+.fa-arrow-right-long::before {
+  content: "\f178"; }
+
+.fa-long-arrow-right::before {
+  content: "\f178"; }
+
+.fa-anchor-circle-xmark::before {
+  content: "\e4ac"; }
+
+.fa-ellipsis::before {
+  content: "\f141"; }
+
+.fa-ellipsis-h::before {
+  content: "\f141"; }
+
+.fa-chess-pawn::before {
+  content: "\f443"; }
+
+.fa-kit-medical::before {
+  content: "\f479"; }
+
+.fa-first-aid::before {
+  content: "\f479"; }
+
+.fa-person-through-window::before {
+  content: "\e5a9"; }
+
+.fa-toolbox::before {
+  content: "\f552"; }
+
+.fa-hands-holding-circle::before {
+  content: "\e4fb"; }
+
+.fa-bug::before {
+  content: "\f188"; }
+
+.fa-credit-card::before {
+  content: "\f09d"; }
+
+.fa-credit-card-alt::before {
+  content: "\f09d"; }
+
+.fa-car::before {
+  content: "\f1b9"; }
+
+.fa-automobile::before {
+  content: "\f1b9"; }
+
+.fa-hand-holding-hand::before {
+  content: "\e4f7"; }
+
+.fa-book-open-reader::before {
+  content: "\f5da"; }
+
+.fa-book-reader::before {
+  content: "\f5da"; }
+
+.fa-mountain-sun::before {
+  content: "\e52f"; }
+
+.fa-arrows-left-right-to-line::before {
+  content: "\e4ba"; }
+
+.fa-dice-d20::before {
+  content: "\f6cf"; }
+
+.fa-truck-droplet::before {
+  content: "\e58c"; }
+
+.fa-file-circle-xmark::before {
+  content: "\e5a1"; }
+
+.fa-temperature-arrow-up::before {
+  content: "\e040"; }
+
+.fa-temperature-up::before {
+  content: "\e040"; }
+
+.fa-medal::before {
+  content: "\f5a2"; }
+
+.fa-bed::before {
+  content: "\f236"; }
+
+.fa-square-h::before {
+  content: "\f0fd"; }
+
+.fa-h-square::before {
+  content: "\f0fd"; }
+
+.fa-podcast::before {
+  content: "\f2ce"; }
+
+.fa-temperature-full::before {
+  content: "\f2c7"; }
+
+.fa-temperature-4::before {
+  content: "\f2c7"; }
+
+.fa-thermometer-4::before {
+  content: "\f2c7"; }
+
+.fa-thermometer-full::before {
+  content: "\f2c7"; }
+
+.fa-bell::before {
+  content: "\f0f3"; }
+
+.fa-superscript::before {
+  content: "\f12b"; }
+
+.fa-plug-circle-xmark::before {
+  content: "\e560"; }
+
+.fa-star-of-life::before {
+  content: "\f621"; }
+
+.fa-phone-slash::before {
+  content: "\f3dd"; }
+
+.fa-paint-roller::before {
+  content: "\f5aa"; }
+
+.fa-handshake-angle::before {
+  content: "\f4c4"; }
+
+.fa-hands-helping::before {
+  content: "\f4c4"; }
+
+.fa-location-dot::before {
+  content: "\f3c5"; }
+
+.fa-map-marker-alt::before {
+  content: "\f3c5"; }
+
+.fa-file::before {
+  content: "\f15b"; }
+
+.fa-greater-than::before {
+  content: "\3e"; }
+
+.fa-person-swimming::before {
+  content: "\f5c4"; }
+
+.fa-swimmer::before {
+  content: "\f5c4"; }
+
+.fa-arrow-down::before {
+  content: "\f063"; }
+
+.fa-droplet::before {
+  content: "\f043"; }
+
+.fa-tint::before {
+  content: "\f043"; }
+
+.fa-eraser::before {
+  content: "\f12d"; }
+
+.fa-earth-americas::before {
+  content: "\f57d"; }
+
+.fa-earth::before {
+  content: "\f57d"; }
+
+.fa-earth-america::before {
+  content: "\f57d"; }
+
+.fa-globe-americas::before {
+  content: "\f57d"; }
+
+.fa-person-burst::before {
+  content: "\e53b"; }
+
+.fa-dove::before {
+  content: "\f4ba"; }
+
+.fa-battery-empty::before {
+  content: "\f244"; }
+
+.fa-battery-0::before {
+  content: "\f244"; }
+
+.fa-socks::before {
+  content: "\f696"; }
+
+.fa-inbox::before {
+  content: "\f01c"; }
+
+.fa-section::before {
+  content: "\e447"; }
+
+.fa-gauge-high::before {
+  content: "\f625"; }
+
+.fa-tachometer-alt::before {
+  content: "\f625"; }
+
+.fa-tachometer-alt-fast::before {
+  content: "\f625"; }
+
+.fa-envelope-open-text::before {
+  content: "\f658"; }
+
+.fa-hospital::before {
+  content: "\f0f8"; }
+
+.fa-hospital-alt::before {
+  content: "\f0f8"; }
+
+.fa-hospital-wide::before {
+  content: "\f0f8"; }
+
+.fa-wine-bottle::before {
+  content: "\f72f"; }
+
+.fa-chess-rook::before {
+  content: "\f447"; }
+
+.fa-bars-staggered::before {
+  content: "\f550"; }
+
+.fa-reorder::before {
+  content: "\f550"; }
+
+.fa-stream::before {
+  content: "\f550"; }
+
+.fa-dharmachakra::before {
+  content: "\f655"; }
+
+.fa-hotdog::before {
+  content: "\f80f"; }
+
+.fa-person-walking-with-cane::before {
+  content: "\f29d"; }
+
+.fa-blind::before {
+  content: "\f29d"; }
+
+.fa-drum::before {
+  content: "\f569"; }
+
+.fa-ice-cream::before {
+  content: "\f810"; }
+
+.fa-heart-circle-bolt::before {
+  content: "\e4fc"; }
+
+.fa-fax::before {
+  content: "\f1ac"; }
+
+.fa-paragraph::before {
+  content: "\f1dd"; }
+
+.fa-check-to-slot::before {
+  content: "\f772"; }
+
+.fa-vote-yea::before {
+  content: "\f772"; }
+
+.fa-star-half::before {
+  content: "\f089"; }
+
+.fa-boxes-stacked::before {
+  content: "\f468"; }
+
+.fa-boxes::before {
+  content: "\f468"; }
+
+.fa-boxes-alt::before {
+  content: "\f468"; }
+
+.fa-link::before {
+  content: "\f0c1"; }
+
+.fa-chain::before {
+  content: "\f0c1"; }
+
+.fa-ear-listen::before {
+  content: "\f2a2"; }
+
+.fa-assistive-listening-systems::before {
+  content: "\f2a2"; }
+
+.fa-tree-city::before {
+  content: "\e587"; }
+
+.fa-play::before {
+  content: "\f04b"; }
+
+.fa-font::before {
+  content: "\f031"; }
+
+.fa-rupiah-sign::before {
+  content: "\e23d"; }
+
+.fa-magnifying-glass::before {
+  content: "\f002"; }
+
+.fa-search::before {
+  content: "\f002"; }
+
+.fa-table-tennis-paddle-ball::before {
+  content: "\f45d"; }
+
+.fa-ping-pong-paddle-ball::before {
+  content: "\f45d"; }
+
+.fa-table-tennis::before {
+  content: "\f45d"; }
+
+.fa-person-dots-from-line::before {
+  content: "\f470"; }
+
+.fa-diagnoses::before {
+  content: "\f470"; }
+
+.fa-trash-can-arrow-up::before {
+  content: "\f82a"; }
+
+.fa-trash-restore-alt::before {
+  content: "\f82a"; }
+
+.fa-naira-sign::before {
+  content: "\e1f6"; }
+
+.fa-cart-arrow-down::before {
+  content: "\f218"; }
+
+.fa-walkie-talkie::before {
+  content: "\f8ef"; }
+
+.fa-file-pen::before {
+  content: "\f31c"; }
+
+.fa-file-edit::before {
+  content: "\f31c"; }
+
+.fa-receipt::before {
+  content: "\f543"; }
+
+.fa-square-pen::before {
+  content: "\f14b"; }
+
+.fa-pen-square::before {
+  content: "\f14b"; }
+
+.fa-pencil-square::before {
+  content: "\f14b"; }
+
+.fa-suitcase-rolling::before {
+  content: "\f5c1"; }
+
+.fa-person-circle-exclamation::before {
+  content: "\e53f"; }
+
+.fa-chevron-down::before {
+  content: "\f078"; }
+
+.fa-battery-full::before {
+  content: "\f240"; }
+
+.fa-battery::before {
+  content: "\f240"; }
+
+.fa-battery-5::before {
+  content: "\f240"; }
+
+.fa-skull-crossbones::before {
+  content: "\f714"; }
+
+.fa-code-compare::before {
+  content: "\e13a"; }
+
+.fa-list-ul::before {
+  content: "\f0ca"; }
+
+.fa-list-dots::before {
+  content: "\f0ca"; }
+
+.fa-school-lock::before {
+  content: "\e56f"; }
+
+.fa-tower-cell::before {
+  content: "\e585"; }
+
+.fa-down-long::before {
+  content: "\f309"; }
+
+.fa-long-arrow-alt-down::before {
+  content: "\f309"; }
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+.fa-ranking-star::before {
+  content: "\e561"; }
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+.fa-chess-king::before {
+  content: "\f43f"; }
+
+.fa-person-harassing::before {
+  content: "\e549"; }
+
+.fa-brazilian-real-sign::before {
+  content: "\e46c"; }
+
+.fa-landmark-dome::before {
+  content: "\f752"; }
+
+.fa-landmark-alt::before {
+  content: "\f752"; }
+
+.fa-arrow-up::before {
+  content: "\f062"; }
+
+.fa-tv::before {
+  content: "\f26c"; }
+
+.fa-television::before {
+  content: "\f26c"; }
+
+.fa-tv-alt::before {
+  content: "\f26c"; }
+
+.fa-shrimp::before {
+  content: "\e448"; }
+
+.fa-list-check::before {
+  content: "\f0ae"; }
+
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+  content: "\f0ae"; }
+
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+  content: "\e519"; }
+
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+  content: "\f2bd"; }
+
+.fa-user-circle::before {
+  content: "\f2bd"; }
+
+.fa-user-shield::before {
+  content: "\f505"; }
+
+.fa-wind::before {
+  content: "\f72e"; }
+
+.fa-car-burst::before {
+  content: "\f5e1"; }
+
+.fa-car-crash::before {
+  content: "\f5e1"; }
+
+.fa-y::before {
+  content: "\59"; }
+
+.fa-person-snowboarding::before {
+  content: "\f7ce"; }
+
+.fa-snowboarding::before {
+  content: "\f7ce"; }
+
+.fa-truck-fast::before {
+  content: "\f48b"; }
+
+.fa-shipping-fast::before {
+  content: "\f48b"; }
+
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+  content: "\f578"; }
+
+.fa-user-graduate::before {
+  content: "\f501"; }
+
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+  content: "\f042"; }
+
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+  content: "\f042"; }
+
+.fa-clapperboard::before {
+  content: "\e131"; }
+
+.fa-circle-radiation::before {
+  content: "\f7ba"; }
+
+.fa-radiation-alt::before {
+  content: "\f7ba"; }
+
+.fa-baseball::before {
+  content: "\f433"; }
+
+.fa-baseball-ball::before {
+  content: "\f433"; }
+
+.fa-jet-fighter-up::before {
+  content: "\e518"; }
+
+.fa-diagram-project::before {
+  content: "\f542"; }
+
+.fa-project-diagram::before {
+  content: "\f542"; }
+
+.fa-copy::before {
+  content: "\f0c5"; }
+
+.fa-volume-xmark::before {
+  content: "\f6a9"; }
+
+.fa-volume-mute::before {
+  content: "\f6a9"; }
+
+.fa-volume-times::before {
+  content: "\f6a9"; }
+
+.fa-hand-sparkles::before {
+  content: "\e05d"; }
+
+.fa-grip::before {
+  content: "\f58d"; }
+
+.fa-grip-horizontal::before {
+  content: "\f58d"; }
+
+.fa-share-from-square::before {
+  content: "\f14d"; }
+
+.fa-share-square::before {
+  content: "\f14d"; }
+
+.fa-child-combatant::before {
+  content: "\e4e0"; }
+
+.fa-child-rifle::before {
+  content: "\e4e0"; }
+
+.fa-gun::before {
+  content: "\e19b"; }
+
+.fa-square-phone::before {
+  content: "\f098"; }
+
+.fa-phone-square::before {
+  content: "\f098"; }
+
+.fa-plus::before {
+  content: "\2b"; }
+
+.fa-add::before {
+  content: "\2b"; }
+
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+  content: "\f065"; }
+
+.fa-computer::before {
+  content: "\e4e5"; }
+
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+  content: "\f00d"; }
+
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+  content: "\f00d"; }
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+  content: "\f00d"; }
+
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+  content: "\f00d"; }
+
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+  content: "\f00d"; }
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+  content: "\f047"; }
+
+.fa-arrows::before {
+  content: "\f047"; }
+
+.fa-chalkboard-user::before {
+  content: "\f51c"; }
+
+.fa-chalkboard-teacher::before {
+  content: "\f51c"; }
+
+.fa-peso-sign::before {
+  content: "\e222"; }
+
+.fa-building-shield::before {
+  content: "\e4d8"; }
+
+.fa-baby::before {
+  content: "\f77c"; }
+
+.fa-users-line::before {
+  content: "\e592"; }
+
+.fa-quote-left::before {
+  content: "\f10d"; }
+
+.fa-quote-left-alt::before {
+  content: "\f10d"; }
+
+.fa-tractor::before {
+  content: "\f722"; }
+
+.fa-trash-arrow-up::before {
+  content: "\f829"; }
+
+.fa-trash-restore::before {
+  content: "\f829"; }
+
+.fa-arrow-down-up-lock::before {
+  content: "\e4b0"; }
+
+.fa-lines-leaning::before {
+  content: "\e51e"; }
+
+.fa-ruler-combined::before {
+  content: "\f546"; }
+
+.fa-copyright::before {
+  content: "\f1f9"; }
+
+.fa-equals::before {
+  content: "\3d"; }
+
+.fa-blender::before {
+  content: "\f517"; }
+
+.fa-teeth::before {
+  content: "\f62e"; }
+
+.fa-shekel-sign::before {
+  content: "\f20b"; }
+
+.fa-ils::before {
+  content: "\f20b"; }
+
+.fa-shekel::before {
+  content: "\f20b"; }
+
+.fa-sheqel::before {
+  content: "\f20b"; }
+
+.fa-sheqel-sign::before {
+  content: "\f20b"; }
+
+.fa-map::before {
+  content: "\f279"; }
+
+.fa-rocket::before {
+  content: "\f135"; }
+
+.fa-photo-film::before {
+  content: "\f87c"; }
+
+.fa-photo-video::before {
+  content: "\f87c"; }
+
+.fa-folder-minus::before {
+  content: "\f65d"; }
+
+.fa-store::before {
+  content: "\f54e"; }
+
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+  content: "\e098"; }
+
+.fa-plug-circle-minus::before {
+  content: "\e55e"; }
+
+.fa-sign-hanging::before {
+  content: "\f4d9"; }
+
+.fa-sign::before {
+  content: "\f4d9"; }
+
+.fa-bezier-curve::before {
+  content: "\f55b"; }
+
+.fa-bell-slash::before {
+  content: "\f1f6"; }
+
+.fa-tablet::before {
+  content: "\f3fb"; }
+
+.fa-tablet-android::before {
+  content: "\f3fb"; }
+
+.fa-school-flag::before {
+  content: "\e56e"; }
+
+.fa-fill::before {
+  content: "\f575"; }
+
+.fa-angle-up::before {
+  content: "\f106"; }
+
+.fa-drumstick-bite::before {
+  content: "\f6d7"; }
+
+.fa-holly-berry::before {
+  content: "\f7aa"; }
+
+.fa-chevron-left::before {
+  content: "\f053"; }
+
+.fa-bacteria::before {
+  content: "\e059"; }
+
+.fa-hand-lizard::before {
+  content: "\f258"; }
+
+.fa-notdef::before {
+  content: "\e1fe"; }
+
+.fa-disease::before {
+  content: "\f7fa"; }
+
+.fa-briefcase-medical::before {
+  content: "\f469"; }
+
+.fa-genderless::before {
+  content: "\f22d"; }
+
+.fa-chevron-right::before {
+  content: "\f054"; }
+
+.fa-retweet::before {
+  content: "\f079"; }
+
+.fa-car-rear::before {
+  content: "\f5de"; }
+
+.fa-car-alt::before {
+  content: "\f5de"; }
+
+.fa-pump-soap::before {
+  content: "\e06b"; }
+
+.fa-video-slash::before {
+  content: "\f4e2"; }
+
+.fa-battery-quarter::before {
+  content: "\f243"; }
+
+.fa-battery-2::before {
+  content: "\f243"; }
+
+.fa-radio::before {
+  content: "\f8d7"; }
+
+.fa-baby-carriage::before {
+  content: "\f77d"; }
+
+.fa-carriage-baby::before {
+  content: "\f77d"; }
+
+.fa-traffic-light::before {
+  content: "\f637"; }
+
+.fa-thermometer::before {
+  content: "\f491"; }
+
+.fa-vr-cardboard::before {
+  content: "\f729"; }
+
+.fa-hand-middle-finger::before {
+  content: "\f806"; }
+
+.fa-percent::before {
+  content: "\25"; }
+
+.fa-percentage::before {
+  content: "\25"; }
+
+.fa-truck-moving::before {
+  content: "\f4df"; }
+
+.fa-glass-water-droplet::before {
+  content: "\e4f5"; }
+
+.fa-display::before {
+  content: "\e163"; }
+
+.fa-face-smile::before {
+  content: "\f118"; }
+
+.fa-smile::before {
+  content: "\f118"; }
+
+.fa-thumbtack::before {
+  content: "\f08d"; }
+
+.fa-thumb-tack::before {
+  content: "\f08d"; }
+
+.fa-trophy::before {
+  content: "\f091"; }
+
+.fa-person-praying::before {
+  content: "\f683"; }
+
+.fa-pray::before {
+  content: "\f683"; }
+
+.fa-hammer::before {
+  content: "\f6e3"; }
+
+.fa-hand-peace::before {
+  content: "\f25b"; }
+
+.fa-rotate::before {
+  content: "\f2f1"; }
+
+.fa-sync-alt::before {
+  content: "\f2f1"; }
+
+.fa-spinner::before {
+  content: "\f110"; }
+
+.fa-robot::before {
+  content: "\f544"; }
+
+.fa-peace::before {
+  content: "\f67c"; }
+
+.fa-gears::before {
+  content: "\f085"; }
+
+.fa-cogs::before {
+  content: "\f085"; }
+
+.fa-warehouse::before {
+  content: "\f494"; }
+
+.fa-arrow-up-right-dots::before {
+  content: "\e4b7"; }
+
+.fa-splotch::before {
+  content: "\f5bc"; }
+
+.fa-face-grin-hearts::before {
+  content: "\f584"; }
+
+.fa-grin-hearts::before {
+  content: "\f584"; }
+
+.fa-dice-four::before {
+  content: "\f524"; }
+
+.fa-sim-card::before {
+  content: "\f7c4"; }
+
+.fa-transgender::before {
+  content: "\f225"; }
+
+.fa-transgender-alt::before {
+  content: "\f225"; }
+
+.fa-mercury::before {
+  content: "\f223"; }
+
+.fa-arrow-turn-down::before {
+  content: "\f149"; }
+
+.fa-level-down::before {
+  content: "\f149"; }
+
+.fa-person-falling-burst::before {
+  content: "\e547"; }
+
+.fa-award::before {
+  content: "\f559"; }
+
+.fa-ticket-simple::before {
+  content: "\f3ff"; }
+
+.fa-ticket-alt::before {
+  content: "\f3ff"; }
+
+.fa-building::before {
+  content: "\f1ad"; }
+
+.fa-angles-left::before {
+  content: "\f100"; }
+
+.fa-angle-double-left::before {
+  content: "\f100"; }
+
+.fa-qrcode::before {
+  content: "\f029"; }
+
+.fa-clock-rotate-left::before {
+  content: "\f1da"; }
+
+.fa-history::before {
+  content: "\f1da"; }
+
+.fa-face-grin-beam-sweat::before {
+  content: "\f583"; }
+
+.fa-grin-beam-sweat::before {
+  content: "\f583"; }
+
+.fa-file-export::before {
+  content: "\f56e"; }
+
+.fa-arrow-right-from-file::before {
+  content: "\f56e"; }
+
+.fa-shield::before {
+  content: "\f132"; }
+
+.fa-shield-blank::before {
+  content: "\f132"; }
+
+.fa-arrow-up-short-wide::before {
+  content: "\f885"; }
+
+.fa-sort-amount-up-alt::before {
+  content: "\f885"; }
+
+.fa-house-medical::before {
+  content: "\e3b2"; }
+
+.fa-golf-ball-tee::before {
+  content: "\f450"; }
+
+.fa-golf-ball::before {
+  content: "\f450"; }
+
+.fa-circle-chevron-left::before {
+  content: "\f137"; }
+
+.fa-chevron-circle-left::before {
+  content: "\f137"; }
+
+.fa-house-chimney-window::before {
+  content: "\e00d"; }
+
+.fa-pen-nib::before {
+  content: "\f5ad"; }
+
+.fa-tent-arrow-turn-left::before {
+  content: "\e580"; }
+
+.fa-tents::before {
+  content: "\e582"; }
+
+.fa-wand-magic::before {
+  content: "\f0d0"; }
+
+.fa-magic::before {
+  content: "\f0d0"; }
+
+.fa-dog::before {
+  content: "\f6d3"; }
+
+.fa-carrot::before {
+  content: "\f787"; }
+
+.fa-moon::before {
+  content: "\f186"; }
+
+.fa-wine-glass-empty::before {
+  content: "\f5ce"; }
+
+.fa-wine-glass-alt::before {
+  content: "\f5ce"; }
+
+.fa-cheese::before {
+  content: "\f7ef"; }
+
+.fa-yin-yang::before {
+  content: "\f6ad"; }
+
+.fa-music::before {
+  content: "\f001"; }
+
+.fa-code-commit::before {
+  content: "\f386"; }
+
+.fa-temperature-low::before {
+  content: "\f76b"; }
+
+.fa-person-biking::before {
+  content: "\f84a"; }
+
+.fa-biking::before {
+  content: "\f84a"; }
+
+.fa-broom::before {
+  content: "\f51a"; }
+
+.fa-shield-heart::before {
+  content: "\e574"; }
+
+.fa-gopuram::before {
+  content: "\f664"; }
+
+.fa-earth-oceania::before {
+  content: "\e47b"; }
+
+.fa-globe-oceania::before {
+  content: "\e47b"; }
+
+.fa-square-xmark::before {
+  content: "\f2d3"; }
+
+.fa-times-square::before {
+  content: "\f2d3"; }
+
+.fa-xmark-square::before {
+  content: "\f2d3"; }
+
+.fa-hashtag::before {
+  content: "\23"; }
+
+.fa-up-right-and-down-left-from-center::before {
+  content: "\f424"; }
+
+.fa-expand-alt::before {
+  content: "\f424"; }
+
+.fa-oil-can::before {
+  content: "\f613"; }
+
+.fa-t::before {
+  content: "\54"; }
+
+.fa-hippo::before {
+  content: "\f6ed"; }
+
+.fa-chart-column::before {
+  content: "\e0e3"; }
+
+.fa-infinity::before {
+  content: "\f534"; }
+
+.fa-vial-circle-check::before {
+  content: "\e596"; }
+
+.fa-person-arrow-down-to-line::before {
+  content: "\e538"; }
+
+.fa-voicemail::before {
+  content: "\f897"; }
+
+.fa-fan::before {
+  content: "\f863"; }
+
+.fa-person-walking-luggage::before {
+  content: "\e554"; }
+
+.fa-up-down::before {
+  content: "\f338"; }
+
+.fa-arrows-alt-v::before {
+  content: "\f338"; }
+
+.fa-cloud-moon-rain::before {
+  content: "\f73c"; }
+
+.fa-calendar::before {
+  content: "\f133"; }
+
+.fa-trailer::before {
+  content: "\e041"; }
+
+.fa-bahai::before {
+  content: "\f666"; }
+
+.fa-haykal::before {
+  content: "\f666"; }
+
+.fa-sd-card::before {
+  content: "\f7c2"; }
+
+.fa-dragon::before {
+  content: "\f6d5"; }
+
+.fa-shoe-prints::before {
+  content: "\f54b"; }
+
+.fa-circle-plus::before {
+  content: "\f055"; }
+
+.fa-plus-circle::before {
+  content: "\f055"; }
+
+.fa-face-grin-tongue-wink::before {
+  content: "\f58b"; }
+
+.fa-grin-tongue-wink::before {
+  content: "\f58b"; }
+
+.fa-hand-holding::before {
+  content: "\f4bd"; }
+
+.fa-plug-circle-exclamation::before {
+  content: "\e55d"; }
+
+.fa-link-slash::before {
+  content: "\f127"; }
+
+.fa-chain-broken::before {
+  content: "\f127"; }
+
+.fa-chain-slash::before {
+  content: "\f127"; }
+
+.fa-unlink::before {
+  content: "\f127"; }
+
+.fa-clone::before {
+  content: "\f24d"; }
+
+.fa-person-walking-arrow-loop-left::before {
+  content: "\e551"; }
+
+.fa-arrow-up-z-a::before {
+  content: "\f882"; }
+
+.fa-sort-alpha-up-alt::before {
+  content: "\f882"; }
+
+.fa-fire-flame-curved::before {
+  content: "\f7e4"; }
+
+.fa-fire-alt::before {
+  content: "\f7e4"; }
+
+.fa-tornado::before {
+  content: "\f76f"; }
+
+.fa-file-circle-plus::before {
+  content: "\e494"; }
+
+.fa-book-quran::before {
+  content: "\f687"; }
+
+.fa-quran::before {
+  content: "\f687"; }
+
+.fa-anchor::before {
+  content: "\f13d"; }
+
+.fa-border-all::before {
+  content: "\f84c"; }
+
+.fa-face-angry::before {
+  content: "\f556"; }
+
+.fa-angry::before {
+  content: "\f556"; }
+
+.fa-cookie-bite::before {
+  content: "\f564"; }
+
+.fa-arrow-trend-down::before {
+  content: "\e097"; }
+
+.fa-rss::before {
+  content: "\f09e"; }
+
+.fa-feed::before {
+  content: "\f09e"; }
+
+.fa-draw-polygon::before {
+  content: "\f5ee"; }
+
+.fa-scale-balanced::before {
+  content: "\f24e"; }
+
+.fa-balance-scale::before {
+  content: "\f24e"; }
+
+.fa-gauge-simple-high::before {
+  content: "\f62a"; }
+
+.fa-tachometer::before {
+  content: "\f62a"; }
+
+.fa-tachometer-fast::before {
+  content: "\f62a"; }
+
+.fa-shower::before {
+  content: "\f2cc"; }
+
+.fa-desktop::before {
+  content: "\f390"; }
+
+.fa-desktop-alt::before {
+  content: "\f390"; }
+
+.fa-m::before {
+  content: "\4d"; }
+
+.fa-table-list::before {
+  content: "\f00b"; }
+
+.fa-th-list::before {
+  content: "\f00b"; }
+
+.fa-comment-sms::before {
+  content: "\f7cd"; }
+
+.fa-sms::before {
+  content: "\f7cd"; }
+
+.fa-book::before {
+  content: "\f02d"; }
+
+.fa-user-plus::before {
+  content: "\f234"; }
+
+.fa-check::before {
+  content: "\f00c"; }
+
+.fa-battery-three-quarters::before {
+  content: "\f241"; }
+
+.fa-battery-4::before {
+  content: "\f241"; }
+
+.fa-house-circle-check::before {
+  content: "\e509"; }
+
+.fa-angle-left::before {
+  content: "\f104"; }
+
+.fa-diagram-successor::before {
+  content: "\e47a"; }
+
+.fa-truck-arrow-right::before {
+  content: "\e58b"; }
+
+.fa-arrows-split-up-and-left::before {
+  content: "\e4bc"; }
+
+.fa-hand-fist::before {
+  content: "\f6de"; }
+
+.fa-fist-raised::before {
+  content: "\f6de"; }
+
+.fa-cloud-moon::before {
+  content: "\f6c3"; }
+
+.fa-briefcase::before {
+  content: "\f0b1"; }
+
+.fa-person-falling::before {
+  content: "\e546"; }
+
+.fa-image-portrait::before {
+  content: "\f3e0"; }
+
+.fa-portrait::before {
+  content: "\f3e0"; }
+
+.fa-user-tag::before {
+  content: "\f507"; }
+
+.fa-rug::before {
+  content: "\e569"; }
+
+.fa-earth-europe::before {
+  content: "\f7a2"; }
+
+.fa-globe-europe::before {
+  content: "\f7a2"; }
+
+.fa-cart-flatbed-suitcase::before {
+  content: "\f59d"; }
+
+.fa-luggage-cart::before {
+  content: "\f59d"; }
+
+.fa-rectangle-xmark::before {
+  content: "\f410"; }
+
+.fa-rectangle-times::before {
+  content: "\f410"; }
+
+.fa-times-rectangle::before {
+  content: "\f410"; }
+
+.fa-window-close::before {
+  content: "\f410"; }
+
+.fa-baht-sign::before {
+  content: "\e0ac"; }
+
+.fa-book-open::before {
+  content: "\f518"; }
+
+.fa-book-journal-whills::before {
+  content: "\f66a"; }
+
+.fa-journal-whills::before {
+  content: "\f66a"; }
+
+.fa-handcuffs::before {
+  content: "\e4f8"; }
+
+.fa-triangle-exclamation::before {
+  content: "\f071"; }
+
+.fa-exclamation-triangle::before {
+  content: "\f071"; }
+
+.fa-warning::before {
+  content: "\f071"; }
+
+.fa-database::before {
+  content: "\f1c0"; }
+
+.fa-share::before {
+  content: "\f064"; }
+
+.fa-arrow-turn-right::before {
+  content: "\f064"; }
+
+.fa-mail-forward::before {
+  content: "\f064"; }
+
+.fa-bottle-droplet::before {
+  content: "\e4c4"; }
+
+.fa-mask-face::before {
+  content: "\e1d7"; }
+
+.fa-hill-rockslide::before {
+  content: "\e508"; }
+
+.fa-right-left::before {
+  content: "\f362"; }
+
+.fa-exchange-alt::before {
+  content: "\f362"; }
+
+.fa-paper-plane::before {
+  content: "\f1d8"; }
+
+.fa-road-circle-exclamation::before {
+  content: "\e565"; }
+
+.fa-dungeon::before {
+  content: "\f6d9"; }
+
+.fa-align-right::before {
+  content: "\f038"; }
+
+.fa-money-bill-1-wave::before {
+  content: "\f53b"; }
+
+.fa-money-bill-wave-alt::before {
+  content: "\f53b"; }
+
+.fa-life-ring::before {
+  content: "\f1cd"; }
+
+.fa-hands::before {
+  content: "\f2a7"; }
+
+.fa-sign-language::before {
+  content: "\f2a7"; }
+
+.fa-signing::before {
+  content: "\f2a7"; }
+
+.fa-calendar-day::before {
+  content: "\f783"; }
+
+.fa-water-ladder::before {
+  content: "\f5c5"; }
+
+.fa-ladder-water::before {
+  content: "\f5c5"; }
+
+.fa-swimming-pool::before {
+  content: "\f5c5"; }
+
+.fa-arrows-up-down::before {
+  content: "\f07d"; }
+
+.fa-arrows-v::before {
+  content: "\f07d"; }
+
+.fa-face-grimace::before {
+  content: "\f57f"; }
+
+.fa-grimace::before {
+  content: "\f57f"; }
+
+.fa-wheelchair-move::before {
+  content: "\e2ce"; }
+
+.fa-wheelchair-alt::before {
+  content: "\e2ce"; }
+
+.fa-turn-down::before {
+  content: "\f3be"; }
+
+.fa-level-down-alt::before {
+  content: "\f3be"; }
+
+.fa-person-walking-arrow-right::before {
+  content: "\e552"; }
+
+.fa-square-envelope::before {
+  content: "\f199"; }
+
+.fa-envelope-square::before {
+  content: "\f199"; }
+
+.fa-dice::before {
+  content: "\f522"; }
+
+.fa-bowling-ball::before {
+  content: "\f436"; }
+
+.fa-brain::before {
+  content: "\f5dc"; }
+
+.fa-bandage::before {
+  content: "\f462"; }
+
+.fa-band-aid::before {
+  content: "\f462"; }
+
+.fa-calendar-minus::before {
+  content: "\f272"; }
+
+.fa-circle-xmark::before {
+  content: "\f057"; }
+
+.fa-times-circle::before {
+  content: "\f057"; }
+
+.fa-xmark-circle::before {
+  content: "\f057"; }
+
+.fa-gifts::before {
+  content: "\f79c"; }
+
+.fa-hotel::before {
+  content: "\f594"; }
+
+.fa-earth-asia::before {
+  content: "\f57e"; }
+
+.fa-globe-asia::before {
+  content: "\f57e"; }
+
+.fa-id-card-clip::before {
+  content: "\f47f"; }
+
+.fa-id-card-alt::before {
+  content: "\f47f"; }
+
+.fa-magnifying-glass-plus::before {
+  content: "\f00e"; }
+
+.fa-search-plus::before {
+  content: "\f00e"; }
+
+.fa-thumbs-up::before {
+  content: "\f164"; }
+
+.fa-user-clock::before {
+  content: "\f4fd"; }
+
+.fa-hand-dots::before {
+  content: "\f461"; }
+
+.fa-allergies::before {
+  content: "\f461"; }
+
+.fa-file-invoice::before {
+  content: "\f570"; }
+
+.fa-window-minimize::before {
+  content: "\f2d1"; }
+
+.fa-mug-saucer::before {
+  content: "\f0f4"; }
+
+.fa-coffee::before {
+  content: "\f0f4"; }
+
+.fa-brush::before {
+  content: "\f55d"; }
+
+.fa-mask::before {
+  content: "\f6fa"; }
+
+.fa-magnifying-glass-minus::before {
+  content: "\f010"; }
+
+.fa-search-minus::before {
+  content: "\f010"; }
+
+.fa-ruler-vertical::before {
+  content: "\f548"; }
+
+.fa-user-large::before {
+  content: "\f406"; }
+
+.fa-user-alt::before {
+  content: "\f406"; }
+
+.fa-train-tram::before {
+  content: "\e5b4"; }
+
+.fa-user-nurse::before {
+  content: "\f82f"; }
+
+.fa-syringe::before {
+  content: "\f48e"; }
+
+.fa-cloud-sun::before {
+  content: "\f6c4"; }
+
+.fa-stopwatch-20::before {
+  content: "\e06f"; }
+
+.fa-square-full::before {
+  content: "\f45c"; }
+
+.fa-magnet::before {
+  content: "\f076"; }
+
+.fa-jar::before {
+  content: "\e516"; }
+
+.fa-note-sticky::before {
+  content: "\f249"; }
+
+.fa-sticky-note::before {
+  content: "\f249"; }
+
+.fa-bug-slash::before {
+  content: "\e490"; }
+
+.fa-arrow-up-from-water-pump::before {
+  content: "\e4b6"; }
+
+.fa-bone::before {
+  content: "\f5d7"; }
+
+.fa-user-injured::before {
+  content: "\f728"; }
+
+.fa-face-sad-tear::before {
+  content: "\f5b4"; }
+
+.fa-sad-tear::before {
+  content: "\f5b4"; }
+
+.fa-plane::before {
+  content: "\f072"; }
+
+.fa-tent-arrows-down::before {
+  content: "\e581"; }
+
+.fa-exclamation::before {
+  content: "\21"; }
+
+.fa-arrows-spin::before {
+  content: "\e4bb"; }
+
+.fa-print::before {
+  content: "\f02f"; }
+
+.fa-turkish-lira-sign::before {
+  content: "\e2bb"; }
+
+.fa-try::before {
+  content: "\e2bb"; }
+
+.fa-turkish-lira::before {
+  content: "\e2bb"; }
+
+.fa-dollar-sign::before {
+  content: "\24"; }
+
+.fa-dollar::before {
+  content: "\24"; }
+
+.fa-usd::before {
+  content: "\24"; }
+
+.fa-x::before {
+  content: "\58"; }
+
+.fa-magnifying-glass-dollar::before {
+  content: "\f688"; }
+
+.fa-search-dollar::before {
+  content: "\f688"; }
+
+.fa-users-gear::before {
+  content: "\f509"; }
+
+.fa-users-cog::before {
+  content: "\f509"; }
+
+.fa-person-military-pointing::before {
+  content: "\e54a"; }
+
+.fa-building-columns::before {
+  content: "\f19c"; }
+
+.fa-bank::before {
+  content: "\f19c"; }
+
+.fa-institution::before {
+  content: "\f19c"; }
+
+.fa-museum::before {
+  content: "\f19c"; }
+
+.fa-university::before {
+  content: "\f19c"; }
+
+.fa-umbrella::before {
+  content: "\f0e9"; }
+
+.fa-trowel::before {
+  content: "\e589"; }
+
+.fa-d::before {
+  content: "\44"; }
+
+.fa-stapler::before {
+  content: "\e5af"; }
+
+.fa-masks-theater::before {
+  content: "\f630"; }
+
+.fa-theater-masks::before {
+  content: "\f630"; }
+
+.fa-kip-sign::before {
+  content: "\e1c4"; }
+
+.fa-hand-point-left::before {
+  content: "\f0a5"; }
+
+.fa-handshake-simple::before {
+  content: "\f4c6"; }
+
+.fa-handshake-alt::before {
+  content: "\f4c6"; }
+
+.fa-jet-fighter::before {
+  content: "\f0fb"; }
+
+.fa-fighter-jet::before {
+  content: "\f0fb"; }
+
+.fa-square-share-nodes::before {
+  content: "\f1e1"; }
+
+.fa-share-alt-square::before {
+  content: "\f1e1"; }
+
+.fa-barcode::before {
+  content: "\f02a"; }
+
+.fa-plus-minus::before {
+  content: "\e43c"; }
+
+.fa-video::before {
+  content: "\f03d"; }
+
+.fa-video-camera::before {
+  content: "\f03d"; }
+
+.fa-graduation-cap::before {
+  content: "\f19d"; }
+
+.fa-mortar-board::before {
+  content: "\f19d"; }
+
+.fa-hand-holding-medical::before {
+  content: "\e05c"; }
+
+.fa-person-circle-check::before {
+  content: "\e53e"; }
+
+.fa-turn-up::before {
+  content: "\f3bf"; }
+
+.fa-level-up-alt::before {
+  content: "\f3bf"; }
+
+.sr-only,
+.fa-sr-only {
+  position: absolute;
+  width: 1px;
+  height: 1px;
+  padding: 0;
+  margin: -1px;
+  overflow: hidden;
+  clip: rect(0, 0, 0, 0);
+  white-space: nowrap;
+  border-width: 0; }
+
+.sr-only-focusable:not(:focus),
+.fa-sr-only-focusable:not(:focus) {
+  position: absolute;
+  width: 1px;
+  height: 1px;
+  padding: 0;
+  margin: -1px;
+  overflow: hidden;
+  clip: rect(0, 0, 0, 0);
+  white-space: nowrap;
+  border-width: 0; }
+:root, :host {
+  --fa-style-family-brands: 'Font Awesome 6 Brands';
+  --fa-font-brands: normal 400 1em/1 'Font Awesome 6 Brands'; }
+
+@font-face {
+  font-family: 'Font Awesome 6 Brands';
+  font-style: normal;
+  font-weight: 400;
+  font-display: block;
+  src: url("../webfonts/fa-brands-400.woff2") format("woff2"), url("../webfonts/fa-brands-400.ttf") format("truetype"); }
+
+.fab,
+.fa-brands {
+  font-weight: 400; }
+
+.fa-monero:before {
+  content: "\f3d0"; }
+
+.fa-hooli:before {
+  content: "\f427"; }
+
+.fa-yelp:before {
+  content: "\f1e9"; }
+
+.fa-cc-visa:before {
+  content: "\f1f0"; }
+
+.fa-lastfm:before {
+  content: "\f202"; }
+
+.fa-shopware:before {
+  content: "\f5b5"; }
+
+.fa-creative-commons-nc:before {
+  content: "\f4e8"; }
+
+.fa-aws:before {
+  content: "\f375"; }
+
+.fa-redhat:before {
+  content: "\f7bc"; }
+
+.fa-yoast:before {
+  content: "\f2b1"; }
+
+.fa-cloudflare:before {
+  content: "\e07d"; }
+
+.fa-ups:before {
+  content: "\f7e0"; }
+
+.fa-wpexplorer:before {
+  content: "\f2de"; }
+
+.fa-dyalog:before {
+  content: "\f399"; }
+
+.fa-bity:before {
+  content: "\f37a"; }
+
+.fa-stackpath:before {
+  content: "\f842"; }
+
+.fa-buysellads:before {
+  content: "\f20d"; }
+
+.fa-first-order:before {
+  content: "\f2b0"; }
+
+.fa-modx:before {
+  content: "\f285"; }
+
+.fa-guilded:before {
+  content: "\e07e"; }
+
+.fa-vnv:before {
+  content: "\f40b"; }
+
+.fa-square-js:before {
+  content: "\f3b9"; }
+
+.fa-js-square:before {
+  content: "\f3b9"; }
+
+.fa-microsoft:before {
+  content: "\f3ca"; }
+
+.fa-qq:before {
+  content: "\f1d6"; }
+
+.fa-orcid:before {
+  content: "\f8d2"; }
+
+.fa-java:before {
+  content: "\f4e4"; }
+
+.fa-invision:before {
+  content: "\f7b0"; }
+
+.fa-creative-commons-pd-alt:before {
+  content: "\f4ed"; }
+
+.fa-centercode:before {
+  content: "\f380"; }
+
+.fa-glide-g:before {
+  content: "\f2a6"; }
+
+.fa-drupal:before {
+  content: "\f1a9"; }
+
+.fa-hire-a-helper:before {
+  content: "\f3b0"; }
+
+.fa-creative-commons-by:before {
+  content: "\f4e7"; }
+
+.fa-unity:before {
+  content: "\e049"; }
+
+.fa-whmcs:before {
+  content: "\f40d"; }
+
+.fa-rocketchat:before {
+  content: "\f3e8"; }
+
+.fa-vk:before {
+  content: "\f189"; }
+
+.fa-untappd:before {
+  content: "\f405"; }
+
+.fa-mailchimp:before {
+  content: "\f59e"; }
+
+.fa-css3-alt:before {
+  content: "\f38b"; }
+
+.fa-square-reddit:before {
+  content: "\f1a2"; }
+
+.fa-reddit-square:before {
+  content: "\f1a2"; }
+
+.fa-vimeo-v:before {
+  content: "\f27d"; }
+
+.fa-contao:before {
+  content: "\f26d"; }
+
+.fa-square-font-awesome:before {
+  content: "\e5ad"; }
+
+.fa-deskpro:before {
+  content: "\f38f"; }
+
+.fa-sistrix:before {
+  content: "\f3ee"; }
+
+.fa-square-instagram:before {
+  content: "\e055"; }
+
+.fa-instagram-square:before {
+  content: "\e055"; }
+
+.fa-battle-net:before {
+  content: "\f835"; }
+
+.fa-the-red-yeti:before {
+  content: "\f69d"; }
+
+.fa-square-hacker-news:before {
+  content: "\f3af"; }
+
+.fa-hacker-news-square:before {
+  content: "\f3af"; }
+
+.fa-edge:before {
+  content: "\f282"; }
+
+.fa-threads:before {
+  content: "\e618"; }
+
+.fa-napster:before {
+  content: "\f3d2"; }
+
+.fa-square-snapchat:before {
+  content: "\f2ad"; }
+
+.fa-snapchat-square:before {
+  content: "\f2ad"; }
+
+.fa-google-plus-g:before {
+  content: "\f0d5"; }
+
+.fa-artstation:before {
+  content: "\f77a"; }
+
+.fa-markdown:before {
+  content: "\f60f"; }
+
+.fa-sourcetree:before {
+  content: "\f7d3"; }
+
+.fa-google-plus:before {
+  content: "\f2b3"; }
+
+.fa-diaspora:before {
+  content: "\f791"; }
+
+.fa-foursquare:before {
+  content: "\f180"; }
+
+.fa-stack-overflow:before {
+  content: "\f16c"; }
+
+.fa-github-alt:before {
+  content: "\f113"; }
+
+.fa-phoenix-squadron:before {
+  content: "\f511"; }
+
+.fa-pagelines:before {
+  content: "\f18c"; }
+
+.fa-algolia:before {
+  content: "\f36c"; }
+
+.fa-red-river:before {
+  content: "\f3e3"; }
+
+.fa-creative-commons-sa:before {
+  content: "\f4ef"; }
+
+.fa-safari:before {
+  content: "\f267"; }
+
+.fa-google:before {
+  content: "\f1a0"; }
+
+.fa-square-font-awesome-stroke:before {
+  content: "\f35c"; }
+
+.fa-font-awesome-alt:before {
+  content: "\f35c"; }
+
+.fa-atlassian:before {
+  content: "\f77b"; }
+
+.fa-linkedin-in:before {
+  content: "\f0e1"; }
+
+.fa-digital-ocean:before {
+  content: "\f391"; }
+
+.fa-nimblr:before {
+  content: "\f5a8"; }
+
+.fa-chromecast:before {
+  content: "\f838"; }
+
+.fa-evernote:before {
+  content: "\f839"; }
+
+.fa-hacker-news:before {
+  content: "\f1d4"; }
+
+.fa-creative-commons-sampling:before {
+  content: "\f4f0"; }
+
+.fa-adversal:before {
+  content: "\f36a"; }
+
+.fa-creative-commons:before {
+  content: "\f25e"; }
+
+.fa-watchman-monitoring:before {
+  content: "\e087"; }
+
+.fa-fonticons:before {
+  content: "\f280"; }
+
+.fa-weixin:before {
+  content: "\f1d7"; }
+
+.fa-shirtsinbulk:before {
+  content: "\f214"; }
+
+.fa-codepen:before {
+  content: "\f1cb"; }
+
+.fa-git-alt:before {
+  content: "\f841"; }
+
+.fa-lyft:before {
+  content: "\f3c3"; }
+
+.fa-rev:before {
+  content: "\f5b2"; }
+
+.fa-windows:before {
+  content: "\f17a"; }
+
+.fa-wizards-of-the-coast:before {
+  content: "\f730"; }
+
+.fa-square-viadeo:before {
+  content: "\f2aa"; }
+
+.fa-viadeo-square:before {
+  content: "\f2aa"; }
+
+.fa-meetup:before {
+  content: "\f2e0"; }
+
+.fa-centos:before {
+  content: "\f789"; }
+
+.fa-adn:before {
+  content: "\f170"; }
+
+.fa-cloudsmith:before {
+  content: "\f384"; }
+
+.fa-pied-piper-alt:before {
+  content: "\f1a8"; }
+
+.fa-square-dribbble:before {
+  content: "\f397"; }
+
+.fa-dribbble-square:before {
+  content: "\f397"; }
+
+.fa-codiepie:before {
+  content: "\f284"; }
+
+.fa-node:before {
+  content: "\f419"; }
+
+.fa-mix:before {
+  content: "\f3cb"; }
+
+.fa-steam:before {
+  content: "\f1b6"; }
+
+.fa-cc-apple-pay:before {
+  content: "\f416"; }
+
+.fa-scribd:before {
+  content: "\f28a"; }
+
+.fa-debian:before {
+  content: "\e60b"; }
+
+.fa-openid:before {
+  content: "\f19b"; }
+
+.fa-instalod:before {
+  content: "\e081"; }
+
+.fa-expeditedssl:before {
+  content: "\f23e"; }
+
+.fa-sellcast:before {
+  content: "\f2da"; }
+
+.fa-square-twitter:before {
+  content: "\f081"; }
+
+.fa-twitter-square:before {
+  content: "\f081"; }
+
+.fa-r-project:before {
+  content: "\f4f7"; }
+
+.fa-delicious:before {
+  content: "\f1a5"; }
+
+.fa-freebsd:before {
+  content: "\f3a4"; }
+
+.fa-vuejs:before {
+  content: "\f41f"; }
+
+.fa-accusoft:before {
+  content: "\f369"; }
+
+.fa-ioxhost:before {
+  content: "\f208"; }
+
+.fa-fonticons-fi:before {
+  content: "\f3a2"; }
+
+.fa-app-store:before {
+  content: "\f36f"; }
+
+.fa-cc-mastercard:before {
+  content: "\f1f1"; }
+
+.fa-itunes-note:before {
+  content: "\f3b5"; }
+
+.fa-golang:before {
+  content: "\e40f"; }
+
+.fa-kickstarter:before {
+  content: "\f3bb"; }
+
+.fa-grav:before {
+  content: "\f2d6"; }
+
+.fa-weibo:before {
+  content: "\f18a"; }
+
+.fa-uncharted:before {
+  content: "\e084"; }
+
+.fa-firstdraft:before {
+  content: "\f3a1"; }
+
+.fa-square-youtube:before {
+  content: "\f431"; }
+
+.fa-youtube-square:before {
+  content: "\f431"; }
+
+.fa-wikipedia-w:before {
+  content: "\f266"; }
+
+.fa-wpressr:before {
+  content: "\f3e4"; }
+
+.fa-rendact:before {
+  content: "\f3e4"; }
+
+.fa-angellist:before {
+  content: "\f209"; }
+
+.fa-galactic-republic:before {
+  content: "\f50c"; }
+
+.fa-nfc-directional:before {
+  content: "\e530"; }
+
+.fa-skype:before {
+  content: "\f17e"; }
+
+.fa-joget:before {
+  content: "\f3b7"; }
+
+.fa-fedora:before {
+  content: "\f798"; }
+
+.fa-stripe-s:before {
+  content: "\f42a"; }
+
+.fa-meta:before {
+  content: "\e49b"; }
+
+.fa-laravel:before {
+  content: "\f3bd"; }
+
+.fa-hotjar:before {
+  content: "\f3b1"; }
+
+.fa-bluetooth-b:before {
+  content: "\f294"; }
+
+.fa-sticker-mule:before {
+  content: "\f3f7"; }
+
+.fa-creative-commons-zero:before {
+  content: "\f4f3"; }
+
+.fa-hips:before {
+  content: "\f452"; }
+
+.fa-behance:before {
+  content: "\f1b4"; }
+
+.fa-reddit:before {
+  content: "\f1a1"; }
+
+.fa-discord:before {
+  content: "\f392"; }
+
+.fa-chrome:before {
+  content: "\f268"; }
+
+.fa-app-store-ios:before {
+  content: "\f370"; }
+
+.fa-cc-discover:before {
+  content: "\f1f2"; }
+
+.fa-wpbeginner:before {
+  content: "\f297"; }
+
+.fa-confluence:before {
+  content: "\f78d"; }
+
+.fa-mdb:before {
+  content: "\f8ca"; }
+
+.fa-dochub:before {
+  content: "\f394"; }
+
+.fa-accessible-icon:before {
+  content: "\f368"; }
+
+.fa-ebay:before {
+  content: "\f4f4"; }
+
+.fa-amazon:before {
+  content: "\f270"; }
+
+.fa-unsplash:before {
+  content: "\e07c"; }
+
+.fa-yarn:before {
+  content: "\f7e3"; }
+
+.fa-square-steam:before {
+  content: "\f1b7"; }
+
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+.fa-joomla:before {
+  content: "\f1aa"; }
+
+.fa-mastodon:before {
+  content: "\f4f6"; }
+
+.fa-airbnb:before {
+  content: "\f834"; }
+
+.fa-wolf-pack-battalion:before {
+  content: "\f514"; }
+
+.fa-buy-n-large:before {
+  content: "\f8a6"; }
+
+.fa-gulp:before {
+  content: "\f3ae"; }
+
+.fa-creative-commons-sampling-plus:before {
+  content: "\f4f1"; }
+
+.fa-strava:before {
+  content: "\f428"; }
+
+.fa-ember:before {
+  content: "\f423"; }
+
+.fa-canadian-maple-leaf:before {
+  content: "\f785"; }
+
+.fa-teamspeak:before {
+  content: "\f4f9"; }
+
+.fa-pushed:before {
+  content: "\f3e1"; }
+
+.fa-wordpress-simple:before {
+  content: "\f411"; }
+
+.fa-nutritionix:before {
+  content: "\f3d6"; }
+
+.fa-wodu:before {
+  content: "\e088"; }
+
+.fa-google-pay:before {
+  content: "\e079"; }
+
+.fa-intercom:before {
+  content: "\f7af"; }
+
+.fa-zhihu:before {
+  content: "\f63f"; }
+
+.fa-korvue:before {
+  content: "\f42f"; }
+
+.fa-pix:before {
+  content: "\e43a"; }
+
+.fa-steam-symbol:before {
+  content: "\f3f6"; }
+:root, :host {
+  --fa-style-family-classic: 'Font Awesome 6 Free';
+  --fa-font-regular: normal 400 1em/1 'Font Awesome 6 Free'; }
+
+@font-face {
+  font-family: 'Font Awesome 6 Free';
+  font-style: normal;
+  font-weight: 400;
+  font-display: block;
+  src: url("../webfonts/fa-regular-400.woff2") format("woff2"), url("../webfonts/fa-regular-400.ttf") format("truetype"); }
+
+.far,
+.fa-regular {
+  font-weight: 400; }
+:root, :host {
+  --fa-style-family-classic: 'Font Awesome 6 Free';
+  --fa-font-solid: normal 900 1em/1 'Font Awesome 6 Free'; }
+
+@font-face {
+  font-family: 'Font Awesome 6 Free';
+  font-style: normal;
+  font-weight: 900;
+  font-display: block;
+  src: url("../webfonts/fa-solid-900.woff2") format("woff2"), url("../webfonts/fa-solid-900.ttf") format("truetype"); }
+
+.fas,
+.fa-solid {
+  font-weight: 900; }
+@font-face {
+  font-family: 'Font Awesome 5 Brands';
+  font-display: block;
+  font-weight: 400;
+  src: url("../webfonts/fa-brands-400.woff2") format("woff2"), url("../webfonts/fa-brands-400.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'Font Awesome 5 Free';
+  font-display: block;
+  font-weight: 900;
+  src: url("../webfonts/fa-solid-900.woff2") format("woff2"), url("../webfonts/fa-solid-900.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'Font Awesome 5 Free';
+  font-display: block;
+  font-weight: 400;
+  src: url("../webfonts/fa-regular-400.woff2") format("woff2"), url("../webfonts/fa-regular-400.ttf") format("truetype"); }
+@font-face {
+  font-family: 'FontAwesome';
+  font-display: block;
+  src: url("../webfonts/fa-solid-900.woff2") format("woff2"), url("../webfonts/fa-solid-900.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'FontAwesome';
+  font-display: block;
+  src: url("../webfonts/fa-brands-400.woff2") format("woff2"), url("../webfonts/fa-brands-400.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'FontAwesome';
+  font-display: block;
+  src: url("../webfonts/fa-regular-400.woff2") format("woff2"), url("../webfonts/fa-regular-400.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'FontAwesome';
+  font-display: block;
+  src: url("../webfonts/fa-v4compatibility.woff2") format("woff2"), url("../webfonts/fa-v4compatibility.ttf") format("truetype"); }
diff --git a/deps/font-awesome-6.4.2/css/all.min.css b/deps/font-awesome-6.4.2/css/all.min.css
new file mode 100644
index 000000000..6604a0677
--- /dev/null
+++ b/deps/font-awesome-6.4.2/css/all.min.css
@@ -0,0 +1,9 @@
+/*!
+ * Font Awesome Free 6.4.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
+.fa{font-family:var(--fa-style-family,"Font Awesome 6 Free");font-weight:var(--fa-style,900)}.fa,.fa-brands,.fa-classic,.fa-regular,.fa-sharp,.fa-solid,.fab,.far,.fas{-moz-osx-font-smoothing:grayscale;-webkit-font-smoothing:antialiased;display:var(--fa-display,inline-block);font-style:normal;font-variant:normal;line-height:1;text-rendering:auto}.fa-classic,.fa-regular,.fa-solid,.far,.fas{font-family:"Font Awesome 6 Free"}.fa-brands,.fab{font-family:"Font Awesome 6 Brands"}.fa-1x{font-size:1em}.fa-2x{font-size:2em}.fa-3x{font-size:3em}.fa-4x{font-size:4em}.fa-5x{font-size:5em}.fa-6x{font-size:6em}.fa-7x{font-size:7em}.fa-8x{font-size:8em}.fa-9x{font-size:9em}.fa-10x{font-size:10em}.fa-2xs{font-size:.625em;line-height:.1em;vertical-align:.225em}.fa-xs{font-size:.75em;line-height:.08333em;vertical-align:.125em}.fa-sm{font-size:.875em;line-height:.07143em;vertical-align:.05357em}.fa-lg{font-size:1.25em;line-height:.05em;vertical-align:-.075em}.fa-xl{font-size:1.5em;line-height:.04167em;vertical-align:-.125em}.fa-2xl{font-size:2em;line-height:.03125em;vertical-align:-.1875em}.fa-fw{text-align:center;width:1.25em}.fa-ul{list-style-type:none;margin-left:var(--fa-li-margin,2.5em);padding-left:0}.fa-ul>li{position:relative}.fa-li{left:calc(var(--fa-li-width, 2em)*-1);position:absolute;text-align:center;width:var(--fa-li-width,2em);line-height:inherit}.fa-border{border-radius:var(--fa-border-radius,.1em);border:var(--fa-border-width,.08em) var(--fa-border-style,solid) var(--fa-border-color,#eee);padding:var(--fa-border-padding,.2em .25em .15em)}.fa-pull-left{float:left;margin-right:var(--fa-pull-margin,.3em)}.fa-pull-right{float:right;margin-left:var(--fa-pull-margin,.3em)}.fa-beat{-webkit-animation-name:fa-beat;animation-name:fa-beat;-webkit-animation-delay:var(--fa-animation-delay,0s);animation-delay:var(--fa-animation-delay,0s);-webkit-animation-direction:var(--fa-animation-direction,normal);animation-direction:var(--fa-animation-direction,normal);-webkit-animation-duration:var(--fa-animation-duration,1s);animation-duration:var(--fa-animation-duration,1s);-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,ease-in-out);animation-timing-function:var(--fa-animation-timing,ease-in-out)}.fa-bounce{-webkit-animation-name:fa-bounce;animation-name:fa-bounce;-webkit-animation-delay:var(--fa-animation-delay,0s);animation-delay:var(--fa-animation-delay,0s);-webkit-animation-direction:var(--fa-animation-direction,normal);animation-direction:var(--fa-animation-direction,normal);-webkit-animation-duration:var(--fa-animation-duration,1s);animation-duration:var(--fa-animation-duration,1s);-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,cubic-bezier(.28,.84,.42,1));animation-timing-function:var(--fa-animation-timing,cubic-bezier(.28,.84,.42,1))}.fa-fade{-webkit-animation-name:fa-fade;animation-name:fa-fade;-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,cubic-bezier(.4,0,.6,1));animation-timing-function:var(--fa-animation-timing,cubic-bezier(.4,0,.6,1))}.fa-beat-fade,.fa-fade{-webkit-animation-delay:var(--fa-animation-delay,0s);animation-delay:var(--fa-animation-delay,0s);-webkit-animation-direction:var(--fa-animation-direction,normal);animation-direction:var(--fa-animation-direction,normal);-webkit-animation-duration:var(--fa-animation-duration,1s);animation-duration:var(--fa-animation-duration,1s)}.fa-beat-fade{-webkit-animation-name:fa-beat-fade;animation-name:fa-beat-fade;-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,cubic-bezier(.4,0,.6,1));animation-timing-function:var(--fa-animation-timing,cubic-bezier(.4,0,.6,1))}.fa-flip{-webkit-animation-name:fa-flip;animation-name:fa-flip;-webkit-animation-delay:var(--fa-animation-delay,0s);animation-delay:var(--fa-animation-delay,0s);-webkit-animation-direction:var(--fa-animation-direction,normal);animation-direction:var(--fa-animation-direction,normal);-webkit-animation-duration:var(--fa-animation-duration,1s);animation-duration:var(--fa-animation-duration,1s);-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,ease-in-out);animation-timing-function:var(--fa-animation-timing,ease-in-out)}.fa-shake{-webkit-animation-name:fa-shake;animation-name:fa-shake;-webkit-animation-duration:var(--fa-animation-duration,1s);animation-duration:var(--fa-animation-duration,1s);-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,linear);animation-timing-function:var(--fa-animation-timing,linear)}.fa-shake,.fa-spin{-webkit-animation-delay:var(--fa-animation-delay,0s);animation-delay:var(--fa-animation-delay,0s);-webkit-animation-direction:var(--fa-animation-direction,normal);animation-direction:var(--fa-animation-direction,normal)}.fa-spin{-webkit-animation-name:fa-spin;animation-name:fa-spin;-webkit-animation-duration:var(--fa-animation-duration,2s);animation-duration:var(--fa-animation-duration,2s);-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,linear);animation-timing-function:var(--fa-animation-timing,linear)}.fa-spin-reverse{--fa-animation-direction:reverse}.fa-pulse,.fa-spin-pulse{-webkit-animation-name:fa-spin;animation-name:fa-spin;-webkit-animation-direction:var(--fa-animation-direction,normal);animation-direction:var(--fa-animation-direction,normal);-webkit-animation-duration:var(--fa-animation-duration,1s);animation-duration:var(--fa-animation-duration,1s);-webkit-animation-iteration-count:var(--fa-animation-iteration-count,infinite);animation-iteration-count:var(--fa-animation-iteration-count,infinite);-webkit-animation-timing-function:var(--fa-animation-timing,steps(8));animation-timing-function:var(--fa-animation-timing,steps(8))}@media (prefers-reduced-motion:reduce){.fa-beat,.fa-beat-fade,.fa-bounce,.fa-fade,.fa-flip,.fa-pulse,.fa-shake,.fa-spin,.fa-spin-pulse{-webkit-animation-delay:-1ms;animation-delay:-1ms;-webkit-animation-duration:1ms;animation-duration:1ms;-webkit-animation-iteration-count:1;animation-iteration-count:1;-webkit-transition-delay:0s;transition-delay:0s;-webkit-transition-duration:0s;transition-duration:0s}}@-webkit-keyframes fa-beat{0%,90%{-webkit-transform:scale(1);transform:scale(1)}45%{-webkit-transform:scale(var(--fa-beat-scale,1.25));transform:scale(var(--fa-beat-scale,1.25))}}@keyframes fa-beat{0%,90%{-webkit-transform:scale(1);transform:scale(1)}45%{-webkit-transform:scale(var(--fa-beat-scale,1.25));transform:scale(var(--fa-beat-scale,1.25))}}@-webkit-keyframes fa-bounce{0%{-webkit-transform:scale(1) translateY(0);transform:scale(1) translateY(0)}10%{-webkit-transform:scale(var(--fa-bounce-start-scale-x,1.1),var(--fa-bounce-start-scale-y,.9)) translateY(0);transform:scale(var(--fa-bounce-start-scale-x,1.1),var(--fa-bounce-start-scale-y,.9)) translateY(0)}30%{-webkit-transform:scale(var(--fa-bounce-jump-scale-x,.9),var(--fa-bounce-jump-scale-y,1.1)) translateY(var(--fa-bounce-height,-.5em));transform:scale(var(--fa-bounce-jump-scale-x,.9),var(--fa-bounce-jump-scale-y,1.1)) translateY(var(--fa-bounce-height,-.5em))}50%{-webkit-transform:scale(var(--fa-bounce-land-scale-x,1.05),var(--fa-bounce-land-scale-y,.95)) translateY(0);transform:scale(var(--fa-bounce-land-scale-x,1.05),var(--fa-bounce-land-scale-y,.95)) translateY(0)}57%{-webkit-transform:scale(1) translateY(var(--fa-bounce-rebound,-.125em));transform:scale(1) translateY(var(--fa-bounce-rebound,-.125em))}64%{-webkit-transform:scale(1) translateY(0);transform:scale(1) translateY(0)}to{-webkit-transform:scale(1) translateY(0);transform:scale(1) translateY(0)}}@keyframes fa-bounce{0%{-webkit-transform:scale(1) translateY(0);transform:scale(1) translateY(0)}10%{-webkit-transform:scale(var(--fa-bounce-start-scale-x,1.1),var(--fa-bounce-start-scale-y,.9)) translateY(0);transform:scale(var(--fa-bounce-start-scale-x,1.1),var(--fa-bounce-start-scale-y,.9)) translateY(0)}30%{-webkit-transform:scale(var(--fa-bounce-jump-scale-x,.9),var(--fa-bounce-jump-scale-y,1.1)) translateY(var(--fa-bounce-height,-.5em));transform:scale(var(--fa-bounce-jump-scale-x,.9),var(--fa-bounce-jump-scale-y,1.1)) translateY(var(--fa-bounce-height,-.5em))}50%{-webkit-transform:scale(var(--fa-bounce-land-scale-x,1.05),var(--fa-bounce-land-scale-y,.95)) translateY(0);transform:scale(var(--fa-bounce-land-scale-x,1.05),var(--fa-bounce-land-scale-y,.95)) translateY(0)}57%{-webkit-transform:scale(1) translateY(var(--fa-bounce-rebound,-.125em));transform:scale(1) translateY(var(--fa-bounce-rebound,-.125em))}64%{-webkit-transform:scale(1) translateY(0);transform:scale(1) translateY(0)}to{-webkit-transform:scale(1) translateY(0);transform:scale(1) translateY(0)}}@-webkit-keyframes fa-fade{50%{opacity:var(--fa-fade-opacity,.4)}}@keyframes fa-fade{50%{opacity:var(--fa-fade-opacity,.4)}}@-webkit-keyframes fa-beat-fade{0%,to{opacity:var(--fa-beat-fade-opacity,.4);-webkit-transform:scale(1);transform:scale(1)}50%{opacity:1;-webkit-transform:scale(var(--fa-beat-fade-scale,1.125));transform:scale(var(--fa-beat-fade-scale,1.125))}}@keyframes fa-beat-fade{0%,to{opacity:var(--fa-beat-fade-opacity,.4);-webkit-transform:scale(1);transform:scale(1)}50%{opacity:1;-webkit-transform:scale(var(--fa-beat-fade-scale,1.125));transform:scale(var(--fa-beat-fade-scale,1.125))}}@-webkit-keyframes fa-flip{50%{-webkit-transform:rotate3d(var(--fa-flip-x,0),var(--fa-flip-y,1),var(--fa-flip-z,0),var(--fa-flip-angle,-180deg));transform:rotate3d(var(--fa-flip-x,0),var(--fa-flip-y,1),var(--fa-flip-z,0),var(--fa-flip-angle,-180deg))}}@keyframes fa-flip{50%{-webkit-transform:rotate3d(var(--fa-flip-x,0),var(--fa-flip-y,1),var(--fa-flip-z,0),var(--fa-flip-angle,-180deg));transform:rotate3d(var(--fa-flip-x,0),var(--fa-flip-y,1),var(--fa-flip-z,0),var(--fa-flip-angle,-180deg))}}@-webkit-keyframes fa-shake{0%{-webkit-transform:rotate(-15deg);transform:rotate(-15deg)}4%{-webkit-transform:rotate(15deg);transform:rotate(15deg)}8%,24%{-webkit-transform:rotate(-18deg);transform:rotate(-18deg)}12%,28%{-webkit-transform:rotate(18deg);transform:rotate(18deg)}16%{-webkit-transform:rotate(-22deg);transform:rotate(-22deg)}20%{-webkit-transform:rotate(22deg);transform:rotate(22deg)}32%{-webkit-transform:rotate(-12deg);transform:rotate(-12deg)}36%{-webkit-transform:rotate(12deg);transform:rotate(12deg)}40%,to{-webkit-transform:rotate(0deg);transform:rotate(0deg)}}@keyframes fa-shake{0%{-webkit-transform:rotate(-15deg);transform:rotate(-15deg)}4%{-webkit-transform:rotate(15deg);transform:rotate(15deg)}8%,24%{-webkit-transform:rotate(-18deg);transform:rotate(-18deg)}12%,28%{-webkit-transform:rotate(18deg);transform:rotate(18deg)}16%{-webkit-transform:rotate(-22deg);transform:rotate(-22deg)}20%{-webkit-transform:rotate(22deg);transform:rotate(22deg)}32%{-webkit-transform:rotate(-12deg);transform:rotate(-12deg)}36%{-webkit-transform:rotate(12deg);transform:rotate(12deg)}40%,to{-webkit-transform:rotate(0deg);transform:rotate(0deg)}}@-webkit-keyframes fa-spin{0%{-webkit-transform:rotate(0deg);transform:rotate(0deg)}to{-webkit-transform:rotate(1turn);transform:rotate(1turn)}}@keyframes 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+
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diff --git a/deps/font-awesome-6.4.2/css/v4-shims.css b/deps/font-awesome-6.4.2/css/v4-shims.css
new file mode 100644
index 000000000..a85953d17
--- /dev/null
+++ b/deps/font-awesome-6.4.2/css/v4-shims.css
@@ -0,0 +1,2194 @@
+/*!
+ * Font Awesome Free 6.4.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
+.fa.fa-glass:before {
+  content: "\f000"; }
+
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+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-envelope-o:before {
+  content: "\f0e0"; }
+
+.fa.fa-star-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-star-o:before {
+  content: "\f005"; }
+
+.fa.fa-remove:before {
+  content: "\f00d"; }
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+  content: "\f00d"; }
+
+.fa.fa-gear:before {
+  content: "\f013"; }
+
+.fa.fa-trash-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
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+.fa.fa-trash-o:before {
+  content: "\f2ed"; }
+
+.fa.fa-home:before {
+  content: "\f015"; }
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+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
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+  content: "\f15b"; }
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+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
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+.fa.fa-clock-o:before {
+  content: "\f017"; }
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+.fa.fa-arrow-circle-o-down {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
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+.fa.fa-arrow-circle-o-down:before {
+  content: "\f358"; }
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+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-arrow-circle-o-up:before {
+  content: "\f35b"; }
+
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+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
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+.fa.fa-play-circle-o:before {
+  content: "\f144"; }
+
+.fa.fa-repeat:before {
+  content: "\f01e"; }
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+.fa.fa-rotate-right:before {
+  content: "\f01e"; }
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+  content: "\f021"; }
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+.fa.fa-list-alt {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-list-alt:before {
+  content: "\f022"; }
+
+.fa.fa-dedent:before {
+  content: "\f03b"; }
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+.fa.fa-video-camera:before {
+  content: "\f03d"; }
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+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
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+.fa.fa-photo {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
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+  content: "\f03e"; }
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+  font-weight: 400; }
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+.fa.fa-image:before {
+  content: "\f03e"; }
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+.fa.fa-map-marker:before {
+  content: "\f3c5"; }
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+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
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+  content: "\f044"; }
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+.fa.fa-edit {
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+  font-weight: 400; }
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+.fa.fa-edit:before {
+  content: "\f044"; }
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+.fa.fa-share-square-o:before {
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+  font-weight: 400; }
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+.fa.fa-check-square-o:before {
+  content: "\f14a"; }
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+.fa.fa-arrows:before {
+  content: "\f0b2"; }
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+  font-weight: 400; }
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+  font-weight: 400; }
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+.fa.fa-eye {
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+.fa.fa-eye-slash {
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+  font-weight: 400; }
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+.fa.fa-warning:before {
+  content: "\f071"; }
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+.fa.fa-calendar:before {
+  content: "\f073"; }
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+  content: "\e0e3"; }
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+.fa.fa-bar-chart-o:before {
+  content: "\e0e3"; }
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+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
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+  font-weight: 400; }
+
+.fa.fa-pause-circle-o:before {
+  content: "\f28b"; }
+
+.fa.fa-stop-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-stop-circle-o:before {
+  content: "\f28d"; }
+
+.fa.fa-bluetooth {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-bluetooth-b {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-gitlab {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wpbeginner {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wpforms {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-envira {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wheelchair-alt {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wheelchair-alt:before {
+  content: "\f368"; }
+
+.fa.fa-question-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-question-circle-o:before {
+  content: "\f059"; }
+
+.fa.fa-volume-control-phone:before {
+  content: "\f2a0"; }
+
+.fa.fa-asl-interpreting:before {
+  content: "\f2a3"; }
+
+.fa.fa-deafness:before {
+  content: "\f2a4"; }
+
+.fa.fa-hard-of-hearing:before {
+  content: "\f2a4"; }
+
+.fa.fa-glide {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-glide-g {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-signing:before {
+  content: "\f2a7"; }
+
+.fa.fa-viadeo {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-viadeo-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-viadeo-square:before {
+  content: "\f2aa"; }
+
+.fa.fa-snapchat {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-snapchat-ghost {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-snapchat-ghost:before {
+  content: "\f2ab"; }
+
+.fa.fa-snapchat-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-snapchat-square:before {
+  content: "\f2ad"; }
+
+.fa.fa-pied-piper {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-first-order {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-yoast {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-themeisle {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-google-plus-official {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-google-plus-official:before {
+  content: "\f2b3"; }
+
+.fa.fa-google-plus-circle {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-google-plus-circle:before {
+  content: "\f2b3"; }
+
+.fa.fa-font-awesome {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-fa {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-fa:before {
+  content: "\f2b4"; }
+
+.fa.fa-handshake-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-handshake-o:before {
+  content: "\f2b5"; }
+
+.fa.fa-envelope-open-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-envelope-open-o:before {
+  content: "\f2b6"; }
+
+.fa.fa-linode {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-address-book-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-address-book-o:before {
+  content: "\f2b9"; }
+
+.fa.fa-vcard:before {
+  content: "\f2bb"; }
+
+.fa.fa-address-card-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-address-card-o:before {
+  content: "\f2bb"; }
+
+.fa.fa-vcard-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-vcard-o:before {
+  content: "\f2bb"; }
+
+.fa.fa-user-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-user-circle-o:before {
+  content: "\f2bd"; }
+
+.fa.fa-user-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-user-o:before {
+  content: "\f007"; }
+
+.fa.fa-id-badge {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-drivers-license:before {
+  content: "\f2c2"; }
+
+.fa.fa-id-card-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-id-card-o:before {
+  content: "\f2c2"; }
+
+.fa.fa-drivers-license-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-drivers-license-o:before {
+  content: "\f2c2"; }
+
+.fa.fa-quora {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-free-code-camp {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-telegram {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-thermometer-4:before {
+  content: "\f2c7"; }
+
+.fa.fa-thermometer:before {
+  content: "\f2c7"; }
+
+.fa.fa-thermometer-3:before {
+  content: "\f2c8"; }
+
+.fa.fa-thermometer-2:before {
+  content: "\f2c9"; }
+
+.fa.fa-thermometer-1:before {
+  content: "\f2ca"; }
+
+.fa.fa-thermometer-0:before {
+  content: "\f2cb"; }
+
+.fa.fa-bathtub:before {
+  content: "\f2cd"; }
+
+.fa.fa-s15:before {
+  content: "\f2cd"; }
+
+.fa.fa-window-maximize {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-window-restore {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-times-rectangle:before {
+  content: "\f410"; }
+
+.fa.fa-window-close-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-window-close-o:before {
+  content: "\f410"; }
+
+.fa.fa-times-rectangle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-times-rectangle-o:before {
+  content: "\f410"; }
+
+.fa.fa-bandcamp {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-grav {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-etsy {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-imdb {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-ravelry {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-eercast {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-eercast:before {
+  content: "\f2da"; }
+
+.fa.fa-snowflake-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-snowflake-o:before {
+  content: "\f2dc"; }
+
+.fa.fa-superpowers {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wpexplorer {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-meetup {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
diff --git a/deps/font-awesome-6.4.2/css/v4-shims.min.css b/deps/font-awesome-6.4.2/css/v4-shims.min.css
new file mode 100644
index 000000000..64e4e8d83
--- /dev/null
+++ b/deps/font-awesome-6.4.2/css/v4-shims.min.css
@@ -0,0 +1,6 @@
+/*!
+ * Font Awesome Free 6.4.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
+.fa.fa-glass:before{content:"\f000"}.fa.fa-envelope-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-envelope-o:before{content:"\f0e0"}.fa.fa-star-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-star-o:before{content:"\f005"}.fa.fa-close:before,.fa.fa-remove:before{content:"\f00d"}.fa.fa-gear:before{content:"\f013"}.fa.fa-trash-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-trash-o:before{content:"\f2ed"}.fa.fa-home:before{content:"\f015"}.fa.fa-file-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-file-o:before{content:"\f15b"}.fa.fa-clock-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-clock-o:before{content:"\f017"}.fa.fa-arrow-circle-o-down{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-arrow-circle-o-down:before{content:"\f358"}.fa.fa-arrow-circle-o-up{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-arrow-circle-o-up:before{content:"\f35b"}.fa.fa-play-circle-o{font-family:"Font Awesome 6 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Awesome 6 Free";font-weight:400}.fa.fa-check-square-o:before{content:"\f14a"}.fa.fa-arrows:before{content:"\f0b2"}.fa.fa-times-circle-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-times-circle-o:before{content:"\f057"}.fa.fa-check-circle-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-check-circle-o:before{content:"\f058"}.fa.fa-mail-forward:before{content:"\f064"}.fa.fa-expand:before{content:"\f424"}.fa.fa-compress:before{content:"\f422"}.fa.fa-eye,.fa.fa-eye-slash{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-warning:before{content:"\f071"}.fa.fa-calendar:before{content:"\f073"}.fa.fa-arrows-v:before{content:"\f338"}.fa.fa-arrows-h:before{content:"\f337"}.fa.fa-bar-chart-o:before,.fa.fa-bar-chart:before{content:"\e0e3"}.fa.fa-twitter-square{font-family:"Font Awesome 6 Brands";font-weight:400}.fa.fa-twitter-square:before{content:"\f081"}.fa.fa-facebook-square{font-family:"Font Awesome 6 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+++ b/deps/headroom-0.11.0/headroom.min.js
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+/*!
+ * headroom.js v0.11.0 - Give your page some headroom. Hide your header until you need it
+ * Copyright (c) 2020 Nick Williams - http://wicky.nillia.ms/headroom.js
+ * License: MIT
+ */
+
+!function(t,n){"object"==typeof exports&&"undefined"!=typeof module?module.exports=n():"function"==typeof define&&define.amd?define(n):(t=t||self).Headroom=n()}(this,function(){"use strict";function t(){return"undefined"!=typeof window}function d(t){return function(t){return t&&t.document&&function(t){return 9===t.nodeType}(t.document)}(t)?function(t){var n=t.document,o=n.body,s=n.documentElement;return{scrollHeight:function(){return Math.max(o.scrollHeight,s.scrollHeight,o.offsetHeight,s.offsetHeight,o.clientHeight,s.clientHeight)},height:function(){return t.innerHeight||s.clientHeight||o.clientHeight},scrollY:function(){return void 0!==t.pageYOffset?t.pageYOffset:(s||o.parentNode||o).scrollTop}}}(t):function(t){return{scrollHeight:function(){return Math.max(t.scrollHeight,t.offsetHeight,t.clientHeight)},height:function(){return Math.max(t.offsetHeight,t.clientHeight)},scrollY:function(){return t.scrollTop}}}(t)}function n(t,s,e){var n,o=function(){var n=!1;try{var t={get passive(){n=!0}};window.addEventListener("test",t,t),window.removeEventListener("test",t,t)}catch(t){n=!1}return n}(),i=!1,r=d(t),l=r.scrollY(),a={};function c(){var t=Math.round(r.scrollY()),n=r.height(),o=r.scrollHeight();a.scrollY=t,a.lastScrollY=l,a.direction=l<t?"down":"up",a.distance=Math.abs(t-l),a.isOutOfBounds=t<0||o<t+n,a.top=t<=s.offset,a.bottom=o<=t+n,a.toleranceExceeded=a.distance>s.tolerance[a.direction],e(a),l=t,i=!1}function h(){i||(i=!0,n=requestAnimationFrame(c))}var u=!!o&&{passive:!0,capture:!1};return t.addEventListener("scroll",h,u),c(),{destroy:function(){cancelAnimationFrame(n),t.removeEventListener("scroll",h,u)}}}function o(t,n){n=n||{},Object.assign(this,o.options,n),this.classes=Object.assign({},o.options.classes,n.classes),this.elem=t,this.tolerance=function(t){return t===Object(t)?t:{down:t,up:t}}(this.tolerance),this.initialised=!1,this.frozen=!1}return o.prototype={constructor:o,init:function(){return o.cutsTheMustard&&!this.initialised&&(this.addClass("initial"),this.initialised=!0,setTimeout(function(t){t.scrollTracker=n(t.scroller,{offset:t.offset,tolerance:t.tolerance},t.update.bind(t))},100,this)),this},destroy:function(){this.initialised=!1,Object.keys(this.classes).forEach(this.removeClass,this),this.scrollTracker.destroy()},unpin:function(){!this.hasClass("pinned")&&this.hasClass("unpinned")||(this.addClass("unpinned"),this.removeClass("pinned"),this.onUnpin&&this.onUnpin.call(this))},pin:function(){this.hasClass("unpinned")&&(this.addClass("pinned"),this.removeClass("unpinned"),this.onPin&&this.onPin.call(this))},freeze:function(){this.frozen=!0,this.addClass("frozen")},unfreeze:function(){this.frozen=!1,this.removeClass("frozen")},top:function(){this.hasClass("top")||(this.addClass("top"),this.removeClass("notTop"),this.onTop&&this.onTop.call(this))},notTop:function(){this.hasClass("notTop")||(this.addClass("notTop"),this.removeClass("top"),this.onNotTop&&this.onNotTop.call(this))},bottom:function(){this.hasClass("bottom")||(this.addClass("bottom"),this.removeClass("notBottom"),this.onBottom&&this.onBottom.call(this))},notBottom:function(){this.hasClass("notBottom")||(this.addClass("notBottom"),this.removeClass("bottom"),this.onNotBottom&&this.onNotBottom.call(this))},shouldUnpin:function(t){return"down"===t.direction&&!t.top&&t.toleranceExceeded},shouldPin:function(t){return"up"===t.direction&&t.toleranceExceeded||t.top},addClass:function(t){this.elem.classList.add.apply(this.elem.classList,this.classes[t].split(" "))},removeClass:function(t){this.elem.classList.remove.apply(this.elem.classList,this.classes[t].split(" "))},hasClass:function(t){return this.classes[t].split(" ").every(function(t){return this.classList.contains(t)},this.elem)},update:function(t){t.isOutOfBounds||!0!==this.frozen&&(t.top?this.top():this.notTop(),t.bottom?this.bottom():this.notBottom(),this.shouldUnpin(t)?this.unpin():this.shouldPin(t)&&this.pin())}},o.options={tolerance:{up:0,down:0},offset:0,scroller:t()?window:null,classes:{frozen:"headroom--frozen",pinned:"headroom--pinned",unpinned:"headroom--unpinned",top:"headroom--top",notTop:"headroom--not-top",bottom:"headroom--bottom",notBottom:"headroom--not-bottom",initial:"headroom"}},o.cutsTheMustard=!!(t()&&function(){}.bind&&"classList"in document.documentElement&&Object.assign&&Object.keys&&requestAnimationFrame),o});
\ No newline at end of file
diff --git a/deps/headroom-0.11.0/jQuery.headroom.min.js b/deps/headroom-0.11.0/jQuery.headroom.min.js
new file mode 100644
index 000000000..17f70c9e3
--- /dev/null
+++ b/deps/headroom-0.11.0/jQuery.headroom.min.js
@@ -0,0 +1,7 @@
+/*!
+ * headroom.js v0.9.4 - Give your page some headroom. Hide your header until you need it
+ * Copyright (c) 2017 Nick Williams - http://wicky.nillia.ms/headroom.js
+ * License: MIT
+ */
+
+!function(a){a&&(a.fn.headroom=function(b){return this.each(function(){var c=a(this),d=c.data("headroom"),e="object"==typeof b&&b;e=a.extend(!0,{},Headroom.options,e),d||(d=new Headroom(this,e),d.init(),c.data("headroom",d)),"string"==typeof b&&(d[b](),"destroy"===b&&c.removeData("headroom"))})},a("[data-headroom]").each(function(){var b=a(this);b.headroom(b.data())}))}(window.Zepto||window.jQuery);
\ No newline at end of file
diff --git a/deps/search-1.0.0/autocomplete.jquery.min.js b/deps/search-1.0.0/autocomplete.jquery.min.js
new file mode 100644
index 000000000..fb63a6a28
--- /dev/null
+++ b/deps/search-1.0.0/autocomplete.jquery.min.js
@@ -0,0 +1,7 @@
+/*!
+ * autocomplete.js 0.38.0
+ * https://github.com/algolia/autocomplete.js
+ * Copyright 2020 Algolia, Inc. and other contributors; Licensed MIT
+ */
+!function(a){function b(d){if(c[d])return c[d].exports;var e=c[d]={exports:{},id:d,loaded:!1};return a[d].call(e.exports,e,e.exports,b),e.loaded=!0,e.exports}var c={};b.m=a,b.c=c,b.p="",b(0)}([function(a,b,c){"use strict";a.exports=c(1)},function(a,b,c){"use strict";var d=c(2),e=c(3);d.element=e;var f=c(4);f.isArray=e.isArray,f.isFunction=e.isFunction,f.isObject=e.isPlainObject,f.bind=e.proxy,f.each=function(a,b){function c(a,c){return b(c,a)}e.each(a,c)},f.map=e.map,f.mixin=e.extend,f.Event=e.Event;var g,h,i,j=c(5),k=c(6);g=e.fn.autocomplete,h="aaAutocomplete",i={initialize:function(a,b){function c(){var c,d=e(this),f=new k({el:d});c=new j({input:d,eventBus:f,dropdownMenuContainer:a.dropdownMenuContainer,hint:void 0===a.hint||!!a.hint,minLength:a.minLength,autoselect:a.autoselect,autoselectOnBlur:a.autoselectOnBlur,tabAutocomplete:a.tabAutocomplete,openOnFocus:a.openOnFocus,templates:a.templates,debug:a.debug,clearOnSelected:a.clearOnSelected,cssClasses:a.cssClasses,datasets:b,keyboardShortcuts:a.keyboardShortcuts,appendTo:a.appendTo,autoWidth:a.autoWidth}),d.data(h,c)}return b=f.isArray(b)?b:[].slice.call(arguments,1),a=a||{},this.each(c)},open:function(){function a(){var a,b=e(this);(a=b.data(h))&&a.open()}return this.each(a)},close:function(){function a(){var a,b=e(this);(a=b.data(h))&&a.close()}return this.each(a)},val:function(a){function b(){var b,c=e(this);(b=c.data(h))&&b.setVal(a)}return arguments.length?this.each(b):function(a){var b,c;return(b=a.data(h))&&(c=b.getVal()),c}(this.first())},destroy:function(){function a(){var a,b=e(this);(a=b.data(h))&&(a.destroy(),b.removeData(h))}return this.each(a)}},e.fn.autocomplete=function(a){var b;return i[a]&&"initialize"!==a?(b=this.filter(function(){return!!e(this).data(h)}),i[a].apply(b,[].slice.call(arguments,1))):i.initialize.apply(this,arguments)},e.fn.autocomplete.noConflict=function(){return e.fn.autocomplete=g,this},e.fn.autocomplete.sources=j.sources,e.fn.autocomplete.escapeHighlightedString=f.escapeHighlightedString,a.exports=e.fn.autocomplete},function(a,b){"use strict";a.exports={element:null}},function(a,b){a.exports=jQuery},function(a,b,c){"use strict";function d(a){return a.replace(/[\-\[\]\/\{\}\(\)\*\+\?\.\\\^\$\|]/g,"\\$&")}var e=c(2);a.exports={isArray:null,isFunction:null,isObject:null,bind:null,each:null,map:null,mixin:null,isMsie:function(a){if(void 0===a&&(a=navigator.userAgent),/(msie|trident)/i.test(a)){var b=a.match(/(msie |rv:)(\d+(.\d+)?)/i);if(b)return b[2]}return!1},escapeRegExChars:function(a){return a.replace(/[\-\[\]\/\{\}\(\)\*\+\?\.\\\^\$\|]/g,"\\$&")},isNumber:function(a){return"number"==typeof a},toStr:function(a){return void 0===a||null===a?"":a+""},cloneDeep:function(a){var b=this.mixin({},a),c=this;return this.each(b,function(a,d){a&&(c.isArray(a)?b[d]=[].concat(a):c.isObject(a)&&(b[d]=c.cloneDeep(a)))}),b},error:function(a){throw new Error(a)},every:function(a,b){var c=!0;return a?(this.each(a,function(d,e){c&&(c=b.call(null,d,e,a)&&c)}),!!c):c},any:function(a,b){var c=!1;return a?(this.each(a,function(d,e){if(b.call(null,d,e,a))return c=!0,!1}),c):c},getUniqueId:function(){var a=0;return function(){return a++}}(),templatify:function(a){if(this.isFunction(a))return a;var b=e.element(a);return"SCRIPT"===b.prop("tagName")?function(){return b.text()}:function(){return String(a)}},defer:function(a){setTimeout(a,0)},noop:function(){},formatPrefix:function(a,b){return b?"":a+"-"},className:function(a,b,c){return(c?"":".")+a+b},escapeHighlightedString:function(a,b,c){b=b||"<em>";var e=document.createElement("div");e.appendChild(document.createTextNode(b)),c=c||"</em>";var f=document.createElement("div");f.appendChild(document.createTextNode(c));var g=document.createElement("div");return g.appendChild(document.createTextNode(a)),g.innerHTML.replace(RegExp(d(e.innerHTML),"g"),b).replace(RegExp(d(f.innerHTML),"g"),c)}}},function(a,b,c){"use strict";function d(a){var b,c;if(a=a||{},a.input||i.error("missing input"),this.isActivated=!1,this.debug=!!a.debug,this.autoselect=!!a.autoselect,this.autoselectOnBlur=!!a.autoselectOnBlur,this.openOnFocus=!!a.openOnFocus,this.minLength=i.isNumber(a.minLength)?a.minLength:1,this.autoWidth=void 0===a.autoWidth||!!a.autoWidth,this.clearOnSelected=!!a.clearOnSelected,this.tabAutocomplete=void 0===a.tabAutocomplete||!!a.tabAutocomplete,a.hint=!!a.hint,a.hint&&a.appendTo)throw new Error("[autocomplete.js] hint and appendTo options can't be used at the same time");this.css=a.css=i.mixin({},o,a.appendTo?o.appendTo:{}),this.cssClasses=a.cssClasses=i.mixin({},o.defaultClasses,a.cssClasses||{}),this.cssClasses.prefix=a.cssClasses.formattedPrefix=i.formatPrefix(this.cssClasses.prefix,this.cssClasses.noPrefix),this.listboxId=a.listboxId=[this.cssClasses.root,"listbox",i.getUniqueId()].join("-");var f=e(a);this.$node=f.wrapper;var g=this.$input=f.input;b=f.menu,c=f.hint,a.dropdownMenuContainer&&j.element(a.dropdownMenuContainer).css("position","relative").append(b.css("top","0")),g.on("blur.aa",function(a){var c=document.activeElement;i.isMsie()&&(b[0]===c||b[0].contains(c))&&(a.preventDefault(),a.stopImmediatePropagation(),i.defer(function(){g.focus()}))}),b.on("mousedown.aa",function(a){a.preventDefault()}),this.eventBus=a.eventBus||new k({el:g}),this.dropdown=new d.Dropdown({appendTo:a.appendTo,wrapper:this.$node,menu:b,datasets:a.datasets,templates:a.templates,cssClasses:a.cssClasses,minLength:this.minLength}).onSync("suggestionClicked",this._onSuggestionClicked,this).onSync("cursorMoved",this._onCursorMoved,this).onSync("cursorRemoved",this._onCursorRemoved,this).onSync("opened",this._onOpened,this).onSync("closed",this._onClosed,this).onSync("shown",this._onShown,this).onSync("empty",this._onEmpty,this).onSync("redrawn",this._onRedrawn,this).onAsync("datasetRendered",this._onDatasetRendered,this),this.input=new 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g=n.dropdown.replace("%PREFIX%",a.cssClasses.prefix).replace("%DROPDOWN_MENU%",a.cssClasses.dropdownMenu);d=j.element(g).css(a.css.dropdown).attr({role:"listbox",id:a.listboxId}),a.templates&&a.templates.dropdownMenu&&d.html(i.templatify(a.templates.dropdownMenu)()),e=b.clone().css(a.css.hint).css(f(b)),e.val("").addClass(i.className(a.cssClasses.prefix,a.cssClasses.hint,!0)).removeAttr("id name placeholder required").prop("readonly",!0).attr({"aria-hidden":"true",autocomplete:"off",spellcheck:"false",tabindex:-1}),e.removeData&&e.removeData(),b.data(h,{"aria-autocomplete":b.attr("aria-autocomplete"),"aria-expanded":b.attr("aria-expanded"),"aria-owns":b.attr("aria-owns"),autocomplete:b.attr("autocomplete"),dir:b.attr("dir"),role:b.attr("role"),spellcheck:b.attr("spellcheck"),style:b.attr("style"),type:b.attr("type")}),b.addClass(i.className(a.cssClasses.prefix,a.cssClasses.input,!0)).attr({autocomplete:"off",spellcheck:!1,role:"combobox","aria-autocomplete":a.datasets&&a.datasets[0]&&a.datasets[0].displayKey?"both":"list","aria-expanded":"false","aria-label":a.ariaLabel,"aria-owns":a.listboxId}).css(a.hint?a.css.input:a.css.inputWithNoHint);try{b.attr("dir")||b.attr("dir","auto")}catch(a){}return c=a.appendTo?c.appendTo(j.element(a.appendTo).eq(0)).eq(0):b.wrap(c).parent(),c.prepend(a.hint?e:null).append(d),{wrapper:c,input:b,hint:e,menu:d}}function f(a){return{backgroundAttachment:a.css("background-attachment"),backgroundClip:a.css("background-clip"),backgroundColor:a.css("background-color"),backgroundImage:a.css("background-image"),backgroundOrigin:a.css("background-origin"),backgroundPosition:a.css("background-position"),backgroundRepeat:a.css("background-repeat"),backgroundSize:a.css("background-size")}}function g(a,b){var c=a.find(i.className(b.prefix,b.input));i.each(c.data(h),function(a,b){void 0===a?c.removeAttr(b):c.attr(b,a)}),c.detach().removeClass(i.className(b.prefix,b.input,!0)).insertAfter(a),c.removeData&&c.removeData(h),a.remove()}var h="aaAttrs",i=c(4),j=c(2),k=c(6),l=c(7),m=c(16),n=c(18),o=c(19);i.mixin(d.prototype,{_bindKeyboardShortcuts:function(a){if(a.keyboardShortcuts){var b=this.$input,c=[];i.each(a.keyboardShortcuts,function(a){"string"==typeof a&&(a=a.toUpperCase().charCodeAt(0)),c.push(a)}),j.element(document).keydown(function(a){var d=a.target||a.srcElement,e=d.tagName;if(!d.isContentEditable&&"INPUT"!==e&&"SELECT"!==e&&"TEXTAREA"!==e){var f=a.which||a.keyCode;c.indexOf(f)!==-1&&(b.focus(),a.stopPropagation(),a.preventDefault())}})}},_onSuggestionClicked:function(a,b){var c,d={selectionMethod:"click"};(c=this.dropdown.getDatumForSuggestion(b))&&this._select(c,d)},_onCursorMoved:function(a,b){var c=this.dropdown.getDatumForCursor(),d=this.dropdown.getCurrentCursor().attr("id");this.input.setActiveDescendant(d),c&&(b&&this.input.setInputValue(c.value,!0),this.eventBus.trigger("cursorchanged",c.raw,c.datasetName))},_onCursorRemoved:function(){this.input.resetInputValue(),this._updateHint(),this.eventBus.trigger("cursorremoved")},_onDatasetRendered:function(){this._updateHint(),this.eventBus.trigger("updated")},_onOpened:function(){this._updateHint(),this.input.expand(),this.eventBus.trigger("opened")},_onEmpty:function(){this.eventBus.trigger("empty")},_onRedrawn:function(){this.$node.css("top","0px"),this.$node.css("left","0px");var a=this.$input[0].getBoundingClientRect();this.autoWidth&&this.$node.css("width",a.width+"px");var b=this.$node[0].getBoundingClientRect(),c=a.bottom-b.top;this.$node.css("top",c+"px");var d=a.left-b.left;this.$node.css("left",d+"px"),this.eventBus.trigger("redrawn")},_onShown:function(){this.eventBus.trigger("shown"),this.autoselect&&this.dropdown.cursorTopSuggestion()},_onClosed:function(){this.input.clearHint(),this.input.removeActiveDescendant(),this.input.collapse(),this.eventBus.trigger("closed")},_onFocused:function(){if(this.isActivated=!0,this.openOnFocus){var a=this.input.getQuery();a.length>=this.minLength?this.dropdown.update(a):this.dropdown.empty(),this.dropdown.open()}},_onBlurred:function(){var a,b;a=this.dropdown.getDatumForCursor(),b=this.dropdown.getDatumForTopSuggestion();var c={selectionMethod:"blur"};this.debug||(this.autoselectOnBlur&&a?this._select(a,c):this.autoselectOnBlur&&b?this._select(b,c):(this.isActivated=!1,this.dropdown.empty(),this.dropdown.close()))},_onEnterKeyed:function(a,b){var c,d;c=this.dropdown.getDatumForCursor(),d=this.dropdown.getDatumForTopSuggestion();var e={selectionMethod:"enterKey"};c?(this._select(c,e),b.preventDefault()):this.autoselect&&d&&(this._select(d,e),b.preventDefault())},_onTabKeyed:function(a,b){if(!this.tabAutocomplete)return void this.dropdown.close();var c,d={selectionMethod:"tabKey"};(c=this.dropdown.getDatumForCursor())?(this._select(c,d),b.preventDefault()):this._autocomplete(!0)},_onEscKeyed:function(){this.dropdown.close(),this.input.resetInputValue()},_onUpKeyed:function(){var a=this.input.getQuery();this.dropdown.isEmpty&&a.length>=this.minLength?this.dropdown.update(a):this.dropdown.moveCursorUp(),this.dropdown.open()},_onDownKeyed:function(){var 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a=this.input.getInputValue();a.length>=this.minLength?this.dropdown.update(a):this.dropdown.empty()}this.dropdown.open()},close:function(){this.dropdown.close()},setVal:function(a){a=i.toStr(a),this.isActivated?this.input.setInputValue(a):(this.input.setQuery(a),this.input.setInputValue(a,!0)),this._setLanguageDirection()},getVal:function(){return this.input.getQuery()},destroy:function(){this.input.destroy(),this.dropdown.destroy(),g(this.$node,this.cssClasses),this.$node=null},getWrapper:function(){return this.dropdown.$container[0]}}),d.Dropdown=m,d.Input=l,d.sources=c(20),a.exports=d},function(a,b,c){"use strict";function d(a){a&&a.el||e.error("EventBus initialized without el"),this.$el=f.element(a.el)}var e=c(4),f=c(2);e.mixin(d.prototype,{trigger:function(a,b,c,d){var f=e.Event("autocomplete:"+a);return this.$el.trigger(f,[b,c,d]),f}}),a.exports=d},function(a,b,c){"use strict";function d(a){var b,c,d,f,g=this;a=a||{},a.input||i.error("input is 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+var c=[].slice.call(arguments,1);this.cacheSuggestions(a,b,c),this._render.apply(this,[a,b].concat(c))}}if(this.query=a,this.canceled=!1,this.shouldFetchFromCache(a))b.apply(this,[this.cachedSuggestions].concat(this.cachedRenderExtraArgs));else{var c=this,d=function(){c.canceled||c.source(a,b.bind(c))};if(this.debounce){var e=function(){c.debounceTimeout=null,d()};clearTimeout(this.debounceTimeout),this.debounceTimeout=setTimeout(e,this.debounce)}else d()}},cacheSuggestions:function(a,b,c){this.cachedQuery=a,this.cachedSuggestions=b,this.cachedRenderExtraArgs=c},shouldFetchFromCache:function(a){return this.cache&&this.cachedQuery===a&&this.cachedSuggestions&&this.cachedSuggestions.length},clearCachedSuggestions:function(){delete this.cachedQuery,delete this.cachedSuggestions,delete this.cachedRenderExtraArgs},cancel:function(){this.canceled=!0},clear:function(){this.$el&&(this.cancel(),this.$el.empty(),this.trigger("rendered",""))},isEmpty:function(){return this._isEmpty},destroy:function(){this.clearCachedSuggestions(),this.$el=null}}),a.exports=d},function(a,b){"use strict";a.exports={wrapper:'<span class="%ROOT%"></span>',dropdown:'<span class="%PREFIX%%DROPDOWN_MENU%"></span>',dataset:'<div class="%PREFIX%%DATASET%-%CLASS%"></div>',suggestions:'<span class="%PREFIX%%SUGGESTIONS%"></span>',suggestion:'<div class="%PREFIX%%SUGGESTION%"></div>'}},function(a,b,c){"use strict";var d=c(4),e={wrapper:{position:"relative",display:"inline-block"},hint:{position:"absolute",top:"0",left:"0",borderColor:"transparent",boxShadow:"none",opacity:"1"},input:{position:"relative",verticalAlign:"top",backgroundColor:"transparent"},inputWithNoHint:{position:"relative",verticalAlign:"top"},dropdown:{position:"absolute",top:"100%",left:"0",zIndex:"100",display:"none"},suggestions:{display:"block"},suggestion:{whiteSpace:"nowrap",cursor:"pointer"},suggestionChild:{whiteSpace:"normal"},ltr:{left:"0",right:"auto"},rtl:{left:"auto",right:"0"},defaultClasses:{root:"algolia-autocomplete",prefix:"aa",noPrefix:!1,dropdownMenu:"dropdown-menu",input:"input",hint:"hint",suggestions:"suggestions",suggestion:"suggestion",cursor:"cursor",dataset:"dataset",empty:"empty"},appendTo:{wrapper:{position:"absolute",zIndex:"100",display:"none"},input:{},inputWithNoHint:{},dropdown:{display:"block"}}};d.isMsie()&&d.mixin(e.input,{backgroundImage:"url(data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)"}),d.isMsie()&&d.isMsie()<=7&&d.mixin(e.input,{marginTop:"-1px"}),a.exports=e},function(a,b,c){"use strict";a.exports={hits:c(21),popularIn:c(24)}},function(a,b,c){"use strict";var d=c(4),e=c(22),f=c(23),g=function(){function a(a,d){return window.Promise.resolve().then(function(){return b.length&&(e=a.search(b),b=[]),e}).then(function(a){if(a)return c=a.results,c[d]})}var b=[],c=[],e=window.Promise.resolve();return function(c,e){return function(f,g){a(c.as,b.push({indexName:c.indexName,query:f,params:e})-1).then(function(a){a&&g(a.hits,a)}).catch(function(a){d.error(a.message)})}}}();a.exports=function(a,b){var c=f(a.as._ua);if(c&&c[0]>=3&&c[1]>20){var d="autocomplete.js "+e;a.as._ua.indexOf(d)===-1&&(a.as._ua+="; "+d)}return g(a,b)}},function(a,b){a.exports="0.38.0"},function(a,b){"use strict";a.exports=function(a){var b=a.match(/Algolia for JavaScript \((\d+\.)(\d+\.)(\d+)\)/)||a.match(/Algolia for vanilla JavaScript (\d+\.)(\d+\.)(\d+)/);if(b)return[b[1],b[2],b[3]]}},function(a,b,c){"use strict";var d=c(4),e=c(22),f=c(23);a.exports=function(a,b,c,g){function h(h,i){a.search(h,b,function(a,h){if(a)return void d.error(a.message);if(h.hits.length>0){var l=h.hits[0],m=d.mixin({hitsPerPage:0},c);delete m.source,delete m.index;var n=f(k.as._ua);return n&&n[0]>=3&&n[1]>20&&(b.additionalUA="autocomplete.js "+e),void k.search(j(l),m,function(a,b){if(a)return void d.error(a.message);var c=[];if(g.includeAll){var e=g.allTitle||"All departments";c.push(d.mixin({facet:{value:e,count:b.nbHits}},d.cloneDeep(l)))}d.each(b.facets,function(a,b){d.each(a,function(a,e){c.push(d.mixin({facet:{facet:b,value:e,count:a}},d.cloneDeep(l)))})});for(var f=1;f<h.hits.length;++f)c.push(h.hits[f]);i(c,h)})}i([])})}var i=f(a.as._ua);if(i&&i[0]>=3&&i[1]>20&&(b=b||{},b.additionalUA="autocomplete.js "+e),!c.source)return d.error("Missing 'source' key");var j=d.isFunction(c.source)?c.source:function(a){return a[c.source]};if(!c.index)return d.error("Missing 'index' key");var k=c.index;return g=g||{},h}}]);
\ No newline at end of file
diff --git a/deps/search-1.0.0/fuse.min.js b/deps/search-1.0.0/fuse.min.js
new file mode 100644
index 000000000..7def5985b
--- /dev/null
+++ b/deps/search-1.0.0/fuse.min.js
@@ -0,0 +1,9 @@
+/**
+ * Fuse.js v6.4.6 - Lightweight fuzzy-search (http://fusejs.io)
+ *
+ * Copyright (c) 2021 Kiro Risk (http://kiro.me)
+ * All Rights Reserved. Apache Software License 2.0
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ */
+var e,t;e=this,t=function(){"use strict";function e(t){return(e="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(e){return typeof e}:function(e){return e&&"function"==typeof Symbol&&e.constructor===Symbol&&e!==Symbol.prototype?"symbol":typeof e})(t)}function t(e,t){if(!(e instanceof t))throw new TypeError("Cannot call a class as a function")}function n(e,t){for(var n=0;n<t.length;n++){var r=t[n];r.enumerable=r.enumerable||!1,r.configurable=!0,"value"in r&&(r.writable=!0),Object.defineProperty(e,r.key,r)}}function r(e,t,r){return t&&n(e.prototype,t),r&&n(e,r),e}function i(e,t,n){return t in e?Object.defineProperty(e,t,{value:n,enumerable:!0,configurable:!0,writable:!0}):e[t]=n,e}function o(e,t){var n=Object.keys(e);if(Object.getOwnPropertySymbols){var r=Object.getOwnPropertySymbols(e);t&&(r=r.filter((function(t){return Object.getOwnPropertyDescriptor(e,t).enumerable}))),n.push.apply(n,r)}return n}function c(e){for(var t=1;t<arguments.length;t++){var n=null!=arguments[t]?arguments[t]:{};t%2?o(Object(n),!0).forEach((function(t){i(e,t,n[t])})):Object.getOwnPropertyDescriptors?Object.defineProperties(e,Object.getOwnPropertyDescriptors(n)):o(Object(n)).forEach((function(t){Object.defineProperty(e,t,Object.getOwnPropertyDescriptor(n,t))}))}return e}function a(e,t){if("function"!=typeof t&&null!==t)throw new TypeError("Super expression must either be null or a function");e.prototype=Object.create(t&&t.prototype,{constructor:{value:e,writable:!0,configurable:!0}}),t&&u(e,t)}function s(e){return(s=Object.setPrototypeOf?Object.getPrototypeOf:function(e){return e.__proto__||Object.getPrototypeOf(e)})(e)}function u(e,t){return(u=Object.setPrototypeOf||function(e,t){return e.__proto__=t,e})(e,t)}function h(e,t){return!t||"object"!=typeof t&&"function"!=typeof t?function(e){if(void 0===e)throw new ReferenceError("this hasn't been initialised - super() hasn't been called");return e}(e):t}function f(e){var t=function(){if("undefined"==typeof 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\ No newline at end of file
diff --git a/deps/search-1.0.0/mark.min.js b/deps/search-1.0.0/mark.min.js
new file mode 100644
index 000000000..1eea05338
--- /dev/null
+++ b/deps/search-1.0.0/mark.min.js
@@ -0,0 +1,7 @@
+/*!***************************************************
+* mark.js v8.11.1
+* https://markjs.io/
+* Copyright (c) 2014–2018, Julian Kühnel
+* Released under the MIT license https://git.io/vwTVl
+*****************************************************/
+!function(e,t){"object"==typeof exports&&"undefined"!=typeof module?module.exports=t():"function"==typeof define&&define.amd?define(t):e.Mark=t()}(this,function(){"use strict";var e="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(e){return typeof e}:function(e){return e&&"function"==typeof Symbol&&e.constructor===Symbol&&e!==Symbol.prototype?"symbol":typeof e},t=function(e,t){if(!(e instanceof t))throw new TypeError("Cannot call a class as a function")},n=function(){function e(e,t){for(var n=0;n<t.length;n++){var r=t[n];r.enumerable=r.enumerable||!1,r.configurable=!0,"value"in r&&(r.writable=!0),Object.defineProperty(e,r.key,r)}}return function(t,n,r){return n&&e(t.prototype,n),r&&e(t,r),t}}(),r=Object.assign||function(e){for(var t=1;t<arguments.length;t++){var n=arguments[t];for(var r in n)Object.prototype.hasOwnProperty.call(n,r)&&(e[r]=n[r])}return e},i=function(){function e(n){var r=!(arguments.length>1&&void 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diff --git a/endorsement_clsi_eucast.jpg b/endorsement_clsi_eucast.jpg
deleted file mode 100644
index 6957819d5..000000000
Binary files a/endorsement_clsi_eucast.jpg and /dev/null differ
diff --git a/extra.css b/extra.css
index 1d2c36c90..e63b41098 100644
--- a/extra.css
+++ b/extra.css
@@ -7,9 +7,9 @@
 # https://github.com/msberends/AMR                                     #
 #                                                                      #
 # PLEASE CITE THIS SOFTWARE AS:                                        #
-# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C    #
-# (2022). AMR: An R Package for Working with Antimicrobial Resistance  #
-# Data. Journal of Statistical Software, 104(3), 1-31.                 #
+# Berends MS, Luz CF, Friedrich AW, et al. (2022).                     #
+# AMR: An R Package for Working with Antimicrobial Resistance Data.    #
+# Journal of Statistical Software, 104(3), 1-31.                       #
 # https://doi.org/10.18637/jss.v104.i03                                #
 #                                                                      #
 # Developed at the University of Groningen and the University Medical  #
diff --git a/extra.js b/extra.js
index e638b8549..3ad90dbaf 100644
--- a/extra.js
+++ b/extra.js
@@ -7,9 +7,9 @@
 # https://github.com/msberends/AMR                                     #
 #                                                                      #
 # PLEASE CITE THIS SOFTWARE AS:                                        #
-# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C    #
-# (2022). AMR: An R Package for Working with Antimicrobial Resistance  #
-# Data. Journal of Statistical Software, 104(3), 1-31.                 #
+# Berends MS, Luz CF, Friedrich AW, et al. (2022).                     #
+# AMR: An R Package for Working with Antimicrobial Resistance Data.    #
+# Journal of Statistical Software, 104(3), 1-31.                       #
 # https://doi.org/10.18637/jss.v104.i03                                #
 #                                                                      #
 # Developed at the University of Groningen and the University Medical  #
diff --git a/index.html b/index.html
index a0a7452f3..35d7cda6b 100644
--- a/index.html
+++ b/index.html
@@ -5,7 +5,6 @@
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 <meta http-equiv="X-UA-Compatible" content="IE=edge">
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-<meta name="description" content="Functions to simplify and standardise antimicrobial resistance (AMR) data analysis and to work with microbial and antimicrobial properties by using evidence-based methods, as described in &lt;doi:10.18637/jss.v104.i03&gt;.">
 <title>Antimicrobial Resistance Data Analysis • AMR (for R)</title>
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+<link href="deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet">
+<link href="deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet">
+<script src="deps/headroom-0.11.0/headroom.min.js"></script><script src="deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="deps/search-1.0.0/fuse.min.js"></script><script src="deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="pkgdown.js"></script><link href="extra.css" rel="stylesheet">
 <script src="extra.js"></script><meta property="og:title" content="Antimicrobial Resistance Data Analysis">
+<meta name="description" content="Functions to simplify and standardise antimicrobial resistance (AMR) data analysis and to work with microbial and antimicrobial properties by using evidence-based methods, as described in &lt;doi:10.18637/jss.v104.i03&gt;.">
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     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
-    
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary" data-bs-theme="dark"><div class="container">
-    
+
+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="index.html">AMR (for R)</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9061</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9063</small>
+
 
-    
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
       <span class="navbar-toggler-icon"></span>
     </button>
@@ -49,141 +45,41 @@
     <div id="navbar" class="collapse navbar-collapse ms-3">
       <ul class="navbar-nav me-auto">
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--how-to">
-    <span class="fa fa-question-circle"></span>
-     
-    How to
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--how-to">
-    <a class="dropdown-item" href="articles/AMR.html">
-      <span class="fa fa-directions"></span>
-       
-      Conduct AMR Analysis
-    </a>
-    <a class="dropdown-item" href="reference/antibiogram.html">
-      <span class="fa fa-file-prescription"></span>
-       
-      Generate Antibiogram (Trad./Syndromic/WISCA)
-    </a>
-    <a class="dropdown-item" href="articles/resistance_predict.html">
-      <span class="fa fa-dice"></span>
-       
-      Predict Antimicrobial Resistance
-    </a>
-    <a class="dropdown-item" href="articles/datasets.html">
-      <span class="fa fa-database"></span>
-       
-      Download Data Sets for Own Use
-    </a>
-    <a class="dropdown-item" href="reference/AMR-options.html">
-      <span class="fa fa-gear"></span>
-       
-      Set User- Or Team-specific Package Settings
-    </a>
-    <a class="dropdown-item" href="articles/PCA.html">
-      <span class="fa fa-compress"></span>
-       
-      Conduct Principal Component Analysis for AMR
-    </a>
-    <a class="dropdown-item" href="articles/MDR.html">
-      <span class="fa fa-skull-crossbones"></span>
-       
-      Determine Multi-Drug Resistance (MDR)
-    </a>
-    <a class="dropdown-item" href="articles/WHONET.html">
-      <span class="fa fa-globe-americas"></span>
-       
-      Work with WHONET Data
-    </a>
-    <a class="dropdown-item" href="articles/EUCAST.html">
-      <span class="fa fa-exchange-alt"></span>
-       
-      Apply Eucast Rules
-    </a>
-    <a class="dropdown-item" href="reference/mo_property.html">
-      <span class="fa fa-bug"></span>
-       
-      Get Taxonomy of a Microorganism
-    </a>
-    <a class="dropdown-item" href="reference/ab_property.html">
-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antibiotic Drug
-    </a>
-    <a class="dropdown-item" href="reference/av_property.html">
-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antiviral Drug
-    </a>
-  </div>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-how-to" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-question-circle"></span> How to</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to">
+<li><a class="dropdown-item" href="articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul>
 </li>
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--with-other-pkgs">
-    <span class="fa fa-layer-group"></span>
-     
-    With other pkgs
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--with-other-pkgs">
-    <a class="dropdown-item" href="articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; dplyr/tidyverse
-    </a>
-    <a class="dropdown-item" href="articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; data.table
-    </a>
-    <a class="dropdown-item" href="articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; tidymodels
-    </a>
-    <a class="dropdown-item" href="articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; base R
-    </a>
-  </div>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="reference/index.html">
-    <span class="fa fa-book-open"></span>
-     
-    Manual
-  </a>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="authors.html">
-    <span class="fa fa-users"></span>
-     
-    Authors
-  </a>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs">
+<li><a class="dropdown-item" href="articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul>
 </li>
+<li class="nav-item"><a class="nav-link" href="reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="authors.html"><span class="fa fa-users"></span> Authors</a></li>
       </ul>
-<form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="search.json" id="search-input" placeholder="Search for" autocomplete="off">
-</form>
-
-      <ul class="navbar-nav">
-<li class="nav-item">
-  <a class="nav-link" href="news/index.html">
-    <span class="far fa far fa-newspaper"></span>
-     
-    Changelog
-  </a>
-</li>
-<li class="nav-item">
-  <a class="external-link nav-link" href="https://github.com/msberends/AMR">
-    <span class="fab fa fab fa-github"></span>
-     
-    Source Code
-  </a>
-</li>
+<ul class="navbar-nav">
+<li class="nav-item"><a class="nav-link" href="news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul>
 </div>
 
-    
+
   </div>
 </nav><div class="container template-home">
 <div class="row">
@@ -872,9 +768,9 @@
     </footer>
 </div>
 
-  
 
-  
+
+
 
   </body>
 </html>
diff --git a/katex-auto.js b/katex-auto.js
new file mode 100644
index 000000000..20651d9fd
--- /dev/null
+++ b/katex-auto.js
@@ -0,0 +1,14 @@
+// https://github.com/jgm/pandoc/blob/29fa97ab96b8e2d62d48326e1b949a71dc41f47a/src/Text/Pandoc/Writers/HTML.hs#L332-L345
+document.addEventListener("DOMContentLoaded", function () {
+  var mathElements = document.getElementsByClassName("math");
+  var macros = [];
+  for (var i = 0; i < mathElements.length; i++) {
+    var texText = mathElements[i].firstChild;
+    if (mathElements[i].tagName == "SPAN") {
+      katex.render(texText.data, mathElements[i], {
+        displayMode: mathElements[i].classList.contains("display"),
+        throwOnError: false,
+        macros: macros,
+        fleqn: false
+      });
+    }}});
diff --git a/lang_cs.svg b/lang_cs.svg
deleted file mode 100644
index c18c40a31..000000000
--- a/lang_cs.svg
+++ /dev/null
@@ -1,6 +0,0 @@
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-<svg version="1.0" xmlns="http://www.w3.org/2000/svg" width="900" height="600">
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-	<path d="M 450,300 0,0 V 600 z" fill="#11457e"/>
-</svg>
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diff --git a/lang_da.svg b/lang_da.svg
deleted file mode 100644
index 881430f4a..000000000
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+++ /dev/null
@@ -1 +0,0 @@
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diff --git a/lang_de.svg b/lang_de.svg
deleted file mode 100644
index 65e9a01af..000000000
--- a/lang_de.svg
+++ /dev/null
@@ -1,9 +0,0 @@
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-<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN"
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diff --git a/lang_el.svg b/lang_el.svg
deleted file mode 100644
index 532046f61..000000000
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+++ /dev/null
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-<svg xmlns="http://www.w3.org/2000/svg" width="600" height="400" viewBox="0 0 27 18">
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diff --git a/lang_en.svg b/lang_en.svg
deleted file mode 100644
index 56487b083..000000000
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+++ /dev/null
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diff --git a/lang_es.svg b/lang_es.svg
deleted file mode 100644
index fba167dd6..000000000
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diff --git a/lang_ro.svg b/lang_ro.svg
deleted file mode 100644
index 63a88cde0..000000000
--- a/lang_ro.svg
+++ /dev/null
@@ -1,6 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<svg xmlns="http://www.w3.org/2000/svg" width="600" height="400" viewBox="0 0 3 2">
-<rect width="3" height="2" x="0" y="0" fill="#002B7F"/>
-<rect width="2" height="2" x="1" y="0" fill="#FCD116"/>
-<rect width="1" height="2" x="2" y="0" fill="#CE1126"/>
-</svg>
\ No newline at end of file
diff --git a/lang_ru.svg b/lang_ru.svg
deleted file mode 100644
index 855b805a5..000000000
--- a/lang_ru.svg
+++ /dev/null
@@ -1 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 9 6" width="900" height="600"><rect fill="#fff" width="9" height="3"/><rect fill="#d52b1e" y="3" width="9" height="3"/><rect fill="#0039a6" y="2" width="9" height="2"/></svg>
\ No newline at end of file
diff --git a/lang_sv.svg b/lang_sv.svg
deleted file mode 100644
index 168a29a7a..000000000
--- a/lang_sv.svg
+++ /dev/null
@@ -1 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 10"><path fill="#006aa7" d="M0,0H16V10H0Z"/><path fill="#fecc00" d="M0,4H5V0H7V4H16V6H7V10H5V6H0Z"/></svg>
\ No newline at end of file
diff --git a/lang_tr.svg b/lang_tr.svg
deleted file mode 100644
index 33f5ad1fd..000000000
--- a/lang_tr.svg
+++ /dev/null
@@ -1,5 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" width="1200" height="800" viewBox="0 -30000 90000 60000">
-	<title>Flag of Turkey</title>
-	<path fill="#e30a17" d="m0-30000h90000v60000H0z"/>
-	<path fill="#fff" d="m41750 0 13568-4408-8386 11541V-7133l8386 11541zm925 8021a15000 15000 0 1 1 0-16042 12000 12000 0 1 0 0 16042z"/>
-</svg>
diff --git a/lang_uk.svg b/lang_uk.svg
deleted file mode 100644
index 8f4b0a436..000000000
--- a/lang_uk.svg
+++ /dev/null
@@ -1,4 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" width="1200" height="800">
-<rect width="1200" height="800" fill="#005BBB"/>
-<rect width="1200" height="400" y="400" fill="#FFD500"/>
-</svg>
\ No newline at end of file
diff --git a/lang_zh.svg b/lang_zh.svg
deleted file mode 100644
index 61f4fdcbd..000000000
--- a/lang_zh.svg
+++ /dev/null
@@ -1,12 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="900" height="600" viewBox="0 0 30 20">
-<defs>
-<path id="s" d="M0,-1 0.587785,0.809017 -0.951057,-0.309017H0.951057L-0.587785,0.809017z" fill="#FFFF00"/>
-</defs>
-<rect width="30" height="20" fill="#EE1C25"/>
-<use xlink:href="#s" transform="translate(5,5) scale(3)"/>
-<use xlink:href="#s" transform="translate(10,2) rotate(23.036243)"/>
-<use xlink:href="#s" transform="translate(12,4) rotate(45.869898)"/>
-<use xlink:href="#s" transform="translate(12,7) rotate(69.945396)"/>
-<use xlink:href="#s" transform="translate(10,9) rotate(20.659808)"/>
-</svg>
\ No newline at end of file
diff --git a/lightswitch.js b/lightswitch.js
new file mode 100644
index 000000000..9467125ae
--- /dev/null
+++ b/lightswitch.js
@@ -0,0 +1,85 @@
+
+/*!
+ * Color mode toggler for Bootstrap's docs (https://getbootstrap.com/)
+ * Copyright 2011-2023 The Bootstrap Authors
+ * Licensed under the Creative Commons Attribution 3.0 Unported License.
+ * Updates for {pkgdown} by the {bslib} authors, also licensed under CC-BY-3.0.
+ */
+
+const getStoredTheme = () => localStorage.getItem('theme')
+const setStoredTheme = theme => localStorage.setItem('theme', theme)
+
+const getPreferredTheme = () => {
+  const storedTheme = getStoredTheme()
+  if (storedTheme) {
+    return storedTheme
+  }
+
+  return window.matchMedia('(prefers-color-scheme: dark)').matches ? 'dark' : 'light'
+}
+
+const setTheme = theme => {
+  if (theme === 'auto') {
+    document.documentElement.setAttribute('data-bs-theme', (window.matchMedia('(prefers-color-scheme: dark)').matches ? 'dark' : 'light'))
+  } else {
+    document.documentElement.setAttribute('data-bs-theme', theme)
+  }
+}
+
+function bsSetupThemeToggle () {
+  'use strict'
+
+  const showActiveTheme = (theme, focus = false) => {
+    var activeLabel, activeIcon;
+
+    document.querySelectorAll('[data-bs-theme-value]').forEach(element => {
+      const buttonTheme = element.getAttribute('data-bs-theme-value')
+      const isActive = buttonTheme == theme
+      
+      element.classList.toggle('active', isActive)
+      element.setAttribute('aria-pressed', isActive)
+
+      if (isActive) {
+        activeLabel = element.textContent;
+        activeIcon = element.querySelector('span').classList.value;
+      }
+    })
+
+    const themeSwitcher = document.querySelector('#dropdown-lightswitch')
+    if (!themeSwitcher) {
+      return
+    }
+
+    themeSwitcher.setAttribute('aria-label', activeLabel)
+    themeSwitcher.querySelector('span').classList.value = activeIcon;
+
+    if (focus) {
+      themeSwitcher.focus()
+    }
+  }
+
+  window.matchMedia('(prefers-color-scheme: dark)').addEventListener('change', () => {
+    const storedTheme = getStoredTheme()
+    if (storedTheme !== 'light' && storedTheme !== 'dark') {
+      setTheme(getPreferredTheme())
+    }
+  })
+
+  window.addEventListener('DOMContentLoaded', () => {
+    showActiveTheme(getPreferredTheme())
+
+    document
+      .querySelectorAll('[data-bs-theme-value]')
+      .forEach(toggle => {
+        toggle.addEventListener('click', () => {
+          const theme = toggle.getAttribute('data-bs-theme-value')
+          setTheme(theme)
+          setStoredTheme(theme)
+          showActiveTheme(theme, true)
+        })
+      })
+  })
+}
+
+setTheme(getPreferredTheme());
+bsSetupThemeToggle();
diff --git a/logo_certe.svg b/logo_certe.svg
deleted file mode 100644
index 304528a7d..000000000
--- a/logo_certe.svg
+++ /dev/null
@@ -1,223 +0,0 @@
-<?xml version="1.0" encoding="utf-8"?>
-<!-- Generator: Adobe Illustrator 25.2.3, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
-<svg version="1.1" id="Layer_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
-	 viewBox="0 0 149.3 61.5" style="enable-background:new 0 0 149.3 61.5;" xml:space="preserve">
-<style type="text/css">
-	.st0{fill:#DDBADA;}
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diff --git a/logo_umcg.svg b/logo_umcg.svg
deleted file mode 100644
index 2488a4b21..000000000
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diff --git a/news/index.html b/news/index.html
index 4ce9c1cf2..fc02bc0a6 100644
--- a/news/index.html
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@@ -1,176 +1,70 @@
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Changelog • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Changelog"><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"></head><body>
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+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9063</small>
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to"><li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
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+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
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       <img src="../logo.svg" class="logo" alt=""><h1>Changelog</h1>
-      <small>Source: <a href="https://github.com/msberends/AMR/blob/HEAD/NEWS.md" class="external-link"><code>NEWS.md</code></a></small>
+      <small>Source: <a href="https://github.com/msberends/AMR/blob/main/NEWS.md" class="external-link"><code>NEWS.md</code></a></small>
     </div>
 
     <div class="section level2">
-<h2 class="pkg-version" data-toc-text="2.1.1.9061" id="amr-2119061">AMR 2.1.1.9061<a class="anchor" aria-label="anchor" href="#amr-2119061"></a></h2>
+<h2 class="pkg-version" data-toc-text="2.1.1.9063" id="amr-2119063">AMR 2.1.1.9063<a class="anchor" aria-label="anchor" href="#amr-2119063"></a></h2>
 <p><em>(this beta version will eventually become v3.0. We’re happy to reach a new major milestone soon, which will be all about the new One Health support! Install this beta using <a href="https://msberends.github.io/AMR/#latest-development-version">the instructions here</a>.)</em></p>
 <div class="section level5">
-<h5 id="a-new-milestone-amr-v30-with-one-health-support--human--veterinary--environmental-2-1-1-9061">A New Milestone: AMR v3.0 with One Health Support (= Human + Veterinary + Environmental)<a class="anchor" aria-label="anchor" href="#a-new-milestone-amr-v30-with-one-health-support--human--veterinary--environmental-2-1-1-9061"></a></h5>
+<h5 id="a-new-milestone-amr-v30-with-one-health-support--human--veterinary--environmental-2-1-1-9063">A New Milestone: AMR v3.0 with One Health Support (= Human + Veterinary + Environmental)<a class="anchor" aria-label="anchor" href="#a-new-milestone-amr-v30-with-one-health-support--human--veterinary--environmental-2-1-1-9063"></a></h5>
 <p>This package now supports not only tools for AMR data analysis in clinical settings, but also for veterinary and environmental microbiology. This was made possible through a collaboration with the <a href="https://www.upei.ca/avc" class="external-link">University of Prince Edward Island</a>, Canada. To celebrate this great improvement of the package, we also updated the package logo to reflect this change.</p>
 </div>
 <div class="section level3">
-<h3 id="breaking-2-1-1-9061">Breaking<a class="anchor" aria-label="anchor" href="#breaking-2-1-1-9061"></a></h3>
+<h3 id="breaking-2-1-1-9063">Breaking<a class="anchor" aria-label="anchor" href="#breaking-2-1-1-9063"></a></h3>
 <ul><li>Removed all functions and references that used the deprecated <code>rsi</code> class, which were all replaced with their <code>sir</code> equivalents over a year ago</li>
 </ul></div>
 <div class="section level3">
-<h3 id="new-2-1-1-9061">New<a class="anchor" aria-label="anchor" href="#new-2-1-1-9061"></a></h3>
+<h3 id="new-2-1-1-9063">New<a class="anchor" aria-label="anchor" href="#new-2-1-1-9063"></a></h3>
 <ul><li>One Health implementation
 <ul><li>Function <code><a href="../reference/as.sir.html">as.sir()</a></code> now has extensive support for animal breakpoints from CLSI. Use <code>breakpoint_type = "animal"</code> and set the <code>host</code> argument to a variable that contains animal species names.</li>
 <li>The <code>clinical_breakpoints</code> data set contains all these breakpoints, and can be downloaded on our <a href="https://msberends.github.io/AMR/articles/datasets.html">download page</a>.</li>
@@ -186,15 +80,24 @@
 <code><a href="../reference/as.sir.html">as.sir()</a></code> now brings additional factor levels: “NI” for non-interpretable and “SDD” for susceptible dose-dependent. Currently, the <code>clinical_breakpoints</code> data set contains 24 breakpoints that can return the value “SDD” instead of “I”.</li>
 </ul></li>
 <li>MIC plotting and transforming
-<ul><li>The function group <code>scale_*_mic()</code>, namely: <code><a href="../reference/plot.html">scale_x_mic()</a></code>, <code><a href="../reference/plot.html">scale_y_mic()</a></code>, <code><a href="../reference/plot.html">scale_colour_mic()</a></code> and <code><a href="../reference/plot.html">scale_fill_mic()</a></code>. They are advanced ggplot2 extensions to allow easy plotting of MIC values. They allow for manual range definition and plotting missing intermediate log2 levels.</li>
-<li>Function <code><a href="../reference/as.mic.html">rescale_mic()</a></code>, which allows to rescale MIC values to a manually set range. This is the powerhouse behind the <code>scale_*_mic()</code> functions, but it can be used by users directly to e.g. compare equality in MIC distributions by rescaling them to the same range first.</li>
+<ul><li>New function group <code>scale_*_mic()</code>, namely: <code><a href="../reference/plot.html">scale_x_mic()</a></code>, <code><a href="../reference/plot.html">scale_y_mic()</a></code>, <code><a href="../reference/plot.html">scale_colour_mic()</a></code> and <code><a href="../reference/plot.html">scale_fill_mic()</a></code>. They are advanced ggplot2 extensions to allow easy plotting of MIC values. They allow for manual range definition and plotting missing intermediate log2 levels.</li>
+<li>New function <code><a href="../reference/as.mic.html">rescale_mic()</a></code>, which allows to rescale MIC values to a manually set range. This is the powerhouse behind the <code>scale_*_mic()</code> functions, but it can be used by users directly to e.g. compare equality in MIC distributions by rescaling them to the same range first.</li>
+</ul></li>
+<li>Microbiological taxonomy (<code>microorganisms</code> data set) updated to June 2024, with some exciting new features:
+<ul><li>Added MycoBank as the primary taxonomic source for fungi
+<ul><li>The <code>microorganisms</code> data set now contains additional columns <code>mycobank</code>, <code>mycobank_parent</code>, and <code>mycobank_renamed_to</code>
+</li>
+<li>New function <code><a href="../reference/mo_property.html">mo_mycobank()</a></code> to get the MycoBank record number, analogous to existing functions <code><a href="../reference/mo_property.html">mo_lpsn()</a></code> and <code><a href="../reference/mo_property.html">mo_gbif()</a></code>
+</li>
+</ul></li>
+<li>We’ve welcomed over 2,000 records from 2023, over 900 from 2024, and many thousands of new fungi</li>
 </ul></li>
 <li>Other
-<ul><li>Function <code><a href="../reference/mo_property.html">mo_group_members()</a></code> to retrieve the member microorganisms of a microorganism group. For example, <code>mo_group_members("Strep group C")</code> returns a vector of all microorganisms that are in that group.</li>
+<ul><li>New function <code><a href="../reference/mo_property.html">mo_group_members()</a></code> to retrieve the member microorganisms of a microorganism group. For example, <code>mo_group_members("Strep group C")</code> returns a vector of all microorganisms that are in that group.</li>
 </ul></li>
 </ul></div>
 <div class="section level3">
-<h3 id="changed-2-1-1-9061">Changed<a class="anchor" aria-label="anchor" href="#changed-2-1-1-9061"></a></h3>
+<h3 id="changed-2-1-1-9063">Changed<a class="anchor" aria-label="anchor" href="#changed-2-1-1-9063"></a></h3>
 <ul><li>SIR interpretation
 <ul><li>It is now possible to use column names for argument <code>ab</code>, <code>mo</code>, and <code>uti</code>: <code>as.sir(..., ab = "column1", mo = "column2", uti = "column3")</code>. This greatly improves the flexibility for users.</li>
 <li>Users can now set their own criteria (using regular expressions) as to what should be considered S, I, R, SDD, and NI.</li>
@@ -231,9 +134,10 @@
 <li>Improved overall algorithm of <code><a href="../reference/as.ab.html">as.ab()</a></code> for better performance and accuracy</li>
 <li>Improved overall algorithm of <code><a href="../reference/as.mo.html">as.mo()</a></code> for better performance and accuracy. Specifically, more weight is given to genus and species combinations in cases where the subspecies is miswritten, so that the result will be the correct genus and species.</li>
 <li>Intermediate log2 levels used for MIC plotting are now more common values instead of following a strict dilution range</li>
+<li>Fixed a bug for when <code><a href="../reference/antibiogram.html">antibiogram()</a></code> returns an empty data set</li>
 </ul></div>
 <div class="section level3">
-<h3 id="other-2-1-1-9061">Other<a class="anchor" aria-label="anchor" href="#other-2-1-1-9061"></a></h3>
+<h3 id="other-2-1-1-9063">Other<a class="anchor" aria-label="anchor" href="#other-2-1-1-9063"></a></h3>
 <ul><li>Added Jordan Stull, Matthew Saab, and Javier Sanchez as contributors, to thank them for their valuable input</li>
 </ul></div>
 </div>
@@ -455,7 +359,7 @@
 </ul><hr><p>This changelog only contains changes from AMR v2.0 (January 2023) and later. For prior versions, please see <a href="https://github.com/msberends/AMR/blob/v1.8.2/NEWS.md" class="external-link">our archive</a>.</p>
 </div>
 </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -469,9 +373,9 @@
 
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diff --git a/pkgdown.js b/pkgdown.js
index 9bd6621ee..9757bf9ef 100644
--- a/pkgdown.js
+++ b/pkgdown.js
@@ -152,5 +152,3 @@ async function searchFuse(query, callback) {
   });
   });
 })(window.jQuery || window.$)
-
-
diff --git a/pkgdown.yml b/pkgdown.yml
index e50e9f0f9..facc6eaa2 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -1,5 +1,5 @@
 pandoc: 3.1.11
-pkgdown: 2.0.9
+pkgdown: 2.1.0
 pkgdown_sha: ~
 articles:
   AMR: AMR.html
@@ -11,8 +11,7 @@ articles:
   resistance_predict: resistance_predict.html
   welcome_to_AMR: welcome_to_AMR.html
   WHONET: WHONET.html
-last_built: 2024-06-23T14:21Z
+last_built: 2024-07-16T12:57Z
 urls:
   reference: https://msberends.github.io/AMR/reference
   article: https://msberends.github.io/AMR/articles
-
diff --git a/reference/%like%.html b/reference/%like%.html
new file mode 100644
index 000000000..e456eb274
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new file mode 100644
index 000000000..e456eb274
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new file mode 100644
index 000000000..e456eb274
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@@ -0,0 +1,8 @@
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diff --git a/reference/3MRGN.html b/reference/3MRGN.html
new file mode 100644
index 000000000..9ccef1b51
--- /dev/null
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@@ -0,0 +1,8 @@
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new file mode 100644
index 000000000..9ccef1b51
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@@ -0,0 +1,8 @@
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index 2ac7c1023..e61965ab1 100644
--- a/reference/AMR-options.html
+++ b/reference/AMR-options.html
@@ -1,161 +1,55 @@
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-      Get Properties of an Antibiotic Drug
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-    <a class="dropdown-item" href="../reference/av_property.html">
-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antiviral Drug
-    </a>
-  </div>
-</li>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-how-to" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-question-circle"></span> How to</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to"><li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul></li>
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--with-other-pkgs">
-    <span class="fa fa-layer-group"></span>
-     
-    With other pkgs
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--with-other-pkgs">
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; dplyr/tidyverse
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; data.table
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; tidymodels
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; base R
-    </a>
-  </div>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../reference/index.html">
-    <span class="fa fa-book-open"></span>
-     
-    Manual
-  </a>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../authors.html">
-    <span class="fa fa-users"></span>
-     
-    Authors
-  </a>
-</li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
-  <a class="nav-link" href="../news/index.html">
-    <span class="far fa far fa-newspaper"></span>
-     
-    Changelog
-  </a>
-</li>
-<li class="nav-item">
-  <a class="external-link nav-link" href="https://github.com/msberends/AMR">
-    <span class="fab fa fab fa-github"></span>
-     
-    Source Code
-  </a>
-</li>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Options for the AMR package</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/aa_options.R" class="external-link"><code>R/aa_options.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/aa_options.R" class="external-link"><code>R/aa_options.R</code></a></small>
       <div class="d-none name"><code>AMR-options.Rd</code></div>
     </div>
 
@@ -166,7 +60,7 @@
 
     <div class="section level2">
     <h2 id="options">Options<a class="anchor" aria-label="anchor" href="#options"></a></h2>
-    
+
 
 <ul><li><p><code>AMR_breakpoint_type</code> <br> A <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> to use in <code><a href="as.sir.html">as.sir()</a></code>, to indicate which breakpoint type to use. This must be either "ECOFF", "animal", or "human".</p></li>
 <li><p><code>AMR_cleaning_regex</code> <br> A <a href="https://rdrr.io/r/base/regex.html" class="external-link">regular expression</a> (case-insensitive) to use in <code><a href="as.mo.html">as.mo()</a></code> and all <code><a href="mo_property.html">mo_*</a></code> functions, to clean the user input. The default is the outcome of <code><a href="as.mo.html">mo_cleaning_regex()</a></code>, which removes texts between brackets and texts such as "species" and "serovar".</p></li>
@@ -183,7 +77,7 @@
 </ul></div>
     <div class="section level2">
     <h2 id="saving-settings-between-sessions">Saving Settings Between Sessions<a class="anchor" aria-label="anchor" href="#saving-settings-between-sessions"></a></h2>
-    
+
 
 <p>Settings in <span style="R">R</span> are not saved globally and are thus lost when <span style="R">R</span> is exited. You can save your options to your own <code>.Rprofile</code> file, which is a user-specific file. You can edit it using:</p>
 <p></p><div class="sourceCode r"><pre><code><span>  <span class="fu">utils</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/r/utils/file.edit.html" class="external-link">file.edit</a></span><span class="op">(</span><span class="st">"~/.Rprofile"</span><span class="op">)</span></span></code></pre><p></p></div>
@@ -203,7 +97,7 @@
 
     </div>
 
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -217,9 +111,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/AMR-package.html b/reference/AMR-package.html
new file mode 100644
index 000000000..7c8b9cfd4
--- /dev/null
+++ b/reference/AMR-package.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/AMR.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/AMR.html">
+  </head>
+</html>
+
diff --git a/reference/AMR.html b/reference/AMR.html
index 36378b0ad..937cc8af0 100644
--- a/reference/AMR.html
+++ b/reference/AMR.html
@@ -1,175 +1,69 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Welcome to the AMR package.
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>The AMR Package — AMR • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="The AMR Package — AMR"><meta name="description" content="Welcome to the AMR package.
 The AMR package is a free and open-source R package with zero dependencies to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. Our aim is to provide a standard for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. Many different researchers from around the globe are continually helping us to make this a successful and durable project!
 This work was published in the Journal of Statistical Software (Volume 104(3); doi:10.18637/jss.v104.i03
 ) and formed the basis of two PhD theses (doi:10.33612/diss.177417131
  and doi:10.33612/diss.192486375
 ).
-After installing this package, R knows ~52 000 microorganisms (updated January 2024) and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid SIR and MIC values. The integral clinical breakpoint guidelines from CLSI and EUCAST are included, even with epidemiological cut-off (ECOFF) values. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the public University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice Foundation and University Medical Center Groningen.
-The AMR package is available in English, Chinese, Czech, Danish, Dutch, Finnish, French, German, Greek, Italian, Japanese, Norwegian, Polish, Portuguese, Romanian, Russian, Spanish, Swedish, Turkish, and Ukrainian. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages."><title>The AMR Package — AMR • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="The AMR Package — AMR"><meta property="og:description" content="Welcome to the AMR package.
+After installing this package, R knows ~71 000 microorganisms (updated June 2024) and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid SIR and MIC values. The integral clinical breakpoint guidelines from CLSI and EUCAST are included, even with epidemiological cut-off (ECOFF) values. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the public University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice Foundation and University Medical Center Groningen.
+The AMR package is available in English, Chinese, Czech, Danish, Dutch, Finnish, French, German, Greek, Italian, Japanese, Norwegian, Polish, Portuguese, Romanian, Russian, Spanish, Swedish, Turkish, and Ukrainian. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages."><meta property="og:description" content="Welcome to the AMR package.
 The AMR package is a free and open-source R package with zero dependencies to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. Our aim is to provide a standard for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. Many different researchers from around the globe are continually helping us to make this a successful and durable project!
 This work was published in the Journal of Statistical Software (Volume 104(3); doi:10.18637/jss.v104.i03
 ) and formed the basis of two PhD theses (doi:10.33612/diss.177417131
  and doi:10.33612/diss.192486375
 ).
-After installing this package, R knows ~52 000 microorganisms (updated January 2024) and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid SIR and MIC values. The integral clinical breakpoint guidelines from CLSI and EUCAST are included, even with epidemiological cut-off (ECOFF) values. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the public University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice Foundation and University Medical Center Groningen.
-The AMR package is available in English, Chinese, Czech, Danish, Dutch, Finnish, French, German, Greek, Italian, Japanese, Norwegian, Polish, Portuguese, Romanian, Russian, Spanish, Swedish, Turkish, and Ukrainian. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<![endif]--></head><body>
+After installing this package, R knows ~71 000 microorganisms (updated June 2024) and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid SIR and MIC values. The integral clinical breakpoint guidelines from CLSI and EUCAST are included, even with epidemiological cut-off (ECOFF) values. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the public University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice Foundation and University Medical Center Groningen.
+The AMR package is available in English, Chinese, Czech, Danish, Dutch, Finnish, French, German, Greek, Italian, Japanese, Norwegian, Polish, Portuguese, Romanian, Russian, Spanish, Swedish, Turkish, and Ukrainian. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"></head><body>
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-      Download Data Sets for Own Use
-    </a>
-    <a class="dropdown-item" href="../reference/AMR-options.html">
-      <span class="fa fa-gear"></span>
-       
-      Set User- Or Team-specific Package Settings
-    </a>
-    <a class="dropdown-item" href="../articles/PCA.html">
-      <span class="fa fa-compress"></span>
-       
-      Conduct Principal Component Analysis for AMR
-    </a>
-    <a class="dropdown-item" href="../articles/MDR.html">
-      <span class="fa fa-skull-crossbones"></span>
-       
-      Determine Multi-Drug Resistance (MDR)
-    </a>
-    <a class="dropdown-item" href="../articles/WHONET.html">
-      <span class="fa fa-globe-americas"></span>
-       
-      Work with WHONET Data
-    </a>
-    <a class="dropdown-item" href="../articles/EUCAST.html">
-      <span class="fa fa-exchange-alt"></span>
-       
-      Apply Eucast Rules
-    </a>
-    <a class="dropdown-item" href="../reference/mo_property.html">
-      <span class="fa fa-bug"></span>
-       
-      Get Taxonomy of a Microorganism
-    </a>
-    <a class="dropdown-item" href="../reference/ab_property.html">
-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antibiotic Drug
-    </a>
-    <a class="dropdown-item" href="../reference/av_property.html">
-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antiviral Drug
-    </a>
-  </div>
-</li>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-how-to" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-question-circle"></span> How to</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to"><li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul></li>
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--with-other-pkgs">
-    <span class="fa fa-layer-group"></span>
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-    With other pkgs
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--with-other-pkgs">
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; dplyr/tidyverse
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; data.table
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
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-      AMR &amp; tidymodels
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-  <a class="nav-link" href="../reference/index.html">
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-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>The <code>AMR</code> Package</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/aa_amr-package.R" class="external-link"><code>R/aa_amr-package.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/aa_amr-package.R" class="external-link"><code>R/aa_amr-package.R</code></a></small>
       <div class="d-none name"><code>AMR.Rd</code></div>
     </div>
 
@@ -180,7 +74,7 @@ The AMR package is available in English, Chinese, Czech, Danish, Dutch, Finnish,
 ) and formed the basis of two PhD theses (<a href="https://doi.org/10.33612/diss.177417131" class="external-link">doi:10.33612/diss.177417131</a>
  and <a href="https://doi.org/10.33612/diss.192486375" class="external-link">doi:10.33612/diss.192486375</a>
 ).</p>
-<p>After installing this package, R knows <a href="https://msberends.github.io/AMR/reference/microorganisms.html"><strong>~52 000 microorganisms</strong></a> (updated January 2024) and all <a href="https://msberends.github.io/AMR/reference/antibiotics.html"><strong>~600 antibiotic, antimycotic and antiviral drugs</strong></a> by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid SIR and MIC values. The integral clinical breakpoint guidelines from CLSI and EUCAST are included, even with epidemiological cut-off (ECOFF) values. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). <strong>It was designed to work in any setting, including those with very limited resources</strong>. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the public <a href="https://www.rug.nl" class="external-link">University of Groningen</a>, in collaboration with non-profit organisations <a href="https://www.certe.nl" class="external-link">Certe Medical Diagnostics and Advice Foundation</a> and <a href="https://www.umcg.nl" class="external-link">University Medical Center Groningen</a>.</p>
+<p>After installing this package, R knows <a href="https://msberends.github.io/AMR/reference/microorganisms.html"><strong>~71 000 microorganisms</strong></a> (updated June 2024) and all <a href="https://msberends.github.io/AMR/reference/antibiotics.html"><strong>~600 antibiotic, antimycotic and antiviral drugs</strong></a> by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid SIR and MIC values. The integral clinical breakpoint guidelines from CLSI and EUCAST are included, even with epidemiological cut-off (ECOFF) values. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). <strong>It was designed to work in any setting, including those with very limited resources</strong>. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the public <a href="https://www.rug.nl" class="external-link">University of Groningen</a>, in collaboration with non-profit organisations <a href="https://www.certe.nl" class="external-link">Certe Medical Diagnostics and Advice Foundation</a> and <a href="https://www.umcg.nl" class="external-link">University Medical Center Groningen</a>.</p>
 <p>The <code>AMR</code> package is available in English, Chinese, Czech, Danish, Dutch, Finnish, French, German, Greek, Italian, Japanese, Norwegian, Polish, Portuguese, Romanian, Russian, Spanish, Swedish, Turkish, and Ukrainian. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages.</p>
     </div>
 
@@ -206,7 +100,7 @@ The AMR package is available in English, Chinese, Czech, Danish, Dutch, Finnish,
     </div>
     <div class="section level2">
     <h2 id="reference-data-publicly-available">Reference Data Publicly Available<a class="anchor" aria-label="anchor" href="#reference-data-publicly-available"></a></h2>
-    
+
 
 <p>All data sets in this <code>AMR</code> package (about microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) are publicly and freely available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. We also provide tab-separated plain text files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please visit <a href="https://msberends.github.io/AMR/articles/datasets.html">our website for the download links</a>. The actual files are of course available on <a href="https://github.com/msberends/AMR/tree/main/data-raw" class="external-link">our GitHub repository</a>.</p>
     </div>
@@ -246,7 +140,7 @@ The AMR package is available in English, Chinese, Czech, Danish, Dutch, Finnish,
 <li><p>Anita Williams (<a href="https://orcid.org/0000-0002-5295-8451" class="external-link">ORCID</a>) [contributor]</p></li>
 </ul></div>
 
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -260,9 +154,9 @@ The AMR package is available in English, Chinese, Czech, Danish, Dutch, Finnish,
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/ATC.html b/reference/ATC.html
new file mode 100644
index 000000000..07fd0ee02
--- /dev/null
+++ b/reference/ATC.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/ab_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/ab_property.html">
+  </head>
+</html>
+
diff --git a/reference/BRMO.html b/reference/BRMO.html
new file mode 100644
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+++ b/reference/BRMO.html
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+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mdro.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/mdro.html">
+  </head>
+</html>
+
diff --git a/reference/EUCAST.html b/reference/EUCAST.html
new file mode 100644
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--- /dev/null
+++ b/reference/EUCAST.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/eucast_rules.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/eucast_rules.html">
+  </head>
+</html>
+
diff --git a/reference/MDR.html b/reference/MDR.html
new file mode 100644
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+++ b/reference/MDR.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mdro.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/mdro.html">
+  </head>
+</html>
+
diff --git a/reference/NA_disk_.html b/reference/NA_disk_.html
new file mode 100644
index 000000000..ed1f99ab0
--- /dev/null
+++ b/reference/NA_disk_.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/as.disk.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/as.disk.html">
+  </head>
+</html>
+
diff --git a/reference/NA_mic_.html b/reference/NA_mic_.html
new file mode 100644
index 000000000..977eb978a
--- /dev/null
+++ b/reference/NA_mic_.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/as.mic.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/as.mic.html">
+  </head>
+</html>
+
diff --git a/reference/NA_sir_.html b/reference/NA_sir_.html
new file mode 100644
index 000000000..c99d19d99
--- /dev/null
+++ b/reference/NA_sir_.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/as.sir.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/as.sir.html">
+  </head>
+</html>
+
diff --git a/reference/PDR.html b/reference/PDR.html
new file mode 100644
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--- /dev/null
+++ b/reference/PDR.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mdro.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/mdro.html">
+  </head>
+</html>
+
diff --git a/reference/WHOCC.html b/reference/WHOCC.html
index 0a92e0c5a..19891134d 100644
--- a/reference/WHOCC.html
+++ b/reference/WHOCC.html
@@ -1,161 +1,55 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="All antimicrobial drugs and their official names, ATC codes, ATC groups and defined daily dose (DDD) are included in this package, using the WHO Collaborating Centre for Drug Statistics Methodology."><title>WHOCC: WHO Collaborating Centre for Drug Statistics Methodology — WHOCC • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="WHOCC: WHO Collaborating Centre for Drug Statistics Methodology — WHOCC"><meta property="og:description" content="All antimicrobial drugs and their official names, ATC codes, ATC groups and defined daily dose (DDD) are included in this package, using the WHO Collaborating Centre for Drug Statistics Methodology."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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       <img src="../logo.svg" class="logo" alt=""><h1>WHOCC: WHO Collaborating Centre for Drug Statistics Methodology</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/whocc.R" class="external-link"><code>R/whocc.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/whocc.R" class="external-link"><code>R/whocc.R</code></a></small>
       <div class="d-none name"><code>WHOCC.Rd</code></div>
     </div>
 
@@ -166,7 +60,7 @@
 
     <div class="section level2">
     <h2 id="whocc">WHOCC<a class="anchor" aria-label="anchor" href="#whocc"></a></h2>
-    
+
 
 <p>This package contains <strong>all ~550 antibiotic, antimycotic and antiviral drugs</strong> and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, <a href="https://atcddd.fhi.no" class="external-link">https://atcddd.fhi.no</a>) and the Pharmaceuticals Community Register of the European Commission (<a href="https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm" class="external-link">https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm</a>).</p>
 <p>These have become the gold standard for international drug utilisation monitoring and research.</p>
@@ -189,7 +83,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> [10] "flucloxacillinum"     "fluorochloroxacillin" "staphylex"           </span>
 </code></pre></div>
     </div>
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diff --git a/reference/WHONET.html b/reference/WHONET.html
index 3aae531e3..cf09747f9 100644
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@@ -1,161 +1,55 @@
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+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
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       <img src="../logo.svg" class="logo" alt=""><h1>Data Set with 500 Isolates - WHONET Example</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/data.R" class="external-link"><code>R/data.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/data.R" class="external-link"><code>R/data.R</code></a></small>
       <div class="d-none name"><code>WHONET.Rd</code></div>
     </div>
 
@@ -227,7 +121,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   Carbapenemase &lt;lgl&gt;, `MRSA screening test` &lt;lgl&gt;, …</span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
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@@ -0,0 +1,8 @@
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new file mode 100644
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new file mode 100644
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diff --git a/reference/ab_atc_group2.html b/reference/ab_atc_group2.html
new file mode 100644
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new file mode 100644
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diff --git a/reference/ab_class.html b/reference/ab_class.html
new file mode 100644
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+++ b/reference/ab_class.html
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new file mode 100644
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diff --git a/reference/ab_ddd_units.html b/reference/ab_ddd_units.html
new file mode 100644
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+++ b/reference/ab_ddd_units.html
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diff --git a/reference/ab_from_text.html b/reference/ab_from_text.html
index 8988390e5..89822ad19 100644
--- a/reference/ab_from_text.html
+++ b/reference/ab_from_text.html
@@ -1,161 +1,55 @@
 <!DOCTYPE html>
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     <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9061</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9063</small>
+
 
-    
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-      Get Properties of an Antibiotic Drug
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-    <a class="dropdown-item" href="../reference/av_property.html">
-      <span class="fa fa-capsules"></span>
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-      Get Properties of an Antiviral Drug
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-how-to" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-question-circle"></span> How to</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to"><li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul></li>
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--with-other-pkgs">
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-    With other pkgs
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--with-other-pkgs">
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
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-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; data.table
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-      AMR &amp; tidymodels
-    </a>
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-      <span class="fa fa-layer-group"></span>
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-      AMR &amp; base R
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-    <span class="fa fa-users"></span>
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-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
-  <a class="nav-link" href="../news/index.html">
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-  <a class="external-link nav-link" href="https://github.com/msberends/AMR">
-    <span class="fab fa fab fa-github"></span>
-     
-    Source Code
-  </a>
-</li>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Retrieve Antimicrobial Drug Names and Doses from Clinical Text</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/ab_from_text.R" class="external-link"><code>R/ab_from_text.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/ab_from_text.R" class="external-link"><code>R/ab_from_text.R</code></a></small>
       <div class="d-none name"><code>ab_from_text.Rd</code></div>
     </div>
 
@@ -178,41 +72,39 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>text</dt>
+
+
+<dl><dt id="arg-text">text<a class="anchor" aria-label="anchor" href="#arg-text"></a></dt>
 <dd><p>text to analyse</p></dd>
 
 
-<dt>type</dt>
+<dt id="arg-type">type<a class="anchor" aria-label="anchor" href="#arg-type"></a></dt>
 <dd><p>type of property to search for, either <code>"drug"</code>, <code>"dose"</code> or <code>"administration"</code>, see <em>Examples</em></p></dd>
 
 
-<dt>collapse</dt>
+<dt id="arg-collapse">collapse<a class="anchor" aria-label="anchor" href="#arg-collapse"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> to pass on to <code>paste(, collapse = ...)</code> to only return one <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> per element of <code>text</code>, see <em>Examples</em></p></dd>
 
 
-<dt>translate_ab</dt>
+<dt id="arg-translate-ab">translate_ab<a class="anchor" aria-label="anchor" href="#arg-translate-ab"></a></dt>
 <dd><p>if <code>type = "drug"</code>: a column name of the <a href="antibiotics.html">antibiotics</a> data set to translate the antibiotic abbreviations to, using <code><a href="ab_property.html">ab_property()</a></code>. The default is <code>FALSE</code>. Using <code>TRUE</code> is equal to using "name".</p></dd>
 
 
-<dt>thorough_search</dt>
+<dt id="arg-thorough-search">thorough_search<a class="anchor" aria-label="anchor" href="#arg-thorough-search"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether the input must be extensively searched for misspelling and other faulty input values. Setting this to <code>TRUE</code> will take considerably more time than when using <code>FALSE</code>. At default, it will turn <code>TRUE</code> when all input elements contain a maximum of three words.</p></dd>
 
 
-<dt>info</dt>
+<dt id="arg-info">info<a class="anchor" aria-label="anchor" href="#arg-info"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether a progress bar should be printed - the default is <code>TRUE</code> only in interactive mode</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>arguments passed on to <code><a href="as.ab.html">as.ab()</a></code></p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A <a href="https://rdrr.io/r/base/list.html" class="external-link">list</a>, or a  <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> if <code>collapse</code> is not <code>NULL</code></p>
-
-
+    <p>A <a href="https://rdrr.io/r/base/list.html" class="external-link">list</a>, or a  <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> if <code>collapse</code> is not <code>NULL</code></p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -310,7 +202,7 @@
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -324,9 +216,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/ab_group.html b/reference/ab_group.html
new file mode 100644
index 000000000..07fd0ee02
--- /dev/null
+++ b/reference/ab_group.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/ab_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/ab_property.html">
+  </head>
+</html>
+
diff --git a/reference/ab_info.html b/reference/ab_info.html
new file mode 100644
index 000000000..07fd0ee02
--- /dev/null
+++ b/reference/ab_info.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/ab_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/ab_property.html">
+  </head>
+</html>
+
diff --git a/reference/ab_loinc.html b/reference/ab_loinc.html
new file mode 100644
index 000000000..07fd0ee02
--- /dev/null
+++ b/reference/ab_loinc.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/ab_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/ab_property.html">
+  </head>
+</html>
+
diff --git a/reference/ab_name.html b/reference/ab_name.html
new file mode 100644
index 000000000..07fd0ee02
--- /dev/null
+++ b/reference/ab_name.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/ab_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/ab_property.html">
+  </head>
+</html>
+
diff --git a/reference/ab_property.html b/reference/ab_property.html
index 67373520a..5eeee6929 100644
--- a/reference/ab_property.html
+++ b/reference/ab_property.html
@@ -1,161 +1,55 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Use these functions to return a specific property of an antibiotic from the antibiotics data set. All input values will be evaluated internally with as.ab()."><title>Get Properties of an Antibiotic — ab_property • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Get Properties of an Antibiotic — ab_property"><meta property="og:description" content="Use these functions to return a specific property of an antibiotic from the antibiotics data set. All input values will be evaluated internally with as.ab()."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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       <img src="../logo.svg" class="logo" alt=""><h1>Get Properties of an Antibiotic</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/ab_property.R" class="external-link"><code>R/ab_property.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/ab_property.R" class="external-link"><code>R/ab_property.R</code></a></small>
       <div class="d-none name"><code>ab_property.Rd</code></div>
     </div>
 
@@ -204,49 +98,50 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>any (vector of) text that can be coerced to a valid antibiotic drug code with <code><a href="as.ab.html">as.ab()</a></code></p></dd>
 
 
-<dt>language</dt>
+<dt id="arg-language">language<a class="anchor" aria-label="anchor" href="#arg-language"></a></dt>
 <dd><p>language of the returned text - the default is the current system language (see <code><a href="translate.html">get_AMR_locale()</a></code>) and can also be set with the <a href="AMR-options.html">package option</a> <code><a href="AMR-options.html">AMR_locale</a></code>. Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></dd>
 
 
-<dt>tolower</dt>
+<dt id="arg-tolower">tolower<a class="anchor" aria-label="anchor" href="#arg-tolower"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether the first <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> of every output should be transformed to a lower case <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a>. This will lead to e.g. "polymyxin B" and not "polymyxin b".</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>in case of <code>set_ab_names()</code> and <code>data</code> is a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a>: columns to select (supports tidy selection such as <code>column1:column4</code>), otherwise other arguments passed on to <code><a href="as.ab.html">as.ab()</a></code></p></dd>
 
 
-<dt>only_first</dt>
+<dt id="arg-only-first">only_first<a class="anchor" aria-label="anchor" href="#arg-only-first"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether only the first ATC code must be returned, with giving preference to J0-codes (i.e., the antimicrobial drug group)</p></dd>
 
 
-<dt>administration</dt>
+<dt id="arg-administration">administration<a class="anchor" aria-label="anchor" href="#arg-administration"></a></dt>
 <dd><p>way of administration, either <code>"oral"</code> or <code>"iv"</code></p></dd>
 
 
-<dt>open</dt>
+<dt id="arg-open">open<a class="anchor" aria-label="anchor" href="#arg-open"></a></dt>
 <dd><p>browse the URL using <code><a href="https://rdrr.io/r/utils/browseURL.html" class="external-link">utils::browseURL()</a></code></p></dd>
 
 
-<dt>property</dt>
+<dt id="arg-property">property<a class="anchor" aria-label="anchor" href="#arg-property"></a></dt>
 <dd><p>one of the column names of one of the <a href="antibiotics.html">antibiotics</a> data set: <code>vector_or(colnames(antibiotics), sort = FALSE)</code>.</p></dd>
 
 
-<dt>data</dt>
+<dt id="arg-data">data<a class="anchor" aria-label="anchor" href="#arg-data"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> of which the columns need to be renamed, or a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector of column names</p></dd>
 
 
-<dt>snake_case</dt>
+<dt id="arg-snake-case">snake_case<a class="anchor" aria-label="anchor" href="#arg-snake-case"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether the names should be in so-called <a href="https://en.wikipedia.org/wiki/Snake_case" class="external-link">snake case</a>: in lower case and all spaces/slashes replaced with an underscore (<code>_</code>)</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
 
 <ul><li><p>An <a href="https://rdrr.io/r/base/integer.html" class="external-link">integer</a> in case of <code>ab_cid()</code></p></li>
 <li><p>A named <a href="https://rdrr.io/r/base/list.html" class="external-link">list</a> in case of <code>ab_info()</code> and multiple <code>ab_atc()</code>/<code>ab_synonyms()</code>/<code>ab_tradenames()</code></p></li>
@@ -262,14 +157,14 @@
     </div>
     <div class="section level2">
     <h2 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a></h2>
-    
+
 
 <p>World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: <a href="https://atcddd.fhi.no/atc_ddd_index/" class="external-link">https://atcddd.fhi.no/atc_ddd_index/</a></p>
 <p>European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: <a href="https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm" class="external-link">https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm</a></p>
     </div>
     <div class="section level2">
     <h2 id="reference-data-publicly-available">Reference Data Publicly Available<a class="anchor" aria-label="anchor" href="#reference-data-publicly-available"></a></h2>
-    
+
 
 <p>All data sets in this <code>AMR</code> package (about microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) are publicly and freely available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. We also provide tab-separated plain text files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please visit <a href="https://msberends.github.io/AMR/articles/datasets.html">our website for the download links</a>. The actual files are of course available on <a href="https://github.com/msberends/AMR/tree/main/data-raw" class="external-link">our GitHub repository</a>.</p>
     </div>
@@ -530,7 +425,7 @@
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -544,9 +439,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/ab_selector.html b/reference/ab_selector.html
new file mode 100644
index 000000000..07f8b21e2
--- /dev/null
+++ b/reference/ab_selector.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html">
+  </head>
+</html>
+
diff --git a/reference/ab_synonyms.html b/reference/ab_synonyms.html
new file mode 100644
index 000000000..07fd0ee02
--- /dev/null
+++ b/reference/ab_synonyms.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/ab_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/ab_property.html">
+  </head>
+</html>
+
diff --git a/reference/ab_tradenames.html b/reference/ab_tradenames.html
new file mode 100644
index 000000000..07fd0ee02
--- /dev/null
+++ b/reference/ab_tradenames.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/ab_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/ab_property.html">
+  </head>
+</html>
+
diff --git a/reference/ab_url.html b/reference/ab_url.html
new file mode 100644
index 000000000..07fd0ee02
--- /dev/null
+++ b/reference/ab_url.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/ab_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/ab_property.html">
+  </head>
+</html>
+
diff --git a/reference/add_custom_antimicrobials.html b/reference/add_custom_antimicrobials.html
index 95b7a471d..94542d915 100644
--- a/reference/add_custom_antimicrobials.html
+++ b/reference/add_custom_antimicrobials.html
@@ -1,161 +1,55 @@
 <!DOCTYPE html>
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   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Add Custom Antimicrobials</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/custom_antimicrobials.R" class="external-link"><code>R/custom_antimicrobials.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/custom_antimicrobials.R" class="external-link"><code>R/custom_antimicrobials.R</code></a></small>
       <div class="d-none name"><code>add_custom_antimicrobials.Rd</code></div>
     </div>
 
@@ -172,7 +66,9 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> resembling the <a href="antibiotics.html">antibiotics</a> data set, at least containing columns "ab" and "name"</p></dd>
 
 </dl></div>
@@ -314,7 +210,7 @@
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -328,9 +224,9 @@
 
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diff --git a/reference/add_custom_microorganisms.html b/reference/add_custom_microorganisms.html
index aff926465..960a1049d 100644
--- a/reference/add_custom_microorganisms.html
+++ b/reference/add_custom_microorganisms.html
@@ -1,161 +1,55 @@
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+
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 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Add Custom Microorganisms</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/custom_microorganisms.R" class="external-link"><code>R/custom_microorganisms.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/custom_microorganisms.R" class="external-link"><code>R/custom_microorganisms.R</code></a></small>
       <div class="d-none name"><code>add_custom_microorganisms.Rd</code></div>
     </div>
 
@@ -172,7 +66,9 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> resembling the <a href="microorganisms.html">microorganisms</a> data set, at least containing column "genus" (case-insensitive)</p></dd>
 
 </dl></div>
@@ -337,7 +233,7 @@
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -351,9 +247,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/administrable_iv.html b/reference/administrable_iv.html
new file mode 100644
index 000000000..07f8b21e2
--- /dev/null
+++ b/reference/administrable_iv.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html">
+  </head>
+</html>
+
diff --git a/reference/administrable_per_os.html b/reference/administrable_per_os.html
new file mode 100644
index 000000000..07f8b21e2
--- /dev/null
+++ b/reference/administrable_per_os.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html">
+  </head>
+</html>
+
diff --git a/reference/age.html b/reference/age.html
index e22b8d0e4..1bdede5da 100644
--- a/reference/age.html
+++ b/reference/age.html
@@ -1,161 +1,55 @@
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   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Age in Years of Individuals</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/age.R" class="external-link"><code>R/age.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/age.R" class="external-link"><code>R/age.R</code></a></small>
       <div class="d-none name"><code>age.Rd</code></div>
     </div>
 
@@ -170,31 +64,31 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>date(s), <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> (vectors) will be coerced with <code><a href="https://rdrr.io/r/base/as.POSIXlt.html" class="external-link">as.POSIXlt()</a></code></p></dd>
 
 
-<dt>reference</dt>
+<dt id="arg-reference">reference<a class="anchor" aria-label="anchor" href="#arg-reference"></a></dt>
 <dd><p>reference date(s) (default is today), <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> (vectors) will be coerced with <code><a href="https://rdrr.io/r/base/as.POSIXlt.html" class="external-link">as.POSIXlt()</a></code></p></dd>
 
 
-<dt>exact</dt>
+<dt id="arg-exact">exact<a class="anchor" aria-label="anchor" href="#arg-exact"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether age calculation should be exact, i.e. with decimals. It divides the number of days of <a href="https://en.wikipedia.org/wiki/Year-to-date" class="external-link">year-to-date</a> (YTD) of <code>x</code> by the number of days in the year of <code>reference</code> (either 365 or 366).</p></dd>
 
 
-<dt>na.rm</dt>
+<dt id="arg-na-rm">na.rm<a class="anchor" aria-label="anchor" href="#arg-na-rm"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether missing values should be removed</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>arguments passed on to <code><a href="https://rdrr.io/r/base/as.POSIXlt.html" class="external-link">as.POSIXlt()</a></code>, such as <code>origin</code></p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>An <a href="https://rdrr.io/r/base/integer.html" class="external-link">integer</a> (no decimals) if <code>exact = FALSE</code>, a <a href="https://rdrr.io/r/base/double.html" class="external-link">double</a> (with decimals) otherwise</p>
+    <p>An <a href="https://rdrr.io/r/base/integer.html" class="external-link">integer</a> (no decimals) if <code>exact = FALSE</code>, a <a href="https://rdrr.io/r/base/double.html" class="external-link">double</a> (with decimals) otherwise</p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -222,19 +116,19 @@
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="va">df</span></span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>    birth_date age age_exact age_at_y2k</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 1  1965-12-05  58  58.54918         34</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 2  1980-03-01  44  44.31148         19</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 3  1949-11-01  74  74.64208         50</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 4  1947-02-14  77  77.35519         52</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 5  1940-02-19  84  84.34153         59</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 6  1988-01-10  36  36.45082         11</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 7  1997-08-27  26  26.82240          2</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 8  1978-01-26  46  46.40710         21</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 9  1972-06-17  52  52.01639         27</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 10 1986-08-10  37  37.86885         13</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 1  1965-12-05  58  58.61202         34</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 2  1980-03-01  44  44.37432         19</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 3  1949-11-01  74  74.70492         50</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 4  1947-02-14  77  77.41803         52</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 5  1940-02-19  84  84.40437         59</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 6  1988-01-10  36  36.51366         11</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 7  1997-08-27  26  26.88525          2</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 8  1978-01-26  46  46.46995         21</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 9  1972-06-17  52  52.07923         27</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 10 1986-08-10  37  37.93169         13</span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -248,9 +142,9 @@
 
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-  
 
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+
 
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diff --git a/reference/age_groups.html b/reference/age_groups.html
index d40c18a26..35eaad883 100644
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@@ -1,161 +1,55 @@
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
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       </ul></div>
 
-    
+
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 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Split Ages into Age Groups</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/age.R" class="external-link"><code>R/age.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/age.R" class="external-link"><code>R/age.R</code></a></small>
       <div class="d-none name"><code>age_groups.Rd</code></div>
     </div>
 
@@ -170,25 +64,23 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>age, e.g. calculated with <code><a href="age.html">age()</a></code></p></dd>
 
 
-<dt>split_at</dt>
+<dt id="arg-split-at">split_at<a class="anchor" aria-label="anchor" href="#arg-split-at"></a></dt>
 <dd><p>values to split <code>x</code> at - the default is age groups 0-11, 12-24, 25-54, 55-74 and 75+. See <em>Details</em>.</p></dd>
 
 
-<dt>na.rm</dt>
+<dt id="arg-na-rm">na.rm<a class="anchor" aria-label="anchor" href="#arg-na-rm"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether missing values should be removed</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>Ordered <a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a></p>
-
-
+    <p>Ordered <a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a></p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -263,7 +155,7 @@ The default is to split on young children (0-11), youth (12-24), young adults (2
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -277,9 +169,9 @@ The default is to split on young children (0-11), youth (12-24), young adults (2
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/all_antimicrobials.html b/reference/all_antimicrobials.html
new file mode 100644
index 000000000..f43b48c00
--- /dev/null
+++ b/reference/all_antimicrobials.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
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+  </head>
+</html>
+
diff --git a/reference/aminoglycosides.html b/reference/aminoglycosides.html
new file mode 100644
index 000000000..07f8b21e2
--- /dev/null
+++ b/reference/aminoglycosides.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
+    <meta name="robots" content="noindex">
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+  </head>
+</html>
+
diff --git a/reference/aminopenicillins.html b/reference/aminopenicillins.html
new file mode 100644
index 000000000..07f8b21e2
--- /dev/null
+++ b/reference/aminopenicillins.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
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+
diff --git a/reference/amr_distance_from_row.html b/reference/amr_distance_from_row.html
new file mode 100644
index 000000000..9aab5d00c
--- /dev/null
+++ b/reference/amr_distance_from_row.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mean_amr_distance.html" />
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+
diff --git a/reference/anti_join_microorganisms.html b/reference/anti_join_microorganisms.html
new file mode 100644
index 000000000..0bdfa18c3
--- /dev/null
+++ b/reference/anti_join_microorganisms.html
@@ -0,0 +1,8 @@
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+
diff --git a/reference/antibiogram.html b/reference/antibiogram.html
index 3a7f9cfe3..58b28ae2c 100644
--- a/reference/antibiogram.html
+++ b/reference/antibiogram.html
@@ -1,161 +1,55 @@
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   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted-Incidence Syndromic Combination (WISCA)</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/antibiogram.R" class="external-link"><code>R/antibiogram.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/antibiogram.R" class="external-link"><code>R/antibiogram.R</code></a></small>
       <div class="d-none name"><code>antibiogram.Rd</code></div>
     </div>
 
@@ -182,13 +76,13 @@
 <span>  info <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/interactive.html" class="external-link">interactive</a></span><span class="op">(</span><span class="op">)</span></span>
 <span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for antibiogram</span></span>
+<span><span class="co"># S3 method for class 'antibiogram'</span></span>
 <span><span class="fu"><a href="plot.html">plot</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for antibiogram</span></span>
+<span><span class="co"># S3 method for class 'antibiogram'</span></span>
 <span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for antibiogram</span></span>
+<span><span class="co"># S3 method for class 'antibiogram'</span></span>
 <span><span class="fu">knit_print</span><span class="op">(</span></span>
 <span>  <span class="va">x</span>,</span>
 <span>  italicise <span class="op">=</span> <span class="cn">TRUE</span>,</span>
@@ -199,82 +93,84 @@
 
     <div class="section level2">
     <h2 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a></h2>
-    
+
 <ul><li><p>Klinker KP <em>et al.</em> (2021). <strong>Antimicrobial stewardship and antibiograms: importance of moving beyond traditional antibiograms</strong>. <em>Therapeutic Advances in Infectious Disease</em>, May 5;8:20499361211011373; <a href="https://doi.org/10.1177/20499361211011373" class="external-link">doi:10.1177/20499361211011373</a></p></li>
 <li><p>Barbieri E <em>et al.</em> (2021). <strong>Development of a Weighted-Incidence Syndromic Combination Antibiogram (WISCA) to guide the choice of the empiric antibiotic treatment for urinary tract infection in paediatric patients: a Bayesian approach</strong> <em>Antimicrobial Resistance &amp; Infection Control</em> May 1;10(1):74; <a href="https://doi.org/10.1186/s13756-021-00939-2" class="external-link">doi:10.1186/s13756-021-00939-2</a></p></li>
 <li><p><strong>M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 5th Edition</strong>, 2022, <em>Clinical and Laboratory Standards Institute (CLSI)</em>. <a href="https://clsi.org/standards/products/microbiology/documents/m39/" class="external-link">https://clsi.org/standards/products/microbiology/documents/m39/</a>.</p></li>
 </ul></div>
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> containing at least a column with microorganisms and columns with antibiotic results (class 'sir', see <code><a href="as.sir.html">as.sir()</a></code>)</p></dd>
 
 
-<dt>antibiotics</dt>
+<dt id="arg-antibiotics">antibiotics<a class="anchor" aria-label="anchor" href="#arg-antibiotics"></a></dt>
 <dd><p>vector of any antibiotic name or code (will be evaluated with <code><a href="as.ab.html">as.ab()</a></code>, column name of <code>x</code>, or (any combinations of) <a href="antibiotic_class_selectors.html">antibiotic selectors</a> such as <code><a href="antibiotic_class_selectors.html">aminoglycosides()</a></code> or <code><a href="antibiotic_class_selectors.html">carbapenems()</a></code>. For combination antibiograms, this can also be set to values separated with <code>"+"</code>, such as "TZP+TOB" or "cipro + genta", given that columns resembling such antibiotics exist in <code>x</code>. See <em>Examples</em>.</p></dd>
 
 
-<dt>mo_transform</dt>
-<dd><p>a character to transform microorganism input - must be "name", "shortname", "gramstain", or one of the column names of the <a href="microorganisms.html">microorganisms</a> data set: "mo", "fullname", "status", "kingdom", "phylum", "class", "order", "family", "genus", "species", "subspecies", "rank", "ref", "oxygen_tolerance", "source", "lpsn", "lpsn_parent", "lpsn_renamed_to", "gbif", "gbif_parent", "gbif_renamed_to", "prevalence", or "snomed". Can also be <code>NULL</code> to not transform the input.</p></dd>
+<dt id="arg-mo-transform">mo_transform<a class="anchor" aria-label="anchor" href="#arg-mo-transform"></a></dt>
+<dd><p>a character to transform microorganism input - must be "name", "shortname", "gramstain", or one of the column names of the <a href="microorganisms.html">microorganisms</a> data set: "mo", "fullname", "status", "kingdom", "phylum", "class", "order", "family", "genus", "species", "subspecies", "rank", "ref", "oxygen_tolerance", "source", "lpsn", "lpsn_parent", "lpsn_renamed_to", "mycobank", "mycobank_parent", "mycobank_renamed_to", "gbif", "gbif_parent", "gbif_renamed_to", "prevalence", or "snomed". Can also be <code>NULL</code> to not transform the input.</p></dd>
 
 
-<dt>ab_transform</dt>
+<dt id="arg-ab-transform">ab_transform<a class="anchor" aria-label="anchor" href="#arg-ab-transform"></a></dt>
 <dd><p>a character to transform antibiotic input - must be one of the column names of the <a href="antibiotics.html">antibiotics</a> data set: "ab", "cid", "name", "group", "atc", "atc_group1", "atc_group2", "abbreviations", "synonyms", "oral_ddd", "oral_units", "iv_ddd", "iv_units", or "loinc". Can also be <code>NULL</code> to not transform the input.</p></dd>
 
 
-<dt>syndromic_group</dt>
+<dt id="arg-syndromic-group">syndromic_group<a class="anchor" aria-label="anchor" href="#arg-syndromic-group"></a></dt>
 <dd><p>a column name of <code>x</code>, or values calculated to split rows of <code>x</code>, e.g. by using <code><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse()</a></code> or <code><a href="https://dplyr.tidyverse.org/reference/case_when.html" class="external-link">case_when()</a></code>. See <em>Examples</em>.</p></dd>
 
 
-<dt>add_total_n</dt>
+<dt id="arg-add-total-n">add_total_n<a class="anchor" aria-label="anchor" href="#arg-add-total-n"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether total available numbers per pathogen should be added to the table (default is <code>TRUE</code>). This will add the lowest and highest number of available isolate per antibiotic (e.g, if for <em>E. coli</em> 200 isolates are available for ciprofloxacin and 150 for amoxicillin, the returned number will be "150-200").</p></dd>
 
 
-<dt>only_all_tested</dt>
+<dt id="arg-only-all-tested">only_all_tested<a class="anchor" aria-label="anchor" href="#arg-only-all-tested"></a></dt>
 <dd><p>(for combination antibiograms): a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate that isolates must be tested for all antibiotics, see <em>Details</em></p></dd>
 
 
-<dt>digits</dt>
+<dt id="arg-digits">digits<a class="anchor" aria-label="anchor" href="#arg-digits"></a></dt>
 <dd><p>number of digits to use for rounding</p></dd>
 
 
-<dt>col_mo</dt>
+<dt id="arg-col-mo">col_mo<a class="anchor" aria-label="anchor" href="#arg-col-mo"></a></dt>
 <dd><p>column name of the names or codes of the microorganisms (see <code><a href="as.mo.html">as.mo()</a></code>) - the default is the first column of class <code><a href="as.mo.html">mo</a></code>. Values will be coerced using <code><a href="as.mo.html">as.mo()</a></code>.</p></dd>
 
 
-<dt>language</dt>
+<dt id="arg-language">language<a class="anchor" aria-label="anchor" href="#arg-language"></a></dt>
 <dd><p>language to translate text, which defaults to the system language (see <code><a href="translate.html">get_AMR_locale()</a></code>)</p></dd>
 
 
-<dt>minimum</dt>
+<dt id="arg-minimum">minimum<a class="anchor" aria-label="anchor" href="#arg-minimum"></a></dt>
 <dd><p>the minimum allowed number of available (tested) isolates. Any isolate count lower than <code>minimum</code> will return <code>NA</code> with a warning. The default number of <code>30</code> isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see <em>Source</em>.</p></dd>
 
 
-<dt>combine_SI</dt>
+<dt id="arg-combine-si">combine_SI<a class="anchor" aria-label="anchor" href="#arg-combine-si"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether all susceptibility should be determined by results of either S or I, instead of only S (default is <code>TRUE</code>)</p></dd>
 
 
-<dt>sep</dt>
+<dt id="arg-sep">sep<a class="anchor" aria-label="anchor" href="#arg-sep"></a></dt>
 <dd><p>a separating character for antibiotic columns in combination antibiograms</p></dd>
 
 
-<dt>info</dt>
+<dt id="arg-info">info<a class="anchor" aria-label="anchor" href="#arg-info"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate info should be printed - the default is <code>TRUE</code> only in interactive mode</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>when used in <a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">R Markdown or Quarto</a>: arguments passed on to <code><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">knitr::kable()</a></code> (otherwise, has no use)</p></dd>
 
 
-<dt>object</dt>
+<dt id="arg-object">object<a class="anchor" aria-label="anchor" href="#arg-object"></a></dt>
 <dd><p>an <code>antibiogram()</code> object</p></dd>
 
 
-<dt>italicise</dt>
+<dt id="arg-italicise">italicise<a class="anchor" aria-label="anchor" href="#arg-italicise"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether the microorganism names in the <a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">knitr</a> table should be made italic, using <code><a href="italicise_taxonomy.html">italicise_taxonomy()</a></code>.</p></dd>
 
 
-<dt>na</dt>
+<dt id="arg-na">na<a class="anchor" aria-label="anchor" href="#arg-na"></a></dt>
 <dd><p>character to use for showing <code>NA</code> values</p></dd>
 
 </dl></div>
@@ -370,7 +266,7 @@
 <span class="r-msg co"><span class="r-pr">#&gt;</span> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB'</span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin)</span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem)</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 10 × 7</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An Antibiogram: 10 × 7</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>    `Pathogen (N min-max)`   AMK   GEN   IPM   KAN   MEM   TOB</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>  <span style="color: #BCBCBC;">*</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                  <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> CoNS (43-309)              0    86    52     0    52    22</span>
@@ -383,6 +279,8 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> S. epidermidis (8-163)     0    79    <span style="color: #BB0000;">NA</span>     0    <span style="color: #BB0000;">NA</span>    51</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> S. hominis (3-80)         <span style="color: #BB0000;">NA</span>    92    <span style="color: #BB0000;">NA</span>    <span style="color: #BB0000;">NA</span>    <span style="color: #BB0000;">NA</span>    85</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> S. pneumoniae (11-117)     0     0    <span style="color: #BB0000;">NA</span>     0    <span style="color: #BB0000;">NA</span>     0</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram,</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram</span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="fu">antibiogram</span><span class="op">(</span><span class="va">example_isolates</span>,</span></span>
 <span class="r-in"><span>  antibiotics <span class="op">=</span> <span class="fu"><a href="antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>,</span></span>
@@ -391,11 +289,13 @@
 <span class="r-in"><span><span class="op">)</span></span></span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB'</span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin)</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 2 × 5</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An Antibiogram: 2 × 5</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   `Pathogen (N min-max)`   J01GB01 J01GB03 J01GB04 J01GB06</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">*</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                      <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> Gram-negative (35-686)        96      96       0      98</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> Gram-positive (436-1170)      34      63       0       0</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram,</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram</span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="fu">antibiogram</span><span class="op">(</span><span class="va">example_isolates</span>,</span></span>
 <span class="r-in"><span>  antibiotics <span class="op">=</span> <span class="fu"><a href="antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span>,</span></span>
@@ -403,7 +303,7 @@
 <span class="r-in"><span>  mo_transform <span class="op">=</span> <span class="st">"name"</span></span></span>
 <span class="r-in"><span><span class="op">)</span></span></span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem)</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 5 × 3</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An Antibiogram: 5 × 3</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   `Pathogen (N min-max)`                           Imipenem Meropenem</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">*</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                                               <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> Coagulase-negative Staphylococcus (CoNS) (48-48)       52        52</span>
@@ -411,6 +311,8 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> Escherichia coli (418-422)                            100       100</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> Klebsiella pneumoniae (51-53)                         100       100</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span> Proteus mirabilis (27-32)                              94        <span style="color: #BB0000;">NA</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram,</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram</span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># Combined antibiogram -------------------------------------------------</span></span></span>
@@ -420,11 +322,13 @@
 <span class="r-in"><span>  antibiotics <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"TZP"</span>, <span class="st">"TZP+TOB"</span>, <span class="st">"TZP+GEN"</span><span class="op">)</span>,</span></span>
 <span class="r-in"><span>  mo_transform <span class="op">=</span> <span class="st">"gramstain"</span></span></span>
 <span class="r-in"><span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 2 × 4</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An Antibiogram: 2 × 4</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   `Pathogen (N min-max)`     TZP `TZP + GEN` `TZP + TOB`</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">*</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                    <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>       <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>       <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> Gram-negative (641-693)     88          99          98</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> Gram-positive (345-1044)    86          98          95</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram,</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram</span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># names of antibiotics do not need to resemble columns exactly:</span></span></span>
 <span class="r-in"><span><span class="fu">antibiogram</span><span class="op">(</span><span class="va">example_isolates</span>,</span></span>
@@ -433,11 +337,13 @@
 <span class="r-in"><span>  ab_transform <span class="op">=</span> <span class="st">"name"</span>,</span></span>
 <span class="r-in"><span>  sep <span class="op">=</span> <span class="st">" &amp; "</span></span></span>
 <span class="r-in"><span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 2 × 3</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An Antibiogram: 2 × 3</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   `Pathogen (N min-max)`  Ciprofloxacin `Ciprofloxacin &amp; Gentamicin`</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">*</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                           <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>                        <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> Gram-negative (684-694)            91                           99</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> Gram-positive (724-847)            77                           93</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram,</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram</span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># Syndromic antibiogram ------------------------------------------------</span></span></span>
@@ -450,7 +356,7 @@
 <span class="r-msg co"><span class="r-pr">#&gt;</span> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB'</span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin)</span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem)</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 14 × 8</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An Antibiogram: 14 × 8</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>    `Syndromic Group` `Pathogen (N min-max)`   AMK   GEN   IPM   KAN   MEM   TOB</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>  <span style="color: #BCBCBC;">*</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>             <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                  <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> Clinical          CoNS (23-205)             <span style="color: #BB0000;">NA</span>    89    57    <span style="color: #BB0000;">NA</span>    57    26</span>
@@ -467,6 +373,8 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">12</span> Clinical          S. hominis (1-45)         <span style="color: #BB0000;">NA</span>    96    <span style="color: #BB0000;">NA</span>    <span style="color: #BB0000;">NA</span>    <span style="color: #BB0000;">NA</span>    94</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">13</span> Clinical          S. pneumoniae (5-78)       0     0    <span style="color: #BB0000;">NA</span>     0    <span style="color: #BB0000;">NA</span>     0</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">14</span> ICU               S. pneumoniae (5-30)       0     0    <span style="color: #BB0000;">NA</span>     0    <span style="color: #BB0000;">NA</span>     0</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram,</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram</span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># now define a data set with only E. coli</span></span></span>
 <span class="r-in"><span><span class="va">ex1</span> <span class="op">&lt;-</span> <span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html" class="external-link">which</a></span><span class="op">(</span><span class="fu"><a href="mo_property.html">mo_genus</a></span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Escherichia"</span><span class="op">)</span>, <span class="op">]</span></span></span>
@@ -484,11 +392,13 @@
 <span class="r-in"><span><span class="op">)</span></span></span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB'</span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin)</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 2 × 5</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An Antibiogram: 2 × 5</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   `Grupo sindrómico` `Patógeno (N min-max)` Amikacina Gentamicina Tobramicina</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">*</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>              <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                      <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>       <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>       <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> No UCI             E. coli (0-325)              100          98          98</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> UCI                E. coli (0-137)              100          99          96</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram,</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram</span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># Weighted-incidence syndromic combination antibiogram (WISCA) ---------</span></span></span>
@@ -503,13 +413,15 @@
 <span class="r-in"><span>  <span class="st">"WISCA Group 1"</span>, <span class="st">"WISCA Group 2"</span></span></span>
 <span class="r-in"><span>  <span class="op">)</span></span></span>
 <span class="r-in"><span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 4 × 6</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># An Antibiogram: 4 × 6</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   `Syndromic Group` `Pathogen (N min-max)`    AMC `AMC + CIP`   TZP `TZP + TOB`</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">*</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>             <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>       <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>       <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> WISCA Group 1     Gram-negative (261-285)    76          95    89          99</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> WISCA Group 2     Gram-negative (380-442)    76          98    88          98</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> WISCA Group 1     Gram-positive (123-406)    76          89    81          95</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> WISCA Group 2     Gram-positive (222-732)    76          89    88          95</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram,</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram</span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># Print the output for R Markdown / Quarto -----------------------------</span></span></span>
@@ -563,7 +475,7 @@
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -577,9 +489,9 @@
 
     </footer></div>
 
-  
 
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+
+
 
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diff --git a/reference/antibiotic_class_selectors.html b/reference/antibiotic_class_selectors.html
index 090bb0b03..4a316d4ad 100644
--- a/reference/antibiotic_class_selectors.html
+++ b/reference/antibiotic_class_selectors.html
@@ -1,163 +1,57 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content='These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class or group (according to the antibiotics data set), without the need to define the columns or antibiotic abbreviations.
-In short, if you have a column name that resembles an antimicrobial drug, it will be picked up by any of these functions that matches its pharmaceutical class: "cefazolin", "kefzol", "CZO" and "J01DB04" will all be picked up by cephalosporins().'><title>Antibiotic Selectors — antibiotic_class_selectors • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Antibiotic Selectors — antibiotic_class_selectors"><meta property="og:description" content='These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class or group (according to the antibiotics data set), without the need to define the columns or antibiotic abbreviations.
-In short, if you have a column name that resembles an antimicrobial drug, it will be picked up by any of these functions that matches its pharmaceutical class: "cefazolin", "kefzol", "CZO" and "J01DB04" will all be picked up by cephalosporins().'><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Antibiotic Selectors — antibiotic_class_selectors • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Antibiotic Selectors — antibiotic_class_selectors"><meta name="description" content='These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class or group (according to the antibiotics data set), without the need to define the columns or antibiotic abbreviations.
+In short, if you have a column name that resembles an antimicrobial drug, it will be picked up by any of these functions that matches its pharmaceutical class: "cefazolin", "kefzol", "CZO" and "J01DB04" will all be picked up by cephalosporins().'><meta property="og:description" content='These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class or group (according to the antibiotics data set), without the need to define the columns or antibiotic abbreviations.
+In short, if you have a column name that resembles an antimicrobial drug, it will be picked up by any of these functions that matches its pharmaceutical class: "cefazolin", "kefzol", "CZO" and "J01DB04" will all be picked up by cephalosporins().'><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"></head><body>
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   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Antibiotic Selectors</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/ab_selectors.R" class="external-link"><code>R/ab_selectors.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/ab_selectors.R" class="external-link"><code>R/ab_selectors.R</code></a></small>
       <div class="d-none name"><code>antibiotic_class_selectors.Rd</code></div>
     </div>
 
@@ -240,41 +134,39 @@ In short, if you have a column name that resembles an antimicrobial drug, it wil
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>ab_class</dt>
+
+
+<dl><dt id="arg-ab-class">ab_class<a class="anchor" aria-label="anchor" href="#arg-ab-class"></a></dt>
 <dd><p>an antimicrobial class or a part of it, such as <code>"carba"</code> and <code>"carbapenems"</code>. The columns <code>group</code>, <code>atc_group1</code> and <code>atc_group2</code> of the <a href="antibiotics.html">antibiotics</a> data set will be searched (case-insensitive) for this value.</p></dd>
 
 
-<dt>only_sir_columns</dt>
+<dt id="arg-only-sir-columns">only_sir_columns<a class="anchor" aria-label="anchor" href="#arg-only-sir-columns"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether only columns of class <code>sir</code> must be selected (default is <code>FALSE</code>), see <code><a href="as.sir.html">as.sir()</a></code></p></dd>
 
 
-<dt>only_treatable</dt>
+<dt id="arg-only-treatable">only_treatable<a class="anchor" aria-label="anchor" href="#arg-only-treatable"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether antimicrobial drugs should be excluded that are only for laboratory tests (default is <code>TRUE</code>), such as gentamicin-high (<code>GEH</code>) and imipenem/EDTA (<code>IPE</code>)</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>ignored, only in place to allow future extensions</p></dd>
 
 
-<dt>filter</dt>
+<dt id="arg-filter">filter<a class="anchor" aria-label="anchor" href="#arg-filter"></a></dt>
 <dd><p>an <a href="https://rdrr.io/r/base/expression.html" class="external-link">expression</a> to be evaluated in the <a href="antibiotics.html">antibiotics</a> data set, such as <code>name %like% "trim"</code></p></dd>
 
 
-<dt>col_mo</dt>
+<dt id="arg-col-mo">col_mo<a class="anchor" aria-label="anchor" href="#arg-col-mo"></a></dt>
 <dd><p>column name of the names or codes of the microorganisms (see <code><a href="as.mo.html">as.mo()</a></code>) - the default is the first column of class <code><a href="as.mo.html">mo</a></code>. Values will be coerced using <code><a href="as.mo.html">as.mo()</a></code>.</p></dd>
 
 
-<dt>version_expertrules</dt>
+<dt id="arg-version-expertrules">version_expertrules<a class="anchor" aria-label="anchor" href="#arg-version-expertrules"></a></dt>
 <dd><p>the version number to use for the EUCAST Expert Rules and Intrinsic Resistance guideline. Can be "3.3", "3.2", or "3.1".</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>(internally) a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector of column names, with additional class <code>"ab_selector"</code></p>
-
-
+    <p>(internally) a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector of column names, with additional class <code>"ab_selector"</code></p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -287,7 +179,7 @@ In short, if you have a column name that resembles an antimicrobial drug, it wil
     </div>
     <div class="section level2">
     <h2 id="full-list-of-supported-antibiotic-classes">Full list of supported (antibiotic) classes<a class="anchor" aria-label="anchor" href="#full-list-of-supported-antibiotic-classes"></a></h2>
-    
+
 
 <ul><li><p><code>aminoglycosides()</code> can select: <br> amikacin (AMK), amikacin/fosfomycin (AKF), apramycin (APR), arbekacin (ARB), astromicin (AST), bekanamycin (BEK), dibekacin (DKB), framycetin (FRM), gentamicin (GEN), gentamicin-high (GEH), habekacin (HAB), hygromycin (HYG), isepamicin (ISE), kanamycin (KAN), kanamycin-high (KAH), kanamycin/cephalexin (KAC), micronomicin (MCR), neomycin (NEO), netilmicin (NET), pentisomicin (PIM), plazomicin (PLZ), propikacin (PKA), ribostamycin (RST), sisomicin (SIS), streptoduocin (STR), streptomycin (STR1), streptomycin-high (STH), tobramycin (TOB), and tobramycin-high (TOH)</p></li>
 <li><p><code>aminopenicillins()</code> can select: <br> amoxicillin (AMX) and ampicillin (AMP)</p></li>
@@ -319,7 +211,7 @@ In short, if you have a column name that resembles an antimicrobial drug, it wil
 </ul></div>
     <div class="section level2">
     <h2 id="reference-data-publicly-available">Reference Data Publicly Available<a class="anchor" aria-label="anchor" href="#reference-data-publicly-available"></a></h2>
-    
+
 
 <p>All data sets in this <code>AMR</code> package (about microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) are publicly and freely available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. We also provide tab-separated plain text files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please visit <a href="https://msberends.github.io/AMR/articles/datasets.html">our website for the download links</a>. The actual files are of course available on <a href="https://github.com/msberends/AMR/tree/main/data-raw" class="external-link">our GitHub repository</a>.</p>
     </div>
@@ -1165,7 +1057,7 @@ In short, if you have a column name that resembles an antimicrobial drug, it wil
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -1179,9 +1071,9 @@ In short, if you have a column name that resembles an antimicrobial drug, it wil
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/antibiotics.html b/reference/antibiotics.html
index 74a13ef1a..49a7bef91 100644
--- a/reference/antibiotics.html
+++ b/reference/antibiotics.html
@@ -1,161 +1,55 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Two data sets containing all antibiotics/antimycotics and antivirals. Use as.ab() or one of the ab_* functions to retrieve values from the antibiotics data set. Three identifiers are included in this data set: an antibiotic ID (ab, primarily used in this package) as defined by WHONET/EARS-Net, an ATC code (atc) as defined by the WHO, and a Compound ID (cid) as found in PubChem. Other properties in this data set are derived from one or more of these codes. Note that some drugs have multiple ATC codes."><title>Data Sets with 605 Antimicrobial Drugs — antibiotics • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Data Sets with 605 Antimicrobial Drugs — antibiotics"><meta property="og:description" content="Two data sets containing all antibiotics/antimycotics and antivirals. Use as.ab() or one of the ab_* functions to retrieve values from the antibiotics data set. Three identifiers are included in this data set: an antibiotic ID (ab, primarily used in this package) as defined by WHONET/EARS-Net, an ATC code (atc) as defined by the WHO, and a Compound ID (cid) as found in PubChem. Other properties in this data set are derived from one or more of these codes. Note that some drugs have multiple ATC codes."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Data Sets with 605 Antimicrobial Drugs</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/data.R" class="external-link"><code>R/data.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/data.R" class="external-link"><code>R/data.R</code></a></small>
       <div class="d-none name"><code>antibiotics.Rd</code></div>
     </div>
 
@@ -172,13 +66,13 @@
 
     <div class="section level2">
     <h2 id="format">Format<a class="anchor" aria-label="anchor" href="#format"></a></h2>
-    
+
 <div class="section">
 <h3 id="for-the-antibiotics-data-set-a-tibble-with-observations-and-variables-">For the antibiotics data set: a <a href="https://tibble.tidyverse.org/reference/tibble.html" class="external-link">tibble</a> with 485 observations and 14 variables:<a class="anchor" aria-label="anchor" href="#for-the-antibiotics-data-set-a-tibble-with-observations-and-variables-"></a></h3>
 
-<ul><li><p><code>ab</code><br> Antibiotic ID as used in this package (such as <code>AMC</code>), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available. <em>This is a unique identifier.</em></p></li>
-<li><p><code>cid</code><br> Compound ID as found in PubChem. <em>This is a unique identifier.</em></p></li>
-<li><p><code>name</code><br> Official name as used by WHONET/EARS-Net or the WHO. <em>This is a unique identifier.</em></p></li>
+<ul><li><p><code>ab</code><br> Antibiotic ID as used in this package (such as <code>AMC</code>), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available. <em><strong>This is a unique identifier.</strong></em></p></li>
+<li><p><code>cid</code><br> Compound ID as found in PubChem. <em><strong>This is a unique identifier.</strong></em></p></li>
+<li><p><code>name</code><br> Official name as used by WHONET/EARS-Net or the WHO. <em><strong>This is a unique identifier.</strong></em></p></li>
 <li><p><code>group</code><br> A short and concise group name, based on WHONET and WHOCC definitions</p></li>
 <li><p><code>atc</code><br> ATC codes (Anatomical Therapeutic Chemical) as defined by the WHOCC, like <code>J01CR02</code></p></li>
 <li><p><code>atc_group1</code><br> Official pharmacological subgroup (3rd level ATC code) as defined by the WHOCC, like <code>"Macrolides, lincosamides and streptogramins"</code></p></li>
@@ -195,10 +89,10 @@
 <div class="section">
 <h3 id="for-the-antivirals-data-set-a-tibble-with-observations-and-variables-">For the antivirals data set: a <a href="https://tibble.tidyverse.org/reference/tibble.html" class="external-link">tibble</a> with 120 observations and 11 variables:<a class="anchor" aria-label="anchor" href="#for-the-antivirals-data-set-a-tibble-with-observations-and-variables-"></a></h3>
 
-<ul><li><p><code>av</code><br> Antiviral ID as used in this package (such as <code>ACI</code>), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available. <em>This is a unique identifier.</em> Combinations are codes that contain a <code>+</code> to indicate this, such as <code>ATA+COBI</code> for atazanavir/cobicistat.</p></li>
-<li><p><code>name</code><br> Official name as used by WHONET/EARS-Net or the WHO. <em>This is a unique identifier.</em></p></li>
+<ul><li><p><code>av</code><br> Antiviral ID as used in this package (such as <code>ACI</code>), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available. <em><strong>This is a unique identifier.</strong></em> Combinations are codes that contain a <code>+</code> to indicate this, such as <code>ATA+COBI</code> for atazanavir/cobicistat.</p></li>
+<li><p><code>name</code><br> Official name as used by WHONET/EARS-Net or the WHO. <em><strong>This is a unique identifier.</strong></em></p></li>
 <li><p><code>atc</code><br> ATC codes (Anatomical Therapeutic Chemical) as defined by the WHOCC</p></li>
-<li><p><code>cid</code><br> Compound ID as found in PubChem. <em>This is a unique identifier.</em></p></li>
+<li><p><code>cid</code><br> Compound ID as found in PubChem. <em><strong>This is a unique identifier.</strong></em></p></li>
 <li><p><code>atc_group</code><br> Official pharmacological subgroup (3rd level ATC code) as defined by the WHOCC</p></li>
 <li><p><code>synonyms</code><br> Synonyms (often trade names) of a drug, as found in PubChem based on their compound ID</p></li>
 <li><p><code>oral_ddd</code><br> Defined Daily Dose (DDD), oral treatment</p></li>
@@ -212,7 +106,7 @@
     </div>
     <div class="section level2">
     <h2 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a></h2>
-    
+
 <ul><li><p>World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology (WHOCC): <a href="https://atcddd.fhi.no/atc_ddd_index/" class="external-link">https://atcddd.fhi.no/atc_ddd_index/</a></p></li>
 <li><p>Logical Observation Identifiers Names and Codes (LOINC), Version 2.76 (18 September, 2023). Accessed from <a href="https://loinc.org" class="external-link">https://loinc.org</a> on October 19th, 2023.</p></li>
 <li><p>European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: <a href="https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm" class="external-link">https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm</a></p></li>
@@ -230,7 +124,7 @@
     </div>
     <div class="section level2">
     <h2 id="whocc">WHOCC<a class="anchor" aria-label="anchor" href="#whocc"></a></h2>
-    
+
 
 <p>This package contains <strong>all ~550 antibiotic, antimycotic and antiviral drugs</strong> and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, <a href="https://atcddd.fhi.no" class="external-link">https://atcddd.fhi.no</a>) and the Pharmaceuticals Community Register of the European Commission (<a href="https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm" class="external-link">https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm</a>).</p>
 <p>These have become the gold standard for international drug utilisation monitoring and research.</p>
@@ -279,7 +173,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 2 more variables: iv_units &lt;chr&gt;, loinc &lt;list&gt;</span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -293,9 +187,9 @@
 
     </footer></div>
 
-  
 
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+
 
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diff --git a/reference/antifungals.html b/reference/antifungals.html
new file mode 100644
index 000000000..07f8b21e2
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+++ b/reference/antifungals.html
@@ -0,0 +1,8 @@
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+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html">
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diff --git a/reference/antimicrobials_equal.html b/reference/antimicrobials_equal.html
new file mode 100644
index 000000000..f43b48c00
--- /dev/null
+++ b/reference/antimicrobials_equal.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/key_antimicrobials.html" />
+    <meta name="robots" content="noindex">
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diff --git a/reference/antimycobacterials.html b/reference/antimycobacterials.html
new file mode 100644
index 000000000..07f8b21e2
--- /dev/null
+++ b/reference/antimycobacterials.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
+    <meta name="robots" content="noindex">
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+  </head>
+</html>
+
diff --git a/reference/antivirals.html b/reference/antivirals.html
new file mode 100644
index 000000000..932de6601
--- /dev/null
+++ b/reference/antivirals.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotics.html" />
+    <meta name="robots" content="noindex">
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+  </head>
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+
diff --git a/reference/as.ab.html b/reference/as.ab.html
index f681180f9..12ac04ad6 100644
--- a/reference/as.ab.html
+++ b/reference/as.ab.html
@@ -1,161 +1,55 @@
 <!DOCTYPE html>
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to"><li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul></li>
 <li class="nav-item dropdown">
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
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       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Transform Input to an Antibiotic ID</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/ab.R" class="external-link"><code>R/ab.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/ab.R" class="external-link"><code>R/ab.R</code></a></small>
       <div class="d-none name"><code>as.ab.Rd</code></div>
     </div>
 
@@ -172,31 +66,27 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector to determine to antibiotic ID</p></dd>
 
 
-<dt>flag_multiple_results</dt>
+<dt id="arg-flag-multiple-results">flag_multiple_results<a class="anchor" aria-label="anchor" href="#arg-flag-multiple-results"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether a note should be printed to the console that probably more than one antibiotic drug code or name can be retrieved from a single input value.</p></dd>
 
 
-<dt>info</dt>
+<dt id="arg-info">info<a class="anchor" aria-label="anchor" href="#arg-info"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether a progress bar should be printed - the default is <code>TRUE</code> only in interactive mode</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>arguments passed on to internal functions</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a></p>
-<p></p>
-<p><a href="https://rdrr.io/r/base/vector.html" class="external-link">vector</a> with additional class <code>ab</code></p>
-
-
+    <p>A <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> <a href="https://rdrr.io/r/base/vector.html" class="external-link">vector</a> with additional class <code>ab</code></p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -211,14 +101,14 @@
     </div>
     <div class="section level2">
     <h2 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a></h2>
-    
+
 
 <p>World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: <a href="https://atcddd.fhi.no/atc_ddd_index/" class="external-link">https://atcddd.fhi.no/atc_ddd_index/</a></p>
 <p>European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: <a href="https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm" class="external-link">https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm</a></p>
     </div>
     <div class="section level2">
     <h2 id="whocc">WHOCC<a class="anchor" aria-label="anchor" href="#whocc"></a></h2>
-    
+
 
 <p>This package contains <strong>all ~550 antibiotic, antimycotic and antiviral drugs</strong> and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, <a href="https://atcddd.fhi.no" class="external-link">https://atcddd.fhi.no</a>) and the Pharmaceuticals Community Register of the European Commission (<a href="https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm" class="external-link">https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm</a>).</p>
 <p>These have become the gold standard for international drug utilisation monitoring and research.</p>
@@ -227,7 +117,7 @@
     </div>
     <div class="section level2">
     <h2 id="reference-data-publicly-available">Reference Data Publicly Available<a class="anchor" aria-label="anchor" href="#reference-data-publicly-available"></a></h2>
-    
+
 
 <p>All data sets in this <code>AMR</code> package (about microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) are publicly and freely available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. We also provide tab-separated plain text files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please visit <a href="https://msberends.github.io/AMR/articles/datasets.html">our website for the download links</a>. The actual files are of course available on <a href="https://github.com/msberends/AMR/tree/main/data-raw" class="external-link">our GitHub repository</a>.</p>
     </div>
@@ -319,7 +209,7 @@
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -333,9 +223,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/as.av.html b/reference/as.av.html
index 1f88e4a8f..491a0736b 100644
--- a/reference/as.av.html
+++ b/reference/as.av.html
@@ -1,161 +1,55 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Use this function to determine the antiviral drug code of one or more antiviral drugs. The data set antivirals will be searched for abbreviations, official names and synonyms (brand names)."><title>Transform Input to an Antiviral Drug ID — as.av • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Transform Input to an Antiviral Drug ID — as.av"><meta property="og:description" content="Use this function to determine the antiviral drug code of one or more antiviral drugs. The data set antivirals will be searched for abbreviations, official names and synonyms (brand names)."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9061</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9063</small>
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to"><li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul></li>
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--with-other-pkgs">
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-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--with-other-pkgs">
-    <a class="dropdown-item" href="../articles/other_pkg.html">
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-      AMR &amp; dplyr/tidyverse
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; data.table
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-      AMR &amp; tidymodels
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-      <span class="fa fa-layer-group"></span>
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-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
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-    <span class="fab fa fab fa-github"></span>
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Transform Input to an Antiviral Drug ID</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/av.R" class="external-link"><code>R/av.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/av.R" class="external-link"><code>R/av.R</code></a></small>
       <div class="d-none name"><code>as.av.Rd</code></div>
     </div>
 
@@ -172,31 +66,27 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector to determine to antiviral drug ID</p></dd>
 
 
-<dt>flag_multiple_results</dt>
+<dt id="arg-flag-multiple-results">flag_multiple_results<a class="anchor" aria-label="anchor" href="#arg-flag-multiple-results"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether a note should be printed to the console that probably more than one antiviral drug code or name can be retrieved from a single input value.</p></dd>
 
 
-<dt>info</dt>
+<dt id="arg-info">info<a class="anchor" aria-label="anchor" href="#arg-info"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether a progress bar should be printed - the default is <code>TRUE</code> only in interactive mode</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>arguments passed on to internal functions</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a></p>
-<p></p>
-<p><a href="https://rdrr.io/r/base/vector.html" class="external-link">vector</a> with additional class <code><a href="as.ab.html">ab</a></code></p>
-
-
+    <p>A <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> <a href="https://rdrr.io/r/base/vector.html" class="external-link">vector</a> with additional class <code><a href="as.ab.html">ab</a></code></p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -210,14 +100,14 @@
     </div>
     <div class="section level2">
     <h2 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a></h2>
-    
+
 
 <p>World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: <a href="https://atcddd.fhi.no/atc_ddd_index/" class="external-link">https://atcddd.fhi.no/atc_ddd_index/</a></p>
 <p>European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: <a href="https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm" class="external-link">https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm</a></p>
     </div>
     <div class="section level2">
     <h2 id="whocc">WHOCC<a class="anchor" aria-label="anchor" href="#whocc"></a></h2>
-    
+
 
 <p>This package contains <strong>all ~550 antibiotic, antimycotic and antiviral drugs</strong> and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, <a href="https://atcddd.fhi.no" class="external-link">https://atcddd.fhi.no</a>) and the Pharmaceuticals Community Register of the European Commission (<a href="https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm" class="external-link">https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm</a>).</p>
 <p>These have become the gold standard for international drug utilisation monitoring and research.</p>
@@ -226,7 +116,7 @@
     </div>
     <div class="section level2">
     <h2 id="reference-data-publicly-available">Reference Data Publicly Available<a class="anchor" aria-label="anchor" href="#reference-data-publicly-available"></a></h2>
-    
+
 
 <p>All data sets in this <code>AMR</code> package (about microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) are publicly and freely available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. We also provide tab-separated plain text files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please visit <a href="https://msberends.github.io/AMR/articles/datasets.html">our website for the download links</a>. The actual files are of course available on <a href="https://github.com/msberends/AMR/tree/main/data-raw" class="external-link">our GitHub repository</a>.</p>
     </div>
@@ -281,7 +171,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] "Aciclovir"</span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -295,9 +185,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/as.disk.html b/reference/as.disk.html
index de46ba2ef..ca170fdaf 100644
--- a/reference/as.disk.html
+++ b/reference/as.disk.html
@@ -1,161 +1,55 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="This transforms a vector to a new class disk, which is a disk diffusion growth zone size (around an antibiotic disk) in millimetres between 6 and 50."><title>Transform Input to Disk Diffusion Diameters — as.disk • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Transform Input to Disk Diffusion Diameters — as.disk"><meta property="og:description" content="This transforms a vector to a new class disk, which is a disk diffusion growth zone size (around an antibiotic disk) in millimetres between 6 and 50."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Transform Input to Disk Diffusion Diameters — as.disk • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Transform Input to Disk Diffusion Diameters — as.disk"><meta name="description" content="This transforms a vector to a new class disk, which is a disk diffusion growth zone size (around an antibiotic disk) in millimetres between 6 and 50."><meta property="og:description" content="This transforms a vector to a new class disk, which is a disk diffusion growth zone size (around an antibiotic disk) in millimetres between 6 and 50."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"></head><body>
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+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
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-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9061</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9063</small>
+
 
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+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
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+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul></li>
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
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+
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 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Transform Input to Disk Diffusion Diameters</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/disk.R" class="external-link"><code>R/disk.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/disk.R" class="external-link"><code>R/disk.R</code></a></small>
       <div class="d-none name"><code>as.disk.Rd</code></div>
     </div>
 
@@ -178,21 +72,19 @@
     </div>
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>vector</p></dd>
 
 
-<dt>na.rm</dt>
+<dt id="arg-na-rm">na.rm<a class="anchor" aria-label="anchor" href="#arg-na-rm"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> indicating whether missing values should be removed</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>An <a href="https://rdrr.io/r/base/integer.html" class="external-link">integer</a> with additional class <code>disk</code></p>
-
-
+    <p>An <a href="https://rdrr.io/r/base/integer.html" class="external-link">integer</a> with additional class <code>disk</code></p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -267,7 +159,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> 1 Escherichia coli   S &lt;NA&gt;   S   S</span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -281,9 +173,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/as.mic.html b/reference/as.mic.html
index 8a9805ccf..3596940f9 100644
--- a/reference/as.mic.html
+++ b/reference/as.mic.html
@@ -1,161 +1,55 @@
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 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Transform Input to Minimum Inhibitory Concentrations (MIC)</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/mic.R" class="external-link"><code>R/mic.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/mic.R" class="external-link"><code>R/mic.R</code></a></small>
       <div class="d-none name"><code>as.mic.Rd</code></div>
     </div>
 
@@ -173,41 +67,41 @@
 <span></span>
 <span><span class="fu">rescale_mic</span><span class="op">(</span><span class="va">x</span>, <span class="va">mic_range</span>, keep_operators <span class="op">=</span> <span class="st">"edges"</span>, as.mic <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for mic</span></span>
+<span><span class="co"># S3 method for class 'mic'</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/droplevels.html" class="external-link">droplevels</a></span><span class="op">(</span><span class="va">x</span>, as.mic <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
     </div>
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> or <a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a> vector</p></dd>
 
 
-<dt>na.rm</dt>
+<dt id="arg-na-rm">na.rm<a class="anchor" aria-label="anchor" href="#arg-na-rm"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> indicating whether missing values should be removed</p></dd>
 
 
-<dt>keep_operators</dt>
+<dt id="arg-keep-operators">keep_operators<a class="anchor" aria-label="anchor" href="#arg-keep-operators"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> specifying how to handle operators (such as <code>&gt;</code> and <code>&lt;=</code>) in the input. Accepts one of three values: <code>"all"</code> (or <code>TRUE</code>) to keep all operators, <code>"none"</code> (or <code>FALSE</code>) to remove all operators, or <code>"edges"</code> to keep operators only at both ends of the range.</p></dd>
 
 
-<dt>mic_range</dt>
+<dt id="arg-mic-range">mic_range<a class="anchor" aria-label="anchor" href="#arg-mic-range"></a></dt>
 <dd><p>a manual range to limit the MIC values, e.g., <code>mic_range = c(0.001, 32)</code>. Use <code>NA</code> to set no limit on one side, e.g., <code>mic_range = c(NA, 32)</code>.</p></dd>
 
 
-<dt>as.mic</dt>
+<dt id="arg-as-mic">as.mic<a class="anchor" aria-label="anchor" href="#arg-as-mic"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether the <code>mic</code> class should be kept - the default is <code>FALSE</code></p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>arguments passed on to methods</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>Ordered <a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a> with additional class <code>mic</code>, that in mathematical operations acts as a <a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a> vector. Bear in mind that the outcome of any mathematical operation on MICs will return a <a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a> value.</p>
+    <p>Ordered <a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a> with additional class <code>mic</code>, that in mathematical operations acts as a <a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a> vector. Bear in mind that the outcome of any mathematical operation on MICs will return a <a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a> value.</p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -275,7 +169,7 @@
 <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/all.html" class="external-link">all</a></span><span class="op">(</span><span class="va">mic_data</span> <span class="op">&lt;</span> <span class="fl">512</span><span class="op">)</span></span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] TRUE</span>
 <span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># limit MICs using rescale_mic()</span></span></span>
+<span class="r-in"><span><span class="co"># rescale MICs using rescale_mic()</span></span></span>
 <span class="r-in"><span><span class="fu">rescale_mic</span><span class="op">(</span><span class="va">mic_data</span>, mic_range <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">4</span>, <span class="fl">16</span><span class="op">)</span><span class="op">)</span></span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> Class 'mic'</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] &gt;=16 &lt;=4  &lt;=4  &lt;=4  8    &lt;=4  8    &gt;=16 &gt;=16</span>
@@ -324,7 +218,7 @@
 <span class="r-plt img"><img src="as.mic-4.png" alt="" width="700" height="433"></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -338,9 +232,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/as.mo.html b/reference/as.mo.html
index 23d89f1db..a85537961 100644
--- a/reference/as.mo.html
+++ b/reference/as.mo.html
@@ -1,166 +1,60 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content='Use this function to get a valid microorganism code (mo) based on arbitrary user input. Determination is done using intelligent rules and the complete taxonomic tree of the kingdoms Animalia, Archaea, Bacteria, and Protozoa, and most microbial species from the kingdom Fungi (see Source). The input can be almost anything: a full name (like "Staphylococcus aureus"), an abbreviated name (such as "S. aureus"), an abbreviation known in the field (such as "MRSA"), or just a genus. See Examples.'><title>Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo"><meta property="og:description" content='Use this function to get a valid microorganism code (mo) based on arbitrary user input. Determination is done using intelligent rules and the complete taxonomic tree of the kingdoms Animalia, Archaea, Bacteria, and Protozoa, and most microbial species from the kingdom Fungi (see Source). The input can be almost anything: a full name (like "Staphylococcus aureus"), an abbreviated name (such as "S. aureus"), an abbreviation known in the field (such as "MRSA"), or just a genus. 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   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Transform Arbitrary Input to Valid Microbial Taxonomy</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/mo.R" class="external-link"><code>R/mo.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/mo.R" class="external-link"><code>R/mo.R</code></a></small>
       <div class="d-none name"><code>as.mo.Rd</code></div>
     </div>
 
     <div class="ref-description section level2">
-    <p>Use this function to get a valid microorganism code (<code>mo</code>) based on arbitrary user input. Determination is done using intelligent rules and the complete taxonomic tree of the kingdoms Animalia, Archaea, Bacteria, and Protozoa, and most microbial species from the kingdom Fungi (see <em>Source</em>). The input can be almost anything: a full name (like <code>"Staphylococcus aureus"</code>), an abbreviated name (such as <code>"S. aureus"</code>), an abbreviation known in the field (such as <code>"MRSA"</code>), or just a genus. See <em>Examples</em>.</p>
+    <p>Use this function to get a valid microorganism code (<code>mo</code>) based on arbitrary user input. Determination is done using intelligent rules and the complete taxonomic tree of the kingdoms Animalia, Archaea, Bacteria, Chromista, and Protozoa, and most microbial species from the kingdom Fungi (see <em>Source</em>). The input can be almost anything: a full name (like <code>"Staphylococcus aureus"</code>), an abbreviated name (such as <code>"S. aureus"</code>), an abbreviation known in the field (such as <code>"MRSA"</code>), or just a genus. See <em>Examples</em>.</p>
     </div>
 
     <div class="section level2">
@@ -194,61 +88,57 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector or a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with one or two columns</p></dd>
 
 
-<dt>Becker</dt>
+<dt id="arg-becker">Becker<a class="anchor" aria-label="anchor" href="#arg-becker"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether staphylococci should be categorised into coagulase-negative staphylococci ("CoNS") and coagulase-positive staphylococci ("CoPS") instead of their own species, according to Karsten Becker <em>et al.</em> (see <em>Source</em>). Please see <em>Details</em> for a full list of staphylococcal species that will be converted.</p>
 <p>This excludes <em>Staphylococcus aureus</em> at default, use <code>Becker = "all"</code> to also categorise <em>S. aureus</em> as "CoPS".</p></dd>
 
 
-<dt>Lancefield</dt>
+<dt id="arg-lancefield">Lancefield<a class="anchor" aria-label="anchor" href="#arg-lancefield"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether a beta-haemolytic <em>Streptococcus</em> should be categorised into Lancefield groups instead of their own species, according to Rebecca C. Lancefield (see <em>Source</em>). These streptococci will be categorised in their first group, e.g. <em>Streptococcus dysgalactiae</em> will be group C, although officially it was also categorised into groups G and L. . Please see <em>Details</em> for a full list of streptococcal species that will be converted.</p>
 <p>This excludes enterococci at default (who are in group D), use <code>Lancefield = "all"</code> to also categorise all enterococci as group D.</p></dd>
 
 
-<dt>minimum_matching_score</dt>
+<dt id="arg-minimum-matching-score">minimum_matching_score<a class="anchor" aria-label="anchor" href="#arg-minimum-matching-score"></a></dt>
 <dd><p>a numeric value to set as the lower limit for the <a href="mo_matching_score.html">MO matching score</a>. When left blank, this will be determined automatically based on the character length of <code>x</code>, its <a href="microorganisms.html">taxonomic kingdom</a> and <a href="mo_matching_score.html">human pathogenicity</a>.</p></dd>
 
 
-<dt>keep_synonyms</dt>
+<dt id="arg-keep-synonyms">keep_synonyms<a class="anchor" aria-label="anchor" href="#arg-keep-synonyms"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate if old, previously valid taxonomic names must be preserved and not be corrected to currently accepted names. The default is <code>FALSE</code>, which will return a note if old taxonomic names were processed. The default can be set with the <a href="AMR-options.html">package option</a> <code><a href="AMR-options.html">AMR_keep_synonyms</a></code>, i.e. <code>options(AMR_keep_synonyms = TRUE)</code> or <code>options(AMR_keep_synonyms = FALSE)</code>.</p></dd>
 
 
-<dt>reference_df</dt>
+<dt id="arg-reference-df">reference_df<a class="anchor" aria-label="anchor" href="#arg-reference-df"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> to be used for extra reference when translating <code>x</code> to a valid <code>mo</code>. See <code><a href="mo_source.html">set_mo_source()</a></code> and <code><a href="mo_source.html">get_mo_source()</a></code> to automate the usage of your own codes (e.g. used in your analysis or organisation).</p></dd>
 
 
-<dt>ignore_pattern</dt>
+<dt id="arg-ignore-pattern">ignore_pattern<a class="anchor" aria-label="anchor" href="#arg-ignore-pattern"></a></dt>
 <dd><p>a Perl-compatible <a href="https://rdrr.io/r/base/regex.html" class="external-link">regular expression</a> (case-insensitive) of which all matches in <code>x</code> must return <code>NA</code>. This can be convenient to exclude known non-relevant input and can also be set with the <a href="AMR-options.html">package option</a> <code><a href="AMR-options.html">AMR_ignore_pattern</a></code>, e.g. <code>options(AMR_ignore_pattern = "(not reported|contaminated flora)")</code>.</p></dd>
 
 
-<dt>cleaning_regex</dt>
+<dt id="arg-cleaning-regex">cleaning_regex<a class="anchor" aria-label="anchor" href="#arg-cleaning-regex"></a></dt>
 <dd><p>a Perl-compatible <a href="https://rdrr.io/r/base/regex.html" class="external-link">regular expression</a> (case-insensitive) to clean the input of <code>x</code>. Every matched part in <code>x</code> will be removed. At default, this is the outcome of <code>mo_cleaning_regex()</code>, which removes texts between brackets and texts such as "species" and "serovar". The default can be set with the <a href="AMR-options.html">package option</a> <code><a href="AMR-options.html">AMR_cleaning_regex</a></code>.</p></dd>
 
 
-<dt>language</dt>
+<dt id="arg-language">language<a class="anchor" aria-label="anchor" href="#arg-language"></a></dt>
 <dd><p>language to translate text like "no growth", which defaults to the system language (see <code><a href="translate.html">get_AMR_locale()</a></code>)</p></dd>
 
 
-<dt>info</dt>
+<dt id="arg-info">info<a class="anchor" aria-label="anchor" href="#arg-info"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate if a progress bar should be printed if more than 25 items are to be coerced - the default is <code>TRUE</code> only in interactive mode</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>other arguments passed on to functions</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a></p>
-<p></p>
-<p><a href="https://rdrr.io/r/base/vector.html" class="external-link">vector</a> with additional class <code>mo</code></p>
-
-
+    <p>A <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> <a href="https://rdrr.io/r/base/vector.html" class="external-link">vector</a> with additional class <code>mo</code></p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -290,7 +180,7 @@
     </div>
     <div class="section level2">
     <h2 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a></h2>
-    
+
 
 <ol><li><p>Berends MS <em>et al.</em> (2022). <strong>AMR: An R Package for Working with Antimicrobial Resistance Data</strong>. <em>Journal of Statistical Software</em>, 104(3), 1-31; <a href="https://doi.org/10.18637/jss.v104.i03" class="external-link">doi:10.18637/jss.v104.i03</a></p></li>
 <li><p>Becker K <em>et al.</em> (2014). <strong>Coagulase-Negative Staphylococci.</strong> <em>Clin Microbiol Rev.</em> 27(4): 870-926; <a href="https://doi.org/10.1128/CMR.00109-13" class="external-link">doi:10.1128/CMR.00109-13</a></p></li>
@@ -299,17 +189,17 @@
 <li><p>Lancefield RC (1933). <strong>A serological differentiation of human and other groups of hemolytic streptococci.</strong> <em>J Exp Med.</em> 57(4): 571-95; <a href="https://doi.org/10.1084/jem.57.4.571" class="external-link">doi:10.1084/jem.57.4.571</a></p></li>
 <li><p>Berends MS <em>et al.</em> (2022). <strong>Trends in Occurrence and Phenotypic Resistance of Coagulase-Negative Staphylococci (CoNS) Found in Human Blood in the Northern Netherlands between 2013 and 2019/</strong> <em>Micro.rganisms</em> 10(9), 1801; <a href="https://doi.org/10.3390/microorganisms10091801" class="external-link">doi:10.3390/microorganisms10091801</a></p></li>
 <li><p>Parte, AC <em>et al.</em> (2020). <strong>List of Prokaryotic names with Standing in Nomenclature (LPSN) moves to the DSMZ.</strong> International Journal of Systematic and Evolutionary Microbiology, 70, 5607-5612; <a href="https://doi.org/10.1099/ijsem.0.004332" class="external-link">doi:10.1099/ijsem.0.004332</a>
-. Accessed from <a href="https://lpsn.dsmz.de" class="external-link">https://lpsn.dsmz.de</a> on December 11th, 2022.</p></li>
+. Accessed from <a href="https://lpsn.dsmz.de" class="external-link">https://lpsn.dsmz.de</a> on June 24th, 2024.</p></li>
 <li><p>GBIF Secretariat (2023). GBIF Backbone Taxonomy. Checklist dataset <a href="https://doi.org/10.15468/39omei" class="external-link">doi:10.15468/39omei</a>
-. Accessed from <a href="https://www.gbif.org" class="external-link">https://www.gbif.org</a> on January 8th, 2024.</p></li>
+. Accessed from <a href="https://www.gbif.org" class="external-link">https://www.gbif.org</a> on June 24th, 2024.</p></li>
 <li><p>Reimer, LC <em>et al.</em> (2022). <strong><em>BacDive</em> in 2022: the knowledge base for standardized bacterial and archaeal data.</strong> Nucleic Acids Res., 50(D1):D741-D74; <a href="https://doi.org/10.1093/nar/gkab961" class="external-link">doi:10.1093/nar/gkab961</a>
-. Accessed from <a href="https://bacdive.dsmz.de" class="external-link">https://bacdive.dsmz.de</a> on May 12th, 2023.</p></li>
+. Accessed from <a href="https://bacdive.dsmz.de" class="external-link">https://bacdive.dsmz.de</a> on July 16th, 2024.</p></li>
 <li><p>Public Health Information Network Vocabulary Access and Distribution System (PHIN VADS). US Edition of SNOMED CT from 1 September 2020. Value Set Name 'Microorganism', OID 2.16.840.1.114222.4.11.1009 (v12). URL: <a href="https://phinvads.cdc.gov" class="external-link">https://phinvads.cdc.gov</a></p></li>
 <li><p>Bartlett A <em>et al.</em> (2022). <strong>A comprehensive list of bacterial pathogens infecting humans</strong> <em>Microbiology</em> 168:001269; <a href="https://doi.org/10.1099/mic.0.001269" class="external-link">doi:10.1099/mic.0.001269</a></p></li>
 </ol></div>
     <div class="section level2">
     <h2 id="matching-score-for-microorganisms">Matching Score for Microorganisms<a class="anchor" aria-label="anchor" href="#matching-score-for-microorganisms"></a></h2>
-    
+
 
 <p>With ambiguous user input in <code>as.mo()</code> and all the <code><a href="mo_property.html">mo_*</a></code> functions, the returned results are chosen based on their matching score using <code><a href="mo_matching_score.html">mo_matching_score()</a></code>. This matching score \(m\), is calculated as:</p>
 <p><img src="figures/mo_matching_score.png" width="300" alt="mo matching score"></p>
@@ -325,14 +215,14 @@
 </ul><p>Furthermore,</p><ul><li><p>Any genus present in the <strong>established</strong> list also has <code>prevalence = 1.0</code> in the <a href="microorganisms.html">microorganisms</a> data set;</p></li>
 <li><p>Any other genus present in the <strong>putative</strong> list has <code>prevalence = 1.25</code> in the <a href="microorganisms.html">microorganisms</a> data set;</p></li>
 <li><p>Any other species or subspecies of which the genus is present in the two aforementioned groups, has <code>prevalence = 1.5</code> in the <a href="microorganisms.html">microorganisms</a> data set;</p></li>
-<li><p>Any <em>non-bacterial</em> genus, species or subspecies of which the genus is present in the following list, has <code>prevalence = 1.25</code> in the <a href="microorganisms.html">microorganisms</a> data set: <em>Absidia</em>, <em>Acanthamoeba</em>, <em>Acremonium</em>, <em>Aedes</em>, <em>Alternaria</em>, <em>Amoeba</em>, <em>Ancylostoma</em>, <em>Angiostrongylus</em>, <em>Anisakis</em>, <em>Anopheles</em>, <em>Apophysomyces</em>, <em>Arthroderma</em>, <em>Aspergillus</em>, <em>Aureobasidium</em>, <em>Basidiobolus</em>, <em>Beauveria</em>, <em>Blastocystis</em>, <em>Blastomyces</em>, <em>Candida</em>, <em>Capillaria</em>, <em>Chaetomium</em>, <em>Chrysonilia</em>, <em>Chrysosporium</em>, <em>Cladophialophora</em>, <em>Cladosporium</em>, <em>Conidiobolus</em>, <em>Contracaecum</em>, <em>Cordylobia</em>, <em>Cryptococcus</em>, <em>Curvularia</em>, <em>Demodex</em>, <em>Dermatobia</em>, <em>Dientamoeba</em>, <em>Diphyllobothrium</em>, <em>Dirofilaria</em>, <em>Echinostoma</em>, <em>Entamoeba</em>, <em>Enterobius</em>, <em>Exophiala</em>, <em>Exserohilum</em>, <em>Fasciola</em>, <em>Fonsecaea</em>, <em>Fusarium</em>, <em>Geotrichum</em>, <em>Giardia</em>, <em>Haloarcula</em>, <em>Halobacterium</em>, <em>Halococcus</em>, <em>Hendersonula</em>, <em>Heterophyes</em>, <em>Histomonas</em>, <em>Histoplasma</em>, <em>Hymenolepis</em>, <em>Hypomyces</em>, <em>Hysterothylacium</em>, <em>Kloeckera</em>, <em>Kodamaea</em>, <em>Leishmania</em>, <em>Lichtheimia</em>, <em>Lodderomyces</em>, <em>Malassezia</em>, <em>Malbranchea</em>, <em>Metagonimus</em>, <em>Meyerozyma</em>, <em>Microsporidium</em>, <em>Microsporum</em>, <em>Millerozyma</em>, <em>Mortierella</em>, <em>Mucor</em>, <em>Mycocentrospora</em>, <em>Necator</em>, <em>Nectria</em>, <em>Ochroconis</em>, <em>Oesophagostomum</em>, <em>Oidiodendron</em>, <em>Opisthorchis</em>, <em>Paecilomyces</em>, <em>Pediculus</em>, <em>Penicillium</em>, <em>Phlebotomus</em>, <em>Phoma</em>, <em>Pichia</em>, <em>Piedraia</em>, <em>Pithomyces</em>, <em>Pityrosporum</em>, <em>Pneumocystis</em>, <em>Pseudallescheria</em>, <em>Pseudoterranova</em>, <em>Pulex</em>, <em>Rhizomucor</em>, <em>Rhizopus</em>, <em>Rhodotorula</em>, <em>Saccharomyces</em>, <em>Saprochaete</em>, <em>Sarcoptes</em>, <em>Scedosporium</em>, <em>Scolecobasidium</em>, <em>Scopulariopsis</em>, <em>Scytalidium</em>, <em>Spirometra</em>, <em>Sporobolomyces</em>, <em>Sporotrichum</em>, <em>Stachybotrys</em>, <em>Strongyloides</em>, <em>Syngamus</em>, <em>Taenia</em>, <em>Talaromyces</em>, <em>Toxocara</em>, <em>Trichinella</em>, <em>Trichobilharzia</em>, <em>Trichoderma</em>, <em>Trichomonas</em>, <em>Trichophyton</em>, <em>Trichosporon</em>, <em>Trichostrongylus</em>, <em>Trichuris</em>, <em>Tritirachium</em>, <em>Trombicula</em>, <em>Trypanosoma</em>, <em>Tunga</em>, <em>Verticillium</em>, or <em>Wuchereria</em>;</p></li>
+<li><p>Any <em>non-bacterial</em> genus, species or subspecies of which the genus is present in the following list, has <code>prevalence = 1.25</code> in the <a href="microorganisms.html">microorganisms</a> data set: <em>Absidia</em>, <em>Acanthamoeba</em>, <em>Acremonium</em>, <em>Aedes</em>, <em>Alternaria</em>, <em>Amoeba</em>, <em>Ancylostoma</em>, <em>Angiostrongylus</em>, <em>Anisakis</em>, <em>Anopheles</em>, <em>Apophysomyces</em>, <em>Arthroderma</em>, <em>Aspergillus</em>, <em>Aureobasidium</em>, <em>Basidiobolus</em>, <em>Beauveria</em>, <em>Blastocystis</em>, <em>Blastomyces</em>, <em>Candida</em>, <em>Capillaria</em>, <em>Chaetomium</em>, <em>Chrysonilia</em>, <em>Chrysosporium</em>, <em>Cladophialophora</em>, <em>Cladosporium</em>, <em>Conidiobolus</em>, <em>Contracaecum</em>, <em>Cordylobia</em>, <em>Cryptococcus</em>, <em>Curvularia</em>, <em>Demodex</em>, <em>Dermatobia</em>, <em>Dientamoeba</em>, <em>Diphyllobothrium</em>, <em>Dirofilaria</em>, <em>Echinostoma</em>, <em>Entamoeba</em>, <em>Enterobius</em>, <em>Exophiala</em>, <em>Exserohilum</em>, <em>Fasciola</em>, <em>Fonsecaea</em>, <em>Fusarium</em>, <em>Geotrichum</em>, <em>Giardia</em>, <em>Haloarcula</em>, <em>Halobacterium</em>, <em>Halococcus</em>, <em>Hansenula</em>, <em>Hendersonula</em>, <em>Heterophyes</em>, <em>Histomonas</em>, <em>Histoplasma</em>, <em>Hymenolepis</em>, <em>Hypomyces</em>, <em>Hysterothylacium</em>, <em>Kloeckera</em>, <em>Kluyveromyces</em>, <em>Kodamaea</em>, <em>Leishmania</em>, <em>Lichtheimia</em>, <em>Lodderomyces</em>, <em>Lomentospora</em>, <em>Malassezia</em>, <em>Malbranchea</em>, <em>Metagonimus</em>, <em>Meyerozyma</em>, <em>Microsporidium</em>, <em>Microsporum</em>, <em>Millerozyma</em>, <em>Mortierella</em>, <em>Mucor</em>, <em>Mycocentrospora</em>, <em>Necator</em>, <em>Nectria</em>, <em>Ochroconis</em>, <em>Oesophagostomum</em>, <em>Oidiodendron</em>, <em>Opisthorchis</em>, <em>Paecilomyces</em>, <em>Pediculus</em>, <em>Penicillium</em>, <em>Phlebotomus</em>, <em>Phoma</em>, <em>Pichia</em>, <em>Piedraia</em>, <em>Pithomyces</em>, <em>Pityrosporum</em>, <em>Pneumocystis</em>, <em>Pseudallescheria</em>, <em>Pseudoscopulariopsis</em>, <em>Pseudoterranova</em>, <em>Pulex</em>, <em>Rhizomucor</em>, <em>Rhizopus</em>, <em>Rhodotorula</em>, <em>Saccharomyces</em>, <em>Saprochaete</em>, <em>Sarcoptes</em>, <em>Scedosporium</em>, <em>Scolecobasidium</em>, <em>Scopulariopsis</em>, <em>Scytalidium</em>, <em>Spirometra</em>, <em>Sporobolomyces</em>, <em>Sporotrichum</em>, <em>Stachybotrys</em>, <em>Strongyloides</em>, <em>Syngamus</em>, <em>Taenia</em>, <em>Talaromyces</em>, <em>Toxocara</em>, <em>Trichinella</em>, <em>Trichobilharzia</em>, <em>Trichoderma</em>, <em>Trichomonas</em>, <em>Trichophyton</em>, <em>Trichosporon</em>, <em>Trichostrongylus</em>, <em>Trichuris</em>, <em>Tritirachium</em>, <em>Trombicula</em>, <em>Trypanosoma</em>, <em>Tunga</em>, <em>Verticillium</em>, or <em>Wuchereria</em>;</p></li>
 <li><p>All other records have <code>prevalence = 2.0</code> in the <a href="microorganisms.html">microorganisms</a> data set.</p></li>
 </ul><p>When calculating the matching score, all characters in \(x\) and \(n\) are ignored that are other than A-Z, a-z, 0-9, spaces and parentheses.</p>
 <p>All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., <code>"E. coli"</code> will return the microbial ID of <em>Escherichia coli</em> (\(m = 0.688\), a highly prevalent microorganism found in humans) and not <em>Entamoeba coli</em> (\(m = 0.381\), a less prevalent microorganism in humans), although the latter would alphabetically come first.</p>
     </div>
     <div class="section level2">
     <h2 id="reference-data-publicly-available">Reference Data Publicly Available<a class="anchor" aria-label="anchor" href="#reference-data-publicly-available"></a></h2>
-    
+
 
 <p>All data sets in this <code>AMR</code> package (about microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) are publicly and freely available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. We also provide tab-separated plain text files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please visit <a href="https://msberends.github.io/AMR/articles/datasets.html">our website for the download links</a>. The actual files are of course available on <a href="https://github.com/msberends/AMR/tree/main/data-raw" class="external-link">our GitHub repository</a>.</p>
     </div>
@@ -411,7 +301,7 @@
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
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@@ -425,9 +315,9 @@
 
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index 414af9858..ef13a8730 100644
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+++ b/reference/as.sir.html
@@ -1,175 +1,69 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Clean up existing SIR values, or interpret minimum inhibitory concentration (MIC) values and disk diffusion diameters according to EUCAST or CLSI. as.sir() transforms the input to a new class sir, which is an ordered factor containing the levels S, SDD, I, R, NI.
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir"><meta name="description" content="Clean up existing SIR values, or interpret minimum inhibitory concentration (MIC) values and disk diffusion diameters according to EUCAST or CLSI. as.sir() transforms the input to a new class sir, which is an ordered factor containing the levels S, SDD, I, R, NI.
 These breakpoints are currently implemented:
 For clinical microbiology: EUCAST 2011-2024 and CLSI 2011-2024;
 For veterinary microbiology: EUCAST 2021-2024 and CLSI 2019-2024;
 ECOFFs (Epidemiological cut-off values): EUCAST 2020-2024 and CLSI 2022-2024.
 
 
-All breakpoints used for interpretation are available in our clinical_breakpoints data set."><title>Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir"><meta property="og:description" content="Clean up existing SIR values, or interpret minimum inhibitory concentration (MIC) values and disk diffusion diameters according to EUCAST or CLSI. as.sir() transforms the input to a new class sir, which is an ordered factor containing the levels S, SDD, I, R, NI.
+All breakpoints used for interpretation are available in our clinical_breakpoints data set."><meta property="og:description" content="Clean up existing SIR values, or interpret minimum inhibitory concentration (MIC) values and disk diffusion diameters according to EUCAST or CLSI. as.sir() transforms the input to a new class sir, which is an ordered factor containing the levels S, SDD, I, R, NI.
 These breakpoints are currently implemented:
 For clinical microbiology: EUCAST 2011-2024 and CLSI 2011-2024;
 For veterinary microbiology: EUCAST 2021-2024 and CLSI 2019-2024;
 ECOFFs (Epidemiological cut-off values): EUCAST 2020-2024 and CLSI 2022-2024.
 
 
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-    </a>
-  </div>
-</li>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-how-to" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-question-circle"></span> How to</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to"><li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
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+    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul></li>
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
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 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/sir.R" class="external-link"><code>R/sir.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/sir.R" class="external-link"><code>R/sir.R</code></a></small>
       <div class="d-none name"><code>as.sir.Rd</code></div>
     </div>
 
@@ -191,7 +85,7 @@ All breakpoints used for interpretation are available in our clinical_breakpoint
 <span></span>
 <span><span class="fu">is_sir_eligible</span><span class="op">(</span><span class="va">x</span>, threshold <span class="op">=</span> <span class="fl">0.05</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for default</span></span>
+<span><span class="co"># Default S3 method</span></span>
 <span><span class="fu">as.sir</span><span class="op">(</span></span>
 <span>  <span class="va">x</span>,</span>
 <span>  S <span class="op">=</span> <span class="st">"^(S|U)+$"</span>,</span>
@@ -202,7 +96,7 @@ All breakpoints used for interpretation are available in our clinical_breakpoint
 <span>  <span class="va">...</span></span>
 <span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for mic</span></span>
+<span><span class="co"># S3 method for class 'mic'</span></span>
 <span><span class="fu">as.sir</span><span class="op">(</span></span>
 <span>  <span class="va">x</span>,</span>
 <span>  mo <span class="op">=</span> <span class="cn">NULL</span>,</span>
@@ -220,7 +114,7 @@ All breakpoints used for interpretation are available in our clinical_breakpoint
 <span>  <span class="va">...</span></span>
 <span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for disk</span></span>
+<span><span class="co"># S3 method for class 'disk'</span></span>
 <span><span class="fu">as.sir</span><span class="op">(</span></span>
 <span>  <span class="va">x</span>,</span>
 <span>  mo <span class="op">=</span> <span class="cn">NULL</span>,</span>
@@ -237,7 +131,7 @@ All breakpoints used for interpretation are available in our clinical_breakpoint
 <span>  <span class="va">...</span></span>
 <span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for data.frame</span></span>
+<span><span class="co"># S3 method for class 'data.frame'</span></span>
 <span><span class="fu">as.sir</span><span class="op">(</span></span>
 <span>  <span class="va">x</span>,</span>
 <span>  <span class="va">...</span>,</span>
@@ -267,85 +161,83 @@ All breakpoints used for interpretation are available in our clinical_breakpoint
 </ul></div>
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>vector of values (for class <code><a href="as.mic.html">mic</a></code>: MIC values in mg/L, for class <code><a href="as.disk.html">disk</a></code>: a disk diffusion radius in millimetres)</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>for using on a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a>: names of columns to apply <code>as.sir()</code> on (supports tidy selection such as <code>column1:column4</code>). Otherwise: arguments passed on to methods.</p></dd>
 
 
-<dt>threshold</dt>
+<dt id="arg-threshold">threshold<a class="anchor" aria-label="anchor" href="#arg-threshold"></a></dt>
 <dd><p>maximum fraction of invalid antimicrobial interpretations of <code>x</code>, see <em>Examples</em></p></dd>
 
 
-<dt>S, I, R, NI, SDD</dt>
+<dt id="arg-s-i-r-ni-sdd">S, I, R, NI, SDD<a class="anchor" aria-label="anchor" href="#arg-s-i-r-ni-sdd"></a></dt>
 <dd><p>a case-independent <a href="https://rdrr.io/r/base/regex.html" class="external-link">regular expression</a> to translate input to this result. This regular expression will be run <em>after</em> all non-letters and whitespaces are removed from the input.</p></dd>
 
 
-<dt>mo</dt>
+<dt id="arg-mo">mo<a class="anchor" aria-label="anchor" href="#arg-mo"></a></dt>
 <dd><p>a vector (or column name) with <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a>s that can be coerced to valid microorganism codes with <code><a href="as.mo.html">as.mo()</a></code>, can be left empty to determine it automatically</p></dd>
 
 
-<dt>ab</dt>
+<dt id="arg-ab">ab<a class="anchor" aria-label="anchor" href="#arg-ab"></a></dt>
 <dd><p>a vector (or column name) with <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a>s that can be coerced to a valid antimicrobial drug code with <code><a href="as.ab.html">as.ab()</a></code></p></dd>
 
 
-<dt>guideline</dt>
+<dt id="arg-guideline">guideline<a class="anchor" aria-label="anchor" href="#arg-guideline"></a></dt>
 <dd><p>defaults to EUCAST 2024 (the latest implemented EUCAST guideline in the <a href="clinical_breakpoints.html">clinical_breakpoints</a> data set), but can be set with the <a href="AMR-options.html">package option</a> <code><a href="AMR-options.html">AMR_guideline</a></code>. Currently supports EUCAST (2011-2024) and CLSI (2011-2024), see <em>Details</em>.</p></dd>
 
 
-<dt>uti</dt>
+<dt id="arg-uti">uti<a class="anchor" aria-label="anchor" href="#arg-uti"></a></dt>
 <dd><p>(Urinary Tract Infection) a vector (or column name) with <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a>s (<code>TRUE</code> or <code>FALSE</code>) to specify whether a UTI specific interpretation from the guideline should be chosen. For using <code>as.sir()</code> on a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a>, this can also be a column containing <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a>s or when left blank, the data set will be searched for a column 'specimen', and rows within this column containing 'urin' (such as 'urine', 'urina') will be regarded isolates from a UTI. See <em>Examples</em>.</p></dd>
 
 
-<dt>conserve_capped_values</dt>
+<dt id="arg-conserve-capped-values">conserve_capped_values<a class="anchor" aria-label="anchor" href="#arg-conserve-capped-values"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate that MIC values starting with <code>"&gt;"</code> (but not <code>"&gt;="</code>) must always return "R" , and that MIC values starting with <code>"&lt;"</code> (but not <code>"&lt;="</code>) must always return "S"</p></dd>
 
 
-<dt>add_intrinsic_resistance</dt>
+<dt id="arg-add-intrinsic-resistance">add_intrinsic_resistance<a class="anchor" aria-label="anchor" href="#arg-add-intrinsic-resistance"></a></dt>
 <dd><p><em>(only useful when using a EUCAST guideline)</em> a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether intrinsic antibiotic resistance must also be considered for applicable bug-drug combinations, meaning that e.g. ampicillin will always return "R" in <em>Klebsiella</em> species. Determination is based on the <a href="intrinsic_resistant.html">intrinsic_resistant</a> data set, that itself is based on <a href="https://www.eucast.org/expert_rules_and_expected_phenotypes" class="external-link">'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3</a> (2021).</p></dd>
 
 
-<dt>reference_data</dt>
+<dt id="arg-reference-data">reference_data<a class="anchor" aria-label="anchor" href="#arg-reference-data"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> to be used for interpretation, which defaults to the <a href="clinical_breakpoints.html">clinical_breakpoints</a> data set. Changing this argument allows for using own interpretation guidelines. This argument must contain a data set that is equal in structure to the <a href="clinical_breakpoints.html">clinical_breakpoints</a> data set (same column names and column types). Please note that the <code>guideline</code> argument will be ignored when <code>reference_data</code> is manually set.</p></dd>
 
 
-<dt>include_screening</dt>
+<dt id="arg-include-screening">include_screening<a class="anchor" aria-label="anchor" href="#arg-include-screening"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate that clinical breakpoints for screening are allowed - the default is <code>FALSE</code>. Can also be set with the <a href="AMR-options.html">package option</a> <code><a href="AMR-options.html">AMR_include_screening</a></code>.</p></dd>
 
 
-<dt>include_PKPD</dt>
+<dt id="arg-include-pkpd">include_PKPD<a class="anchor" aria-label="anchor" href="#arg-include-pkpd"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate that PK/PD clinical breakpoints must be applied as a last resort - the default is <code>TRUE</code>. Can also be set with the <a href="AMR-options.html">package option</a> <code><a href="AMR-options.html">AMR_include_PKPD</a></code>.</p></dd>
 
 
-<dt>breakpoint_type</dt>
+<dt id="arg-breakpoint-type">breakpoint_type<a class="anchor" aria-label="anchor" href="#arg-breakpoint-type"></a></dt>
 <dd><p>the type of breakpoints to use, either "ECOFF", "animal", or "human". ECOFF stands for Epidemiological Cut-Off values. The default is <code>"human"</code>, which can also be set with the <a href="AMR-options.html">package option</a> <code><a href="AMR-options.html">AMR_breakpoint_type</a></code>. If <code>host</code> is set to values of veterinary species, this will automatically be set to <code>"animal"</code>.</p></dd>
 
 
-<dt>host</dt>
+<dt id="arg-host">host<a class="anchor" aria-label="anchor" href="#arg-host"></a></dt>
 <dd><p>a vector (or column name) with <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a>s to indicate the host. Only useful for veterinary breakpoints, as it requires <code>breakpoint_type = "animal"</code>. The values can be any text resembling the animal species, even in any of the 20 supported languages of this package. For foreign languages, be sure to set the language with <code><a href="translate.html">set_AMR_locale()</a></code> (though it will be automatically guessed based on the system language).</p></dd>
 
 
-<dt>verbose</dt>
+<dt id="arg-verbose">verbose<a class="anchor" aria-label="anchor" href="#arg-verbose"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate that all notes should be printed during interpretation of MIC values or disk diffusion values.</p></dd>
 
 
-<dt>col_mo</dt>
+<dt id="arg-col-mo">col_mo<a class="anchor" aria-label="anchor" href="#arg-col-mo"></a></dt>
 <dd><p>column name of the names or codes of the microorganisms (see <code><a href="as.mo.html">as.mo()</a></code>) - the default is the first column of class <code><a href="as.mo.html">mo</a></code>. Values will be coerced using <code><a href="as.mo.html">as.mo()</a></code>.</p></dd>
 
 
-<dt>clean</dt>
+<dt id="arg-clean">clean<a class="anchor" aria-label="anchor" href="#arg-clean"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether previously stored results should be forgotten after returning the 'logbook' with results</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>Ordered <a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a> with new class <code>sir</code></p>
-
-
+    <p>Ordered <a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a> with new class <code>sir</code></p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -421,7 +313,7 @@ All breakpoints used for interpretation are available in our clinical_breakpoint
     </div>
     <div class="section level2">
     <h2 id="interpretation-of-sir">Interpretation of SIR<a class="anchor" aria-label="anchor" href="#interpretation-of-sir"></a></h2>
-    
+
 
 <p>In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories S, I, and R as shown below (<a href="https://www.eucast.org/newsiandr" class="external-link">https://www.eucast.org/newsiandr</a>):</p><ul><li><p><strong>S - Susceptible, standard dosing regimen</strong><br>
 A microorganism is categorised as "Susceptible, standard dosing regimen", when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.</p></li>
@@ -434,7 +326,7 @@ A microorganism is categorised as "Resistant" when there is a high likelihood of
     </div>
     <div class="section level2">
     <h2 id="reference-data-publicly-available">Reference Data Publicly Available<a class="anchor" aria-label="anchor" href="#reference-data-publicly-available"></a></h2>
-    
+
 
 <p>All data sets in this <code>AMR</code> package (about microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) are publicly and freely available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. We also provide tab-separated plain text files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please visit <a href="https://msberends.github.io/AMR/articles/datasets.html">our website for the download links</a>. The actual files are of course available on <a href="https://github.com/msberends/AMR/tree/main/data-raw" class="external-link">our GitHub repository</a>.</p>
     </div>
@@ -868,16 +760,16 @@ A microorganism is categorised as "Resistant" when there is a high likelihood of
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 59 × 16</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>    datetime            index ab_given mo_given host_given ab   mo              </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>  <span style="color: #BCBCBC;">*</span> <span style="color: #949494; font-style: italic;">&lt;dttm&gt;</span>              <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;ab&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span>            </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 2024-06-23 <span style="color: #949494;">14:22:38</span>     4 AMX      B_STRPT… human      AMX  B_STRPT_PNMN    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 2024-06-23 <span style="color: #949494;">14:22:44</span>     4 genta    Escheri… human      GEN  B_[ORD]_ENTRBCTR</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> 2024-06-23 <span style="color: #949494;">14:22:44</span>     4 genta    Escheri… human      GEN  B_[ORD]_ENTRBCTR</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 2024-06-23 <span style="color: #949494;">14:22:44</span>     4 genta    Escheri… cattle     GEN  B_[ORD]_ENTRBCTR</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 2024-06-23 <span style="color: #949494;">14:22:45</span>     4 genta    Escheri… cattle     GEN  B_[ORD]_ENTRBCTR</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 2024-06-23 <span style="color: #949494;">14:22:38</span>     3 AMX      B_STRPT… human      AMX  B_STRPT_PNMN    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> 2024-06-23 <span style="color: #949494;">14:22:44</span>     3 tobra    Escheri… human      TOB  B_[ORD]_ENTRBCTR</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> 2024-06-23 <span style="color: #949494;">14:22:44</span>     3 tobra    Escheri… human      TOB  B_[ORD]_ENTRBCTR</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 2024-06-23 <span style="color: #949494;">14:22:44</span>     3 tobra    Escheri… horses     TOB  B_ESCHR_COLI    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 2024-06-23 <span style="color: #949494;">14:22:45</span>     3 tobra    Escheri… horses     TOB  B_ESCHR_COLI    </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 2024-07-16 <span style="color: #949494;">12:58:17</span>     4 AMX      B_STRPT… human      AMX  B_STRPT_PNMN    </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 2024-07-16 <span style="color: #949494;">12:58:23</span>     4 genta    Escheri… human      GEN  B_[ORD]_ENTRBCTR</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> 2024-07-16 <span style="color: #949494;">12:58:24</span>     4 genta    Escheri… human      GEN  B_[ORD]_ENTRBCTR</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 2024-07-16 <span style="color: #949494;">12:58:24</span>     4 genta    Escheri… cattle     GEN  B_[ORD]_ENTRBCTR</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 2024-07-16 <span style="color: #949494;">12:58:25</span>     4 genta    Escheri… cattle     GEN  B_[ORD]_ENTRBCTR</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 2024-07-16 <span style="color: #949494;">12:58:17</span>     3 AMX      B_STRPT… human      AMX  B_STRPT_PNMN    </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> 2024-07-16 <span style="color: #949494;">12:58:23</span>     3 tobra    Escheri… human      TOB  B_[ORD]_ENTRBCTR</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> 2024-07-16 <span style="color: #949494;">12:58:24</span>     3 tobra    Escheri… human      TOB  B_[ORD]_ENTRBCTR</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 2024-07-16 <span style="color: #949494;">12:58:24</span>     3 tobra    Escheri… horses     TOB  B_ESCHR_COLI    </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 2024-07-16 <span style="color: #949494;">12:58:25</span>     3 tobra    Escheri… horses     TOB  B_ESCHR_COLI    </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 49 more rows</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 9 more variables: host &lt;chr&gt;, method &lt;chr&gt;, input &lt;dbl&gt;, outcome &lt;sir&gt;,</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   notes &lt;chr&gt;, guideline &lt;chr&gt;, ref_table &lt;chr&gt;, uti &lt;lgl&gt;,</span></span>
@@ -976,7 +868,7 @@ A microorganism is categorised as "Resistant" when there is a high likelihood of
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -990,9 +882,9 @@ A microorganism is categorised as "Resistant" when there is a high likelihood of
 
     </footer></div>
 
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diff --git a/reference/as.sir.mic.html b/reference/as.sir.mic.html
new file mode 100644
index 000000000..c99d19d99
--- /dev/null
+++ b/reference/as.sir.mic.html
@@ -0,0 +1,8 @@
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diff --git a/reference/atc_online.html b/reference/atc_online.html
index e3288d700..9e3467966 100644
--- a/reference/atc_online.html
+++ b/reference/atc_online.html
@@ -1,161 +1,55 @@
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       <img src="../logo.svg" class="logo" alt=""><h1>Get ATC Properties from WHOCC Website</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/atc_online.R" class="external-link"><code>R/atc_online.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/atc_online.R" class="external-link"><code>R/atc_online.R</code></a></small>
       <div class="d-none name"><code>atc_online.Rd</code></div>
     </div>
 
@@ -186,27 +80,29 @@
     </div>
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>atc_code</dt>
+
+
+<dl><dt id="arg-atc-code">atc_code<a class="anchor" aria-label="anchor" href="#arg-atc-code"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> (vector) with ATC code(s) of antibiotics, will be coerced with <code><a href="as.ab.html">as.ab()</a></code> and <code><a href="ab_property.html">ab_atc()</a></code> internally if not a valid ATC code</p></dd>
 
 
-<dt>property</dt>
+<dt id="arg-property">property<a class="anchor" aria-label="anchor" href="#arg-property"></a></dt>
 <dd><p>property of an ATC code. Valid values are <code>"ATC"</code>, <code>"Name"</code>, <code>"DDD"</code>, <code>"U"</code> (<code>"unit"</code>), <code>"Adm.R"</code>, <code>"Note"</code> and <code>groups</code>. For this last option, all hierarchical groups of an ATC code will be returned, see <em>Examples</em>.</p></dd>
 
 
-<dt>administration</dt>
+<dt id="arg-administration">administration<a class="anchor" aria-label="anchor" href="#arg-administration"></a></dt>
 <dd><p>type of administration when using <code>property = "Adm.R"</code>, see <em>Details</em></p></dd>
 
 
-<dt>url</dt>
+<dt id="arg-url">url<a class="anchor" aria-label="anchor" href="#arg-url"></a></dt>
 <dd><p>url of website of the WHOCC. The sign <code>%s</code> can be used as a placeholder for ATC codes.</p></dd>
 
 
-<dt>url_vet</dt>
+<dt id="arg-url-vet">url_vet<a class="anchor" aria-label="anchor" href="#arg-url-vet"></a></dt>
 <dd><p>url of website of the WHOCC for veterinary medicine. The sign <code>%s</code> can be used as a placeholder for ATC_vet codes (that all start with "Q").</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>arguments to pass on to <code>atc_property</code></p></dd>
 
 </dl></div>
@@ -254,7 +150,7 @@
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -268,9 +164,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/atc_online_ddd.html b/reference/atc_online_ddd.html
new file mode 100644
index 000000000..1f018215f
--- /dev/null
+++ b/reference/atc_online_ddd.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/atc_online.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/atc_online.html">
+  </head>
+</html>
+
diff --git a/reference/atc_online_ddd_units.html b/reference/atc_online_ddd_units.html
new file mode 100644
index 000000000..1f018215f
--- /dev/null
+++ b/reference/atc_online_ddd_units.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/atc_online.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/atc_online.html">
+  </head>
+</html>
+
diff --git a/reference/atc_online_groups.html b/reference/atc_online_groups.html
new file mode 100644
index 000000000..1f018215f
--- /dev/null
+++ b/reference/atc_online_groups.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/atc_online.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/atc_online.html">
+  </head>
+</html>
+
diff --git a/reference/autoplot.antibiogram.html b/reference/autoplot.antibiogram.html
new file mode 100644
index 000000000..4748f41b8
--- /dev/null
+++ b/reference/autoplot.antibiogram.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiogram.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/antibiogram.html">
+  </head>
+</html>
+
diff --git a/reference/autoplot.disk.html b/reference/autoplot.disk.html
new file mode 100644
index 000000000..934dc99fb
--- /dev/null
+++ b/reference/autoplot.disk.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/plot.html" />
+    <meta name="robots" content="noindex">
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+</html>
+
diff --git a/reference/autoplot.mic.html b/reference/autoplot.mic.html
new file mode 100644
index 000000000..934dc99fb
--- /dev/null
+++ b/reference/autoplot.mic.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/plot.html" />
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+</html>
+
diff --git a/reference/autoplot.resistance_predict.html b/reference/autoplot.resistance_predict.html
new file mode 100644
index 000000000..95fc74991
--- /dev/null
+++ b/reference/autoplot.resistance_predict.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/resistance_predict.html" />
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+</html>
+
diff --git a/reference/autoplot.sir.html b/reference/autoplot.sir.html
new file mode 100644
index 000000000..934dc99fb
--- /dev/null
+++ b/reference/autoplot.sir.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/plot.html" />
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+</html>
+
diff --git a/reference/av.html b/reference/av.html
new file mode 100644
index 000000000..49816e58a
--- /dev/null
+++ b/reference/av.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/as.av.html" />
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+  </head>
+</html>
+
diff --git a/reference/av_atc.html b/reference/av_atc.html
new file mode 100644
index 000000000..ce5470f8a
--- /dev/null
+++ b/reference/av_atc.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/av_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/av_property.html">
+  </head>
+</html>
+
diff --git a/reference/av_cid.html b/reference/av_cid.html
new file mode 100644
index 000000000..ce5470f8a
--- /dev/null
+++ b/reference/av_cid.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/av_property.html" />
+    <meta name="robots" content="noindex">
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+  </head>
+</html>
+
diff --git a/reference/av_ddd.html b/reference/av_ddd.html
new file mode 100644
index 000000000..ce5470f8a
--- /dev/null
+++ b/reference/av_ddd.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/av_property.html" />
+    <meta name="robots" content="noindex">
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+  </head>
+</html>
+
diff --git a/reference/av_ddd_units.html b/reference/av_ddd_units.html
new file mode 100644
index 000000000..ce5470f8a
--- /dev/null
+++ b/reference/av_ddd_units.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/av_property.html" />
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+  </head>
+</html>
+
diff --git a/reference/av_from_text.html b/reference/av_from_text.html
index 0aba7bd5b..a03c5d121 100644
--- a/reference/av_from_text.html
+++ b/reference/av_from_text.html
@@ -1,161 +1,55 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Use this function on e.g. clinical texts from health care records. It returns a list with all antiviral drugs, doses and forms of administration found in the texts."><title>Retrieve Antiviral Drug Names and Doses from Clinical Text — av_from_text • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Retrieve Antiviral Drug Names and Doses from Clinical Text — av_from_text"><meta property="og:description" content="Use this function on e.g. clinical texts from health care records. It returns a list with all antiviral drugs, doses and forms of administration found in the texts."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul></li>
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--with-other-pkgs">
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-     
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-  </a>
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Retrieve Antiviral Drug Names and Doses from Clinical Text</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/av_from_text.R" class="external-link"><code>R/av_from_text.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/av_from_text.R" class="external-link"><code>R/av_from_text.R</code></a></small>
       <div class="d-none name"><code>av_from_text.Rd</code></div>
     </div>
 
@@ -178,41 +72,39 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>text</dt>
+
+
+<dl><dt id="arg-text">text<a class="anchor" aria-label="anchor" href="#arg-text"></a></dt>
 <dd><p>text to analyse</p></dd>
 
 
-<dt>type</dt>
+<dt id="arg-type">type<a class="anchor" aria-label="anchor" href="#arg-type"></a></dt>
 <dd><p>type of property to search for, either <code>"drug"</code>, <code>"dose"</code> or <code>"administration"</code>, see <em>Examples</em></p></dd>
 
 
-<dt>collapse</dt>
+<dt id="arg-collapse">collapse<a class="anchor" aria-label="anchor" href="#arg-collapse"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> to pass on to <code>paste(, collapse = ...)</code> to only return one <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> per element of <code>text</code>, see <em>Examples</em></p></dd>
 
 
-<dt>translate_av</dt>
+<dt id="arg-translate-av">translate_av<a class="anchor" aria-label="anchor" href="#arg-translate-av"></a></dt>
 <dd><p>if <code>type = "drug"</code>: a column name of the <a href="antibiotics.html">antivirals</a> data set to translate the antibiotic abbreviations to, using <code><a href="av_property.html">av_property()</a></code>. The default is <code>FALSE</code>. Using <code>TRUE</code> is equal to using "name".</p></dd>
 
 
-<dt>thorough_search</dt>
+<dt id="arg-thorough-search">thorough_search<a class="anchor" aria-label="anchor" href="#arg-thorough-search"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether the input must be extensively searched for misspelling and other faulty input values. Setting this to <code>TRUE</code> will take considerably more time than when using <code>FALSE</code>. At default, it will turn <code>TRUE</code> when all input elements contain a maximum of three words.</p></dd>
 
 
-<dt>info</dt>
+<dt id="arg-info">info<a class="anchor" aria-label="anchor" href="#arg-info"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether a progress bar should be printed - the default is <code>TRUE</code> only in interactive mode</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>arguments passed on to <code><a href="as.av.html">as.av()</a></code></p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A <a href="https://rdrr.io/r/base/list.html" class="external-link">list</a>, or a  <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> if <code>collapse</code> is not <code>NULL</code></p>
-
-
+    <p>A <a href="https://rdrr.io/r/base/list.html" class="external-link">list</a>, or a  <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> if <code>collapse</code> is not <code>NULL</code></p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -249,7 +141,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> </span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -263,9 +155,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/av_group.html b/reference/av_group.html
new file mode 100644
index 000000000..ce5470f8a
--- /dev/null
+++ b/reference/av_group.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/av_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/av_property.html">
+  </head>
+</html>
+
diff --git a/reference/av_info.html b/reference/av_info.html
new file mode 100644
index 000000000..ce5470f8a
--- /dev/null
+++ b/reference/av_info.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/av_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/av_property.html">
+  </head>
+</html>
+
diff --git a/reference/av_loinc.html b/reference/av_loinc.html
new file mode 100644
index 000000000..ce5470f8a
--- /dev/null
+++ b/reference/av_loinc.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/av_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/av_property.html">
+  </head>
+</html>
+
diff --git a/reference/av_name.html b/reference/av_name.html
new file mode 100644
index 000000000..ce5470f8a
--- /dev/null
+++ b/reference/av_name.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/av_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/av_property.html">
+  </head>
+</html>
+
diff --git a/reference/av_property.html b/reference/av_property.html
index 22ed1903f..fda732d27 100644
--- a/reference/av_property.html
+++ b/reference/av_property.html
@@ -1,161 +1,55 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Use these functions to return a specific property of an antiviral drug from the antivirals data set. All input values will be evaluated internally with as.av()."><title>Get Properties of an Antiviral Drug — av_property • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Get Properties of an Antiviral Drug — av_property"><meta property="og:description" content="Use these functions to return a specific property of an antiviral drug from the antivirals data set. All input values will be evaluated internally with as.av()."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Get Properties of an Antiviral Drug — av_property • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Get Properties of an Antiviral Drug — av_property"><meta name="description" content="Use these functions to return a specific property of an antiviral drug from the antivirals data set. All input values will be evaluated internally with as.av()."><meta property="og:description" content="Use these functions to return a specific property of an antiviral drug from the antivirals data set. All input values will be evaluated internally with as.av()."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"></head><body>
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-  </div>
-</li>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-how-to" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-question-circle"></span> How to</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to"><li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul></li>
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--with-other-pkgs">
-    <span class="fa fa-layer-group"></span>
-     
-    With other pkgs
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--with-other-pkgs">
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; dplyr/tidyverse
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; data.table
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; tidymodels
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; base R
-    </a>
-  </div>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../reference/index.html">
-    <span class="fa fa-book-open"></span>
-     
-    Manual
-  </a>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../authors.html">
-    <span class="fa fa-users"></span>
-     
-    Authors
-  </a>
-</li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
-  <a class="nav-link" href="../news/index.html">
-    <span class="far fa far fa-newspaper"></span>
-     
-    Changelog
-  </a>
-</li>
-<li class="nav-item">
-  <a class="external-link nav-link" href="https://github.com/msberends/AMR">
-    <span class="fab fa fab fa-github"></span>
-     
-    Source Code
-  </a>
-</li>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Get Properties of an Antiviral Drug</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/av_property.R" class="external-link"><code>R/av_property.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/av_property.R" class="external-link"><code>R/av_property.R</code></a></small>
       <div class="d-none name"><code>av_property.Rd</code></div>
     </div>
 
@@ -192,37 +86,38 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>any (vector of) text that can be coerced to a valid antiviral drug code with <code><a href="as.av.html">as.av()</a></code></p></dd>
 
 
-<dt>language</dt>
+<dt id="arg-language">language<a class="anchor" aria-label="anchor" href="#arg-language"></a></dt>
 <dd><p>language of the returned text - the default is system language (see <code><a href="translate.html">get_AMR_locale()</a></code>) and can also be set with the <a href="AMR-options.html">package option</a> <code><a href="AMR-options.html">AMR_locale</a></code>. Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></dd>
 
 
-<dt>tolower</dt>
+<dt id="arg-tolower">tolower<a class="anchor" aria-label="anchor" href="#arg-tolower"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether the first <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> of every output should be transformed to a lower case <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a>.</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>other arguments passed on to <code><a href="as.av.html">as.av()</a></code></p></dd>
 
 
-<dt>administration</dt>
+<dt id="arg-administration">administration<a class="anchor" aria-label="anchor" href="#arg-administration"></a></dt>
 <dd><p>way of administration, either <code>"oral"</code> or <code>"iv"</code></p></dd>
 
 
-<dt>open</dt>
+<dt id="arg-open">open<a class="anchor" aria-label="anchor" href="#arg-open"></a></dt>
 <dd><p>browse the URL using <code><a href="https://rdrr.io/r/utils/browseURL.html" class="external-link">utils::browseURL()</a></code></p></dd>
 
 
-<dt>property</dt>
+<dt id="arg-property">property<a class="anchor" aria-label="anchor" href="#arg-property"></a></dt>
 <dd><p>one of the column names of one of the <a href="antibiotics.html">antivirals</a> data set: <code>vector_or(colnames(antivirals), sort = FALSE)</code>.</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
 
 <ul><li><p>An <a href="https://rdrr.io/r/base/integer.html" class="external-link">integer</a> in case of <code>av_cid()</code></p></li>
 <li><p>A named <a href="https://rdrr.io/r/base/list.html" class="external-link">list</a> in case of <code>av_info()</code> and multiple <code>av_atc()</code>/<code>av_synonyms()</code>/<code>av_tradenames()</code></p></li>
@@ -236,14 +131,14 @@
     </div>
     <div class="section level2">
     <h2 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a></h2>
-    
+
 
 <p>World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: <a href="https://atcddd.fhi.no/atc_ddd_index/" class="external-link">https://atcddd.fhi.no/atc_ddd_index/</a></p>
 <p>European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: <a href="https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm" class="external-link">https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm</a></p>
     </div>
     <div class="section level2">
     <h2 id="reference-data-publicly-available">Reference Data Publicly Available<a class="anchor" aria-label="anchor" href="#reference-data-publicly-available"></a></h2>
-    
+
 
 <p>All data sets in this <code>AMR</code> package (about microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) are publicly and freely available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. We also provide tab-separated plain text files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please visit <a href="https://msberends.github.io/AMR/articles/datasets.html">our website for the download links</a>. The actual files are of course available on <a href="https://github.com/msberends/AMR/tree/main/data-raw" class="external-link">our GitHub repository</a>.</p>
     </div>
@@ -365,7 +260,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] "Aciclovir"</span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -379,9 +274,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/av_synonyms.html b/reference/av_synonyms.html
new file mode 100644
index 000000000..ce5470f8a
--- /dev/null
+++ b/reference/av_synonyms.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/av_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/av_property.html">
+  </head>
+</html>
+
diff --git a/reference/av_tradenames.html b/reference/av_tradenames.html
new file mode 100644
index 000000000..ce5470f8a
--- /dev/null
+++ b/reference/av_tradenames.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/av_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/av_property.html">
+  </head>
+</html>
+
diff --git a/reference/av_url.html b/reference/av_url.html
new file mode 100644
index 000000000..ce5470f8a
--- /dev/null
+++ b/reference/av_url.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/av_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/av_property.html">
+  </head>
+</html>
+
diff --git a/reference/availability.html b/reference/availability.html
index 3d351a417..63fc0d530 100644
--- a/reference/availability.html
+++ b/reference/availability.html
@@ -1,161 +1,55 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Easy check for data availability of all columns in a data set. This makes it easy to get an idea of which antimicrobial combinations can be used for calculation with e.g. susceptibility() and resistance()."><title>Check Availability of Columns — availability • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Check Availability of Columns — availability"><meta property="og:description" content="Easy check for data availability of all columns in a data set. This makes it easy to get an idea of which antimicrobial combinations can be used for calculation with e.g. susceptibility() and resistance()."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Check Availability of Columns — availability • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Check Availability of Columns — availability"><meta name="description" content="Easy check for data availability of all columns in a data set. This makes it easy to get an idea of which antimicrobial combinations can be used for calculation with e.g. susceptibility() and resistance()."><meta property="og:description" content="Easy check for data availability of all columns in a data set. This makes it easy to get an idea of which antimicrobial combinations can be used for calculation with e.g. susceptibility() and resistance()."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"></head><body>
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-    
 
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+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9061</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9063</small>
+
 
-    
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
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-       
-      Set User- Or Team-specific Package Settings
-    </a>
-    <a class="dropdown-item" href="../articles/PCA.html">
-      <span class="fa fa-compress"></span>
-       
-      Conduct Principal Component Analysis for AMR
-    </a>
-    <a class="dropdown-item" href="../articles/MDR.html">
-      <span class="fa fa-skull-crossbones"></span>
-       
-      Determine Multi-Drug Resistance (MDR)
-    </a>
-    <a class="dropdown-item" href="../articles/WHONET.html">
-      <span class="fa fa-globe-americas"></span>
-       
-      Work with WHONET Data
-    </a>
-    <a class="dropdown-item" href="../articles/EUCAST.html">
-      <span class="fa fa-exchange-alt"></span>
-       
-      Apply Eucast Rules
-    </a>
-    <a class="dropdown-item" href="../reference/mo_property.html">
-      <span class="fa fa-bug"></span>
-       
-      Get Taxonomy of a Microorganism
-    </a>
-    <a class="dropdown-item" href="../reference/ab_property.html">
-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antibiotic Drug
-    </a>
-    <a class="dropdown-item" href="../reference/av_property.html">
-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antiviral Drug
-    </a>
-  </div>
-</li>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-how-to" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-question-circle"></span> How to</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to"><li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul></li>
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--with-other-pkgs">
-    <span class="fa fa-layer-group"></span>
-     
-    With other pkgs
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--with-other-pkgs">
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; dplyr/tidyverse
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; data.table
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; tidymodels
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; base R
-    </a>
-  </div>
-</li>
-<li class="active nav-item">
-  <a class="nav-link" href="../reference/index.html">
-    <span class="fa fa-book-open"></span>
-     
-    Manual
-  </a>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../authors.html">
-    <span class="fa fa-users"></span>
-     
-    Authors
-  </a>
-</li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
-  <a class="nav-link" href="../news/index.html">
-    <span class="far fa far fa-newspaper"></span>
-     
-    Changelog
-  </a>
-</li>
-<li class="nav-item">
-  <a class="external-link nav-link" href="https://github.com/msberends/AMR">
-    <span class="fab fa fab fa-github"></span>
-     
-    Source Code
-  </a>
-</li>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Check Availability of Columns</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/availability.R" class="external-link"><code>R/availability.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/availability.R" class="external-link"><code>R/availability.R</code></a></small>
       <div class="d-none name"><code>availability.Rd</code></div>
     </div>
 
@@ -170,19 +64,19 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>tbl</dt>
+
+
+<dl><dt id="arg-tbl">tbl<a class="anchor" aria-label="anchor" href="#arg-tbl"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> or <a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></p></dd>
 
 
-<dt>width</dt>
+<dt id="arg-width">width<a class="anchor" aria-label="anchor" href="#arg-width"></a></dt>
 <dd><p>number of characters to present the visual availability - the default is filling the width of the console</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with column names of <code>tbl</code> as row names</p>
+    <p><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with column names of <code>tbl</code> as row names</p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -290,7 +184,7 @@
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -304,9 +198,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/betalactams.html b/reference/betalactams.html
new file mode 100644
index 000000000..07f8b21e2
--- /dev/null
+++ b/reference/betalactams.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html">
+  </head>
+</html>
+
diff --git a/reference/brmo.html b/reference/brmo.html
new file mode 100644
index 000000000..9ccef1b51
--- /dev/null
+++ b/reference/brmo.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mdro.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/mdro.html">
+  </head>
+</html>
+
diff --git a/reference/bug_drug_combinations.html b/reference/bug_drug_combinations.html
index fa677adab..08be74686 100644
--- a/reference/bug_drug_combinations.html
+++ b/reference/bug_drug_combinations.html
@@ -1,161 +1,55 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Determine antimicrobial resistance (AMR) of all bug-drug combinations in your data set where at least 30 (default) isolates are available per species. Use format() on the result to prettify it to a publishable/printable format, see Examples."><title>Determine Bug-Drug Combinations — bug_drug_combinations • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Determine Bug-Drug Combinations — bug_drug_combinations"><meta property="og:description" content="Determine antimicrobial resistance (AMR) of all bug-drug combinations in your data set where at least 30 (default) isolates are available per species. Use format() on the result to prettify it to a publishable/printable format, see Examples."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Determine Bug-Drug Combinations — bug_drug_combinations • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Determine Bug-Drug Combinations — bug_drug_combinations"><meta name="description" content="Determine antimicrobial resistance (AMR) of all bug-drug combinations in your data set where at least 30 (default) isolates are available per species. Use format() on the result to prettify it to a publishable/printable format, see Examples."><meta property="og:description" content="Determine antimicrobial resistance (AMR) of all bug-drug combinations in your data set where at least 30 (default) isolates are available per species. Use format() on the result to prettify it to a publishable/printable format, see Examples."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"></head><body>
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+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
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-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9061</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9063</small>
+
 
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-      Get Properties of an Antibiotic Drug
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+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul></li>
 <li class="nav-item dropdown">
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-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
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+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Determine Bug-Drug Combinations</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/bug_drug_combinations.R" class="external-link"><code>R/bug_drug_combinations.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/bug_drug_combinations.R" class="external-link"><code>R/bug_drug_combinations.R</code></a></small>
       <div class="d-none name"><code>bug_drug_combinations.Rd</code></div>
     </div>
 
@@ -167,7 +61,7 @@
     <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">bug_drug_combinations</span><span class="op">(</span><span class="va">x</span>, col_mo <span class="op">=</span> <span class="cn">NULL</span>, FUN <span class="op">=</span> <span class="va">mo_shortname</span>, <span class="va">...</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for bug_drug_combinations</span></span>
+<span><span class="co"># S3 method for class 'bug_drug_combinations'</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/format.html" class="external-link">format</a></span><span class="op">(</span></span>
 <span>  <span class="va">x</span>,</span>
 <span>  translate_ab <span class="op">=</span> <span class="st">"name (ab, atc)"</span>,</span>
@@ -184,52 +78,54 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>a data set with antibiotic columns, such as <code>amox</code>, <code>AMX</code> and <code>AMC</code></p></dd>
 
 
-<dt>col_mo</dt>
+<dt id="arg-col-mo">col_mo<a class="anchor" aria-label="anchor" href="#arg-col-mo"></a></dt>
 <dd><p>column name of the names or codes of the microorganisms (see <code><a href="as.mo.html">as.mo()</a></code>) - the default is the first column of class <code><a href="as.mo.html">mo</a></code>. Values will be coerced using <code><a href="as.mo.html">as.mo()</a></code>.</p></dd>
 
 
-<dt>FUN</dt>
+<dt id="arg-fun">FUN<a class="anchor" aria-label="anchor" href="#arg-fun"></a></dt>
 <dd><p>the function to call on the <code>mo</code> column to transform the microorganism codes - the default is <code><a href="mo_property.html">mo_shortname()</a></code></p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>arguments passed on to <code>FUN</code></p></dd>
 
 
-<dt>translate_ab</dt>
+<dt id="arg-translate-ab">translate_ab<a class="anchor" aria-label="anchor" href="#arg-translate-ab"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> of length 1 containing column names of the <a href="antibiotics.html">antibiotics</a> data set</p></dd>
 
 
-<dt>language</dt>
+<dt id="arg-language">language<a class="anchor" aria-label="anchor" href="#arg-language"></a></dt>
 <dd><p>language of the returned text - the default is the current system language (see <code><a href="translate.html">get_AMR_locale()</a></code>) and can also be set with the <a href="AMR-options.html">package option</a> <code><a href="AMR-options.html">AMR_locale</a></code>. Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></dd>
 
 
-<dt>minimum</dt>
+<dt id="arg-minimum">minimum<a class="anchor" aria-label="anchor" href="#arg-minimum"></a></dt>
 <dd><p>the minimum allowed number of available (tested) isolates. Any isolate count lower than <code>minimum</code> will return <code>NA</code> with a warning. The default number of <code>30</code> isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see <em>Source</em>.</p></dd>
 
 
-<dt>combine_SI</dt>
+<dt id="arg-combine-si">combine_SI<a class="anchor" aria-label="anchor" href="#arg-combine-si"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether values S and I should be summed, so resistance will be based on only R - the default is <code>TRUE</code></p></dd>
 
 
-<dt>add_ab_group</dt>
+<dt id="arg-add-ab-group">add_ab_group<a class="anchor" aria-label="anchor" href="#arg-add-ab-group"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate where the group of the antimicrobials must be included as a first column</p></dd>
 
 
-<dt>remove_intrinsic_resistant</dt>
+<dt id="arg-remove-intrinsic-resistant">remove_intrinsic_resistant<a class="anchor" aria-label="anchor" href="#arg-remove-intrinsic-resistant"></a></dt>
 <dd><p><a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate that rows and columns with 100% resistance for all tested antimicrobials must be removed from the table</p></dd>
 
 
-<dt>decimal.mark</dt>
+<dt id="arg-decimal-mark">decimal.mark<a class="anchor" aria-label="anchor" href="#arg-decimal-mark"></a></dt>
 <dd><p>the character to be used to indicate the numeric
     decimal point.</p></dd>
 
 
-<dt>big.mark</dt>
+<dt id="arg-big-mark">big.mark<a class="anchor" aria-label="anchor" href="#arg-big-mark"></a></dt>
 <dd><p>character; if not empty used as mark between every
     <code>big.interval</code> decimals <em>before</em> (hence <code>big</code>) the
     decimal point.</p></dd>
@@ -237,9 +133,7 @@
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>The function <code>bug_drug_combinations()</code> returns a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with columns "mo", "ab", "S", "SDD", "I", "R", and "total".</p>
+    <p>The function <code>bug_drug_combinations()</code> returns a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with columns "mo", "ab", "S", "SDD", "I", "R", and "total".</p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -349,7 +243,7 @@
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -363,9 +257,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/carbapenems.html b/reference/carbapenems.html
new file mode 100644
index 000000000..07f8b21e2
--- /dev/null
+++ b/reference/carbapenems.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html">
+  </head>
+</html>
+
diff --git a/reference/cephalosporins.html b/reference/cephalosporins.html
new file mode 100644
index 000000000..07f8b21e2
--- /dev/null
+++ b/reference/cephalosporins.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html">
+  </head>
+</html>
+
diff --git a/reference/cephalosporins_1st.html b/reference/cephalosporins_1st.html
new file mode 100644
index 000000000..07f8b21e2
--- /dev/null
+++ b/reference/cephalosporins_1st.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html">
+  </head>
+</html>
+
diff --git a/reference/cephalosporins_2nd.html b/reference/cephalosporins_2nd.html
new file mode 100644
index 000000000..07f8b21e2
--- /dev/null
+++ b/reference/cephalosporins_2nd.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html">
+  </head>
+</html>
+
diff --git a/reference/cephalosporins_3rd.html b/reference/cephalosporins_3rd.html
new file mode 100644
index 000000000..07f8b21e2
--- /dev/null
+++ b/reference/cephalosporins_3rd.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html">
+  </head>
+</html>
+
diff --git a/reference/cephalosporins_4th.html b/reference/cephalosporins_4th.html
new file mode 100644
index 000000000..07f8b21e2
--- /dev/null
+++ b/reference/cephalosporins_4th.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html">
+  </head>
+</html>
+
diff --git a/reference/cephalosporins_5th.html b/reference/cephalosporins_5th.html
new file mode 100644
index 000000000..07f8b21e2
--- /dev/null
+++ b/reference/cephalosporins_5th.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html">
+  </head>
+</html>
+
diff --git a/reference/clear_custom_antimicrobials.html b/reference/clear_custom_antimicrobials.html
new file mode 100644
index 000000000..1b174b305
--- /dev/null
+++ b/reference/clear_custom_antimicrobials.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/add_custom_antimicrobials.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/add_custom_antimicrobials.html">
+  </head>
+</html>
+
diff --git a/reference/clear_custom_microorganisms.html b/reference/clear_custom_microorganisms.html
new file mode 100644
index 000000000..5c2ab8b7b
--- /dev/null
+++ b/reference/clear_custom_microorganisms.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/add_custom_microorganisms.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/add_custom_microorganisms.html">
+  </head>
+</html>
+
diff --git a/reference/clinical_breakpoints.html b/reference/clinical_breakpoints.html
index c6544c6f4..d96267898 100644
--- a/reference/clinical_breakpoints.html
+++ b/reference/clinical_breakpoints.html
@@ -1,167 +1,61 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Data set containing clinical breakpoints to interpret MIC and disk diffusion to SIR values, according to international guidelines. This dataset contain breakpoints for humans, 7 different animal groups, and ECOFFs.
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints"><meta name="description" content="Data set containing clinical breakpoints to interpret MIC and disk diffusion to SIR values, according to international guidelines. This dataset contain breakpoints for humans, 7 different animal groups, and ECOFFs.
 Currently available breakpoint guidelines for clinical microbiology are EUCAST 2011-2024 and CLSI 2011-2024.
 Currently available breakpoint guidelines for veterinary microbiology are EUCAST 2021-2024 and CLSI 2019-2024.
-Use as.sir() to transform MICs or disks measurements to SIR values."><title>Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints"><meta property="og:description" content="Data set containing clinical breakpoints to interpret MIC and disk diffusion to SIR values, according to international guidelines. This dataset contain breakpoints for humans, 7 different animal groups, and ECOFFs.
+Use as.sir() to transform MICs or disks measurements to SIR values."><meta property="og:description" content="Data set containing clinical breakpoints to interpret MIC and disk diffusion to SIR values, according to international guidelines. This dataset contain breakpoints for humans, 7 different animal groups, and ECOFFs.
 Currently available breakpoint guidelines for clinical microbiology are EUCAST 2011-2024 and CLSI 2011-2024.
 Currently available breakpoint guidelines for veterinary microbiology are EUCAST 2021-2024 and CLSI 2019-2024.
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       <img src="../logo.svg" class="logo" alt=""><h1>Data Set with Clinical Breakpoints for SIR Interpretation</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/data.R" class="external-link"><code>R/data.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/data.R" class="external-link"><code>R/data.R</code></a></small>
       <div class="d-none name"><code>clinical_breakpoints.Rd</code></div>
     </div>
 
@@ -196,7 +90,7 @@ Use as.sir() to transform MICs or disks measurements to SIR values."><meta prope
 </ul></div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
-    
+
 <div class="section">
 <h3 id="different-types-of-breakpoints">Different types of breakpoints<a class="anchor" aria-label="anchor" href="#different-types-of-breakpoints"></a></h3>
 
@@ -254,7 +148,7 @@ Use as.sir() to transform MICs or disks measurements to SIR values."><meta prope
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   uti &lt;lgl&gt;, is_SDD &lt;lgl&gt;</span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -268,9 +162,9 @@ Use as.sir() to transform MICs or disks measurements to SIR values."><meta prope
 
     </footer></div>
 
-  
 
-  
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diff --git a/reference/count.html b/reference/count.html
index 7d7ef098f..b09e7ca34 100644
--- a/reference/count.html
+++ b/reference/count.html
@@ -1,163 +1,57 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in summarise() from the dplyr package and also support grouped variables, see Examples.
-count_resistant() should be used to count resistant isolates, count_susceptible() should be used to count susceptible isolates."><title>Count Available Isolates — count • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Count Available Isolates — count"><meta property="og:description" content="These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in summarise() from the dplyr package and also support grouped variables, see Examples.
-count_resistant() should be used to count resistant isolates, count_susceptible() should be used to count susceptible isolates."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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+count_resistant() should be used to count resistant isolates, count_susceptible() should be used to count susceptible isolates."><meta property="og:description" content="These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in summarise() from the dplyr package and also support grouped variables, see Examples.
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 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Count Available Isolates</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/count.R" class="external-link"><code>R/count.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/count.R" class="external-link"><code>R/count.R</code></a></small>
       <div class="d-none name"><code>count.Rd</code></div>
     </div>
 
@@ -196,37 +90,35 @@ count_resistant() should be used to count resistant isolates, count_susceptible(
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>...</dt>
+
+
+<dl><dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with <code><a href="as.sir.html">as.sir()</a></code> if needed.</p></dd>
 
 
-<dt>only_all_tested</dt>
+<dt id="arg-only-all-tested">only_all_tested<a class="anchor" aria-label="anchor" href="#arg-only-all-tested"></a></dt>
 <dd><p>(for combination therapies, i.e. using more than one variable for <code>...</code>): a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate that isolates must be tested for all antibiotics, see section <em>Combination Therapy</em> below</p></dd>
 
 
-<dt>data</dt>
+<dt id="arg-data">data<a class="anchor" aria-label="anchor" href="#arg-data"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> containing columns with class <code><a href="as.sir.html">sir</a></code> (see <code><a href="as.sir.html">as.sir()</a></code>)</p></dd>
 
 
-<dt>translate_ab</dt>
+<dt id="arg-translate-ab">translate_ab<a class="anchor" aria-label="anchor" href="#arg-translate-ab"></a></dt>
 <dd><p>a column name of the <a href="antibiotics.html">antibiotics</a> data set to translate the antibiotic abbreviations to, using <code><a href="ab_property.html">ab_property()</a></code></p></dd>
 
 
-<dt>language</dt>
+<dt id="arg-language">language<a class="anchor" aria-label="anchor" href="#arg-language"></a></dt>
 <dd><p>language of the returned text - the default is the current system language (see <code><a href="translate.html">get_AMR_locale()</a></code>) and can also be set with the <a href="AMR-options.html">package option</a> <code><a href="AMR-options.html">AMR_locale</a></code>. Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></dd>
 
 
-<dt>combine_SI</dt>
+<dt id="arg-combine-si">combine_SI<a class="anchor" aria-label="anchor" href="#arg-combine-si"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether all values of S and I must be merged into one, so the output only consists of S+I vs. R (susceptible vs. resistant) - the default is <code>TRUE</code></p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>An <a href="https://rdrr.io/r/base/integer.html" class="external-link">integer</a></p>
-
-
+    <p>An <a href="https://rdrr.io/r/base/integer.html" class="external-link">integer</a></p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -237,7 +129,7 @@ count_resistant() should be used to count resistant isolates, count_susceptible(
     </div>
     <div class="section level2">
     <h2 id="interpretation-of-sir">Interpretation of SIR<a class="anchor" aria-label="anchor" href="#interpretation-of-sir"></a></h2>
-    
+
 
 <p>In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories S, I, and R as shown below (<a href="https://www.eucast.org/newsiandr" class="external-link">https://www.eucast.org/newsiandr</a>):</p><ul><li><p><strong>S - Susceptible, standard dosing regimen</strong><br>
 A microorganism is categorised as "Susceptible, standard dosing regimen", when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.</p></li>
@@ -250,7 +142,7 @@ A microorganism is categorised as "Resistant" when there is a high likelihood of
     </div>
     <div class="section level2">
     <h2 id="combination-therapy">Combination Therapy<a class="anchor" aria-label="anchor" href="#combination-therapy"></a></h2>
-    
+
 
 <p>When using more than one variable for <code>...</code> (= combination therapy), use <code>only_all_tested</code> to only count isolates that are tested for all antibiotics/variables that you test them for. See this example for two antibiotics, Drug A and Drug B, about how <code><a href="proportion.html">susceptibility()</a></code> works to calculate the %SI:</p>
 <p></p><div class="sourceCode"><pre><code><span id="cb1-1"><a href="#cb1-1" tabindex="-1"></a><span class="sc">--------------------------------------------------------------------</span></span>
@@ -395,7 +287,7 @@ A microorganism is categorised as "Resistant" when there is a high likelihood of
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -409,9 +301,9 @@ A microorganism is categorised as "Resistant" when there is a high likelihood of
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/count_I.html b/reference/count_I.html
new file mode 100644
index 000000000..c15e60ab1
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+++ b/reference/count_I.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/count.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/count.html">
+  </head>
+</html>
+
diff --git a/reference/count_IR.html b/reference/count_IR.html
new file mode 100644
index 000000000..c15e60ab1
--- /dev/null
+++ b/reference/count_IR.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/count.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/count.html">
+  </head>
+</html>
+
diff --git a/reference/count_R.html b/reference/count_R.html
new file mode 100644
index 000000000..c15e60ab1
--- /dev/null
+++ b/reference/count_R.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/count.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/count.html">
+  </head>
+</html>
+
diff --git a/reference/count_S.html b/reference/count_S.html
new file mode 100644
index 000000000..c15e60ab1
--- /dev/null
+++ b/reference/count_S.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/count.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/count.html">
+  </head>
+</html>
+
diff --git a/reference/count_SI.html b/reference/count_SI.html
new file mode 100644
index 000000000..c15e60ab1
--- /dev/null
+++ b/reference/count_SI.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/count.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/count.html">
+  </head>
+</html>
+
diff --git a/reference/count_all.html b/reference/count_all.html
new file mode 100644
index 000000000..c15e60ab1
--- /dev/null
+++ b/reference/count_all.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/count.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/count.html">
+  </head>
+</html>
+
diff --git a/reference/count_df.html b/reference/count_df.html
new file mode 100644
index 000000000..c15e60ab1
--- /dev/null
+++ b/reference/count_df.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/count.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/count.html">
+  </head>
+</html>
+
diff --git a/reference/count_resistant.html b/reference/count_resistant.html
new file mode 100644
index 000000000..c15e60ab1
--- /dev/null
+++ b/reference/count_resistant.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/count.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/count.html">
+  </head>
+</html>
+
diff --git a/reference/count_susceptible.html b/reference/count_susceptible.html
new file mode 100644
index 000000000..c15e60ab1
--- /dev/null
+++ b/reference/count_susceptible.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/count.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/count.html">
+  </head>
+</html>
+
diff --git a/reference/custom_eucast_rules.html b/reference/custom_eucast_rules.html
index 9723b4d86..9e946ec15 100644
--- a/reference/custom_eucast_rules.html
+++ b/reference/custom_eucast_rules.html
@@ -1,161 +1,55 @@
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       <img src="../logo.svg" class="logo" alt=""><h1>Define Custom EUCAST Rules</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/custom_eucast_rules.R" class="external-link"><code>R/custom_eucast_rules.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/custom_eucast_rules.R" class="external-link"><code>R/custom_eucast_rules.R</code></a></small>
       <div class="d-none name"><code>custom_eucast_rules.Rd</code></div>
     </div>
 
@@ -170,15 +64,15 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>...</dt>
+
+
+<dl><dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>rules in <a href="https://rdrr.io/r/base/tilde.html" class="external-link">formula</a> notation, see below for instructions, and in <em>Examples</em></p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A <a href="https://rdrr.io/r/base/list.html" class="external-link">list</a> containing the custom rules</p>
+    <p>A <a href="https://rdrr.io/r/base/list.html" class="external-link">list</a> containing the custom rules</p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -186,7 +80,7 @@
     </div>
     <div class="section level2">
     <h2 id="how-it-works">How it works<a class="anchor" aria-label="anchor" href="#how-it-works"></a></h2>
-    
+
 
 <div class="section">
 <h3 id="basics">Basics<a class="anchor" aria-label="anchor" href="#basics"></a></h3>
@@ -224,7 +118,7 @@
 <h3 id="using-taxonomic-properties-in-rules">Using taxonomic properties in rules<a class="anchor" aria-label="anchor" href="#using-taxonomic-properties-in-rules"></a></h3>
 
 
-<p>There is one exception in columns used for the rules: all column names of the <a href="microorganisms.html">microorganisms</a> data set can also be used, but do not have to exist in the data set. These column names are: "mo", "fullname", "status", "kingdom", "phylum", "class", "order", "family", "genus", "species", "subspecies", "rank", "ref", "oxygen_tolerance", "source", "lpsn", "lpsn_parent", "lpsn_renamed_to", "gbif", "gbif_parent", "gbif_renamed_to", "prevalence", and "snomed". Thus, this next example will work as well, despite the fact that the <code>df</code> data set does not contain a column <code>genus</code>:</p>
+<p>There is one exception in columns used for the rules: all column names of the <a href="microorganisms.html">microorganisms</a> data set can also be used, but do not have to exist in the data set. These column names are: "mo", "fullname", "status", "kingdom", "phylum", "class", "order", "family", "genus", "species", "subspecies", "rank", "ref", "oxygen_tolerance", "source", "lpsn", "lpsn_parent", "lpsn_renamed_to", "mycobank", "mycobank_parent", "mycobank_renamed_to", "gbif", "gbif_parent", "gbif_renamed_to", "prevalence", and "snomed". Thus, this next example will work as well, despite the fact that the <code>df</code> data set does not contain a column <code>genus</code>:</p>
 <p></p><div class="sourceCode r"><pre><code><span><span class="va">y</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/custom_eucast_rules.html">custom_eucast_rules</a></span><span class="op">(</span><span class="va">TZP</span> <span class="op">==</span> <span class="st">"S"</span> <span class="op">&amp;</span> <span class="va">genus</span> <span class="op">==</span> <span class="st">"Klebsiella"</span> <span class="op">~</span> <span class="va">aminopenicillins</span> <span class="op">==</span> <span class="st">"S"</span>,</span>
 <span>                         <span class="va">TZP</span> <span class="op">==</span> <span class="st">"R"</span> <span class="op">&amp;</span> <span class="va">genus</span> <span class="op">==</span> <span class="st">"Klebsiella"</span> <span class="op">~</span> <span class="va">aminopenicillins</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span></span>
 <span></span>
@@ -243,7 +137,7 @@
 <p></p><div class="sourceCode r"><pre><code><span><span class="va">x</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/custom_eucast_rules.html">custom_eucast_rules</a></span><span class="op">(</span><span class="va">TZP</span> <span class="op">==</span> <span class="st">"R"</span> <span class="op">~</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="va">aminopenicillins</span>, <span class="va">ureidopenicillins</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span></span>
 <span><span class="va">x</span></span>
 <span><span class="co">#&gt; A set of custom EUCAST rules:</span></span>
-<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt;</span></span>
 <span><span class="co">#&gt;   1. If TZP is "R" then set to "R":</span></span>
 <span><span class="co">#&gt;      amoxicillin (AMX), ampicillin (AMP), azlocillin (AZL), mezlocillin (MEZ), piperacillin (PIP), piperacillin/tazobactam (TZP)</span></span></code></pre><p></p></div>
 <p>These 30 antibiotic groups are allowed in the rules (case-insensitive) and can be used in any combination:</p><ul><li><p>aminoglycosides<br>(amikacin, amikacin/fosfomycin, apramycin, arbekacin, astromicin, bekanamycin, dibekacin, framycetin, gentamicin, gentamicin-high, habekacin, hygromycin, isepamicin, kanamycin, kanamycin-high, kanamycin/cephalexin, micronomicin, neomycin, netilmicin, pentisomicin, plazomicin, propikacin, ribostamycin, sisomicin, streptoduocin, streptomycin, streptomycin-high, tobramycin, and tobramycin-high)</p></li>
@@ -335,7 +229,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span>      razupenem (RZM), ritipenem (RIT), ritipenem acoxil (RIA), tebipenem (TBP)</span>
 </code></pre></div>
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+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
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       <div class="d-none name"><code>dosage.Rd</code></div>
     </div>
 
@@ -205,7 +99,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 1 more variable: eucast_version &lt;dbl&gt;</span></span>
 </code></pre></div>
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new file mode 100644
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@@ -0,0 +1,8 @@
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new file mode 100644
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index be3bb8720..b812786c1 100644
--- a/reference/eucast_rules.html
+++ b/reference/eucast_rules.html
@@ -1,163 +1,57 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Apply rules for clinical breakpoints and intrinsic resistance as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, https://www.eucast.org), see Source. Use eucast_dosage() to get a data.frame with advised dosages of a certain bug-drug combination, which is based on the dosage data set.
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+To improve the interpretation of the antibiogram before EUCAST rules are applied, some non-EUCAST rules can applied at default, see Details."><meta property="og:description" content="Apply rules for clinical breakpoints and intrinsic resistance as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, https://www.eucast.org), see Source. Use eucast_dosage() to get a data.frame with advised dosages of a certain bug-drug combination, which is based on the dosage data set.
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       <img src="../logo.svg" class="logo" alt=""><h1>Apply EUCAST Rules</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/eucast_rules.R" class="external-link"><code>R/eucast_rules.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/eucast_rules.R" class="external-link"><code>R/eucast_rules.R</code></a></small>
       <div class="d-none name"><code>eucast_rules.Rd</code></div>
     </div>
 
@@ -187,7 +81,7 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
 
     <div class="section level2">
     <h2 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a></h2>
-    
+
 <ul><li><p>EUCAST Expert Rules. Version 2.0, 2012.<br>
 Leclercq et al. <strong>EUCAST expert rules in antimicrobial susceptibility testing.</strong> <em>Clin Microbiol Infect.</em> 2013;19(2):141-60; <a href="https://doi.org/10.1111/j.1469-0691.2011.03703.x" class="external-link">doi:10.1111/j.1469-0691.2011.03703.x</a></p></li>
 <li><p>EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes Tables. Version 3.1, 2016. <a href="https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf" class="external-link">(link)</a></p></li>
@@ -200,68 +94,68 @@ Leclercq et al. <strong>EUCAST expert rules in antimicrobial susceptibility test
 </ul></div>
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>a data set with antibiotic columns, such as <code>amox</code>, <code>AMX</code> and <code>AMC</code></p></dd>
 
 
-<dt>col_mo</dt>
+<dt id="arg-col-mo">col_mo<a class="anchor" aria-label="anchor" href="#arg-col-mo"></a></dt>
 <dd><p>column name of the names or codes of the microorganisms (see <code><a href="as.mo.html">as.mo()</a></code>) - the default is the first column of class <code><a href="as.mo.html">mo</a></code>. Values will be coerced using <code><a href="as.mo.html">as.mo()</a></code>.</p></dd>
 
 
-<dt>info</dt>
+<dt id="arg-info">info<a class="anchor" aria-label="anchor" href="#arg-info"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether progress should be printed to the console - the default is only print while in interactive sessions</p></dd>
 
 
-<dt>rules</dt>
+<dt id="arg-rules">rules<a class="anchor" aria-label="anchor" href="#arg-rules"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector that specifies which rules should be applied. Must be one or more of <code>"breakpoints"</code>, <code>"expert"</code>, <code>"other"</code>, <code>"custom"</code>, <code>"all"</code>, and defaults to <code>c("breakpoints", "expert")</code>. The default value can be set to another value using the <a href="AMR-options.html">package option</a> <code><a href="AMR-options.html">AMR_eucastrules</a></code>: <code>options(AMR_eucastrules = "all")</code>. If using <code>"custom"</code>, be sure to fill in argument <code>custom_rules</code> too. Custom rules can be created with <code><a href="custom_eucast_rules.html">custom_eucast_rules()</a></code>.</p></dd>
 
 
-<dt>verbose</dt>
+<dt id="arg-verbose">verbose<a class="anchor" aria-label="anchor" href="#arg-verbose"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to turn Verbose mode on and off (default is off). In Verbose mode, the function does not apply rules to the data, but instead returns a data set in logbook form with extensive info about which rows and columns would be effected and in which way. Using Verbose mode takes a lot more time.</p></dd>
 
 
-<dt>version_breakpoints</dt>
+<dt id="arg-version-breakpoints">version_breakpoints<a class="anchor" aria-label="anchor" href="#arg-version-breakpoints"></a></dt>
 <dd><p>the version number to use for the EUCAST Clinical Breakpoints guideline. Can be "12.0", "11.0", or "10.0".</p></dd>
 
 
-<dt>version_expertrules</dt>
+<dt id="arg-version-expertrules">version_expertrules<a class="anchor" aria-label="anchor" href="#arg-version-expertrules"></a></dt>
 <dd><p>the version number to use for the EUCAST Expert Rules and Intrinsic Resistance guideline. Can be "3.3", "3.2", or "3.1".</p></dd>
 
 
-<dt>ampc_cephalosporin_resistance</dt>
+<dt id="arg-ampc-cephalosporin-resistance">ampc_cephalosporin_resistance<a class="anchor" aria-label="anchor" href="#arg-ampc-cephalosporin-resistance"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> value that should be applied to cefotaxime, ceftriaxone and ceftazidime for AmpC de-repressed cephalosporin-resistant mutants - the default is <code>NA</code>. Currently only works when <code>version_expertrules</code> is <code>3.2</code> and higher; these version of '<em>EUCAST Expert Rules on Enterobacterales</em>' state that results of cefotaxime, ceftriaxone and ceftazidime should be reported with a note, or results should be suppressed (emptied) for these three drugs. A value of <code>NA</code> (the default) for this argument will remove results for these three drugs, while e.g. a value of <code>"R"</code> will make the results for these drugs resistant. Use <code>NULL</code> or <code>FALSE</code> to not alter results for these three drugs of AmpC de-repressed cephalosporin-resistant mutants. Using <code>TRUE</code> is equal to using <code>"R"</code>. <br> For <em>EUCAST Expert Rules</em> v3.2, this rule applies to: <em>Citrobacter braakii</em>, <em>Citrobacter freundii</em>, <em>Citrobacter gillenii</em>, <em>Citrobacter murliniae</em>, <em>Citrobacter rodenticum</em>, <em>Citrobacter sedlakii</em>, <em>Citrobacter werkmanii</em>, <em>Citrobacter youngae</em>, <em>Enterobacter</em>, <em>Hafnia alvei</em>, <em>Klebsiella aerogenes</em>, <em>Morganella morganii</em>, <em>Providencia</em>, and <em>Serratia</em>.</p></dd>
 
 
-<dt>only_sir_columns</dt>
+<dt id="arg-only-sir-columns">only_sir_columns<a class="anchor" aria-label="anchor" href="#arg-only-sir-columns"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether only antibiotic columns must be detected that were transformed to class <code>sir</code> (see <code><a href="as.sir.html">as.sir()</a></code>) on beforehand (default is <code>FALSE</code>)</p></dd>
 
 
-<dt>custom_rules</dt>
+<dt id="arg-custom-rules">custom_rules<a class="anchor" aria-label="anchor" href="#arg-custom-rules"></a></dt>
 <dd><p>custom rules to apply, created with <code><a href="custom_eucast_rules.html">custom_eucast_rules()</a></code></p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>column name of an antibiotic, see section <em>Antibiotics</em> below</p></dd>
 
 
-<dt>ab</dt>
+<dt id="arg-ab">ab<a class="anchor" aria-label="anchor" href="#arg-ab"></a></dt>
 <dd><p>any (vector of) text that can be coerced to a valid antibiotic drug code with <code><a href="as.ab.html">as.ab()</a></code></p></dd>
 
 
-<dt>administration</dt>
+<dt id="arg-administration">administration<a class="anchor" aria-label="anchor" href="#arg-administration"></a></dt>
 <dd><p>route of administration, either "im", "iv", or "oral"</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>The input of <code>x</code>, possibly with edited values of antibiotics. Or, if <code>verbose = TRUE</code>, a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with all original and new values of the affected bug-drug combinations.</p>
+    <p>The input of <code>x</code>, possibly with edited values of antibiotics. Or, if <code>verbose = TRUE</code>, a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with all original and new values of the affected bug-drug combinations.</p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
     <p><strong>Note:</strong> This function does not translate MIC values to SIR values. Use <code><a href="as.sir.html">as.sir()</a></code> for that. <br><strong>Note:</strong> When ampicillin (AMP, J01CA01) is not available but amoxicillin (AMX, J01CA04) is, the latter will be used for all rules where there is a dependency on ampicillin. These drugs are interchangeable when it comes to expression of antimicrobial resistance. <br></p>
-<p>The file containing all EUCAST rules is located here: <a href="https://github.com/msberends/AMR/blob/main/data-raw/eucast_rules.tsv" class="external-link">https://github.com/msberends/AMR/blob/main/data-raw/eucast_rules.tsv</a>.  <strong>Note:</strong> Old taxonomic names are replaced with the current taxonomy where applicable. For example, <em>Ochrobactrum anthropi</em> was renamed to <em>Brucella anthropi</em> in 2020; the original EUCAST rules v3.1 and v3.2 did not yet contain this new taxonomic name. The <code>AMR</code> package contains the full microbial taxonomy updated until January 8th, 2024, see <a href="microorganisms.html">microorganisms</a>.</p><div class="section">
+<p>The file containing all EUCAST rules is located here: <a href="https://github.com/msberends/AMR/blob/main/data-raw/eucast_rules.tsv" class="external-link">https://github.com/msberends/AMR/blob/main/data-raw/eucast_rules.tsv</a>.  <strong>Note:</strong> Old taxonomic names are replaced with the current taxonomy where applicable. For example, <em>Ochrobactrum anthropi</em> was renamed to <em>Brucella anthropi</em> in 2020; the original EUCAST rules v3.1 and v3.2 did not yet contain this new taxonomic name. The <code>AMR</code> package contains the full microbial taxonomy updated until June 24th, 2024, see <a href="microorganisms.html">microorganisms</a>.</p><div class="section">
 <h3 id="custom-rules">Custom Rules<a class="anchor" aria-label="anchor" href="#custom-rules"></a></h3>
 
 
@@ -285,7 +179,7 @@ Leclercq et al. <strong>EUCAST expert rules in antimicrobial susceptibility test
     </div>
     <div class="section level2">
     <h2 id="antibiotics">Antibiotics<a class="anchor" aria-label="anchor" href="#antibiotics"></a></h2>
-    
+
 
 <p>To define antibiotics column names, leave as it is to determine it automatically with <code><a href="guess_ab_col.html">guess_ab_col()</a></code> or input a text (case-insensitive), or use <code>NULL</code> to skip a column (e.g. <code>TIC = NULL</code> to skip ticarcillin). Manually defined but non-existing columns will be skipped with a warning.</p>
 <p>The following antibiotics are eligible for the functions <code>eucast_rules()</code> and <code><a href="mdro.html">mdro()</a></code>. These are shown below in the format 'name (<code>antimicrobial ID</code>, <a href="https://atcddd.fhi.no/atc/structure_and_principles/" class="external-link">ATC code</a>)', sorted alphabetically:</p>
@@ -293,7 +187,7 @@ Leclercq et al. <strong>EUCAST expert rules in antimicrobial susceptibility test
     </div>
     <div class="section level2">
     <h2 id="reference-data-publicly-available">Reference Data Publicly Available<a class="anchor" aria-label="anchor" href="#reference-data-publicly-available"></a></h2>
-    
+
 
 <p>All data sets in this <code>AMR</code> package (about microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) are publicly and freely available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. We also provide tab-separated plain text files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please visit <a href="https://msberends.github.io/AMR/articles/datasets.html">our website for the download links</a>. The actual files are of course available on <a href="https://github.com/msberends/AMR/tree/main/data-raw" class="external-link">our GitHub repository</a>.</p>
     </div>
@@ -400,7 +294,7 @@ Leclercq et al. <strong>EUCAST expert rules in antimicrobial susceptibility test
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> CIP  Ciprofloxacin 0.4 g x 2 iv     0.4 g x 3 iv</span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -414,9 +308,9 @@ Leclercq et al. <strong>EUCAST expert rules in antimicrobial susceptibility test
 
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-  
 
-  
+
+
 
   </body></html>
 
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index 52b7f29c5..50e2562f0 100644
--- a/reference/example_isolates.html
+++ b/reference/example_isolates.html
@@ -1,161 +1,55 @@
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul></div>
 
-    
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 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Data Set with 2 000 Example Isolates</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/data.R" class="external-link"><code>R/data.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/data.R" class="external-link"><code>R/data.R</code></a></small>
       <div class="d-none name"><code>example_isolates.Rd</code></div>
     </div>
 
@@ -208,7 +102,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   IPM &lt;sir&gt;, MEM &lt;sir&gt;, MTR &lt;sir&gt;, CHL &lt;sir&gt;, COL &lt;sir&gt;, MUP &lt;sir&gt;, …</span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -222,9 +116,9 @@
 
     </footer></div>
 
-  
 
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+
 
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diff --git a/reference/example_isolates_unclean.html b/reference/example_isolates_unclean.html
index 5d211b18d..353198358 100644
--- a/reference/example_isolates_unclean.html
+++ b/reference/example_isolates_unclean.html
@@ -1,161 +1,55 @@
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-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="A data set containing 3 000 microbial isolates that are not cleaned up and consequently not ready for AMR data analysis. This data set can be used for practice."><title>Data Set with Unclean Data — example_isolates_unclean • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Data Set with Unclean Data — example_isolates_unclean"><meta property="og:description" content="A data set containing 3 000 microbial isolates that are not cleaned up and consequently not ready for AMR data analysis. This data set can be used for practice."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
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+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
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 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Data Set with Unclean Data</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/data.R" class="external-link"><code>R/data.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/data.R" class="external-link"><code>R/data.R</code></a></small>
       <div class="d-none name"><code>example_isolates_unclean.Rd</code></div>
     </div>
 
@@ -200,7 +94,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 2,990 more rows</span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -214,9 +108,9 @@
 
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diff --git a/reference/export_ncbi_biosample.html b/reference/export_ncbi_biosample.html
index d8fb377a4..e6495befc 100644
--- a/reference/export_ncbi_biosample.html
+++ b/reference/export_ncbi_biosample.html
@@ -1,161 +1,55 @@
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       <img src="../logo.svg" class="logo" alt=""><h1>Export Data Set as NCBI BioSample Antibiogram</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/export_biosample.R" class="external-link"><code>R/export_biosample.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/export_biosample.R" class="external-link"><code>R/export_biosample.R</code></a></small>
       <div class="d-none name"><code>export_ncbi_biosample.Rd</code></div>
     </div>
 
@@ -176,20 +70,22 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>a data set</p></dd>
 
 
-<dt>filename</dt>
+<dt id="arg-filename">filename<a class="anchor" aria-label="anchor" href="#arg-filename"></a></dt>
 <dd><p>a character string specifying the file name</p></dd>
 
 
-<dt>type</dt>
+<dt id="arg-type">type<a class="anchor" aria-label="anchor" href="#arg-type"></a></dt>
 <dd><p>a character string specifying the type of data set, either "pathogen MIC" or "beta-lactamase MIC", see <a href="https://www.ncbi.nlm.nih.gov/biosample/docs/" class="external-link">https://www.ncbi.nlm.nih.gov/biosample/docs/</a></p></dd>
 
 </dl></div>
 
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -203,9 +99,9 @@
 
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diff --git a/reference/facet_sir.html b/reference/facet_sir.html
new file mode 100644
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@@ -0,0 +1,8 @@
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diff --git a/reference/filter_first_isolate.html b/reference/filter_first_isolate.html
new file mode 100644
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--- /dev/null
+++ b/reference/filter_first_isolate.html
@@ -0,0 +1,8 @@
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diff --git a/reference/first_isolate.html b/reference/first_isolate.html
index af73eefb5..a1ee47c10 100644
--- a/reference/first_isolate.html
+++ b/reference/first_isolate.html
@@ -1,163 +1,57 @@
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-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Determine first isolates of all microorganisms of every patient per episode and (if needed) per specimen type. These functions support all four methods as summarised by Hindler et al. in 2007 (doi:10.1086/511864
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+). To determine patient episodes not necessarily based on microorganisms, use is_new_episode() that also supports grouping with the dplyr package."><meta property="og:description" content="Determine first isolates of all microorganisms of every patient per episode and (if needed) per specimen type. These functions support all four methods as summarised by Hindler et al. in 2007 (doi:10.1086/511864
+). To determine patient episodes not necessarily based on microorganisms, use is_new_episode() that also supports grouping with the dplyr package."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"></head><body>
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       <img src="../logo.svg" class="logo" alt=""><h1>Determine First Isolates</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/first_isolate.R" class="external-link"><code>R/first_isolate.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/first_isolate.R" class="external-link"><code>R/first_isolate.R</code></a></small>
       <div class="d-none name"><code>first_isolate.Rd</code></div>
     </div>
 
@@ -209,91 +103,91 @@
 </ul></div>
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> containing isolates. Can be left blank for automatic determination, see <em>Examples</em>.</p></dd>
 
 
-<dt>col_date</dt>
+<dt id="arg-col-date">col_date<a class="anchor" aria-label="anchor" href="#arg-col-date"></a></dt>
 <dd><p>column name of the result date (or date that is was received on the lab) - the default is the first column with a date class</p></dd>
 
 
-<dt>col_patient_id</dt>
+<dt id="arg-col-patient-id">col_patient_id<a class="anchor" aria-label="anchor" href="#arg-col-patient-id"></a></dt>
 <dd><p>column name of the unique IDs of the patients - the default is the first column that starts with 'patient' or 'patid' (case insensitive)</p></dd>
 
 
-<dt>col_mo</dt>
+<dt id="arg-col-mo">col_mo<a class="anchor" aria-label="anchor" href="#arg-col-mo"></a></dt>
 <dd><p>column name of the names or codes of the microorganisms (see <code><a href="as.mo.html">as.mo()</a></code>) - the default is the first column of class <code><a href="as.mo.html">mo</a></code>. Values will be coerced using <code><a href="as.mo.html">as.mo()</a></code>.</p></dd>
 
 
-<dt>col_testcode</dt>
+<dt id="arg-col-testcode">col_testcode<a class="anchor" aria-label="anchor" href="#arg-col-testcode"></a></dt>
 <dd><p>column name of the test codes. Use <code>col_testcode = NULL</code> to <strong>not</strong> exclude certain test codes (such as test codes for screening). In that case <code>testcodes_exclude</code> will be ignored.</p></dd>
 
 
-<dt>col_specimen</dt>
+<dt id="arg-col-specimen">col_specimen<a class="anchor" aria-label="anchor" href="#arg-col-specimen"></a></dt>
 <dd><p>column name of the specimen type or group</p></dd>
 
 
-<dt>col_icu</dt>
+<dt id="arg-col-icu">col_icu<a class="anchor" aria-label="anchor" href="#arg-col-icu"></a></dt>
 <dd><p>column name of the logicals (<code>TRUE</code>/<code>FALSE</code>) whether a ward or department is an Intensive Care Unit (ICU). This can also be a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> vector with the same length as rows in <code>x</code>.</p></dd>
 
 
-<dt>col_keyantimicrobials</dt>
+<dt id="arg-col-keyantimicrobials">col_keyantimicrobials<a class="anchor" aria-label="anchor" href="#arg-col-keyantimicrobials"></a></dt>
 <dd><p>(only useful when <code>method = "phenotype-based"</code>) column name of the key antimicrobials to determine first isolates, see <code><a href="key_antimicrobials.html">key_antimicrobials()</a></code>. The default is the first column that starts with 'key' followed by 'ab' or 'antibiotics' or 'antimicrobials' (case insensitive). Use <code>col_keyantimicrobials = FALSE</code> to prevent this. Can also be the output of <code><a href="key_antimicrobials.html">key_antimicrobials()</a></code>.</p></dd>
 
 
-<dt>episode_days</dt>
+<dt id="arg-episode-days">episode_days<a class="anchor" aria-label="anchor" href="#arg-episode-days"></a></dt>
 <dd><p>episode in days after which a genus/species combination will be determined as 'first isolate' again. The default of 365 days is based on the guideline by CLSI, see <em>Source</em>.</p></dd>
 
 
-<dt>testcodes_exclude</dt>
+<dt id="arg-testcodes-exclude">testcodes_exclude<a class="anchor" aria-label="anchor" href="#arg-testcodes-exclude"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector with test codes that should be excluded (case-insensitive)</p></dd>
 
 
-<dt>icu_exclude</dt>
+<dt id="arg-icu-exclude">icu_exclude<a class="anchor" aria-label="anchor" href="#arg-icu-exclude"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether ICU isolates should be excluded (rows with value <code>TRUE</code> in the column set with <code>col_icu</code>)</p></dd>
 
 
-<dt>specimen_group</dt>
+<dt id="arg-specimen-group">specimen_group<a class="anchor" aria-label="anchor" href="#arg-specimen-group"></a></dt>
 <dd><p>value in the column set with <code>col_specimen</code> to filter on</p></dd>
 
 
-<dt>type</dt>
+<dt id="arg-type">type<a class="anchor" aria-label="anchor" href="#arg-type"></a></dt>
 <dd><p>type to determine weighed isolates; can be <code>"keyantimicrobials"</code> or <code>"points"</code>, see <em>Details</em></p></dd>
 
 
-<dt>method</dt>
+<dt id="arg-method">method<a class="anchor" aria-label="anchor" href="#arg-method"></a></dt>
 <dd><p>the method to apply, either <code>"phenotype-based"</code>, <code>"episode-based"</code>, <code>"patient-based"</code> or <code>"isolate-based"</code> (can be abbreviated), see <em>Details</em>. The default is <code>"phenotype-based"</code> if antimicrobial test results are present in the data, and <code>"episode-based"</code> otherwise.</p></dd>
 
 
-<dt>ignore_I</dt>
+<dt id="arg-ignore-i">ignore_I<a class="anchor" aria-label="anchor" href="#arg-ignore-i"></a></dt>
 <dd><p><a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether antibiotic interpretations with <code>"I"</code> will be ignored when <code>type = "keyantimicrobials"</code>, see <em>Details</em></p></dd>
 
 
-<dt>points_threshold</dt>
+<dt id="arg-points-threshold">points_threshold<a class="anchor" aria-label="anchor" href="#arg-points-threshold"></a></dt>
 <dd><p>minimum number of points to require before differences in the antibiogram will lead to inclusion of an isolate when <code>type = "points"</code>, see <em>Details</em></p></dd>
 
 
-<dt>info</dt>
+<dt id="arg-info">info<a class="anchor" aria-label="anchor" href="#arg-info"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate info should be printed - the default is <code>TRUE</code> only in interactive mode</p></dd>
 
 
-<dt>include_unknown</dt>
+<dt id="arg-include-unknown">include_unknown<a class="anchor" aria-label="anchor" href="#arg-include-unknown"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether 'unknown' microorganisms should be included too, i.e. microbial code <code>"UNKNOWN"</code>, which defaults to <code>FALSE</code>. For WHONET users, this means that all records with organism code <code>"con"</code> (<em>contamination</em>) will be excluded at default. Isolates with a microbial ID of <code>NA</code> will always be excluded as first isolate.</p></dd>
 
 
-<dt>include_untested_sir</dt>
+<dt id="arg-include-untested-sir">include_untested_sir<a class="anchor" aria-label="anchor" href="#arg-include-untested-sir"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether also rows without antibiotic results are still eligible for becoming a first isolate. Use <code>include_untested_sir = FALSE</code> to always return <code>FALSE</code> for such rows. This checks the data set for columns of class <code>sir</code> and consequently requires transforming columns with antibiotic results using <code><a href="as.sir.html">as.sir()</a></code> first.</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>arguments passed on to <code>first_isolate()</code> when using <code>filter_first_isolate()</code>, otherwise arguments passed on to <code><a href="key_antimicrobials.html">key_antimicrobials()</a></code> (such as <code>universal</code>, <code>gram_negative</code>, <code>gram_positive</code>)</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> vector</p>
+    <p>A <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> vector</p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -507,7 +401,7 @@
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -521,9 +415,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
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new file mode 100644
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new file mode 100644
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new file mode 100644
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diff --git a/reference/fortify.mic.html b/reference/fortify.mic.html
new file mode 100644
index 000000000..934dc99fb
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@@ -0,0 +1,8 @@
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diff --git a/reference/fortify.sir.html b/reference/fortify.sir.html
new file mode 100644
index 000000000..934dc99fb
--- /dev/null
+++ b/reference/fortify.sir.html
@@ -0,0 +1,8 @@
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diff --git a/reference/full_join_microorganisms.html b/reference/full_join_microorganisms.html
new file mode 100644
index 000000000..0bdfa18c3
--- /dev/null
+++ b/reference/full_join_microorganisms.html
@@ -0,0 +1,8 @@
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diff --git a/reference/g.test.html b/reference/g.test.html
index 8f9cd80a2..ed3703f69 100644
--- a/reference/g.test.html
+++ b/reference/g.test.html
@@ -1,161 +1,55 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="g.test() performs chi-squared contingency table tests and goodness-of-fit tests, just like chisq.test() but is more reliable (1). 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-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
-  <a class="nav-link" href="../news/index.html">
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-  <a class="external-link nav-link" href="https://github.com/msberends/AMR">
-    <span class="fab fa fab fa-github"></span>
-     
-    Source Code
-  </a>
-</li>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1><em>G</em>-test for Count Data</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/g.test.R" class="external-link"><code>R/g.test.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/g.test.R" class="external-link"><code>R/g.test.R</code></a></small>
       <div class="d-none name"><code>g.test.Rd</code></div>
     </div>
 
@@ -176,22 +70,24 @@
 </ul></div>
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>a numeric vector or matrix. <code>x</code> and <code>y</code> can also
     both be factors.</p></dd>
 
 
-<dt>y</dt>
+<dt id="arg-y">y<a class="anchor" aria-label="anchor" href="#arg-y"></a></dt>
 <dd><p>a numeric vector; ignored if <code>x</code> is a matrix.  If
     <code>x</code> is a factor, <code>y</code> should be a factor of the same length.</p></dd>
 
 
-<dt>p</dt>
+<dt id="arg-p">p<a class="anchor" aria-label="anchor" href="#arg-p"></a></dt>
 <dd><p>a vector of probabilities of the same length as <code>x</code>.
     An error is given if any entry of <code>p</code> is negative.</p></dd>
 
 
-<dt>rescale.p</dt>
+<dt id="arg-rescale-p">rescale.p<a class="anchor" aria-label="anchor" href="#arg-rescale-p"></a></dt>
 <dd><p>a logical scalar; if TRUE then <code>p</code> is rescaled
     (if necessary) to sum to 1.  If <code>rescale.p</code> is FALSE, and
     <code>p</code> does not sum to 1, an error is given.</p></dd>
@@ -199,9 +95,7 @@
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A list with class <code>"htest"</code> containing the following
+    <p>A list with class <code>"htest"</code> containing the following
   components:</p>
 <dl><dt>statistic</dt>
 <dd><p>the value the chi-squared test statistic.</p></dd>
@@ -280,7 +174,7 @@
     </div>
     <div class="section level2">
     <h2 id="references">References<a class="anchor" aria-label="anchor" href="#references"></a></h2>
-    
+
 <ol><li><p>McDonald, J.H. 2014. <strong>Handbook of Biological Statistics (3rd ed.)</strong>. Sparky House Publishing, Baltimore, Maryland. <a href="http://www.biostathandbook.com/gtestgof.html" class="external-link">http://www.biostathandbook.com/gtestgof.html</a>.</p></li>
 </ol></div>
     <div class="section level2">
@@ -333,7 +227,7 @@
 <span class="r-in"><span><span class="co"># Meaning: there are significantly more left-billed birds.</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -347,9 +241,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/geom_sir.html b/reference/geom_sir.html
new file mode 100644
index 000000000..9e142046a
--- /dev/null
+++ b/reference/geom_sir.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/ggplot_sir.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/ggplot_sir.html">
+  </head>
+</html>
+
diff --git a/reference/get_AMR_locale.html b/reference/get_AMR_locale.html
new file mode 100644
index 000000000..b4dcf12f0
--- /dev/null
+++ b/reference/get_AMR_locale.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/translate.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/translate.html">
+  </head>
+</html>
+
diff --git a/reference/get_episode.html b/reference/get_episode.html
index ab45035bb..70521af83 100644
--- a/reference/get_episode.html
+++ b/reference/get_episode.html
@@ -1,161 +1,55 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="These functions determine which items in a vector can be considered (the start of) a new episode. This can be used to determine clinical episodes for any epidemiological analysis. The get_episode() function returns the index number of the episode per group, while the is_new_episode() function returns TRUE for every new get_episode() index. Both absolute and relative episode determination are supported."><title>Determine Clinical or Epidemic Episodes — get_episode • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Determine Clinical or Epidemic Episodes — get_episode"><meta property="og:description" content="These functions determine which items in a vector can be considered (the start of) a new episode. This can be used to determine clinical episodes for any epidemiological analysis. The get_episode() function returns the index number of the episode per group, while the is_new_episode() function returns TRUE for every new get_episode() index. Both absolute and relative episode determination are supported."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Determine Clinical or Epidemic Episodes — get_episode • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Determine Clinical or Epidemic Episodes — get_episode"><meta name="description" content="These functions determine which items in a vector can be considered (the start of) a new episode. This can be used to determine clinical episodes for any epidemiological analysis. The get_episode() function returns the index number of the episode per group, while the is_new_episode() function returns TRUE for every new get_episode() index. Both absolute and relative episode determination are supported."><meta property="og:description" content="These functions determine which items in a vector can be considered (the start of) a new episode. This can be used to determine clinical episodes for any epidemiological analysis. The get_episode() function returns the index number of the episode per group, while the is_new_episode() function returns TRUE for every new get_episode() index. Both absolute and relative episode determination are supported."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"></head><body>
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Determine Clinical or Epidemic Episodes</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/get_episode.R" class="external-link"><code>R/get_episode.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/get_episode.R" class="external-link"><code>R/get_episode.R</code></a></small>
       <div class="d-none name"><code>get_episode.Rd</code></div>
     </div>
 
@@ -172,25 +66,26 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>vector of dates (class <code>Date</code> or <code>POSIXt</code>), will be sorted internally to determine episodes</p></dd>
 
 
-<dt>episode_days</dt>
+<dt id="arg-episode-days">episode_days<a class="anchor" aria-label="anchor" href="#arg-episode-days"></a></dt>
 <dd><p>episode length in days to specify the time period after which a new episode begins, can also be less than a day or <code>Inf</code>, see <em>Details</em></p></dd>
 
 
-<dt>case_free_days</dt>
+<dt id="arg-case-free-days">case_free_days<a class="anchor" aria-label="anchor" href="#arg-case-free-days"></a></dt>
 <dd><p>(inter-epidemic) interval length in days after which a new episode will start, can also be less than a day or <code>Inf</code>, see <em>Details</em></p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>ignored, only in place to allow future extensions</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
 
 <ul><li><p><code>get_episode()</code>: an <a href="https://rdrr.io/r/base/integer.html" class="external-link">integer</a> vector</p></li>
 <li><p><code>is_new_episode()</code>: a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> vector</p></li>
@@ -419,7 +314,7 @@
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -433,9 +328,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/get_mo_source.html b/reference/get_mo_source.html
new file mode 100644
index 000000000..2e3e3c3d0
--- /dev/null
+++ b/reference/get_mo_source.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mo_source.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/mo_source.html">
+  </head>
+</html>
+
diff --git a/reference/ggplot_pca.html b/reference/ggplot_pca.html
index 0da6b2f40..e04005fba 100644
--- a/reference/ggplot_pca.html
+++ b/reference/ggplot_pca.html
@@ -1,161 +1,55 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Produces a ggplot2 variant of a so-called biplot for PCA (principal component analysis), but is more flexible and more appealing than the base R biplot() function."><title>PCA Biplot with ggplot2 — ggplot_pca • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="PCA Biplot with ggplot2 — ggplot_pca"><meta property="og:description" content="Produces a ggplot2 variant of a so-called biplot for PCA (principal component analysis), but is more flexible and more appealing than the base R biplot() function."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<![endif]--></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>PCA Biplot with ggplot2 — ggplot_pca • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="PCA Biplot with ggplot2 — ggplot_pca"><meta name="description" content="Produces a ggplot2 variant of a so-called biplot for PCA (principal component analysis), but is more flexible and more appealing than the base R biplot() function."><meta property="og:description" content="Produces a ggplot2 variant of a so-called biplot for PCA (principal component analysis), but is more flexible and more appealing than the base R biplot() function."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"></head><body>
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-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9061</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9063</small>
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+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
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+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
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+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
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+
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 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>PCA Biplot with <code>ggplot2</code></h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/ggplot_pca.R" class="external-link"><code>R/ggplot_pca.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/ggplot_pca.R" class="external-link"><code>R/ggplot_pca.R</code></a></small>
       <div class="d-none name"><code>ggplot_pca.Rd</code></div>
     </div>
 
@@ -203,16 +97,18 @@
 </ol></div>
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>an object returned by <code><a href="pca.html">pca()</a></code>, <code><a href="https://rdrr.io/r/stats/prcomp.html" class="external-link">prcomp()</a></code> or <code><a href="https://rdrr.io/r/stats/princomp.html" class="external-link">princomp()</a></code></p></dd>
 
 
-<dt>choices</dt>
+<dt id="arg-choices">choices<a class="anchor" aria-label="anchor" href="#arg-choices"></a></dt>
 <dd><p>length 2 vector specifying the components to plot. Only the default
     is a biplot in the strict sense.</p></dd>
 
 
-<dt>scale</dt>
+<dt id="arg-scale">scale<a class="anchor" aria-label="anchor" href="#arg-scale"></a></dt>
 <dd><p>The variables are scaled by <code>lambda ^ scale</code> and the
     observations are scaled by <code>lambda ^ (1-scale)</code> where
     <code>lambda</code> are the singular values as computed by
@@ -220,7 +116,7 @@
     will be issued if the specified <code>scale</code> is outside this range.</p></dd>
 
 
-<dt>pc.biplot</dt>
+<dt id="arg-pc-biplot">pc.biplot<a class="anchor" aria-label="anchor" href="#arg-pc-biplot"></a></dt>
 <dd><p>If true, use what Gabriel (1971) refers to as a "principal component
     biplot", with <code>lambda = 1</code> and observations scaled up by sqrt(n) and
     variables scaled down by sqrt(n).  Then inner products between
@@ -228,75 +124,75 @@
     approximate Mahalanobis distance.</p></dd>
 
 
-<dt>labels</dt>
+<dt id="arg-labels">labels<a class="anchor" aria-label="anchor" href="#arg-labels"></a></dt>
 <dd><p>an optional vector of labels for the observations. If set, the labels will be placed below their respective points. When using the <code><a href="pca.html">pca()</a></code> function as input for <code>x</code>, this will be determined automatically based on the attribute <code>non_numeric_cols</code>, see <code><a href="pca.html">pca()</a></code>.</p></dd>
 
 
-<dt>labels_textsize</dt>
+<dt id="arg-labels-textsize">labels_textsize<a class="anchor" aria-label="anchor" href="#arg-labels-textsize"></a></dt>
 <dd><p>the size of the text used for the labels</p></dd>
 
 
-<dt>labels_text_placement</dt>
+<dt id="arg-labels-text-placement">labels_text_placement<a class="anchor" aria-label="anchor" href="#arg-labels-text-placement"></a></dt>
 <dd><p>adjustment factor the placement of the variable names (<code>&gt;=1</code> means further away from the arrow head)</p></dd>
 
 
-<dt>groups</dt>
+<dt id="arg-groups">groups<a class="anchor" aria-label="anchor" href="#arg-groups"></a></dt>
 <dd><p>an optional vector of groups for the labels, with the same length as <code>labels</code>. If set, the points and labels will be coloured according to these groups. When using the <code><a href="pca.html">pca()</a></code> function as input for <code>x</code>, this will be determined automatically based on the attribute <code>non_numeric_cols</code>, see <code><a href="pca.html">pca()</a></code>.</p></dd>
 
 
-<dt>ellipse</dt>
+<dt id="arg-ellipse">ellipse<a class="anchor" aria-label="anchor" href="#arg-ellipse"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether a normal data ellipse should be drawn for each group (set with <code>groups</code>)</p></dd>
 
 
-<dt>ellipse_prob</dt>
+<dt id="arg-ellipse-prob">ellipse_prob<a class="anchor" aria-label="anchor" href="#arg-ellipse-prob"></a></dt>
 <dd><p>statistical size of the ellipse in normal probability</p></dd>
 
 
-<dt>ellipse_size</dt>
+<dt id="arg-ellipse-size">ellipse_size<a class="anchor" aria-label="anchor" href="#arg-ellipse-size"></a></dt>
 <dd><p>the size of the ellipse line</p></dd>
 
 
-<dt>ellipse_alpha</dt>
+<dt id="arg-ellipse-alpha">ellipse_alpha<a class="anchor" aria-label="anchor" href="#arg-ellipse-alpha"></a></dt>
 <dd><p>the alpha (transparency) of the ellipse line</p></dd>
 
 
-<dt>points_size</dt>
+<dt id="arg-points-size">points_size<a class="anchor" aria-label="anchor" href="#arg-points-size"></a></dt>
 <dd><p>the size of the points</p></dd>
 
 
-<dt>points_alpha</dt>
+<dt id="arg-points-alpha">points_alpha<a class="anchor" aria-label="anchor" href="#arg-points-alpha"></a></dt>
 <dd><p>the alpha (transparency) of the points</p></dd>
 
 
-<dt>arrows</dt>
+<dt id="arg-arrows">arrows<a class="anchor" aria-label="anchor" href="#arg-arrows"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether arrows should be drawn</p></dd>
 
 
-<dt>arrows_colour</dt>
+<dt id="arg-arrows-colour">arrows_colour<a class="anchor" aria-label="anchor" href="#arg-arrows-colour"></a></dt>
 <dd><p>the colour of the arrow and their text</p></dd>
 
 
-<dt>arrows_size</dt>
+<dt id="arg-arrows-size">arrows_size<a class="anchor" aria-label="anchor" href="#arg-arrows-size"></a></dt>
 <dd><p>the size (thickness) of the arrow lines</p></dd>
 
 
-<dt>arrows_textsize</dt>
+<dt id="arg-arrows-textsize">arrows_textsize<a class="anchor" aria-label="anchor" href="#arg-arrows-textsize"></a></dt>
 <dd><p>the size of the text at the end of the arrows</p></dd>
 
 
-<dt>arrows_textangled</dt>
+<dt id="arg-arrows-textangled">arrows_textangled<a class="anchor" aria-label="anchor" href="#arg-arrows-textangled"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> whether the text at the end of the arrows should be angled</p></dd>
 
 
-<dt>arrows_alpha</dt>
+<dt id="arg-arrows-alpha">arrows_alpha<a class="anchor" aria-label="anchor" href="#arg-arrows-alpha"></a></dt>
 <dd><p>the alpha (transparency) of the arrows and their text</p></dd>
 
 
-<dt>base_textsize</dt>
+<dt id="arg-base-textsize">base_textsize<a class="anchor" aria-label="anchor" href="#arg-base-textsize"></a></dt>
 <dd><p>the text size for all plot elements except the labels and arrows</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>arguments passed on to functions</p></dd>
 
 </dl></div>
@@ -361,7 +257,7 @@
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -375,9 +271,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
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index 71dce6d2a..eac1fdb69 100644
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+++ b/reference/ggplot_sir.html
@@ -1,161 +1,55 @@
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+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>AMR Plots with <code>ggplot2</code></h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/ggplot_sir.R" class="external-link"><code>R/ggplot_sir.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/ggplot_sir.R" class="external-link"><code>R/ggplot_sir.R</code></a></small>
       <div class="d-none name"><code>ggplot_sir.Rd</code></div>
     </div>
 
@@ -224,95 +118,97 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>data</dt>
+
+
+<dl><dt id="arg-data">data<a class="anchor" aria-label="anchor" href="#arg-data"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with column(s) of class <code><a href="as.sir.html">sir</a></code> (see <code><a href="as.sir.html">as.sir()</a></code>)</p></dd>
 
 
-<dt>position</dt>
+<dt id="arg-position">position<a class="anchor" aria-label="anchor" href="#arg-position"></a></dt>
 <dd><p>position adjustment of bars, either <code>"fill"</code>, <code>"stack"</code> or <code>"dodge"</code></p></dd>
 
 
-<dt>x</dt>
+<dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>variable to show on x axis, either <code>"antibiotic"</code> (default) or <code>"interpretation"</code> or a grouping variable</p></dd>
 
 
-<dt>fill</dt>
+<dt id="arg-fill">fill<a class="anchor" aria-label="anchor" href="#arg-fill"></a></dt>
 <dd><p>variable to categorise using the plots legend, either <code>"antibiotic"</code> (default) or <code>"interpretation"</code> or a grouping variable</p></dd>
 
 
-<dt>facet</dt>
+<dt id="arg-facet">facet<a class="anchor" aria-label="anchor" href="#arg-facet"></a></dt>
 <dd><p>variable to split plots by, either <code>"interpretation"</code> (default) or <code>"antibiotic"</code> or a grouping variable</p></dd>
 
 
-<dt>breaks</dt>
+<dt id="arg-breaks">breaks<a class="anchor" aria-label="anchor" href="#arg-breaks"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a> vector of positions</p></dd>
 
 
-<dt>limits</dt>
+<dt id="arg-limits">limits<a class="anchor" aria-label="anchor" href="#arg-limits"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a> vector of length two providing limits of the scale, use <code>NA</code> to refer to the existing minimum or maximum</p></dd>
 
 
-<dt>translate_ab</dt>
+<dt id="arg-translate-ab">translate_ab<a class="anchor" aria-label="anchor" href="#arg-translate-ab"></a></dt>
 <dd><p>a column name of the <a href="antibiotics.html">antibiotics</a> data set to translate the antibiotic abbreviations to, using <code><a href="ab_property.html">ab_property()</a></code></p></dd>
 
 
-<dt>combine_SI</dt>
+<dt id="arg-combine-si">combine_SI<a class="anchor" aria-label="anchor" href="#arg-combine-si"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether all values of S and I must be merged into one, so the output only consists of S+I vs. R (susceptible vs. resistant) - the default is <code>TRUE</code></p></dd>
 
 
-<dt>minimum</dt>
+<dt id="arg-minimum">minimum<a class="anchor" aria-label="anchor" href="#arg-minimum"></a></dt>
 <dd><p>the minimum allowed number of available (tested) isolates. Any isolate count lower than <code>minimum</code> will return <code>NA</code> with a warning. The default number of <code>30</code> isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see <em>Source</em>.</p></dd>
 
 
-<dt>language</dt>
+<dt id="arg-language">language<a class="anchor" aria-label="anchor" href="#arg-language"></a></dt>
 <dd><p>language of the returned text - the default is the current system language (see <code><a href="translate.html">get_AMR_locale()</a></code>) and can also be set with the <a href="AMR-options.html">package option</a> <code><a href="AMR-options.html">AMR_locale</a></code>. Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></dd>
 
 
-<dt>nrow</dt>
+<dt id="arg-nrow">nrow<a class="anchor" aria-label="anchor" href="#arg-nrow"></a></dt>
 <dd><p>(when using <code>facet</code>) number of rows</p></dd>
 
 
-<dt>colours</dt>
+<dt id="arg-colours">colours<a class="anchor" aria-label="anchor" href="#arg-colours"></a></dt>
 <dd><p>a named vactor with colour to be used for filling. The default colours are colour-blind friendly.</p></dd>
 
 
-<dt>datalabels</dt>
+<dt id="arg-datalabels">datalabels<a class="anchor" aria-label="anchor" href="#arg-datalabels"></a></dt>
 <dd><p>show datalabels using <code>labels_sir_count()</code></p></dd>
 
 
-<dt>datalabels.size</dt>
+<dt id="arg-datalabels-size">datalabels.size<a class="anchor" aria-label="anchor" href="#arg-datalabels-size"></a></dt>
 <dd><p>size of the datalabels</p></dd>
 
 
-<dt>datalabels.colour</dt>
+<dt id="arg-datalabels-colour">datalabels.colour<a class="anchor" aria-label="anchor" href="#arg-datalabels-colour"></a></dt>
 <dd><p>colour of the datalabels</p></dd>
 
 
-<dt>title</dt>
+<dt id="arg-title">title<a class="anchor" aria-label="anchor" href="#arg-title"></a></dt>
 <dd><p>text to show as title of the plot</p></dd>
 
 
-<dt>subtitle</dt>
+<dt id="arg-subtitle">subtitle<a class="anchor" aria-label="anchor" href="#arg-subtitle"></a></dt>
 <dd><p>text to show as subtitle of the plot</p></dd>
 
 
-<dt>caption</dt>
+<dt id="arg-caption">caption<a class="anchor" aria-label="anchor" href="#arg-caption"></a></dt>
 <dd><p>text to show as caption of the plot</p></dd>
 
 
-<dt>x.title</dt>
+<dt id="arg-x-title">x.title<a class="anchor" aria-label="anchor" href="#arg-x-title"></a></dt>
 <dd><p>text to show as x axis description</p></dd>
 
 
-<dt>y.title</dt>
+<dt id="arg-y-title">y.title<a class="anchor" aria-label="anchor" href="#arg-y-title"></a></dt>
 <dd><p>text to show as y axis description</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>other arguments passed on to <code>geom_sir()</code> or, in case of <code>scale_sir_colours()</code>, named values to set colours. The default colours are colour-blind friendly, while maintaining the convention that e.g. 'susceptible' should be green and 'resistant' should be red. See <em>Examples</em>.</p></dd>
 
 
-<dt>aesthetics</dt>
+<dt id="arg-aesthetics">aesthetics<a class="anchor" aria-label="anchor" href="#arg-aesthetics"></a></dt>
 <dd><p>aesthetics to apply the colours to - the default is "fill" but can also be (a combination of) "alpha", "colour", "fill", "linetype", "shape" or "size"</p></dd>
 
 </dl></div>
@@ -446,7 +342,7 @@
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -460,9 +356,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/ggplot_sir_predict.html b/reference/ggplot_sir_predict.html
new file mode 100644
index 000000000..95fc74991
--- /dev/null
+++ b/reference/ggplot_sir_predict.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/resistance_predict.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/resistance_predict.html">
+  </head>
+</html>
+
diff --git a/reference/glycopeptides.html b/reference/glycopeptides.html
new file mode 100644
index 000000000..07f8b21e2
--- /dev/null
+++ b/reference/glycopeptides.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html">
+  </head>
+</html>
+
diff --git a/reference/guess_ab_col.html b/reference/guess_ab_col.html
index 28728cbfe..d7e7f8d41 100644
--- a/reference/guess_ab_col.html
+++ b/reference/guess_ab_col.html
@@ -1,161 +1,55 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="This tries to find a column name in a data set based on information from the antibiotics data set. Also supports WHONET abbreviations."><title>Guess Antibiotic Column — guess_ab_col • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Guess Antibiotic Column — guess_ab_col"><meta property="og:description" content="This tries to find a column name in a data set based on information from the antibiotics data set. Also supports WHONET abbreviations."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Guess Antibiotic Column — guess_ab_col • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Guess Antibiotic Column — guess_ab_col"><meta name="description" content="This tries to find a column name in a data set based on information from the antibiotics data set. Also supports WHONET abbreviations."><meta property="og:description" content="This tries to find a column name in a data set based on information from the antibiotics data set. Also supports WHONET abbreviations."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"></head><body>
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-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9061</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9063</small>
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+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul></li>
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--with-other-pkgs">
-    <span class="fa fa-layer-group"></span>
-     
-    With other pkgs
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--with-other-pkgs">
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; dplyr/tidyverse
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; data.table
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; tidymodels
-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
-       
-      AMR &amp; base R
-    </a>
-  </div>
-</li>
-<li class="active nav-item">
-  <a class="nav-link" href="../reference/index.html">
-    <span class="fa fa-book-open"></span>
-     
-    Manual
-  </a>
-</li>
-<li class="nav-item">
-  <a class="nav-link" href="../authors.html">
-    <span class="fa fa-users"></span>
-     
-    Authors
-  </a>
-</li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
-  <a class="nav-link" href="../news/index.html">
-    <span class="far fa far fa-newspaper"></span>
-     
-    Changelog
-  </a>
-</li>
-<li class="nav-item">
-  <a class="external-link nav-link" href="https://github.com/msberends/AMR">
-    <span class="fab fa fab fa-github"></span>
-     
-    Source Code
-  </a>
-</li>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Guess Antibiotic Column</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/guess_ab_col.R" class="external-link"><code>R/guess_ab_col.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/guess_ab_col.R" class="external-link"><code>R/guess_ab_col.R</code></a></small>
       <div class="d-none name"><code>guess_ab_col.Rd</code></div>
     </div>
 
@@ -175,27 +69,27 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></p></dd>
 
 
-<dt>search_string</dt>
+<dt id="arg-search-string">search_string<a class="anchor" aria-label="anchor" href="#arg-search-string"></a></dt>
 <dd><p>a text to search <code>x</code> for, will be checked with <code><a href="as.ab.html">as.ab()</a></code> if this value is not a column in <code>x</code></p></dd>
 
 
-<dt>verbose</dt>
+<dt id="arg-verbose">verbose<a class="anchor" aria-label="anchor" href="#arg-verbose"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether additional info should be printed</p></dd>
 
 
-<dt>only_sir_columns</dt>
+<dt id="arg-only-sir-columns">only_sir_columns<a class="anchor" aria-label="anchor" href="#arg-only-sir-columns"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether only antibiotic columns must be detected that were transformed to class <code>sir</code> (see <code><a href="as.sir.html">as.sir()</a></code>) on beforehand (default is <code>FALSE</code>)</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A column name of <code>x</code>, or <code>NULL</code> when no result is found.</p>
+    <p>A column name of <code>x</code>, or <code>NULL</code> when no result is found.</p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -237,7 +131,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] "AMC_ED20"</span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -251,9 +145,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/index.html b/reference/index.html
index bcca27260..3ea6405e2 100644
--- a/reference/index.html
+++ b/reference/index.html
@@ -1,580 +1,533 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Function reference • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Function reference"><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-<![endif]--></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Package index • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Package index"><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
-    
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-primary" data-bs-theme="dark"><div class="container">
-    
+
+    <nav class="navbar navbar-expand-lg fixed-top bg-primary" data-bs-theme="dark" aria-label="Site navigation"><div class="container">
+
     <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9061</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9063</small>
+
 
-    
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
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     </button>
 
     <div id="navbar" class="collapse navbar-collapse ms-3">
       <ul class="navbar-nav me-auto"><li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--how-to">
-    <span class="fa fa-question-circle"></span>
-     
-    How to
-  </a>
-  <div class="dropdown-menu" aria-labelledby="dropdown--how-to">
-    <a class="dropdown-item" href="../articles/AMR.html">
-      <span class="fa fa-directions"></span>
-       
-      Conduct AMR Analysis
-    </a>
-    <a class="dropdown-item" href="../reference/antibiogram.html">
-      <span class="fa fa-file-prescription"></span>
-       
-      Generate Antibiogram (Trad./Syndromic/WISCA)
-    </a>
-    <a class="dropdown-item" href="../articles/resistance_predict.html">
-      <span class="fa fa-dice"></span>
-       
-      Predict Antimicrobial Resistance
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-      Download Data Sets for Own Use
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-      <span class="fa fa-gear"></span>
-       
-      Set User- Or Team-specific Package Settings
-    </a>
-    <a class="dropdown-item" href="../articles/PCA.html">
-      <span class="fa fa-compress"></span>
-       
-      Conduct Principal Component Analysis for AMR
-    </a>
-    <a class="dropdown-item" href="../articles/MDR.html">
-      <span class="fa fa-skull-crossbones"></span>
-       
-      Determine Multi-Drug Resistance (MDR)
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-    <a class="dropdown-item" href="../articles/WHONET.html">
-      <span class="fa fa-globe-americas"></span>
-       
-      Work with WHONET Data
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-      <span class="fa fa-exchange-alt"></span>
-       
-      Apply Eucast Rules
-    </a>
-    <a class="dropdown-item" href="../reference/mo_property.html">
-      <span class="fa fa-bug"></span>
-       
-      Get Taxonomy of a Microorganism
-    </a>
-    <a class="dropdown-item" href="../reference/ab_property.html">
-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antibiotic Drug
-    </a>
-    <a class="dropdown-item" href="../reference/av_property.html">
-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antiviral Drug
-    </a>
-  </div>
-</li>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-how-to" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-question-circle"></span> How to</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to"><li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul></li>
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--with-other-pkgs">
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-    </a>
-    <a class="dropdown-item" href="../articles/other_pkg.html">
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-      AMR &amp; data.table
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-      AMR &amp; tidymodels
-    </a>
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-      AMR &amp; base R
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-<li class="active nav-item">
-  <a class="nav-link" href="../reference/index.html">
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-index">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.svg" class="logo" alt=""><h1>Function reference</h1>
+      <img src="../logo.svg" class="logo" alt=""><h1>Package index</h1>
     </div>
 
     <div class="section level2">
       <h2 id="introduction-to-the-package">Introduction to the package<a class="anchor" aria-label="anchor" href="#introduction-to-the-package"></a></h2>
-      
+
       <div class="section-desc"><p>Please find the introduction to (and some general information about) our package here.</p></div>
 
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+    </div><div class="section level2">
+
+
+
 
       <dl><dt>
-          
-          <code><a href="AMR.html">AMR-package</a></code> <code><a href="AMR.html">AMR</a></code> 
+
+          <code><a href="AMR.html">AMR-package</a></code> <code><a href="AMR.html">AMR</a></code>
+
         </dt>
         <dd>The <code>AMR</code> Package</dd>
       </dl></div><div class="section level2">
       <h2 id="preparing-data-microorganisms">Preparing data: microorganisms<a class="anchor" aria-label="anchor" href="#preparing-data-microorganisms"></a></h2>
-      
+
       <div class="section-desc"><p>These functions are meant to get taxonomically valid properties of microorganisms from any input, but also properties derived from taxonomy, such as the Gram stain (<code><a href="../reference/mo_property.html">mo_gramstain()</a></code>) , or <code><a href="../reference/mo_property.html">mo_is_yeast()</a></code>. Use <code><a href="../reference/mo_source.html">mo_source()</a></code> to teach this package how to translate your own codes to valid microorganisms, and use `add_custom_microorganisms() to add your own custom microorganisms to this package.</p></div>
 
-      
-    </div><div id="" class="section level2">
-      
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+
+    </div><div class="section level2">
+
+
+
 
       <dl><dt>
-          
-          <code><a href="as.mo.html">as.mo()</a></code> <code><a href="as.mo.html">is.mo()</a></code> <code><a href="as.mo.html">mo_uncertainties()</a></code> <code><a href="as.mo.html">mo_renamed()</a></code> <code><a href="as.mo.html">mo_failures()</a></code> <code><a href="as.mo.html">mo_reset_session()</a></code> <code><a href="as.mo.html">mo_cleaning_regex()</a></code> 
+
+          <code><a href="as.mo.html">as.mo()</a></code> <code><a href="as.mo.html">is.mo()</a></code> <code><a href="as.mo.html">mo_uncertainties()</a></code> <code><a href="as.mo.html">mo_renamed()</a></code> <code><a href="as.mo.html">mo_failures()</a></code> <code><a href="as.mo.html">mo_reset_session()</a></code> <code><a href="as.mo.html">mo_cleaning_regex()</a></code>
+
         </dt>
         <dd>Transform Arbitrary Input to Valid Microbial Taxonomy</dd>
       </dl><dl><dt>
-          
-          <code><a href="mo_property.html">mo_name()</a></code> <code><a href="mo_property.html">mo_fullname()</a></code> <code><a href="mo_property.html">mo_shortname()</a></code> <code><a href="mo_property.html">mo_subspecies()</a></code> <code><a href="mo_property.html">mo_species()</a></code> <code><a href="mo_property.html">mo_genus()</a></code> <code><a href="mo_property.html">mo_family()</a></code> <code><a href="mo_property.html">mo_order()</a></code> <code><a href="mo_property.html">mo_class()</a></code> <code><a href="mo_property.html">mo_phylum()</a></code> <code><a href="mo_property.html">mo_kingdom()</a></code> <code><a href="mo_property.html">mo_domain()</a></code> <code><a href="mo_property.html">mo_type()</a></code> <code><a href="mo_property.html">mo_status()</a></code> <code><a href="mo_property.html">mo_pathogenicity()</a></code> <code><a href="mo_property.html">mo_gramstain()</a></code> <code><a href="mo_property.html">mo_is_gram_negative()</a></code> <code><a href="mo_property.html">mo_is_gram_positive()</a></code> <code><a href="mo_property.html">mo_is_yeast()</a></code> <code><a href="mo_property.html">mo_is_intrinsic_resistant()</a></code> <code><a href="mo_property.html">mo_oxygen_tolerance()</a></code> <code><a href="mo_property.html">mo_is_anaerobic()</a></code> <code><a href="mo_property.html">mo_snomed()</a></code> <code><a href="mo_property.html">mo_ref()</a></code> <code><a href="mo_property.html">mo_authors()</a></code> <code><a href="mo_property.html">mo_year()</a></code> <code><a href="mo_property.html">mo_lpsn()</a></code> <code><a href="mo_property.html">mo_gbif()</a></code> <code><a href="mo_property.html">mo_rank()</a></code> <code><a href="mo_property.html">mo_taxonomy()</a></code> <code><a href="mo_property.html">mo_synonyms()</a></code> <code><a href="mo_property.html">mo_current()</a></code> <code><a href="mo_property.html">mo_group_members()</a></code> <code><a href="mo_property.html">mo_info()</a></code> <code><a href="mo_property.html">mo_url()</a></code> <code><a href="mo_property.html">mo_property()</a></code> 
+
+          <code><a href="mo_property.html">mo_name()</a></code> <code><a href="mo_property.html">mo_fullname()</a></code> <code><a href="mo_property.html">mo_shortname()</a></code> <code><a href="mo_property.html">mo_subspecies()</a></code> <code><a href="mo_property.html">mo_species()</a></code> <code><a href="mo_property.html">mo_genus()</a></code> <code><a href="mo_property.html">mo_family()</a></code> <code><a href="mo_property.html">mo_order()</a></code> <code><a href="mo_property.html">mo_class()</a></code> <code><a href="mo_property.html">mo_phylum()</a></code> <code><a href="mo_property.html">mo_kingdom()</a></code> <code><a href="mo_property.html">mo_domain()</a></code> <code><a href="mo_property.html">mo_type()</a></code> <code><a href="mo_property.html">mo_status()</a></code> <code><a href="mo_property.html">mo_pathogenicity()</a></code> <code><a href="mo_property.html">mo_gramstain()</a></code> <code><a href="mo_property.html">mo_is_gram_negative()</a></code> <code><a href="mo_property.html">mo_is_gram_positive()</a></code> <code><a href="mo_property.html">mo_is_yeast()</a></code> <code><a href="mo_property.html">mo_is_intrinsic_resistant()</a></code> <code><a href="mo_property.html">mo_oxygen_tolerance()</a></code> <code><a href="mo_property.html">mo_is_anaerobic()</a></code> <code><a href="mo_property.html">mo_snomed()</a></code> <code><a href="mo_property.html">mo_ref()</a></code> <code><a href="mo_property.html">mo_authors()</a></code> <code><a href="mo_property.html">mo_year()</a></code> <code><a href="mo_property.html">mo_lpsn()</a></code> <code><a href="mo_property.html">mo_mycobank()</a></code> <code><a href="mo_property.html">mo_gbif()</a></code> <code><a href="mo_property.html">mo_rank()</a></code> <code><a href="mo_property.html">mo_taxonomy()</a></code> <code><a href="mo_property.html">mo_synonyms()</a></code> <code><a href="mo_property.html">mo_current()</a></code> <code><a href="mo_property.html">mo_group_members()</a></code> <code><a href="mo_property.html">mo_info()</a></code> <code><a href="mo_property.html">mo_url()</a></code> <code><a href="mo_property.html">mo_property()</a></code>
+
         </dt>
         <dd>Get Properties of a Microorganism</dd>
       </dl><dl><dt>
-          
-          <code><a href="add_custom_microorganisms.html">add_custom_microorganisms()</a></code> <code><a href="add_custom_microorganisms.html">clear_custom_microorganisms()</a></code> 
+
+          <code><a href="add_custom_microorganisms.html">add_custom_microorganisms()</a></code> <code><a href="add_custom_microorganisms.html">clear_custom_microorganisms()</a></code>
+
         </dt>
         <dd>Add Custom Microorganisms</dd>
       </dl><dl><dt>
-          
-          <code><a href="mo_source.html">set_mo_source()</a></code> <code><a href="mo_source.html">get_mo_source()</a></code> 
+
+          <code><a href="mo_source.html">set_mo_source()</a></code> <code><a href="mo_source.html">get_mo_source()</a></code>
+
         </dt>
         <dd>User-Defined Reference Data Set for Microorganisms</dd>
       </dl></div><div class="section level2">
       <h2 id="preparing-data-antibiotics">Preparing data: antibiotics<a class="anchor" aria-label="anchor" href="#preparing-data-antibiotics"></a></h2>
-      
+
       <div class="section-desc"><p>Use these functions to get valid properties of antibiotics from any input or to clean your input. You can even retrieve drug names and doses from clinical text records, using <code><a href="../reference/ab_from_text.html">ab_from_text()</a></code>.</p></div>
 
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+    </div><div class="section level2">
+
+
+
 
       <dl><dt>
-          
-          <code><a href="as.ab.html">as.ab()</a></code> <code><a href="as.ab.html">is.ab()</a></code> 
+
+          <code><a href="as.ab.html">as.ab()</a></code> <code><a href="as.ab.html">is.ab()</a></code>
+
         </dt>
         <dd>Transform Input to an Antibiotic ID</dd>
       </dl><dl><dt>
-          
-          <code><a href="ab_property.html">ab_name()</a></code> <code><a href="ab_property.html">ab_cid()</a></code> <code><a href="ab_property.html">ab_synonyms()</a></code> <code><a href="ab_property.html">ab_tradenames()</a></code> <code><a href="ab_property.html">ab_group()</a></code> <code><a href="ab_property.html">ab_atc()</a></code> <code><a href="ab_property.html">ab_atc_group1()</a></code> <code><a href="ab_property.html">ab_atc_group2()</a></code> <code><a href="ab_property.html">ab_loinc()</a></code> <code><a href="ab_property.html">ab_ddd()</a></code> <code><a href="ab_property.html">ab_ddd_units()</a></code> <code><a href="ab_property.html">ab_info()</a></code> <code><a href="ab_property.html">ab_url()</a></code> <code><a href="ab_property.html">ab_property()</a></code> <code><a href="ab_property.html">set_ab_names()</a></code> 
+
+          <code><a href="ab_property.html">ab_name()</a></code> <code><a href="ab_property.html">ab_cid()</a></code> <code><a href="ab_property.html">ab_synonyms()</a></code> <code><a href="ab_property.html">ab_tradenames()</a></code> <code><a href="ab_property.html">ab_group()</a></code> <code><a href="ab_property.html">ab_atc()</a></code> <code><a href="ab_property.html">ab_atc_group1()</a></code> <code><a href="ab_property.html">ab_atc_group2()</a></code> <code><a href="ab_property.html">ab_loinc()</a></code> <code><a href="ab_property.html">ab_ddd()</a></code> <code><a href="ab_property.html">ab_ddd_units()</a></code> <code><a href="ab_property.html">ab_info()</a></code> <code><a href="ab_property.html">ab_url()</a></code> <code><a href="ab_property.html">ab_property()</a></code> <code><a href="ab_property.html">set_ab_names()</a></code>
+
         </dt>
         <dd>Get Properties of an Antibiotic</dd>
       </dl><dl><dt>
-          
-          <code><a href="ab_from_text.html">ab_from_text()</a></code> 
+
+          <code><a href="ab_from_text.html">ab_from_text()</a></code>
+
         </dt>
         <dd>Retrieve Antimicrobial Drug Names and Doses from Clinical Text</dd>
       </dl><dl><dt>
-          
-          <code><a href="atc_online.html">atc_online_property()</a></code> <code><a href="atc_online.html">atc_online_groups()</a></code> <code><a href="atc_online.html">atc_online_ddd()</a></code> <code><a href="atc_online.html">atc_online_ddd_units()</a></code> 
+
+          <code><a href="atc_online.html">atc_online_property()</a></code> <code><a href="atc_online.html">atc_online_groups()</a></code> <code><a href="atc_online.html">atc_online_ddd()</a></code> <code><a href="atc_online.html">atc_online_ddd_units()</a></code>
+
         </dt>
         <dd>Get ATC Properties from WHOCC Website</dd>
       </dl><dl><dt>
-          
-          <code><a href="add_custom_antimicrobials.html">add_custom_antimicrobials()</a></code> <code><a href="add_custom_antimicrobials.html">clear_custom_antimicrobials()</a></code> 
+
+          <code><a href="add_custom_antimicrobials.html">add_custom_antimicrobials()</a></code> <code><a href="add_custom_antimicrobials.html">clear_custom_antimicrobials()</a></code>
+
         </dt>
         <dd>Add Custom Antimicrobials</dd>
       </dl></div><div class="section level2">
       <h2 id="preparing-data-antimicrobial-results">Preparing data: antimicrobial results<a class="anchor" aria-label="anchor" href="#preparing-data-antimicrobial-results"></a></h2>
-      
+
       <div class="section-desc"><p>With <code><a href="../reference/as.mic.html">as.mic()</a></code> and <code><a href="../reference/as.disk.html">as.disk()</a></code> you can transform your raw input to valid MIC or disk diffusion values. Use <code><a href="../reference/as.sir.html">as.sir()</a></code> for cleaning raw data to let it only contain “R”, “I” and “S”, or to interpret MIC or disk diffusion values as SIR based on the lastest EUCAST and CLSI guidelines. Afterwards, you can extend antibiotic interpretations by applying <a href="https://www.eucast.org/expert_rules_and_intrinsic_resistance/" class="external-link">EUCAST rules</a> with <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>.</p></div>
 
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-    </div><div id="" class="section level2">
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+    </div><div class="section level2">
+
+
+
 
       <dl><dt>
-          
-          <code><a href="as.sir.html">as.sir()</a></code> <code><a href="as.sir.html">NA_sir_</a></code> <code><a href="as.sir.html">is.sir()</a></code> <code><a href="as.sir.html">is_sir_eligible()</a></code> <code><a href="as.sir.html">sir_interpretation_history()</a></code> 
+
+          <code><a href="as.sir.html">as.sir()</a></code> <code><a href="as.sir.html">NA_sir_</a></code> <code><a href="as.sir.html">is.sir()</a></code> <code><a href="as.sir.html">is_sir_eligible()</a></code> <code><a href="as.sir.html">sir_interpretation_history()</a></code>
+
         </dt>
         <dd>Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data</dd>
       </dl><dl><dt>
-          
-          <code><a href="as.mic.html">as.mic()</a></code> <code><a href="as.mic.html">is.mic()</a></code> <code><a href="as.mic.html">NA_mic_</a></code> <code><a href="as.mic.html">rescale_mic()</a></code> <code><a href="as.mic.html">droplevels(<i>&lt;mic&gt;</i>)</a></code> 
+
+          <code><a href="as.mic.html">as.mic()</a></code> <code><a href="as.mic.html">is.mic()</a></code> <code><a href="as.mic.html">NA_mic_</a></code> <code><a href="as.mic.html">rescale_mic()</a></code> <code><a href="as.mic.html">droplevels(<i>&lt;mic&gt;</i>)</a></code>
+
         </dt>
         <dd>Transform Input to Minimum Inhibitory Concentrations (MIC)</dd>
       </dl><dl><dt>
-          
-          <code><a href="as.disk.html">as.disk()</a></code> <code><a href="as.disk.html">NA_disk_</a></code> <code><a href="as.disk.html">is.disk()</a></code> 
+
+          <code><a href="as.disk.html">as.disk()</a></code> <code><a href="as.disk.html">NA_disk_</a></code> <code><a href="as.disk.html">is.disk()</a></code>
+
         </dt>
         <dd>Transform Input to Disk Diffusion Diameters</dd>
       </dl><dl><dt>
-          
-          <code><a href="eucast_rules.html">eucast_rules()</a></code> <code><a href="eucast_rules.html">eucast_dosage()</a></code> 
+
+          <code><a href="eucast_rules.html">eucast_rules()</a></code> <code><a href="eucast_rules.html">eucast_dosage()</a></code>
+
         </dt>
         <dd>Apply EUCAST Rules</dd>
       </dl><dl><dt>
-          
-          <code><a href="custom_eucast_rules.html">custom_eucast_rules()</a></code> 
+
+          <code><a href="custom_eucast_rules.html">custom_eucast_rules()</a></code>
+
         </dt>
         <dd>Define Custom EUCAST Rules</dd>
       </dl></div><div class="section level2">
       <h2 id="analysing-data">Analysing data<a class="anchor" aria-label="anchor" href="#analysing-data"></a></h2>
-      
+
       <div class="section-desc"><p>Use these function for the analysis part. You can use <code><a href="../reference/proportion.html">susceptibility()</a></code> or <code><a href="../reference/proportion.html">resistance()</a></code> on any antibiotic column. With <code><a href="../reference/antibiogram.html">antibiogram()</a></code>, you can generate a traditional, combined, syndromic, or weighted-incidence syndromic combination antibiogram(WISCA). This function also comes with support for R Markdown and Quarto. Be sure to first select the isolates that are appropiate for analysis, by using <code><a href="../reference/first_isolate.html">first_isolate()</a></code> or <code><a href="../reference/get_episode.html">is_new_episode()</a></code>. You can also filter your data on certain resistance in certain antibiotic classes (<code><a href="../reference/antibiotic_class_selectors.html">carbapenems()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">aminoglycosides()</a></code>), or determine multi-drug resistant microorganisms (MDRO, <code><a href="../reference/mdro.html">mdro()</a></code>).</p></div>
 
-      
-    </div><div id="" class="section level2">
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+    </div><div class="section level2">
+
+
+
 
       <dl><dt>
-          
-          <code><a href="antibiogram.html">antibiogram()</a></code> <code><a href="antibiogram.html">plot(<i>&lt;antibiogram&gt;</i>)</a></code> <code><a href="antibiogram.html">autoplot(<i>&lt;antibiogram&gt;</i>)</a></code> <code><a href="antibiogram.html">knit_print(<i>&lt;antibiogram&gt;</i>)</a></code> 
+
+          <code><a href="antibiogram.html">antibiogram()</a></code> <code><a href="antibiogram.html">plot(<i>&lt;antibiogram&gt;</i>)</a></code> <code><a href="antibiogram.html">autoplot(<i>&lt;antibiogram&gt;</i>)</a></code> <code><a href="antibiogram.html">knit_print(<i>&lt;antibiogram&gt;</i>)</a></code>
+
         </dt>
         <dd>Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted-Incidence Syndromic Combination (WISCA)</dd>
       </dl><dl><dt>
-          
-          <code><a href="proportion.html">resistance()</a></code> <code><a href="proportion.html">susceptibility()</a></code> <code><a href="proportion.html">sir_confidence_interval()</a></code> <code><a href="proportion.html">proportion_R()</a></code> <code><a href="proportion.html">proportion_IR()</a></code> <code><a href="proportion.html">proportion_I()</a></code> <code><a href="proportion.html">proportion_SI()</a></code> <code><a href="proportion.html">proportion_S()</a></code> <code><a href="proportion.html">proportion_df()</a></code> <code><a href="proportion.html">sir_df()</a></code> 
+
+          <code><a href="proportion.html">resistance()</a></code> <code><a href="proportion.html">susceptibility()</a></code> <code><a href="proportion.html">sir_confidence_interval()</a></code> <code><a href="proportion.html">proportion_R()</a></code> <code><a href="proportion.html">proportion_IR()</a></code> <code><a href="proportion.html">proportion_I()</a></code> <code><a href="proportion.html">proportion_SI()</a></code> <code><a href="proportion.html">proportion_S()</a></code> <code><a href="proportion.html">proportion_df()</a></code> <code><a href="proportion.html">sir_df()</a></code>
+
         </dt>
         <dd>Calculate Antimicrobial Resistance</dd>
       </dl><dl><dt>
-          
-          <code><a href="count.html">count_resistant()</a></code> <code><a href="count.html">count_susceptible()</a></code> <code><a href="count.html">count_S()</a></code> <code><a href="count.html">count_SI()</a></code> <code><a href="count.html">count_I()</a></code> <code><a href="count.html">count_IR()</a></code> <code><a href="count.html">count_R()</a></code> <code><a href="count.html">count_all()</a></code> <code><a href="count.html">n_sir()</a></code> <code><a href="count.html">count_df()</a></code> 
+
+          <code><a href="count.html">count_resistant()</a></code> <code><a href="count.html">count_susceptible()</a></code> <code><a href="count.html">count_S()</a></code> <code><a href="count.html">count_SI()</a></code> <code><a href="count.html">count_I()</a></code> <code><a href="count.html">count_IR()</a></code> <code><a href="count.html">count_R()</a></code> <code><a href="count.html">count_all()</a></code> <code><a href="count.html">n_sir()</a></code> <code><a href="count.html">count_df()</a></code>
+
         </dt>
         <dd>Count Available Isolates</dd>
       </dl><dl><dt>
-          
-          <code><a href="get_episode.html">get_episode()</a></code> <code><a href="get_episode.html">is_new_episode()</a></code> 
+
+          <code><a href="get_episode.html">get_episode()</a></code> <code><a href="get_episode.html">is_new_episode()</a></code>
+
         </dt>
         <dd>Determine Clinical or Epidemic Episodes</dd>
       </dl><dl><dt>
-          
-          <code><a href="first_isolate.html">first_isolate()</a></code> <code><a href="first_isolate.html">filter_first_isolate()</a></code> 
+
+          <code><a href="first_isolate.html">first_isolate()</a></code> <code><a href="first_isolate.html">filter_first_isolate()</a></code>
+
         </dt>
         <dd>Determine First Isolates</dd>
       </dl><dl><dt>
-          
-          <code><a href="key_antimicrobials.html">key_antimicrobials()</a></code> <code><a href="key_antimicrobials.html">all_antimicrobials()</a></code> <code><a href="key_antimicrobials.html">antimicrobials_equal()</a></code> 
+
+          <code><a href="key_antimicrobials.html">key_antimicrobials()</a></code> <code><a href="key_antimicrobials.html">all_antimicrobials()</a></code> <code><a href="key_antimicrobials.html">antimicrobials_equal()</a></code>
+
         </dt>
         <dd>(Key) Antimicrobials for First Weighted Isolates</dd>
       </dl><dl><dt>
-          
-          <code><a href="mdro.html">mdro()</a></code> <code><a href="mdro.html">custom_mdro_guideline()</a></code> <code><a href="mdro.html">brmo()</a></code> <code><a href="mdro.html">mrgn()</a></code> <code><a href="mdro.html">mdr_tb()</a></code> <code><a href="mdro.html">mdr_cmi2012()</a></code> <code><a href="mdro.html">eucast_exceptional_phenotypes()</a></code> 
+
+          <code><a href="mdro.html">mdro()</a></code> <code><a href="mdro.html">custom_mdro_guideline()</a></code> <code><a href="mdro.html">brmo()</a></code> <code><a href="mdro.html">mrgn()</a></code> <code><a href="mdro.html">mdr_tb()</a></code> <code><a href="mdro.html">mdr_cmi2012()</a></code> <code><a href="mdro.html">eucast_exceptional_phenotypes()</a></code>
+
         </dt>
         <dd>Determine Multidrug-Resistant Organisms (MDRO)</dd>
       </dl><dl><dt>
-          
-          <code><a href="bug_drug_combinations.html">bug_drug_combinations()</a></code> <code><a href="bug_drug_combinations.html">format(<i>&lt;bug_drug_combinations&gt;</i>)</a></code> 
+
+          <code><a href="bug_drug_combinations.html">bug_drug_combinations()</a></code> <code><a href="bug_drug_combinations.html">format(<i>&lt;bug_drug_combinations&gt;</i>)</a></code>
+
         </dt>
         <dd>Determine Bug-Drug Combinations</dd>
       </dl><dl><dt>
-          
-          <code><a href="antibiotic_class_selectors.html">ab_class()</a></code> <code><a href="antibiotic_class_selectors.html">ab_selector()</a></code> <code><a href="antibiotic_class_selectors.html">aminoglycosides()</a></code> <code><a href="antibiotic_class_selectors.html">aminopenicillins()</a></code> <code><a href="antibiotic_class_selectors.html">antifungals()</a></code> <code><a href="antibiotic_class_selectors.html">antimycobacterials()</a></code> <code><a href="antibiotic_class_selectors.html">betalactams()</a></code> <code><a href="antibiotic_class_selectors.html">carbapenems()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins_1st()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins_2nd()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins_3rd()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins_4th()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins_5th()</a></code> <code><a href="antibiotic_class_selectors.html">fluoroquinolones()</a></code> <code><a href="antibiotic_class_selectors.html">glycopeptides()</a></code> <code><a href="antibiotic_class_selectors.html">lincosamides()</a></code> <code><a href="antibiotic_class_selectors.html">lipoglycopeptides()</a></code> <code><a href="antibiotic_class_selectors.html">macrolides()</a></code> <code><a href="antibiotic_class_selectors.html">nitrofurans()</a></code> <code><a href="antibiotic_class_selectors.html">oxazolidinones()</a></code> <code><a href="antibiotic_class_selectors.html">penicillins()</a></code> <code><a href="antibiotic_class_selectors.html">polymyxins()</a></code> <code><a href="antibiotic_class_selectors.html">quinolones()</a></code> <code><a href="antibiotic_class_selectors.html">rifamycins()</a></code> <code><a href="antibiotic_class_selectors.html">streptogramins()</a></code> <code><a href="antibiotic_class_selectors.html">tetracyclines()</a></code> <code><a href="antibiotic_class_selectors.html">trimethoprims()</a></code> <code><a href="antibiotic_class_selectors.html">ureidopenicillins()</a></code> <code><a href="antibiotic_class_selectors.html">administrable_per_os()</a></code> <code><a href="antibiotic_class_selectors.html">administrable_iv()</a></code> <code><a href="antibiotic_class_selectors.html">not_intrinsic_resistant()</a></code> 
+
+          <code><a href="antibiotic_class_selectors.html">ab_class()</a></code> <code><a href="antibiotic_class_selectors.html">ab_selector()</a></code> <code><a href="antibiotic_class_selectors.html">aminoglycosides()</a></code> <code><a href="antibiotic_class_selectors.html">aminopenicillins()</a></code> <code><a href="antibiotic_class_selectors.html">antifungals()</a></code> <code><a href="antibiotic_class_selectors.html">antimycobacterials()</a></code> <code><a href="antibiotic_class_selectors.html">betalactams()</a></code> <code><a href="antibiotic_class_selectors.html">carbapenems()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins_1st()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins_2nd()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins_3rd()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins_4th()</a></code> <code><a href="antibiotic_class_selectors.html">cephalosporins_5th()</a></code> <code><a href="antibiotic_class_selectors.html">fluoroquinolones()</a></code> <code><a href="antibiotic_class_selectors.html">glycopeptides()</a></code> <code><a href="antibiotic_class_selectors.html">lincosamides()</a></code> <code><a href="antibiotic_class_selectors.html">lipoglycopeptides()</a></code> <code><a href="antibiotic_class_selectors.html">macrolides()</a></code> <code><a href="antibiotic_class_selectors.html">nitrofurans()</a></code> <code><a href="antibiotic_class_selectors.html">oxazolidinones()</a></code> <code><a href="antibiotic_class_selectors.html">penicillins()</a></code> <code><a href="antibiotic_class_selectors.html">polymyxins()</a></code> <code><a href="antibiotic_class_selectors.html">quinolones()</a></code> <code><a href="antibiotic_class_selectors.html">rifamycins()</a></code> <code><a href="antibiotic_class_selectors.html">streptogramins()</a></code> <code><a href="antibiotic_class_selectors.html">tetracyclines()</a></code> <code><a href="antibiotic_class_selectors.html">trimethoprims()</a></code> <code><a href="antibiotic_class_selectors.html">ureidopenicillins()</a></code> <code><a href="antibiotic_class_selectors.html">administrable_per_os()</a></code> <code><a href="antibiotic_class_selectors.html">administrable_iv()</a></code> <code><a href="antibiotic_class_selectors.html">not_intrinsic_resistant()</a></code>
+
         </dt>
         <dd>Antibiotic Selectors</dd>
       </dl><dl><dt>
-          
-          <code><a href="mean_amr_distance.html">mean_amr_distance()</a></code> <code><a href="mean_amr_distance.html">amr_distance_from_row()</a></code> 
+
+          <code><a href="mean_amr_distance.html">mean_amr_distance()</a></code> <code><a href="mean_amr_distance.html">amr_distance_from_row()</a></code>
+
         </dt>
         <dd>Calculate the Mean AMR Distance</dd>
       </dl><dl><dt>
-          
-          <code><a href="resistance_predict.html">resistance_predict()</a></code> <code><a href="resistance_predict.html">sir_predict()</a></code> <code><a href="resistance_predict.html">plot(<i>&lt;resistance_predict&gt;</i>)</a></code> <code><a href="resistance_predict.html">ggplot_sir_predict()</a></code> <code><a href="resistance_predict.html">autoplot(<i>&lt;resistance_predict&gt;</i>)</a></code> 
+
+          <code><a href="resistance_predict.html">resistance_predict()</a></code> <code><a href="resistance_predict.html">sir_predict()</a></code> <code><a href="resistance_predict.html">plot(<i>&lt;resistance_predict&gt;</i>)</a></code> <code><a href="resistance_predict.html">ggplot_sir_predict()</a></code> <code><a href="resistance_predict.html">autoplot(<i>&lt;resistance_predict&gt;</i>)</a></code>
+
         </dt>
         <dd>Predict Antimicrobial Resistance</dd>
       </dl><dl><dt>
-          
-          <code><a href="guess_ab_col.html">guess_ab_col()</a></code> 
+
+          <code><a href="guess_ab_col.html">guess_ab_col()</a></code>
+
         </dt>
         <dd>Guess Antibiotic Column</dd>
       </dl></div><div class="section level2">
       <h2 id="plotting-data">Plotting data<a class="anchor" aria-label="anchor" href="#plotting-data"></a></h2>
-      
+
       <div class="section-desc"><p>Use these functions for the plotting part. The <code>scale_*_mic()</code> functions extend the ggplot2 package to allow plotting of MIC values, even within a manually set range. If using <code><a href="../reference/plot.html">plot()</a></code> (base R) or <code>autoplot()</code> (ggplot2) on MIC values or disk diffusion values, the user can set the interpretation guideline to give the bars the right SIR colours. The <code><a href="../reference/ggplot_sir.html">ggplot_sir()</a></code> function is a short wrapper for users not much accustomed to ggplot2 yet. The <code><a href="../reference/ggplot_pca.html">ggplot_pca()</a></code> function is a specific function to plot so-called biplots for PCA (principal component analysis).</p></div>
 
-      
-    </div><div id="" class="section level2">
-      
-      
-      
+
+    </div><div class="section level2">
+
+
+
 
       <dl><dt>
-          
-          <code><a href="plot.html">scale_x_mic()</a></code> <code><a href="plot.html">scale_y_mic()</a></code> <code><a href="plot.html">scale_colour_mic()</a></code> <code><a href="plot.html">scale_fill_mic()</a></code> <code><a href="plot.html">plot(<i>&lt;mic&gt;</i>)</a></code> <code><a href="plot.html">autoplot(<i>&lt;mic&gt;</i>)</a></code> <code><a href="plot.html">fortify(<i>&lt;mic&gt;</i>)</a></code> <code><a href="plot.html">plot(<i>&lt;disk&gt;</i>)</a></code> <code><a href="plot.html">autoplot(<i>&lt;disk&gt;</i>)</a></code> <code><a href="plot.html">fortify(<i>&lt;disk&gt;</i>)</a></code> <code><a href="plot.html">plot(<i>&lt;sir&gt;</i>)</a></code> <code><a href="plot.html">autoplot(<i>&lt;sir&gt;</i>)</a></code> <code><a href="plot.html">fortify(<i>&lt;sir&gt;</i>)</a></code> 
+
+          <code><a href="plot.html">scale_x_mic()</a></code> <code><a href="plot.html">scale_y_mic()</a></code> <code><a href="plot.html">scale_colour_mic()</a></code> <code><a href="plot.html">scale_fill_mic()</a></code> <code><a href="plot.html">plot(<i>&lt;mic&gt;</i>)</a></code> <code><a href="plot.html">autoplot(<i>&lt;mic&gt;</i>)</a></code> <code><a href="plot.html">fortify(<i>&lt;mic&gt;</i>)</a></code> <code><a href="plot.html">plot(<i>&lt;disk&gt;</i>)</a></code> <code><a href="plot.html">autoplot(<i>&lt;disk&gt;</i>)</a></code> <code><a href="plot.html">fortify(<i>&lt;disk&gt;</i>)</a></code> <code><a href="plot.html">plot(<i>&lt;sir&gt;</i>)</a></code> <code><a href="plot.html">autoplot(<i>&lt;sir&gt;</i>)</a></code> <code><a href="plot.html">fortify(<i>&lt;sir&gt;</i>)</a></code>
+
         </dt>
         <dd>Plotting for Classes <code>sir</code>, <code>mic</code> and <code>disk</code></dd>
       </dl><dl><dt>
-          
-          <code><a href="ggplot_sir.html">ggplot_sir()</a></code> <code><a href="ggplot_sir.html">geom_sir()</a></code> <code><a href="ggplot_sir.html">facet_sir()</a></code> <code><a href="ggplot_sir.html">scale_y_percent()</a></code> <code><a href="ggplot_sir.html">scale_sir_colours()</a></code> <code><a href="ggplot_sir.html">theme_sir()</a></code> <code><a href="ggplot_sir.html">labels_sir_count()</a></code> 
+
+          <code><a href="ggplot_sir.html">ggplot_sir()</a></code> <code><a href="ggplot_sir.html">geom_sir()</a></code> <code><a href="ggplot_sir.html">facet_sir()</a></code> <code><a href="ggplot_sir.html">scale_y_percent()</a></code> <code><a href="ggplot_sir.html">scale_sir_colours()</a></code> <code><a href="ggplot_sir.html">theme_sir()</a></code> <code><a href="ggplot_sir.html">labels_sir_count()</a></code>
+
         </dt>
         <dd>AMR Plots with <code>ggplot2</code></dd>
       </dl><dl><dt>
-          
-          <code><a href="ggplot_pca.html">ggplot_pca()</a></code> 
+
+          <code><a href="ggplot_pca.html">ggplot_pca()</a></code>
+
         </dt>
         <dd>PCA Biplot with <code>ggplot2</code></dd>
       </dl></div><div class="section level2">
       <h2 id="amr-specific-options">AMR-specific options<a class="anchor" aria-label="anchor" href="#amr-specific-options"></a></h2>
-      
+
       <div class="section-desc"><p>The AMR package is customisable, by providing settings that can be set per user or per team. For example, the default interpretation guideline can be changed from EUCAST to CLSI, or a supported language can be set for the whole team (system-language independent) for antibiotic names in a foreign language.</p></div>
 
-      
-    </div><div id="" class="section level2">
-      
-      
-      
+
+    </div><div class="section level2">
+
+
+
 
       <dl><dt>
-          
-          <code><a href="AMR-options.html">AMR-options</a></code> 
+
+          <code><a href="AMR-options.html">AMR-options</a></code>
+
         </dt>
         <dd>Options for the AMR package</dd>
       </dl></div><div class="section level2">
       <h2 id="other-antiviral-drugs">Other: antiviral drugs<a class="anchor" aria-label="anchor" href="#other-antiviral-drugs"></a></h2>
-      
+
       <div class="section-desc"><p>This package also provides extensive support for antiviral agents, even though it is not the primary scope of this package. Working with data containing information about antiviral drugs was never easier. Use these functions to get valid properties of antiviral drugs from any input or to clean your input. You can even retrieve drug names and doses from clinical text records, using <code><a href="../reference/av_from_text.html">av_from_text()</a></code>.</p></div>
 
-      
-    </div><div id="" class="section level2">
-      
-      
-      
+
+    </div><div class="section level2">
+
+
+
 
       <dl><dt>
-          
-          <code><a href="as.av.html">as.av()</a></code> <code><a href="as.av.html">is.av()</a></code> 
+
+          <code><a href="as.av.html">as.av()</a></code> <code><a href="as.av.html">is.av()</a></code>
+
         </dt>
         <dd>Transform Input to an Antiviral Drug ID</dd>
       </dl><dl><dt>
-          
-          <code><a href="av_property.html">av_name()</a></code> <code><a href="av_property.html">av_cid()</a></code> <code><a href="av_property.html">av_synonyms()</a></code> <code><a href="av_property.html">av_tradenames()</a></code> <code><a href="av_property.html">av_group()</a></code> <code><a href="av_property.html">av_atc()</a></code> <code><a href="av_property.html">av_loinc()</a></code> <code><a href="av_property.html">av_ddd()</a></code> <code><a href="av_property.html">av_ddd_units()</a></code> <code><a href="av_property.html">av_info()</a></code> <code><a href="av_property.html">av_url()</a></code> <code><a href="av_property.html">av_property()</a></code> 
+
+          <code><a href="av_property.html">av_name()</a></code> <code><a href="av_property.html">av_cid()</a></code> <code><a href="av_property.html">av_synonyms()</a></code> <code><a href="av_property.html">av_tradenames()</a></code> <code><a href="av_property.html">av_group()</a></code> <code><a href="av_property.html">av_atc()</a></code> <code><a href="av_property.html">av_loinc()</a></code> <code><a href="av_property.html">av_ddd()</a></code> <code><a href="av_property.html">av_ddd_units()</a></code> <code><a href="av_property.html">av_info()</a></code> <code><a href="av_property.html">av_url()</a></code> <code><a href="av_property.html">av_property()</a></code>
+
         </dt>
         <dd>Get Properties of an Antiviral Drug</dd>
       </dl><dl><dt>
-          
-          <code><a href="av_from_text.html">av_from_text()</a></code> 
+
+          <code><a href="av_from_text.html">av_from_text()</a></code>
+
         </dt>
         <dd>Retrieve Antiviral Drug Names and Doses from Clinical Text</dd>
       </dl></div><div class="section level2">
       <h2 id="other-background-information-on-included-data">Other: background information on included data<a class="anchor" aria-label="anchor" href="#other-background-information-on-included-data"></a></h2>
-      
+
       <div class="section-desc"><p>Some pages about our package and its external sources. Be sure to read our <a href="./../articles/index.html">How To’s</a> for more information about how to work with functions in this package.</p></div>
 
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-    </div><div id="" class="section level2">
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-      
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+
+    </div><div class="section level2">
+
+
+
 
       <dl><dt>
-          
-          <code><a href="microorganisms.html">microorganisms</a></code> 
+
+          <code><a href="microorganisms.html">microorganisms</a></code>
+
         </dt>
-        <dd>Data Set with 52 171 Microorganisms</dd>
+        <dd>Data Set with 70 547 Taxonomic Records of Microorganisms</dd>
       </dl><dl><dt>
-          
-          <code><a href="antibiotics.html">antibiotics</a></code> <code><a href="antibiotics.html">antivirals</a></code> 
+
+          <code><a href="antibiotics.html">antibiotics</a></code> <code><a href="antibiotics.html">antivirals</a></code>
+
         </dt>
         <dd>Data Sets with 605 Antimicrobial Drugs</dd>
       </dl><dl><dt>
-          
-          <code><a href="clinical_breakpoints.html">clinical_breakpoints</a></code> 
+
+          <code><a href="clinical_breakpoints.html">clinical_breakpoints</a></code>
+
         </dt>
         <dd>Data Set with Clinical Breakpoints for SIR Interpretation</dd>
       </dl><dl><dt>
-          
-          <code><a href="example_isolates.html">example_isolates</a></code> 
+
+          <code><a href="example_isolates.html">example_isolates</a></code>
+
         </dt>
         <dd>Data Set with 2 000 Example Isolates</dd>
       </dl><dl><dt>
-          
-          <code><a href="microorganisms.codes.html">microorganisms.codes</a></code> 
+
+          <code><a href="microorganisms.codes.html">microorganisms.codes</a></code>
+
         </dt>
         <dd>Data Set with 4 971 Common Microorganism Codes</dd>
       </dl><dl><dt>
-          
-          <code><a href="microorganisms.groups.html">microorganisms.groups</a></code> 
+
+          <code><a href="microorganisms.groups.html">microorganisms.groups</a></code>
+
         </dt>
         <dd>Data Set with 521 Microorganisms In Species Groups</dd>
       </dl><dl><dt>
-          
-          <code><a href="intrinsic_resistant.html">intrinsic_resistant</a></code> 
+
+          <code><a href="intrinsic_resistant.html">intrinsic_resistant</a></code>
+
         </dt>
         <dd>Data Set with Bacterial Intrinsic Resistance</dd>
       </dl><dl><dt>
-          
-          <code><a href="dosage.html">dosage</a></code> 
+
+          <code><a href="dosage.html">dosage</a></code>
+
         </dt>
         <dd>Data Set with Treatment Dosages as Defined by EUCAST</dd>
       </dl><dl><dt>
-          
-          <code><a href="WHOCC.html">WHOCC</a></code> 
+
+          <code><a href="WHOCC.html">WHOCC</a></code>
+
         </dt>
         <dd>WHOCC: WHO Collaborating Centre for Drug Statistics Methodology</dd>
       </dl><dl><dt>
-          
-          <code><a href="example_isolates_unclean.html">example_isolates_unclean</a></code> 
+
+          <code><a href="example_isolates_unclean.html">example_isolates_unclean</a></code>
+
         </dt>
         <dd>Data Set with Unclean Data</dd>
       </dl><dl><dt>
-          
-          <code><a href="WHONET.html">WHONET</a></code> 
+
+          <code><a href="WHONET.html">WHONET</a></code>
+
         </dt>
         <dd>Data Set with 500 Isolates - WHONET Example</dd>
       </dl></div><div class="section level2">
       <h2 id="other-miscellaneous-functions">Other: miscellaneous functions<a class="anchor" aria-label="anchor" href="#other-miscellaneous-functions"></a></h2>
-      
+
       <div class="section-desc"><p>These functions are mostly for internal use, but some of them may also be suitable for your analysis. Especially the ‘like’ function can be useful: <code>if (x %like% y) {...}</code>.</p></div>
 
-      
-    </div><div id="" class="section level2">
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-      
+
+    </div><div class="section level2">
+
+
+
 
       <dl><dt>
-          
-          <code><a href="age_groups.html">age_groups()</a></code> 
+
+          <code><a href="age_groups.html">age_groups()</a></code>
+
         </dt>
         <dd>Split Ages into Age Groups</dd>
       </dl><dl><dt>
-          
-          <code><a href="age.html">age()</a></code> 
+
+          <code><a href="age.html">age()</a></code>
+
         </dt>
         <dd>Age in Years of Individuals</dd>
       </dl><dl><dt>
-          
-          <code><a href="export_ncbi_biosample.html">export_ncbi_biosample()</a></code> 
+
+          <code><a href="export_ncbi_biosample.html">export_ncbi_biosample()</a></code>
+
         </dt>
         <dd>Export Data Set as NCBI BioSample Antibiogram</dd>
       </dl><dl><dt>
-          
-          <code><a href="availability.html">availability()</a></code> 
+
+          <code><a href="availability.html">availability()</a></code>
+
         </dt>
         <dd>Check Availability of Columns</dd>
       </dl><dl><dt>
-          
-          <code><a href="translate.html">get_AMR_locale()</a></code> <code><a href="translate.html">set_AMR_locale()</a></code> <code><a href="translate.html">reset_AMR_locale()</a></code> <code><a href="translate.html">translate_AMR()</a></code> 
+
+          <code><a href="translate.html">get_AMR_locale()</a></code> <code><a href="translate.html">set_AMR_locale()</a></code> <code><a href="translate.html">reset_AMR_locale()</a></code> <code><a href="translate.html">translate_AMR()</a></code>
+
         </dt>
         <dd>Translate Strings from the AMR Package</dd>
       </dl><dl><dt>
-          
-          <code><a href="italicise_taxonomy.html">italicise_taxonomy()</a></code> <code><a href="italicise_taxonomy.html">italicize_taxonomy()</a></code> 
+
+          <code><a href="italicise_taxonomy.html">italicise_taxonomy()</a></code> <code><a href="italicise_taxonomy.html">italicize_taxonomy()</a></code>
+
         </dt>
         <dd>Italicise Taxonomic Families, Genera, Species, Subspecies</dd>
       </dl><dl><dt>
-          
-          <code><a href="join.html">inner_join_microorganisms()</a></code> <code><a href="join.html">left_join_microorganisms()</a></code> <code><a href="join.html">right_join_microorganisms()</a></code> <code><a href="join.html">full_join_microorganisms()</a></code> <code><a href="join.html">semi_join_microorganisms()</a></code> <code><a href="join.html">anti_join_microorganisms()</a></code> 
+
+          <code><a href="join.html">inner_join_microorganisms()</a></code> <code><a href="join.html">left_join_microorganisms()</a></code> <code><a href="join.html">right_join_microorganisms()</a></code> <code><a href="join.html">full_join_microorganisms()</a></code> <code><a href="join.html">semi_join_microorganisms()</a></code> <code><a href="join.html">anti_join_microorganisms()</a></code>
+
         </dt>
         <dd>Join microorganisms to a Data Set</dd>
       </dl><dl><dt>
-          
-          <code><a href="like.html">like()</a></code> <code><a href="like.html">`%like%`</a></code> <code><a href="like.html">`%unlike%`</a></code> <code><a href="like.html">`%like_case%`</a></code> <code><a href="like.html">`%unlike_case%`</a></code> 
+
+          <code><a href="like.html">like()</a></code> <code><a href="like.html">`%like%`</a></code> <code><a href="like.html">`%unlike%`</a></code> <code><a href="like.html">`%like_case%`</a></code> <code><a href="like.html">`%unlike_case%`</a></code>
+
         </dt>
         <dd>Vectorised Pattern Matching with Keyboard Shortcut</dd>
       </dl><dl><dt>
-          
-          <code><a href="mo_matching_score.html">mo_matching_score()</a></code> 
+
+          <code><a href="mo_matching_score.html">mo_matching_score()</a></code>
+
         </dt>
         <dd>Calculate the Matching Score for Microorganisms</dd>
       </dl><dl><dt>
-          
-          <code><a href="pca.html">pca()</a></code> 
+
+          <code><a href="pca.html">pca()</a></code>
+
         </dt>
         <dd>Principal Component Analysis (for AMR)</dd>
       </dl><dl><dt>
-          
-          <code><a href="random.html">random_mic()</a></code> <code><a href="random.html">random_disk()</a></code> <code><a href="random.html">random_sir()</a></code> 
+
+          <code><a href="random.html">random_mic()</a></code> <code><a href="random.html">random_disk()</a></code> <code><a href="random.html">random_sir()</a></code>
+
         </dt>
         <dd>Random MIC Values/Disk Zones/SIR Generation</dd>
       </dl></div><div class="section level2">
       <h2 id="other-statistical-tests">Other: statistical tests<a class="anchor" aria-label="anchor" href="#other-statistical-tests"></a></h2>
-      
+
       <div class="section-desc"><p>Some statistical tests or methods are not part of base R and were added to this package for convenience.</p></div>
 
-      
-    </div><div id="" class="section level2">
-      
-      
-      
+
+    </div><div class="section level2">
+
+
+
 
       <dl><dt>
-          
-          <code><a href="g.test.html">g.test()</a></code> 
+
+          <code><a href="g.test.html">g.test()</a></code>
+
         </dt>
         <dd><em>G</em>-test for Count Data</dd>
       </dl><dl><dt>
-          
-          <code><a href="kurtosis.html">kurtosis()</a></code> 
+
+          <code><a href="kurtosis.html">kurtosis()</a></code>
+
         </dt>
         <dd>Kurtosis of the Sample</dd>
       </dl><dl><dt>
-          
-          <code><a href="skewness.html">skewness()</a></code> 
+
+          <code><a href="skewness.html">skewness()</a></code>
+
         </dt>
         <dd>Skewness of the Sample</dd>
       </dl></div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -588,9 +541,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/inner_join.html b/reference/inner_join.html
new file mode 100644
index 000000000..0bdfa18c3
--- /dev/null
+++ b/reference/inner_join.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/join.html" />
+    <meta name="robots" content="noindex">
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+  </head>
+</html>
+
diff --git a/reference/inner_join_microorganisms.html b/reference/inner_join_microorganisms.html
new file mode 100644
index 000000000..0bdfa18c3
--- /dev/null
+++ b/reference/inner_join_microorganisms.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/join.html" />
+    <meta name="robots" content="noindex">
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+  </head>
+</html>
+
diff --git a/reference/intrinsic_resistant.html b/reference/intrinsic_resistant.html
index 80195cdb7..0a783a2fc 100644
--- a/reference/intrinsic_resistant.html
+++ b/reference/intrinsic_resistant.html
@@ -1,161 +1,55 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Data set containing defined intrinsic resistance by EUCAST of all bug-drug combinations."><title>Data Set with Bacterial Intrinsic Resistance — intrinsic_resistant • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Data Set with Bacterial Intrinsic Resistance — intrinsic_resistant"><meta property="og:description" content="Data set containing defined intrinsic resistance by EUCAST of all bug-drug combinations."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Data Set with Bacterial Intrinsic Resistance — intrinsic_resistant • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Data Set with Bacterial Intrinsic Resistance — intrinsic_resistant"><meta name="description" content="Data set containing defined intrinsic resistance by EUCAST of all bug-drug combinations."><meta property="og:description" content="Data set containing defined intrinsic resistance by EUCAST of all bug-drug combinations."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"></head><body>
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+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
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+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul></li>
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
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+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
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       <img src="../logo.svg" class="logo" alt=""><h1>Data Set with Bacterial Intrinsic Resistance</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/data.R" class="external-link"><code>R/data.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/data.R" class="external-link"><code>R/data.R</code></a></small>
       <div class="d-none name"><code>intrinsic_resistant.Rd</code></div>
     </div>
 
@@ -170,7 +64,7 @@
 
     <div class="section level2">
     <h2 id="format">Format<a class="anchor" aria-label="anchor" href="#format"></a></h2>
-    <p>A <a href="https://tibble.tidyverse.org/reference/tibble.html" class="external-link">tibble</a> with 134 634 observations and 2 variables:</p><ul><li><p><code>mo</code><br> Microorganism ID</p></li>
+    <p>A <a href="https://tibble.tidyverse.org/reference/tibble.html" class="external-link">tibble</a> with 340 804 observations and 2 variables:</p><ul><li><p><code>mo</code><br> Microorganism ID</p></li>
 <li><p><code>ab</code><br> Antibiotic ID</p></li>
 </ul></div>
     <div class="section level2">
@@ -188,23 +82,23 @@
     <div class="section level2">
     <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">intrinsic_resistant</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 134,634 × 2</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    mo      ab   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> B_GRAMP ATM  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> B_GRAMP COL  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> B_GRAMP NAL  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> B_GRAMP PLB  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> B_GRAMP TEM  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> B_ABTRP ATM  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> B_ABTRP COL  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> B_ABTRP NAL  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> B_ABTRP PLB  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> B_ABTRP TEM  </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 134,624 more rows</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 340,804 × 2</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>    mo          ab  </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span>        <span style="color: #949494; font-style: italic;">&lt;ab&gt;</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> B_GRAMP     ATM </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> B_GRAMP     COL </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> B_GRAMP     NAL </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> B_GRAMP     PLB </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> B_GRAMP     TEM </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> B_ANAER-POS ATM </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> B_ANAER-POS COL </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> B_ANAER-POS NAL </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> B_ANAER-POS PLB </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> B_ANAER-POS TEM </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 340,794 more rows</span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -218,9 +112,9 @@
 
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new file mode 100644
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new file mode 100644
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+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul></li>
 <li class="nav-item dropdown">
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Italicise Taxonomic Families, Genera, Species, Subspecies</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/italicise_taxonomy.R" class="external-link"><code>R/italicise_taxonomy.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/italicise_taxonomy.R" class="external-link"><code>R/italicise_taxonomy.R</code></a></small>
       <div class="d-none name"><code>italicise_taxonomy.Rd</code></div>
     </div>
 
@@ -172,11 +66,13 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>string</dt>
+
+
+<dl><dt id="arg-string">string<a class="anchor" aria-label="anchor" href="#arg-string"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> (vector)</p></dd>
 
 
-<dt>type</dt>
+<dt id="arg-type">type<a class="anchor" aria-label="anchor" href="#arg-type"></a></dt>
 <dd><p>type of conversion of the taxonomic names, either "markdown", "html" or "ansi", see <em>Details</em></p></dd>
 
 </dl></div>
@@ -198,7 +94,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> An overview of <span style="font-style: italic;">S. aureus</span> isolates</span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -212,9 +108,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/italicize_taxonomy.html b/reference/italicize_taxonomy.html
new file mode 100644
index 000000000..e0b607717
--- /dev/null
+++ b/reference/italicize_taxonomy.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/italicise_taxonomy.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/italicise_taxonomy.html">
+  </head>
+</html>
+
diff --git a/reference/join.html b/reference/join.html
index be5d1eafd..1f183585f 100644
--- a/reference/join.html
+++ b/reference/join.html
@@ -1,161 +1,55 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Join the data set microorganisms easily to an existing data set or to a character vector."><title>Join microorganisms to a Data Set — join • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Join microorganisms to a Data Set — join"><meta property="og:description" content="Join the data set microorganisms easily to an existing data set or to a character vector."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9061</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9063</small>
+
 
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+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
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+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Join <a href="microorganisms.html">microorganisms</a> to a Data Set</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/join_microorganisms.R" class="external-link"><code>R/join_microorganisms.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/join_microorganisms.R" class="external-link"><code>R/join_microorganisms.R</code></a></small>
       <div class="d-none name"><code>join.Rd</code></div>
     </div>
 
@@ -180,29 +74,27 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>existing data set to join, or <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector. In case of a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector, the resulting <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> will contain a column 'x' with these values.</p></dd>
 
 
-<dt>by</dt>
+<dt id="arg-by">by<a class="anchor" aria-label="anchor" href="#arg-by"></a></dt>
 <dd><p>a variable to join by - if left empty will search for a column with class <code><a href="as.mo.html">mo</a></code> (created with <code><a href="as.mo.html">as.mo()</a></code>) or will be <code>"mo"</code> if that column name exists in <code>x</code>, could otherwise be a column name of <code>x</code> with values that exist in <code>microorganisms$mo</code> (such as <code>by = "bacteria_id"</code>), or another column in <a href="microorganisms.html">microorganisms</a> (but then it should be named, like <code>by = c("bacteria_id" = "fullname")</code>)</p></dd>
 
 
-<dt>suffix</dt>
+<dt id="arg-suffix">suffix<a class="anchor" aria-label="anchor" href="#arg-suffix"></a></dt>
 <dd><p>if there are non-joined duplicate variables in <code>x</code> and <code>y</code>, these suffixes will be added to the output to disambiguate them. Should be a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector of length 2.</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>ignored, only in place to allow future extensions</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></p>
-
-
+    <p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -213,22 +105,24 @@
     <div class="section level2">
     <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="fu">left_join_microorganisms</span><span class="op">(</span><span class="fu"><a href="as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 1 × 23</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 1 × 26</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   mo           fullname   status kingdom phylum class order family genus species</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>  </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> B_KLBSL_PNMN Klebsiell… accep… Bacter… Pseud… Gamm… Ente… Enter… Kleb… pneumo…</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 13 more variables: subspecies &lt;chr&gt;, rank &lt;chr&gt;, ref &lt;chr&gt;,</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 16 more variables: subspecies &lt;chr&gt;, rank &lt;chr&gt;, ref &lt;chr&gt;,</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   oxygen_tolerance &lt;chr&gt;, source &lt;chr&gt;, lpsn &lt;chr&gt;, lpsn_parent &lt;chr&gt;,</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   lpsn_renamed_to &lt;chr&gt;, gbif &lt;chr&gt;, gbif_parent &lt;chr&gt;,</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   lpsn_renamed_to &lt;chr&gt;, mycobank &lt;chr&gt;, mycobank_parent &lt;chr&gt;,</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   mycobank_renamed_to &lt;chr&gt;, gbif &lt;chr&gt;, gbif_parent &lt;chr&gt;,</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   gbif_renamed_to &lt;chr&gt;, prevalence &lt;dbl&gt;, snomed &lt;list&gt;</span></span>
 <span class="r-in"><span><span class="fu">left_join_microorganisms</span><span class="op">(</span><span class="st">"B_KLBSL_PNMN"</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 1 × 23</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 1 × 26</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   mo           fullname   status kingdom phylum class order family genus species</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>  </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> B_KLBSL_PNMN Klebsiell… accep… Bacter… Pseud… Gamm… Ente… Enter… Kleb… pneumo…</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 13 more variables: subspecies &lt;chr&gt;, rank &lt;chr&gt;, ref &lt;chr&gt;,</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 16 more variables: subspecies &lt;chr&gt;, rank &lt;chr&gt;, ref &lt;chr&gt;,</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   oxygen_tolerance &lt;chr&gt;, source &lt;chr&gt;, lpsn &lt;chr&gt;, lpsn_parent &lt;chr&gt;,</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   lpsn_renamed_to &lt;chr&gt;, gbif &lt;chr&gt;, gbif_parent &lt;chr&gt;,</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   lpsn_renamed_to &lt;chr&gt;, mycobank &lt;chr&gt;, mycobank_parent &lt;chr&gt;,</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   mycobank_renamed_to &lt;chr&gt;, gbif &lt;chr&gt;, gbif_parent &lt;chr&gt;,</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   gbif_renamed_to &lt;chr&gt;, prevalence &lt;dbl&gt;, snomed &lt;list&gt;</span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="va">df</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span></span></span>
@@ -248,12 +142,15 @@
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="va">df_joined</span> <span class="op">&lt;-</span> <span class="fu">left_join_microorganisms</span><span class="op">(</span><span class="va">df</span>, <span class="st">"bacteria"</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">colnames</a></span><span class="op">(</span><span class="va">df_joined</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [1] "date"             "bacteria"         "fullname"         "status"          </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [5] "kingdom"          "phylum"           "class"            "order"           </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [9] "family"           "genus"            "species"          "subspecies"      </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [13] "rank"             "ref"              "oxygen_tolerance" "source"          </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [17] "lpsn"             "lpsn_parent"      "lpsn_renamed_to"  "gbif"            </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [21] "gbif_parent"      "gbif_renamed_to"  "prevalence"       "snomed"          </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>  [1] "date"                "bacteria"            "fullname"           </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>  [4] "status"              "kingdom"             "phylum"             </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>  [7] "class"               "order"               "family"             </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [10] "genus"               "species"             "subspecies"         </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [13] "rank"                "ref"                 "oxygen_tolerance"   </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [16] "source"              "lpsn"                "lpsn_parent"        </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [19] "lpsn_renamed_to"     "mycobank"            "mycobank_parent"    </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [22] "mycobank_renamed_to" "gbif"                "gbif_parent"        </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [25] "gbif_renamed_to"     "prevalence"          "snomed"             </span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># \donttest{</span></span></span>
 <span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
@@ -262,27 +159,34 @@
 <span class="r-in"><span>    <span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">colnames</a></span><span class="op">(</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="op">}</span></span></span>
 <span class="r-msg co"><span class="r-pr">#&gt;</span> Joining, by = "mo"</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [1] "date"             "patient"          "age"              "gender"          </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [5] "ward"             "mo"               "PEN"              "OXA"             </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [9] "FLC"              "AMX"              "AMC"              "AMP"             </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [13] "TZP"              "CZO"              "FEP"              "CXM"             </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [17] "FOX"              "CTX"              "CAZ"              "CRO"             </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [21] "GEN"              "TOB"              "AMK"              "KAN"             </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [25] "TMP"              "SXT"              "NIT"              "FOS"             </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [29] "LNZ"              "CIP"              "MFX"              "VAN"             </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [33] "TEC"              "TCY"              "TGC"              "DOX"             </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [37] "ERY"              "CLI"              "AZM"              "IPM"             </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [41] "MEM"              "MTR"              "CHL"              "COL"             </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [45] "MUP"              "RIF"              "fullname"         "status"          </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [49] "kingdom"          "phylum"           "class"            "order"           </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [53] "family"           "genus"            "species"          "subspecies"      </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [57] "rank"             "ref"              "oxygen_tolerance" "source"          </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [61] "lpsn"             "lpsn_parent"      "lpsn_renamed_to"  "gbif"            </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [65] "gbif_parent"      "gbif_renamed_to"  "prevalence"       "snomed"          </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>  [1] "date"                "patient"             "age"                </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>  [4] "gender"              "ward"                "mo"                 </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>  [7] "PEN"                 "OXA"                 "FLC"                </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [10] "AMX"                 "AMC"                 "AMP"                </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [13] "TZP"                 "CZO"                 "FEP"                </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [16] "CXM"                 "FOX"                 "CTX"                </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [19] "CAZ"                 "CRO"                 "GEN"                </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [22] "TOB"                 "AMK"                 "KAN"                </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [25] "TMP"                 "SXT"                 "NIT"                </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [28] "FOS"                 "LNZ"                 "CIP"                </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [31] "MFX"                 "VAN"                 "TEC"                </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [34] "TCY"                 "TGC"                 "DOX"                </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [37] "ERY"                 "CLI"                 "AZM"                </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [40] "IPM"                 "MEM"                 "MTR"                </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [43] "CHL"                 "COL"                 "MUP"                </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [46] "RIF"                 "fullname"            "status"             </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [49] "kingdom"             "phylum"              "class"              </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [52] "order"               "family"              "genus"              </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [55] "species"             "subspecies"          "rank"               </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [58] "ref"                 "oxygen_tolerance"    "source"             </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [61] "lpsn"                "lpsn_parent"         "lpsn_renamed_to"    </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [64] "mycobank"            "mycobank_parent"     "mycobank_renamed_to"</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [67] "gbif"                "gbif_parent"         "gbif_renamed_to"    </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [70] "prevalence"          "snomed"             </span>
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -296,9 +200,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/key_antimicrobials.html b/reference/key_antimicrobials.html
index 636da0181..b4295642d 100644
--- a/reference/key_antimicrobials.html
+++ b/reference/key_antimicrobials.html
@@ -1,161 +1,55 @@
 <!DOCTYPE html>
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       <img src="../logo.svg" class="logo" alt=""><h1>(Key) Antimicrobials for First Weighted Isolates</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/key_antimicrobials.R" class="external-link"><code>R/key_antimicrobials.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/key_antimicrobials.R" class="external-link"><code>R/key_antimicrobials.R</code></a></small>
       <div class="d-none name"><code>key_antimicrobials.Rd</code></div>
     </div>
 
@@ -194,51 +88,53 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with antibiotics columns, like <code>AMX</code> or <code>amox</code>. Can be left blank to determine automatically</p></dd>
 
 
-<dt>col_mo</dt>
+<dt id="arg-col-mo">col_mo<a class="anchor" aria-label="anchor" href="#arg-col-mo"></a></dt>
 <dd><p>column name of the names or codes of the microorganisms (see <code><a href="as.mo.html">as.mo()</a></code>) - the default is the first column of class <code><a href="as.mo.html">mo</a></code>. Values will be coerced using <code><a href="as.mo.html">as.mo()</a></code>.</p></dd>
 
 
-<dt>universal</dt>
+<dt id="arg-universal">universal<a class="anchor" aria-label="anchor" href="#arg-universal"></a></dt>
 <dd><p>names of <strong>broad-spectrum</strong> antimicrobial drugs, case-insensitive. Set to <code>NULL</code> to ignore. See <em>Details</em> for the default antimicrobial drugs</p></dd>
 
 
-<dt>gram_negative</dt>
+<dt id="arg-gram-negative">gram_negative<a class="anchor" aria-label="anchor" href="#arg-gram-negative"></a></dt>
 <dd><p>names of antibiotic drugs for <strong>Gram-positives</strong>, case-insensitive. Set to <code>NULL</code> to ignore. See <em>Details</em> for the default antibiotic drugs</p></dd>
 
 
-<dt>gram_positive</dt>
+<dt id="arg-gram-positive">gram_positive<a class="anchor" aria-label="anchor" href="#arg-gram-positive"></a></dt>
 <dd><p>names of antibiotic drugs for <strong>Gram-negatives</strong>, case-insensitive. Set to <code>NULL</code> to ignore. See <em>Details</em> for the default antibiotic drugs</p></dd>
 
 
-<dt>antifungal</dt>
+<dt id="arg-antifungal">antifungal<a class="anchor" aria-label="anchor" href="#arg-antifungal"></a></dt>
 <dd><p>names of antifungal drugs for <strong>fungi</strong>, case-insensitive. Set to <code>NULL</code> to ignore. See <em>Details</em> for the default antifungal drugs</p></dd>
 
 
-<dt>only_sir_columns</dt>
+<dt id="arg-only-sir-columns">only_sir_columns<a class="anchor" aria-label="anchor" href="#arg-only-sir-columns"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether only columns must be included that were transformed to class <code>sir</code> (see <code><a href="as.sir.html">as.sir()</a></code>) on beforehand (default is <code>FALSE</code>)</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>ignored, only in place to allow future extensions</p></dd>
 
 
-<dt>y, z</dt>
+<dt id="arg-y-z">y, z<a class="anchor" aria-label="anchor" href="#arg-y-z"></a></dt>
 <dd><p><a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vectors to compare</p></dd>
 
 
-<dt>type</dt>
+<dt id="arg-type">type<a class="anchor" aria-label="anchor" href="#arg-type"></a></dt>
 <dd><p>type to determine weighed isolates; can be <code>"keyantimicrobials"</code> or <code>"points"</code>, see <em>Details</em></p></dd>
 
 
-<dt>ignore_I</dt>
+<dt id="arg-ignore-i">ignore_I<a class="anchor" aria-label="anchor" href="#arg-ignore-i"></a></dt>
 <dd><p><a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether antibiotic interpretations with <code>"I"</code> will be ignored when <code>type = "keyantimicrobials"</code>, see <em>Details</em></p></dd>
 
 
-<dt>points_threshold</dt>
+<dt id="arg-points-threshold">points_threshold<a class="anchor" aria-label="anchor" href="#arg-points-threshold"></a></dt>
 <dd><p>minimum number of points to require before differences in the antibiogram will lead to inclusion of an isolate when <code>type = "points"</code>, see <em>Details</em></p></dd>
 
 </dl></div>
@@ -315,7 +211,7 @@
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -329,9 +225,9 @@
 
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-  
 
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new file mode 100644
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@@ -0,0 +1,8 @@
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   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Kurtosis of the Sample</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/kurtosis.R" class="external-link"><code>R/kurtosis.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/kurtosis.R" class="external-link"><code>R/kurtosis.R</code></a></small>
       <div class="d-none name"><code>kurtosis.Rd</code></div>
     </div>
 
@@ -167,27 +61,29 @@
     <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">kurtosis</span><span class="op">(</span><span class="va">x</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span>, excess <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for default</span></span>
+<span><span class="co"># Default S3 method</span></span>
 <span><span class="fu">kurtosis</span><span class="op">(</span><span class="va">x</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span>, excess <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for matrix</span></span>
+<span><span class="co"># S3 method for class 'matrix'</span></span>
 <span><span class="fu">kurtosis</span><span class="op">(</span><span class="va">x</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span>, excess <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for data.frame</span></span>
+<span><span class="co"># S3 method for class 'data.frame'</span></span>
 <span><span class="fu">kurtosis</span><span class="op">(</span><span class="va">x</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span>, excess <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div>
     </div>
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>a vector of values, a <a href="https://rdrr.io/r/base/matrix.html" class="external-link">matrix</a> or a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></p></dd>
 
 
-<dt>na.rm</dt>
+<dt id="arg-na-rm">na.rm<a class="anchor" aria-label="anchor" href="#arg-na-rm"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether <code>NA</code> values should be stripped before the computation proceeds</p></dd>
 
 
-<dt>excess</dt>
+<dt id="arg-excess">excess<a class="anchor" aria-label="anchor" href="#arg-excess"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether the <em>excess kurtosis</em> should be returned, defined as the kurtosis minus 3.</p></dd>
 
 </dl></div>
@@ -204,7 +100,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.08143396</span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -218,9 +114,9 @@
 
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diff --git a/reference/left_join_microorganisms.html b/reference/left_join_microorganisms.html
new file mode 100644
index 000000000..0bdfa18c3
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@@ -0,0 +1,8 @@
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diff --git a/reference/like.html b/reference/like.html
index afbd807fd..3bc78e2aa 100644
--- a/reference/like.html
+++ b/reference/like.html
@@ -1,161 +1,55 @@
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
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+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
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+
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 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Vectorised Pattern Matching with Keyboard Shortcut</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/like.R" class="external-link"><code>R/like.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/like.R" class="external-link"><code>R/like.R</code></a></small>
       <div class="d-none name"><code>like.Rd</code></div>
     </div>
 
@@ -182,23 +76,23 @@
     </div>
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector where matches are sought, or an object which can be coerced by <code><a href="https://rdrr.io/r/base/character.html" class="external-link">as.character()</a></code> to a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector.</p></dd>
 
 
-<dt>pattern</dt>
+<dt id="arg-pattern">pattern<a class="anchor" aria-label="anchor" href="#arg-pattern"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector containing regular expressions (or a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> string for <code>fixed = TRUE</code>) to be matched in the given <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector. Coerced by <code><a href="https://rdrr.io/r/base/character.html" class="external-link">as.character()</a></code> to a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> string if possible.</p></dd>
 
 
-<dt>ignore.case</dt>
+<dt id="arg-ignore-case">ignore.case<a class="anchor" aria-label="anchor" href="#arg-ignore-case"></a></dt>
 <dd><p>if <code>FALSE</code>, the pattern matching is <em>case sensitive</em> and if <code>TRUE</code>, case is ignored during matching.</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> vector</p>
+    <p>A <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> vector</p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -291,7 +185,7 @@
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -305,9 +199,9 @@
 
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-  
 
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diff --git a/reference/lincosamides.html b/reference/lincosamides.html
new file mode 100644
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@@ -0,0 +1,8 @@
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new file mode 100644
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       <img src="../logo.svg" class="logo" alt=""><h1>Determine Multidrug-Resistant Organisms (MDRO)</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/mdro.R" class="external-link"><code>R/mdro.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/mdro.R" class="external-link"><code>R/mdro.R</code></a></small>
       <div class="d-none name"><code>mdro.Rd</code></div>
     </div>
 
@@ -196,49 +90,50 @@
     </div>
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with antibiotics columns, like <code>AMX</code> or <code>amox</code>. Can be left blank for automatic determination.</p></dd>
 
 
-<dt>guideline</dt>
+<dt id="arg-guideline">guideline<a class="anchor" aria-label="anchor" href="#arg-guideline"></a></dt>
 <dd><p>a specific guideline to follow, see sections <em>Supported international / national guidelines</em> and <em>Using Custom Guidelines</em> below. When left empty, the publication by Magiorakos <em>et al.</em> (see below) will be followed.</p></dd>
 
 
-<dt>col_mo</dt>
+<dt id="arg-col-mo">col_mo<a class="anchor" aria-label="anchor" href="#arg-col-mo"></a></dt>
 <dd><p>column name of the names or codes of the microorganisms (see <code><a href="as.mo.html">as.mo()</a></code>) - the default is the first column of class <code><a href="as.mo.html">mo</a></code>. Values will be coerced using <code><a href="as.mo.html">as.mo()</a></code>.</p></dd>
 
 
-<dt>info</dt>
+<dt id="arg-info">info<a class="anchor" aria-label="anchor" href="#arg-info"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether progress should be printed to the console - the default is only print while in interactive sessions</p></dd>
 
 
-<dt>pct_required_classes</dt>
+<dt id="arg-pct-required-classes">pct_required_classes<a class="anchor" aria-label="anchor" href="#arg-pct-required-classes"></a></dt>
 <dd><p>minimal required percentage of antimicrobial classes that must be available per isolate, rounded down. For example, with the default guideline, 17 antimicrobial classes must be available for <em>S. aureus</em>. Setting this <code>pct_required_classes</code> argument to <code>0.5</code> (default) means that for every <em>S. aureus</em> isolate at least 8 different classes must be available. Any lower number of available classes will return <code>NA</code> for that isolate.</p></dd>
 
 
-<dt>combine_SI</dt>
+<dt id="arg-combine-si">combine_SI<a class="anchor" aria-label="anchor" href="#arg-combine-si"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether all values of S and I must be merged into one, so resistance is only considered when isolates are R, not I. As this is the default behaviour of the <code>mdro()</code> function, it follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section 'Interpretation of S, I and R' below. When using <code>combine_SI = FALSE</code>, resistance is considered when isolates are R or I.</p></dd>
 
 
-<dt>verbose</dt>
+<dt id="arg-verbose">verbose<a class="anchor" aria-label="anchor" href="#arg-verbose"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to turn Verbose mode on and off (default is off). In Verbose mode, the function does not return the MDRO results, but instead returns a data set in logbook form with extensive info about which isolates would be MDRO-positive, or why they are not.</p></dd>
 
 
-<dt>only_sir_columns</dt>
+<dt id="arg-only-sir-columns">only_sir_columns<a class="anchor" aria-label="anchor" href="#arg-only-sir-columns"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether only antibiotic columns must be detected that were transformed to class <code>sir</code> (see <code><a href="as.sir.html">as.sir()</a></code>) on beforehand (default is <code>FALSE</code>)</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>in case of <code>custom_mdro_guideline()</code>: a set of rules, see section <em>Using Custom Guidelines</em> below. Otherwise: column name of an antibiotic, see section <em>Antibiotics</em> below.</p></dd>
 
 
-<dt>as_factor</dt>
+<dt id="arg-as-factor">as_factor<a class="anchor" aria-label="anchor" href="#arg-as-factor"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether the returned value should be an ordered <a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a> (<code>TRUE</code>, default), or otherwise a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> vector</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
 
 <ul><li><p>CMI 2012 paper - function <code>mdr_cmi2012()</code> or <code>mdro()</code>:<br>
 Ordered <a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a> with levels <code>Negative</code> &lt; <code>Multi-drug-resistant (MDR)</code> &lt; <code>Extensively drug-resistant (XDR)</code> &lt; <code>Pandrug-resistant (PDR)</code></p></li>
@@ -257,7 +152,7 @@ Ordered <a href="https://rdrr.io/r/base/factor.html" class="external-link">facto
     </div>
     <div class="section level2">
     <h2 id="supported-international-national-guidelines">Supported International / National Guidelines<a class="anchor" aria-label="anchor" href="#supported-international-national-guidelines"></a></h2>
-    
+
 
 
 <p>Currently supported guidelines are (case-insensitive):</p><ul><li><p><code>guideline = "CMI2012"</code> (default)</p>
@@ -279,7 +174,7 @@ Ordered <a href="https://rdrr.io/r/base/factor.html" class="external-link">facto
     </div>
     <div class="section level2">
     <h2 id="using-custom-guidelines">Using Custom Guidelines<a class="anchor" aria-label="anchor" href="#using-custom-guidelines"></a></h2>
-    
+
 
 
 <p>Custom guidelines can be set with the <code>custom_mdro_guideline()</code> function. This is of great importance if you have custom rules to determine MDROs in your hospital, e.g., rules that are dependent on ward, state of contact isolation or other variables in your data.</p>
@@ -312,7 +207,7 @@ Ordered <a href="https://rdrr.io/r/base/factor.html" class="external-link">facto
     </div>
     <div class="section level2">
     <h2 id="antibiotics">Antibiotics<a class="anchor" aria-label="anchor" href="#antibiotics"></a></h2>
-    
+
 
 <p>To define antibiotics column names, leave as it is to determine it automatically with <code><a href="guess_ab_col.html">guess_ab_col()</a></code> or input a text (case-insensitive), or use <code>NULL</code> to skip a column (e.g. <code>TIC = NULL</code> to skip ticarcillin). Manually defined but non-existing columns will be skipped with a warning.</p>
 <p>The following antibiotics are eligible for the functions <code><a href="eucast_rules.html">eucast_rules()</a></code> and <code>mdro()</code>. These are shown below in the format 'name (<code>antimicrobial ID</code>, <a href="https://atcddd.fhi.no/atc/structure_and_principles/" class="external-link">ATC code</a>)', sorted alphabetically:</p>
@@ -320,7 +215,7 @@ Ordered <a href="https://rdrr.io/r/base/factor.html" class="external-link">facto
     </div>
     <div class="section level2">
     <h2 id="interpretation-of-sir">Interpretation of SIR<a class="anchor" aria-label="anchor" href="#interpretation-of-sir"></a></h2>
-    
+
 
 <p>In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories S, I, and R as shown below (<a href="https://www.eucast.org/newsiandr" class="external-link">https://www.eucast.org/newsiandr</a>):</p><ul><li><p><strong>S - Susceptible, standard dosing regimen</strong><br>
 A microorganism is categorised as "Susceptible, standard dosing regimen", when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.</p></li>
@@ -380,7 +275,7 @@ A microorganism is categorised as "Resistant" when there is a high likelihood of
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -394,9 +289,9 @@ A microorganism is categorised as "Resistant" when there is a high likelihood of
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/mean_amr_distance.data.frame.html b/reference/mean_amr_distance.data.frame.html
new file mode 100644
index 000000000..9aab5d00c
--- /dev/null
+++ b/reference/mean_amr_distance.data.frame.html
@@ -0,0 +1,8 @@
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index 7a4664f6c..ac52016fe 100644
--- a/reference/mean_amr_distance.html
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@@ -1,161 +1,55 @@
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       <img src="../logo.svg" class="logo" alt=""><h1>Calculate the Mean AMR Distance</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/mean_amr_distance.R" class="external-link"><code>R/mean_amr_distance.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/mean_amr_distance.R" class="external-link"><code>R/mean_amr_distance.R</code></a></small>
       <div class="d-none name"><code>mean_amr_distance.Rd</code></div>
     </div>
 
@@ -167,10 +61,10 @@
     <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">mean_amr_distance</span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for sir</span></span>
+<span><span class="co"># S3 method for class 'sir'</span></span>
 <span><span class="fu">mean_amr_distance</span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span>, combine_SI <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for data.frame</span></span>
+<span><span class="co"># S3 method for class 'data.frame'</span></span>
 <span><span class="fu">mean_amr_distance</span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span>, combine_SI <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span>
 <span></span>
 <span><span class="fu">amr_distance_from_row</span><span class="op">(</span><span class="va">amr_distance</span>, <span class="va">row</span><span class="op">)</span></span></code></pre></div>
@@ -178,23 +72,25 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>a vector of class <a href="as.sir.html">sir</a>, <a href="as.mic.html">mic</a> or <a href="as.disk.html">disk</a>, or a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> containing columns of any of these classes</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>variables to select (supports <a href="https://tidyselect.r-lib.org/reference/language.html" class="external-link">tidyselect language</a> such as <code>column1:column4</code> and <code>where(is.mic)</code>, and can thus also be <a href="antibiotic_class_selectors.html">antibiotic selectors</a></p></dd>
 
 
-<dt>combine_SI</dt>
+<dt id="arg-combine-si">combine_SI<a class="anchor" aria-label="anchor" href="#arg-combine-si"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether all values of S and I must be merged into one, so the input only consists of S+I vs. R (susceptible vs. resistant) - the default is <code>TRUE</code></p></dd>
 
 
-<dt>amr_distance</dt>
+<dt id="arg-amr-distance">amr_distance<a class="anchor" aria-label="anchor" href="#arg-amr-distance"></a></dt>
 <dd><p>the outcome of <code>mean_amr_distance()</code></p></dd>
 
 
-<dt>row</dt>
+<dt id="arg-row">row<a class="anchor" aria-label="anchor" href="#arg-row"></a></dt>
 <dd><p>an index, such as a row number</p></dd>
 
 </dl></div>
@@ -208,7 +104,7 @@
     </div>
     <div class="section level2">
     <h2 id="interpretation">Interpretation<a class="anchor" aria-label="anchor" href="#interpretation"></a></h2>
-    
+
 
 <p>Isolates with distances less than 0.01 difference from each other should be considered similar. Differences lower than 0.025 should be considered suspicious.</p>
     </div>
@@ -323,7 +219,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 53 more rows</span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -337,9 +233,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/mean_amr_distance.sir.html b/reference/mean_amr_distance.sir.html
new file mode 100644
index 000000000..9aab5d00c
--- /dev/null
+++ b/reference/mean_amr_distance.sir.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mean_amr_distance.html" />
+    <meta name="robots" content="noindex">
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+  </head>
+</html>
+
diff --git a/reference/mic.html b/reference/mic.html
new file mode 100644
index 000000000..977eb978a
--- /dev/null
+++ b/reference/mic.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/as.mic.html" />
+    <meta name="robots" content="noindex">
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+
diff --git a/reference/microorganisms.codes.html b/reference/microorganisms.codes.html
index 379ad437d..02f13d322 100644
--- a/reference/microorganisms.codes.html
+++ b/reference/microorganisms.codes.html
@@ -1,161 +1,55 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="A data set containing commonly used codes for microorganisms, from laboratory systems and WHONET. Define your own with set_mo_source(). They will all be searched when using as.mo() and consequently all the mo_* functions."><title>Data Set with 4 971 Common Microorganism Codes — microorganisms.codes • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Data Set with 4 971 Common Microorganism Codes — microorganisms.codes"><meta property="og:description" content="A data set containing commonly used codes for microorganisms, from laboratory systems and WHONET. Define your own with set_mo_source(). They will all be searched when using as.mo() and consequently all the mo_* functions."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Data Set with 4 971 Common Microorganism Codes</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/data.R" class="external-link"><code>R/data.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/data.R" class="external-link"><code>R/data.R</code></a></small>
       <div class="d-none name"><code>microorganisms.codes.Rd</code></div>
     </div>
 
@@ -170,7 +64,7 @@
 
     <div class="section level2">
     <h2 id="format">Format<a class="anchor" aria-label="anchor" href="#format"></a></h2>
-    <p>A <a href="https://tibble.tidyverse.org/reference/tibble.html" class="external-link">tibble</a> with 4 971 observations and 2 variables:</p><ul><li><p><code>code</code><br> Commonly used code of a microorganism. <em>This is a unique identifier.</em></p></li>
+    <p>A <a href="https://tibble.tidyverse.org/reference/tibble.html" class="external-link">tibble</a> with 4 971 observations and 2 variables:</p><ul><li><p><code>code</code><br> Commonly used code of a microorganism. <em><strong>This is a unique identifier.</strong></em></p></li>
 <li><p><code>mo</code><br> ID of the microorganism in the <a href="microorganisms.html">microorganisms</a> data set</p></li>
 </ul></div>
     <div class="section level2">
@@ -279,7 +173,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] TRUE</span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -293,9 +187,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/microorganisms.groups.html b/reference/microorganisms.groups.html
index 00a4b3828..808659442 100644
--- a/reference/microorganisms.groups.html
+++ b/reference/microorganisms.groups.html
@@ -1,161 +1,55 @@
 <!DOCTYPE html>
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+  </ul></li>
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
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+  </ul></li>
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 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Data Set with 521 Microorganisms In Species Groups</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/data.R" class="external-link"><code>R/data.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/data.R" class="external-link"><code>R/data.R</code></a></small>
       <div class="d-none name"><code>microorganisms.groups.Rd</code></div>
     </div>
 
@@ -214,7 +108,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span> B_BCTRD_FRGL-C B_PRBCT_DSTS Bacteroides fragilis complex Parabacteroides dist…</span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -228,9 +122,9 @@
 
     </footer></div>
 
-  
 
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+
+
 
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diff --git a/reference/microorganisms.html b/reference/microorganisms.html
index 4fd260bb4..6c8159b78 100644
--- a/reference/microorganisms.html
+++ b/reference/microorganisms.html
@@ -1,166 +1,63 @@
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Data Set with 70 547 Taxonomic Records of Microorganisms — microorganisms • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.4.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Data Set with 70 547 Taxonomic Records of Microorganisms — microorganisms"><meta name="description" content="A data set containing the full microbial taxonomy (last updated: June 24th, 2024) of six kingdoms. This data set is the backbone of this AMR package. MO codes can be looked up using as.mo() and microorganism properties can be looked up using any of the mo_* functions.
+This data set is carefully crafted, yet made 100% reproducible from public and authoritative taxonomic sources (using this script), namely: List of Prokaryotic names with Standing in Nomenclature (LPSN) for bacteria, MycoBank for fungi, and Global Biodiversity Information Facility (GBIF) for all others taxons."><meta property="og:description" content="A data set containing the full microbial taxonomy (last updated: June 24th, 2024) of six kingdoms. This data set is the backbone of this AMR package. MO codes can be looked up using as.mo() and microorganism properties can be looked up using any of the mo_* functions.
+This data set is carefully crafted, yet made 100% reproducible from public and authoritative taxonomic sources (using this script), namely: List of Prokaryotic names with Standing in Nomenclature (LPSN) for bacteria, MycoBank for fungi, and Global Biodiversity Information Facility (GBIF) for all others taxons."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"></head><body>
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-      <img src="../logo.svg" class="logo" alt=""><h1>Data Set with 52 171 Microorganisms</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/data.R" class="external-link"><code>R/data.R</code></a></small>
+      <img src="../logo.svg" class="logo" alt=""><h1>Data Set with 70 547 Taxonomic Records of Microorganisms</h1>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/data.R" class="external-link"><code>R/data.R</code></a></small>
       <div class="d-none name"><code>microorganisms.Rd</code></div>
     </div>
 
     <div class="ref-description section level2">
-    <p>A data set containing the full microbial taxonomy (<strong>last updated: January 8th, 2024</strong>) of five kingdoms from the List of Prokaryotic names with Standing in Nomenclature (LPSN) and the Global Biodiversity Information Facility (GBIF). This data set is the backbone of this <code>AMR</code> package. MO codes can be looked up using <code><a href="as.mo.html">as.mo()</a></code>.</p>
+    <p>A data set containing the full microbial taxonomy (<strong>last updated: June 24th, 2024</strong>) of six kingdoms. This data set is the backbone of this <code>AMR</code> package. MO codes can be looked up using <code><a href="as.mo.html">as.mo()</a></code> and microorganism properties can be looked up using any of the <code><a href="mo_property.html">mo_*</a></code> functions.</p>
+<p>This data set is carefully crafted, yet made 100% reproducible from public and authoritative taxonomic sources (using <a href="https://github.com/msberends/AMR/blob/main/data-raw/reproduction_of_microorganisms.R" class="external-link">this script</a>), namely: <em>List of Prokaryotic names with Standing in Nomenclature (LPSN)</em> for bacteria, <em>MycoBank</em> for fungi, and <em>Global Biodiversity Information Facility (GBIF)</em> for all others taxons.</p>
     </div>
 
     <div class="section level2">
@@ -170,53 +67,62 @@
 
     <div class="section level2">
     <h2 id="format">Format<a class="anchor" aria-label="anchor" href="#format"></a></h2>
-    <p>A <a href="https://tibble.tidyverse.org/reference/tibble.html" class="external-link">tibble</a> with 52 171 observations and 23 variables:</p><ul><li><p><code>mo</code><br> ID of microorganism as used by this package. <em>This is a unique identifier.</em></p></li>
-<li><p><code>fullname</code><br> Full name, like <code>"Escherichia coli"</code>. For the taxonomic ranks genus, species and subspecies, this is the 'pasted' text of genus, species, and subspecies. For all taxonomic ranks higher than genus, this is the name of the taxon. <em>This is a unique identifier.</em></p></li>
-<li><p><code>status</code> <br> Status of the taxon, either "accepted" or "synonym"</p></li>
-<li><p><code>kingdom</code>, <code>phylum</code>, <code>class</code>, <code>order</code>, <code>family</code>, <code>genus</code>, <code>species</code>, <code>subspecies</code><br> Taxonomic rank of the microorganism</p></li>
+    <p>A <a href="https://tibble.tidyverse.org/reference/tibble.html" class="external-link">tibble</a> with 70 547 observations and 26 variables:</p><ul><li><p><code>mo</code><br> ID of microorganism as used by this package. <em><strong>This is a unique identifier.</strong></em></p></li>
+<li><p><code>fullname</code><br> Full name, like <code>"Escherichia coli"</code>. For the taxonomic ranks genus, species and subspecies, this is the 'pasted' text of genus, species, and subspecies. For all taxonomic ranks higher than genus, this is the name of the taxon. <em><strong>This is a unique identifier.</strong></em></p></li>
+<li><p><code>status</code> <br> Status of the taxon, either "accepted", "not validly published", "synonym", or "unknown"</p></li>
+<li><p><code>kingdom</code>, <code>phylum</code>, <code>class</code>, <code>order</code>, <code>family</code>, <code>genus</code>, <code>species</code>, <code>subspecies</code><br> Taxonomic rank of the microorganism. Note that for fungi, <em>phylum</em> is equal to their taxonomic <em>division</em>. Also, for fungi, <em>subkingdom</em> and <em>subdivision</em> were left out since they do not occur in the bacterial taxonomy.</p></li>
 <li><p><code>rank</code><br> Text of the taxonomic rank of the microorganism, such as <code>"species"</code> or <code>"genus"</code></p></li>
 <li><p><code>ref</code><br> Author(s) and year of related scientific publication. This contains only the <em>first surname</em> and year of the <em>latest</em> authors, e.g. "Wallis <em>et al.</em> 2006 <em>emend.</em> Smith and Jones 2018" becomes "Smith <em>et al.</em>, 2018". This field is directly retrieved from the source specified in the column <code>source</code>. Moreover, accents were removed to comply with CRAN that only allows ASCII characters.</p></li>
-<li><p><code>lpsn</code><br> Identifier ('Record number') of the List of Prokaryotic names with Standing in Nomenclature (LPSN). This will be the first/highest LPSN identifier to keep one identifier per row. For example, <em>Acetobacter ascendens</em> has LPSN Record number 7864 and 11011. Only the first is available in the <code>microorganisms</code> data set.</p></li>
-<li><p><code>oxygen_tolerance</code> <br> Oxygen tolerance, either "aerobe", "anaerobe", "anaerobe/microaerophile", "facultative anaerobe", "likely facultative anaerobe", or "microaerophile". These data were retrieved from BacDive (see <em>Source</em>). Items that contain "likely" are missing from BacDive and were extrapolated from other species within the same genus to guess the oxygen tolerance. Currently 73.4% of all ~37 000 bacteria in the data set contain an oxygen tolerance.</p></li>
+<li><p><code>oxygen_tolerance</code> <br> Oxygen tolerance, either "aerobe", "anaerobe", "anaerobe/microaerophile", "facultative anaerobe", "likely facultative anaerobe", or "microaerophile". These data were retrieved from BacDive (see <em>Source</em>). Items that contain "likely" are missing from BacDive and were extrapolated from other species within the same genus to guess the oxygen tolerance. Currently 68.3% of all ~39 000 bacteria in the data set contain an oxygen tolerance.</p></li>
+<li><p><code>source</code><br> Either "GBIF", "LPSN", "MycoBank", or "manually added" (see <em>Source</em>)</p></li>
+<li><p><code>lpsn</code><br> Identifier ('Record number') of List of Prokaryotic names with Standing in Nomenclature (LPSN). This will be the first/highest LPSN identifier to keep one identifier per row. For example, <em>Acetobacter ascendens</em> has LPSN Record number 7864 and 11011. Only the first is available in the <code>microorganisms</code> data set. <em><strong>This is a unique identifier</strong></em>, though available for only ~32 000 records.</p></li>
 <li><p><code>lpsn_parent</code><br> LPSN identifier of the parent taxon</p></li>
 <li><p><code>lpsn_renamed_to</code><br> LPSN identifier of the currently valid taxon</p></li>
-<li><p><code>gbif</code><br> Identifier ('taxonID') of the Global Biodiversity Information Facility (GBIF)</p></li>
+<li><p><code>mycobank</code><br> Identifier ('MycoBank #') of MycoBank. <em><strong>This is a unique identifier</strong></em>, though available for only ~15 000 records.</p></li>
+<li><p><code>mycobank_parent</code><br> MycoBank identifier of the parent taxon</p></li>
+<li><p><code>mycobank_renamed_to</code><br> MycoBank identifier of the currently valid taxon</p></li>
+<li><p><code>gbif</code><br> Identifier ('taxonID') of Global Biodiversity Information Facility (GBIF). <em><strong>This is a unique identifier</strong></em>, though available for only ~46 000 records.</p></li>
 <li><p><code>gbif_parent</code><br> GBIF identifier of the parent taxon</p></li>
 <li><p><code>gbif_renamed_to</code><br> GBIF identifier of the currently valid taxon</p></li>
-<li><p><code>source</code><br> Either "GBIF", "LPSN", or "manually added" (see <em>Source</em>)</p></li>
 <li><p><code>prevalence</code><br> Prevalence of the microorganism based on Bartlett <em>et al.</em> (2022, <a href="https://doi.org/10.1099/mic.0.001269" class="external-link">doi:10.1099/mic.0.001269</a>
 ), see <code><a href="mo_matching_score.html">mo_matching_score()</a></code> for the full explanation</p></li>
-<li><p><code>snomed</code><br> Systematized Nomenclature of Medicine (SNOMED) code of the microorganism, version of July 1st, 2021 (see <em>Source</em>). Use <code><a href="mo_property.html">mo_snomed()</a></code> to retrieve it quickly, see <code><a href="mo_property.html">mo_property()</a></code>.</p></li>
+<li><p><code>snomed</code><br> Systematized Nomenclature of Medicine (SNOMED) code of the microorganism, version of July 16th, 2024 (see <em>Source</em>). Use <code><a href="mo_property.html">mo_snomed()</a></code> to retrieve it quickly, see <code><a href="mo_property.html">mo_property()</a></code>.</p></li>
 </ul></div>
     <div class="section level2">
     <h2 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a></h2>
-    
-<ul><li><p>Parte, AC <em>et al.</em> (2020). <strong>List of Prokaryotic names with Standing in Nomenclature (LPSN) moves to the DSMZ.</strong> International Journal of Systematic and Evolutionary Microbiology, 70, 5607-5612; <a href="https://doi.org/10.1099/ijsem.0.004332" class="external-link">doi:10.1099/ijsem.0.004332</a>
-. Accessed from <a href="https://lpsn.dsmz.de" class="external-link">https://lpsn.dsmz.de</a> on December 11th, 2022.</p></li>
-<li><p>GBIF Secretariat (2023). GBIF Backbone Taxonomy. Checklist dataset <a href="https://doi.org/10.15468/39omei" class="external-link">doi:10.15468/39omei</a>
-. Accessed from <a href="https://www.gbif.org" class="external-link">https://www.gbif.org</a> on January 8th, 2024.</p></li>
-<li><p>Reimer, LC <em>et al.</em> (2022). <strong><em>BacDive</em> in 2022: the knowledge base for standardized bacterial and archaeal data.</strong> Nucleic Acids Res., 50(D1):D741-D74; <a href="https://doi.org/10.1093/nar/gkab961" class="external-link">doi:10.1093/nar/gkab961</a>
-. Accessed from <a href="https://bacdive.dsmz.de" class="external-link">https://bacdive.dsmz.de</a> on May 12th, 2023.</p></li>
-<li><p>Public Health Information Network Vocabulary Access and Distribution System (PHIN VADS). US Edition of SNOMED CT from 1 September 2020. Value Set Name 'Microorganism', OID 2.16.840.1.114222.4.11.1009 (v12). URL: <a href="https://phinvads.cdc.gov" class="external-link">https://phinvads.cdc.gov</a></p></li>
+    <p>Taxonomic entries were imported in this order of importance:</p><ol><li><p>List of Prokaryotic names with Standing in Nomenclature (LPSN):<br><br>
+Parte, AC <em>et al.</em> (2020). <strong>List of Prokaryotic names with Standing in Nomenclature (LPSN) moves to the DSMZ.</strong> International Journal of Systematic and Evolutionary Microbiology, 70, 5607-5612; <a href="https://doi.org/10.1099/ijsem.0.004332" class="external-link">doi:10.1099/ijsem.0.004332</a>
+. Accessed from <a href="https://lpsn.dsmz.de" class="external-link">https://lpsn.dsmz.de</a> on June 24th, 2024.</p></li>
+<li><p>MycoBank:<br><br>
+Vincent, R <em>et al</em> (2013). <strong>MycoBank gearing up for new horizons.</strong> IMA Fungus, 4(2), 371-9; <a href="https://doi.org/10.5598/imafungus.2013.04.02.16" class="external-link">doi:10.5598/imafungus.2013.04.02.16</a>
+. Accessed from <a href="https://www.mycobank.org" class="external-link">https://www.mycobank.org</a> on June 24th, 2024.</p></li>
+<li><p>Global Biodiversity Information Facility (GBIF):<br><br>
+GBIF Secretariat (2023). GBIF Backbone Taxonomy. Checklist dataset <a href="https://doi.org/10.15468/39omei" class="external-link">doi:10.15468/39omei</a>
+. Accessed from <a href="https://www.gbif.org" class="external-link">https://www.gbif.org</a> on June 24th, 2024.</p></li>
+</ol><p>Furthermore, these sources were used for additional details:</p><ul><li><p>BacDive:<br><br>
+Reimer, LC <em>et al.</em> (2022). <strong><em>BacDive</em> in 2022: the knowledge base for standardized bacterial and archaeal data.</strong> Nucleic Acids Res., 50(D1):D741-D74; <a href="https://doi.org/10.1093/nar/gkab961" class="external-link">doi:10.1093/nar/gkab961</a>
+. Accessed from <a href="https://bacdive.dsmz.de" class="external-link">https://bacdive.dsmz.de</a> on July 16th, 2024.</p></li>
+<li><p>Systematized Nomenclature of Medicine - Clinical Terms (SNOMED-CT):<br><br>
+Public Health Information Network Vocabulary Access and Distribution System (PHIN VADS). US Edition of SNOMED CT from 1 September 2020. Value Set Name 'Microorganism', OID 2.16.840.1.114222.4.11.1009 (v12). Accessed from <a href="https://phinvads.cdc.gov" class="external-link">https://phinvads.cdc.gov</a> on July 16th, 2024.</p></li>
 <li><p>Grimont <em>et al.</em> (2007). Antigenic Formulae of the Salmonella Serovars, 9th Edition. WHO Collaborating Centre for Reference and Research on <em>Salmonella</em> (WHOCC-SALM).</p></li>
 <li><p>Bartlett <em>et al.</em> (2022). <strong>A comprehensive list of bacterial pathogens infecting humans</strong> <em>Microbiology</em> 168:001269; <a href="https://doi.org/10.1099/mic.0.001269" class="external-link">doi:10.1099/mic.0.001269</a></p></li>
 </ul></div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
-    <p>Please note that entries are only based on the List of Prokaryotic names with Standing in Nomenclature (LPSN) and the Global Biodiversity Information Facility (GBIF) (see below). Since these sources incorporate entries based on (recent) publications in the International Journal of Systematic and Evolutionary Microbiology (IJSEM), it can happen that the year of publication is sometimes later than one might expect.</p>
+    <p>Please note that entries are only based on LPSN, MycoBank, and GBIF (see below). Since these sources incorporate entries based on (recent) publications in the International Journal of Systematic and Evolutionary Microbiology (IJSEM), it can happen that the year of publication is sometimes later than one might expect.</p>
 <p>For example, <em>Staphylococcus pettenkoferi</em> was described for the first time in Diagnostic Microbiology and Infectious Disease in 2002 (<a href="https://doi.org/10.1016/s0732-8893%2802%2900399-1" class="external-link">doi:10.1016/s0732-8893(02)00399-1</a>
-), but it was not before 2007 that a publication in IJSEM followed (<a href="https://doi.org/10.1099/ijs.0.64381-0" class="external-link">doi:10.1099/ijs.0.64381-0</a>
+), but it was not until 2007 that a publication in IJSEM followed (<a href="https://doi.org/10.1099/ijs.0.64381-0" class="external-link">doi:10.1099/ijs.0.64381-0</a>
 ). Consequently, the <code>AMR</code> package returns 2007 for <code>mo_year("S. pettenkoferi")</code>.</p>
     </div>
     <div class="section level2">
     <h2 id="included-taxa">Included Taxa<a class="anchor" aria-label="anchor" href="#included-taxa"></a></h2>
-    
 
-<p>Included taxonomic data are:</p><ul><li><p>All ~37 000 (sub)species from the kingdoms of Archaea and Bacteria</p></li>
-<li><p>~7 900 (sub)species from the kingdom of Fungi. The kingdom of Fungi is a very large taxon with almost 300,000 different (sub)species, of which most are not microbial (but rather macroscopic, like mushrooms). Because of this, not all fungi fit the scope of this package. Only relevant fungi are covered (such as all species of <em>Aspergillus</em>, <em>Candida</em>, <em>Cryptococcus</em>, <em>Histoplasma</em>, <em>Pneumocystis</em>, <em>Saccharomyces</em> and <em>Trichophyton</em>).</p></li>
-<li><p>~5 100 (sub)species from the kingdom of Protozoa</p></li>
-<li><p>~1 400 (sub)species from 43 other relevant genera from the kingdom of Animalia (such as <em>Strongyloides</em> and <em>Taenia</em>)</p></li>
-<li><p>All ~9 800 previously accepted names of all included (sub)species (these were taxonomically renamed)</p></li>
+
+<p>Included taxonomic data from <a href="https://lpsn.dsmz.de" class="external-link">LPSN</a>, <a href="https://www.mycobank.org" class="external-link">MycoBank</a>, and <a href="https://www.gbif.org" class="external-link">GBIF</a> are:</p><ul><li><p>All ~39 000 (sub)species from the kingdoms of Archaea and Bacteria</p></li>
+<li><p>~20 000 species from the kingdom of Fungi. The kingdom of Fungi is a very large taxon with almost 300,000 different (sub)species, of which most are not microbial (but rather macroscopic, like mushrooms). Because of this, not all fungi fit the scope of this package. Only relevant fungi are covered (such as all species of <em>Aspergillus</em>, <em>Candida</em>, <em>Cryptococcus</em>, <em>Histoplasma</em>, <em>Pneumocystis</em>, <em>Saccharomyces</em> and <em>Trichophyton</em>).</p></li>
+<li><p>~8 100 (sub)species from the kingdom of Protozoa</p></li>
+<li><p>~1 700 (sub)species from 45 other relevant genera from the kingdom of Animalia (such as <em>Strongyloides</em> and <em>Taenia</em>)</p></li>
+<li><p>All ~17 000 previously accepted names of all included (sub)species (these were taxonomically renamed)</p></li>
 <li><p>The complete taxonomic tree of all included (sub)species: from kingdom to subspecies</p></li>
 <li><p>The identifier of the parent taxons</p></li>
 <li><p>The year and first author of the related scientific publication</p></li>
@@ -229,7 +135,7 @@
 <li><p>1 entry of <em>Blastocystis</em> (<em>B.  hominis</em>), although it officially does not exist (Noel <em>et al.</em> 2005, PMID 15634993)</p></li>
 <li><p>1 entry of <em>Moraxella</em> (<em>M. catarrhalis</em>), which was formally named <em>Branhamella catarrhalis</em> (Catlin, 1970) though this change was never accepted within the field of clinical microbiology</p></li>
 <li><p>8 other 'undefined' entries (unknown, unknown Gram-negatives, unknown Gram-positives, unknown yeast, unknown fungus, and unknown anaerobic Gram-pos/Gram-neg bacteria)</p></li>
-</ul><p>The syntax used to transform the original data to a cleansed <span style="R">R</span> format, can be found here: <a href="https://github.com/msberends/AMR/blob/main/data-raw/reproduction_of_microorganisms.R" class="external-link">https://github.com/msberends/AMR/blob/main/data-raw/reproduction_of_microorganisms.R</a>.</p>
+</ul><p>The syntax used to transform the original data to a cleansed <span style="R">R</span> format, can be <a href="https://github.com/msberends/AMR/blob/main/data-raw/reproduction_of_microorganisms.R" class="external-link">found here</a>.</p>
 </div>
 
 <div class="section">
@@ -239,13 +145,6 @@
 <p>Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit <a href="https://msberends.github.io/AMR/articles/datasets.html">our website for the download links</a>. The actual files are of course available on <a href="https://github.com/msberends/AMR/tree/main/data-raw" class="external-link">our GitHub repository</a>.</p>
 </div>
 
-    </div>
-    <div class="section level2">
-    <h2 id="about-the-records-from-lpsn-see-source-">About the Records from LPSN (see <em>Source</em>)<a class="anchor" aria-label="anchor" href="#about-the-records-from-lpsn-see-source-"></a></h2>
-    
-
-<p>LPSN is the main source for bacteriological taxonomy of this <code>AMR</code> package.</p>
-<p>The List of Prokaryotic names with Standing in Nomenclature (LPSN) provides comprehensive information on the nomenclature of prokaryotes. LPSN is a free to use service founded by Jean P. Euzeby in 1997 and later on maintained by Aidan C. Parte.</p>
     </div>
     <div class="section level2">
     <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
@@ -255,27 +154,28 @@
     <div class="section level2">
     <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">microorganisms</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 52,171 × 23</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 70,547 × 26</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>    mo               fullname      status kingdom phylum class order family genus</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span>             <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> B_GRAMN          (unknown Gra… accep… Bacter… (unkn… (unk… (unk… <span style="color: #949494;">"</span>(unk… <span style="color: #949494;">"</span>(un…</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> B_GRAMP          (unknown Gra… accep… Bacter… (unkn… (unk… (unk… <span style="color: #949494;">"</span>(unk… <span style="color: #949494;">"</span>(un…</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> B_ANAER-NEG      (unknown ana… accep… Bacter… (unkn… (unk… (unk… <span style="color: #949494;">"</span>(unk… <span style="color: #949494;">"</span>(un…</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> B_ANAER-POS      (unknown ana… accep… Bacter… (unkn… (unk… (unk… <span style="color: #949494;">"</span>(unk… <span style="color: #949494;">"</span>(un…</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> B_ANAER          (unknown ana… accep… Bacter… (unkn… (unk… (unk… <span style="color: #949494;">"</span>(unk… <span style="color: #949494;">"</span>(un…</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> F_FUNGUS         (unknown fun… accep… Fungi   (unkn… (unk… (unk… <span style="color: #949494;">"</span>(unk… <span style="color: #949494;">"</span>(un…</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>   UNKNOWN        (unknown nam… accep… (unkno… (unkn… (unk… (unk… <span style="color: #949494;">"</span>(unk… <span style="color: #949494;">"</span>(un…</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> F_YEAST          (unknown yea… accep… Fungi   (unkn… (unk… (unk… <span style="color: #949494;">"</span>(unk… <span style="color: #949494;">"</span>(un…</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> B_[FAM]_ABDTBCTR Abditibacter… accep… Bacter… Abdit… Abdi… Abdi… <span style="color: #949494;">"</span>Abdi… <span style="color: #949494;">""</span>   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> B_[ORD]_ABDTBCTR Abditibacter… accep… Bacter… Abdit… Abdi… Abdi… <span style="color: #949494;">""</span>     <span style="color: #949494;">""</span>   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 52,161 more rows</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 14 more variables: species &lt;chr&gt;, subspecies &lt;chr&gt;, rank &lt;chr&gt;, ref &lt;chr&gt;,</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> B_GRAMN          (unknown Gra… unkno… Bacter… (unkn… (unk… (unk… <span style="color: #949494;">"</span>(unk… <span style="color: #949494;">"</span>(un…</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> B_GRAMP          (unknown Gra… unkno… Bacter… (unkn… (unk… (unk… <span style="color: #949494;">"</span>(unk… <span style="color: #949494;">"</span>(un…</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> B_ANAER-NEG      (unknown ana… unkno… Bacter… (unkn… (unk… (unk… <span style="color: #949494;">"</span>(unk… <span style="color: #949494;">"</span>(un…</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> B_ANAER-POS      (unknown ana… unkno… Bacter… (unkn… (unk… (unk… <span style="color: #949494;">"</span>(unk… <span style="color: #949494;">"</span>(un…</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> B_ANAER          (unknown ana… unkno… Bacter… (unkn… (unk… (unk… <span style="color: #949494;">"</span>(unk… <span style="color: #949494;">"</span>(un…</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> F_FUNGUS         (unknown fun… unkno… Fungi   (unkn… (unk… (unk… <span style="color: #949494;">"</span>(unk… <span style="color: #949494;">"</span>(un…</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span>   UNKNOWN        (unknown nam… unkno… (unkno… (unkn… (unk… (unk… <span style="color: #949494;">"</span>(unk… <span style="color: #949494;">"</span>(un…</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> F_YEAST          (unknown yea… unkno… Fungi   (unkn… (unk… (unk… <span style="color: #949494;">"</span>(unk… <span style="color: #949494;">"</span>(un…</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> F_AABRN          Aabaarnia     unkno… Fungi   Ascom… Leca… Ostr… <span style="color: #949494;">""</span>     <span style="color: #949494;">"</span>Aab…</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> B_[FAM]_ABDTBCTR Abditibacter… accep… Bacter… Abdit… Abdi… Abdi… <span style="color: #949494;">"</span>Abdi… <span style="color: #949494;">""</span>   </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 70,537 more rows</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 17 more variables: species &lt;chr&gt;, subspecies &lt;chr&gt;, rank &lt;chr&gt;, ref &lt;chr&gt;,</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   oxygen_tolerance &lt;chr&gt;, source &lt;chr&gt;, lpsn &lt;chr&gt;, lpsn_parent &lt;chr&gt;,</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   lpsn_renamed_to &lt;chr&gt;, gbif &lt;chr&gt;, gbif_parent &lt;chr&gt;,</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   lpsn_renamed_to &lt;chr&gt;, mycobank &lt;chr&gt;, mycobank_parent &lt;chr&gt;,</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   mycobank_renamed_to &lt;chr&gt;, gbif &lt;chr&gt;, gbif_parent &lt;chr&gt;,</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   gbif_renamed_to &lt;chr&gt;, prevalence &lt;dbl&gt;, snomed &lt;list&gt;</span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -289,9 +189,9 @@
 
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-  
 
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diff --git a/reference/mo_matching_score.html b/reference/mo_matching_score.html
index cf2f2294e..cd13ed020 100644
--- a/reference/mo_matching_score.html
+++ b/reference/mo_matching_score.html
@@ -1,161 +1,55 @@
 <!DOCTYPE html>
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-      <span class="fa fa-gear"></span>
-       
-      Set User- Or Team-specific Package Settings
-    </a>
-    <a class="dropdown-item" href="../articles/PCA.html">
-      <span class="fa fa-compress"></span>
-       
-      Conduct Principal Component Analysis for AMR
-    </a>
-    <a class="dropdown-item" href="../articles/MDR.html">
-      <span class="fa fa-skull-crossbones"></span>
-       
-      Determine Multi-Drug Resistance (MDR)
-    </a>
-    <a class="dropdown-item" href="../articles/WHONET.html">
-      <span class="fa fa-globe-americas"></span>
-       
-      Work with WHONET Data
-    </a>
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-      <span class="fa fa-exchange-alt"></span>
-       
-      Apply Eucast Rules
-    </a>
-    <a class="dropdown-item" href="../reference/mo_property.html">
-      <span class="fa fa-bug"></span>
-       
-      Get Taxonomy of a Microorganism
-    </a>
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-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antibiotic Drug
-    </a>
-    <a class="dropdown-item" href="../reference/av_property.html">
-      <span class="fa fa-capsules"></span>
-       
-      Get Properties of an Antiviral Drug
-    </a>
-  </div>
-</li>
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-how-to" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-question-circle"></span> How to</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to"><li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul></li>
 <li class="nav-item dropdown">
-  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown--with-other-pkgs">
-    <span class="fa fa-layer-group"></span>
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-    With other pkgs
-  </a>
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-    <a class="dropdown-item" href="../articles/other_pkg.html">
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-  </a>
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-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
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-  <a class="nav-link" href="../news/index.html">
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-  <a class="external-link nav-link" href="https://github.com/msberends/AMR">
-    <span class="fab fa fab fa-github"></span>
-     
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-  </a>
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-with-other-pkgs" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-layer-group"></span> With other pkgs</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/msberends/AMR"><span class="fa fab fa-github"></span> Source Code</a></li>
       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Calculate the Matching Score for Microorganisms</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/mo_matching_score.R" class="external-link"><code>R/mo_matching_score.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/mo_matching_score.R" class="external-link"><code>R/mo_matching_score.R</code></a></small>
       <div class="d-none name"><code>mo_matching_score.Rd</code></div>
     </div>
 
@@ -170,11 +64,13 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>Any user input value(s)</p></dd>
 
 
-<dt>n</dt>
+<dt id="arg-n">n<a class="anchor" aria-label="anchor" href="#arg-n"></a></dt>
 <dd><p>A full taxonomic name, that exists in <code><a href="microorganisms.html">microorganisms$fullname</a></code></p></dd>
 
 </dl></div>
@@ -187,7 +83,7 @@
     </div>
     <div class="section level2">
     <h2 id="matching-score-for-microorganisms">Matching Score for Microorganisms<a class="anchor" aria-label="anchor" href="#matching-score-for-microorganisms"></a></h2>
-    
+
 
 <p>With ambiguous user input in <code><a href="as.mo.html">as.mo()</a></code> and all the <code><a href="mo_property.html">mo_*</a></code> functions, the returned results are chosen based on their matching score using <code>mo_matching_score()</code>. This matching score \(m\), is calculated as:</p>
 <p><img src="figures/mo_matching_score.png" width="300" alt="mo matching score"></p>
@@ -203,14 +99,14 @@
 </ul><p>Furthermore,</p><ul><li><p>Any genus present in the <strong>established</strong> list also has <code>prevalence = 1.0</code> in the <a href="microorganisms.html">microorganisms</a> data set;</p></li>
 <li><p>Any other genus present in the <strong>putative</strong> list has <code>prevalence = 1.25</code> in the <a href="microorganisms.html">microorganisms</a> data set;</p></li>
 <li><p>Any other species or subspecies of which the genus is present in the two aforementioned groups, has <code>prevalence = 1.5</code> in the <a href="microorganisms.html">microorganisms</a> data set;</p></li>
-<li><p>Any <em>non-bacterial</em> genus, species or subspecies of which the genus is present in the following list, has <code>prevalence = 1.25</code> in the <a href="microorganisms.html">microorganisms</a> data set: <em>Absidia</em>, <em>Acanthamoeba</em>, <em>Acremonium</em>, <em>Aedes</em>, <em>Alternaria</em>, <em>Amoeba</em>, <em>Ancylostoma</em>, <em>Angiostrongylus</em>, <em>Anisakis</em>, <em>Anopheles</em>, <em>Apophysomyces</em>, <em>Arthroderma</em>, <em>Aspergillus</em>, <em>Aureobasidium</em>, <em>Basidiobolus</em>, <em>Beauveria</em>, <em>Blastocystis</em>, <em>Blastomyces</em>, <em>Candida</em>, <em>Capillaria</em>, <em>Chaetomium</em>, <em>Chrysonilia</em>, <em>Chrysosporium</em>, <em>Cladophialophora</em>, <em>Cladosporium</em>, <em>Conidiobolus</em>, <em>Contracaecum</em>, <em>Cordylobia</em>, <em>Cryptococcus</em>, <em>Curvularia</em>, <em>Demodex</em>, <em>Dermatobia</em>, <em>Dientamoeba</em>, <em>Diphyllobothrium</em>, <em>Dirofilaria</em>, <em>Echinostoma</em>, <em>Entamoeba</em>, <em>Enterobius</em>, <em>Exophiala</em>, <em>Exserohilum</em>, <em>Fasciola</em>, <em>Fonsecaea</em>, <em>Fusarium</em>, <em>Geotrichum</em>, <em>Giardia</em>, <em>Haloarcula</em>, <em>Halobacterium</em>, <em>Halococcus</em>, <em>Hendersonula</em>, <em>Heterophyes</em>, <em>Histomonas</em>, <em>Histoplasma</em>, <em>Hymenolepis</em>, <em>Hypomyces</em>, <em>Hysterothylacium</em>, <em>Kloeckera</em>, <em>Kodamaea</em>, <em>Leishmania</em>, <em>Lichtheimia</em>, <em>Lodderomyces</em>, <em>Malassezia</em>, <em>Malbranchea</em>, <em>Metagonimus</em>, <em>Meyerozyma</em>, <em>Microsporidium</em>, <em>Microsporum</em>, <em>Millerozyma</em>, <em>Mortierella</em>, <em>Mucor</em>, <em>Mycocentrospora</em>, <em>Necator</em>, <em>Nectria</em>, <em>Ochroconis</em>, <em>Oesophagostomum</em>, <em>Oidiodendron</em>, <em>Opisthorchis</em>, <em>Paecilomyces</em>, <em>Pediculus</em>, <em>Penicillium</em>, <em>Phlebotomus</em>, <em>Phoma</em>, <em>Pichia</em>, <em>Piedraia</em>, <em>Pithomyces</em>, <em>Pityrosporum</em>, <em>Pneumocystis</em>, <em>Pseudallescheria</em>, <em>Pseudoterranova</em>, <em>Pulex</em>, <em>Rhizomucor</em>, <em>Rhizopus</em>, <em>Rhodotorula</em>, <em>Saccharomyces</em>, <em>Saprochaete</em>, <em>Sarcoptes</em>, <em>Scedosporium</em>, <em>Scolecobasidium</em>, <em>Scopulariopsis</em>, <em>Scytalidium</em>, <em>Spirometra</em>, <em>Sporobolomyces</em>, <em>Sporotrichum</em>, <em>Stachybotrys</em>, <em>Strongyloides</em>, <em>Syngamus</em>, <em>Taenia</em>, <em>Talaromyces</em>, <em>Toxocara</em>, <em>Trichinella</em>, <em>Trichobilharzia</em>, <em>Trichoderma</em>, <em>Trichomonas</em>, <em>Trichophyton</em>, <em>Trichosporon</em>, <em>Trichostrongylus</em>, <em>Trichuris</em>, <em>Tritirachium</em>, <em>Trombicula</em>, <em>Trypanosoma</em>, <em>Tunga</em>, <em>Verticillium</em>, or <em>Wuchereria</em>;</p></li>
+<li><p>Any <em>non-bacterial</em> genus, species or subspecies of which the genus is present in the following list, has <code>prevalence = 1.25</code> in the <a href="microorganisms.html">microorganisms</a> data set: <em>Absidia</em>, <em>Acanthamoeba</em>, <em>Acremonium</em>, <em>Aedes</em>, <em>Alternaria</em>, <em>Amoeba</em>, <em>Ancylostoma</em>, <em>Angiostrongylus</em>, <em>Anisakis</em>, <em>Anopheles</em>, <em>Apophysomyces</em>, <em>Arthroderma</em>, <em>Aspergillus</em>, <em>Aureobasidium</em>, <em>Basidiobolus</em>, <em>Beauveria</em>, <em>Blastocystis</em>, <em>Blastomyces</em>, <em>Candida</em>, <em>Capillaria</em>, <em>Chaetomium</em>, <em>Chrysonilia</em>, <em>Chrysosporium</em>, <em>Cladophialophora</em>, <em>Cladosporium</em>, <em>Conidiobolus</em>, <em>Contracaecum</em>, <em>Cordylobia</em>, <em>Cryptococcus</em>, <em>Curvularia</em>, <em>Demodex</em>, <em>Dermatobia</em>, <em>Dientamoeba</em>, <em>Diphyllobothrium</em>, <em>Dirofilaria</em>, <em>Echinostoma</em>, <em>Entamoeba</em>, <em>Enterobius</em>, <em>Exophiala</em>, <em>Exserohilum</em>, <em>Fasciola</em>, <em>Fonsecaea</em>, <em>Fusarium</em>, <em>Geotrichum</em>, <em>Giardia</em>, <em>Haloarcula</em>, <em>Halobacterium</em>, <em>Halococcus</em>, <em>Hansenula</em>, <em>Hendersonula</em>, <em>Heterophyes</em>, <em>Histomonas</em>, <em>Histoplasma</em>, <em>Hymenolepis</em>, <em>Hypomyces</em>, <em>Hysterothylacium</em>, <em>Kloeckera</em>, <em>Kluyveromyces</em>, <em>Kodamaea</em>, <em>Leishmania</em>, <em>Lichtheimia</em>, <em>Lodderomyces</em>, <em>Lomentospora</em>, <em>Malassezia</em>, <em>Malbranchea</em>, <em>Metagonimus</em>, <em>Meyerozyma</em>, <em>Microsporidium</em>, <em>Microsporum</em>, <em>Millerozyma</em>, <em>Mortierella</em>, <em>Mucor</em>, <em>Mycocentrospora</em>, <em>Necator</em>, <em>Nectria</em>, <em>Ochroconis</em>, <em>Oesophagostomum</em>, <em>Oidiodendron</em>, <em>Opisthorchis</em>, <em>Paecilomyces</em>, <em>Pediculus</em>, <em>Penicillium</em>, <em>Phlebotomus</em>, <em>Phoma</em>, <em>Pichia</em>, <em>Piedraia</em>, <em>Pithomyces</em>, <em>Pityrosporum</em>, <em>Pneumocystis</em>, <em>Pseudallescheria</em>, <em>Pseudoscopulariopsis</em>, <em>Pseudoterranova</em>, <em>Pulex</em>, <em>Rhizomucor</em>, <em>Rhizopus</em>, <em>Rhodotorula</em>, <em>Saccharomyces</em>, <em>Saprochaete</em>, <em>Sarcoptes</em>, <em>Scedosporium</em>, <em>Scolecobasidium</em>, <em>Scopulariopsis</em>, <em>Scytalidium</em>, <em>Spirometra</em>, <em>Sporobolomyces</em>, <em>Sporotrichum</em>, <em>Stachybotrys</em>, <em>Strongyloides</em>, <em>Syngamus</em>, <em>Taenia</em>, <em>Talaromyces</em>, <em>Toxocara</em>, <em>Trichinella</em>, <em>Trichobilharzia</em>, <em>Trichoderma</em>, <em>Trichomonas</em>, <em>Trichophyton</em>, <em>Trichosporon</em>, <em>Trichostrongylus</em>, <em>Trichuris</em>, <em>Tritirachium</em>, <em>Trombicula</em>, <em>Trypanosoma</em>, <em>Tunga</em>, <em>Verticillium</em>, or <em>Wuchereria</em>;</p></li>
 <li><p>All other records have <code>prevalence = 2.0</code> in the <a href="microorganisms.html">microorganisms</a> data set.</p></li>
 </ul><p>When calculating the matching score, all characters in \(x\) and \(n\) are ignored that are other than A-Z, a-z, 0-9, spaces and parentheses.</p>
 <p>All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., <code>"E. coli"</code> will return the microbial ID of <em>Escherichia coli</em> (\(m = 0.688\), a highly prevalent microorganism found in humans) and not <em>Entamoeba coli</em> (\(m = 0.381\), a less prevalent microorganism in humans), although the latter would alphabetically come first.</p>
     </div>
     <div class="section level2">
     <h2 id="reference-data-publicly-available">Reference Data Publicly Available<a class="anchor" aria-label="anchor" href="#reference-data-publicly-available"></a></h2>
-    
+
 
 <p>All data sets in this <code>AMR</code> package (about microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) are publicly and freely available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. We also provide tab-separated plain text files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please visit <a href="https://msberends.github.io/AMR/articles/datasets.html">our website for the download links</a>. The actual files are of course available on <a href="https://github.com/msberends/AMR/tree/main/data-raw" class="external-link">our GitHub repository</a>.</p>
     </div>
@@ -233,12 +129,12 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> --------------------------------------------------------------------------------</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> "E. coli" -&gt; Escherichia coli (B_ESCHR_COLI, 0.688)</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> Also matched: Enterobacter cowanii (0.600), Eubacterium combesii</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> Also matched: Escherichia coli coli (0.643), Escherichia coli</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>               expressing (0.611), Enterobacter cowanii (0.600), Eubacterium combesii</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>               (0.600), Eggerthia catenaformis (0.591), Eubacterium callanderi</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>               (0.591), Enterocloster citroniae (0.587), Eubacterium cylindroides</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>               (0.583), Enterococcus casseliflavus (0.577), Enterobacter cloacae</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>               cloacae (0.571), Enterobacter cloacae complex (0.571), and Ehrlichia</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>               canis (0.567)</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>               (0.583), Enterococcus casseliflavus (0.577), and Enterobacter cloacae</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>               cloacae (0.571)</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> Only the first 10 other matches of each record are shown. Run</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> print(mo_uncertainties(), n = ...) to view more entries, or save</span>
@@ -251,7 +147,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.6875000 0.3809524</span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -265,9 +161,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/mo_mycobank.html b/reference/mo_mycobank.html
new file mode 100644
index 000000000..32a922060
--- /dev/null
+++ b/reference/mo_mycobank.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mo_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/mo_property.html">
+  </head>
+</html>
+
diff --git a/reference/mo_name.html b/reference/mo_name.html
new file mode 100644
index 000000000..32a922060
--- /dev/null
+++ b/reference/mo_name.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mo_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/mo_property.html">
+  </head>
+</html>
+
diff --git a/reference/mo_order.html b/reference/mo_order.html
new file mode 100644
index 000000000..32a922060
--- /dev/null
+++ b/reference/mo_order.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mo_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/mo_property.html">
+  </head>
+</html>
+
diff --git a/reference/mo_oxygen_tolerance.html b/reference/mo_oxygen_tolerance.html
new file mode 100644
index 000000000..32a922060
--- /dev/null
+++ b/reference/mo_oxygen_tolerance.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mo_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/mo_property.html">
+  </head>
+</html>
+
diff --git a/reference/mo_pathogenicity.html b/reference/mo_pathogenicity.html
new file mode 100644
index 000000000..32a922060
--- /dev/null
+++ b/reference/mo_pathogenicity.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
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new file mode 100644
index 000000000..32a922060
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index 07449cff9..0ec5df267 100644
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 <!DOCTYPE html>
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   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Get Properties of a Microorganism</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/mo_property.R" class="external-link"><code>R/mo_property.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/mo_property.R" class="external-link"><code>R/mo_property.R</code></a></small>
       <div class="d-none name"><code>mo_property.Rd</code></div>
     </div>
 
@@ -355,6 +249,13 @@
 <span>  <span class="va">...</span></span>
 <span><span class="op">)</span></span>
 <span></span>
+<span><span class="fu">mo_mycobank</span><span class="op">(</span></span>
+<span>  <span class="va">x</span>,</span>
+<span>  language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>,</span>
+<span>  keep_synonyms <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"AMR_keep_synonyms"</span>, <span class="cn">FALSE</span><span class="op">)</span>,</span>
+<span>  <span class="va">...</span></span>
+<span><span class="op">)</span></span>
+<span></span>
 <span><span class="fu">mo_gbif</span><span class="op">(</span></span>
 <span>  <span class="va">x</span>,</span>
 <span>  language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>,</span>
@@ -418,37 +319,38 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>any <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> (vector) that can be coerced to a valid microorganism code with <code><a href="as.mo.html">as.mo()</a></code>. Can be left blank for auto-guessing the column containing microorganism codes if used in a data set, see <em>Examples</em>.</p></dd>
 
 
-<dt>language</dt>
+<dt id="arg-language">language<a class="anchor" aria-label="anchor" href="#arg-language"></a></dt>
 <dd><p>language to translate text like "no growth", which defaults to the system language (see <code><a href="translate.html">get_AMR_locale()</a></code>)</p></dd>
 
 
-<dt>keep_synonyms</dt>
+<dt id="arg-keep-synonyms">keep_synonyms<a class="anchor" aria-label="anchor" href="#arg-keep-synonyms"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate if old, previously valid taxonomic names must be preserved and not be corrected to currently accepted names. The default is <code>FALSE</code>, which will return a note if old taxonomic names were processed. The default can be set with the <a href="AMR-options.html">package option</a> <code><a href="AMR-options.html">AMR_keep_synonyms</a></code>, i.e. <code>options(AMR_keep_synonyms = TRUE)</code> or <code>options(AMR_keep_synonyms = FALSE)</code>.</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>other arguments passed on to <code><a href="as.mo.html">as.mo()</a></code>, such as 'minimum_matching_score', 'ignore_pattern', and 'remove_from_input'</p></dd>
 
 
-<dt>ab</dt>
+<dt id="arg-ab">ab<a class="anchor" aria-label="anchor" href="#arg-ab"></a></dt>
 <dd><p>any (vector of) text that can be coerced to a valid antibiotic drug code with <code><a href="as.ab.html">as.ab()</a></code></p></dd>
 
 
-<dt>open</dt>
+<dt id="arg-open">open<a class="anchor" aria-label="anchor" href="#arg-open"></a></dt>
 <dd><p>browse the URL using <code><a href="https://rdrr.io/r/utils/browseURL.html" class="external-link">browseURL()</a></code></p></dd>
 
 
-<dt>property</dt>
-<dd><p>one of the column names of the <a href="microorganisms.html">microorganisms</a> data set: "mo", "fullname", "status", "kingdom", "phylum", "class", "order", "family", "genus", "species", "subspecies", "rank", "ref", "oxygen_tolerance", "source", "lpsn", "lpsn_parent", "lpsn_renamed_to", "gbif", "gbif_parent", "gbif_renamed_to", "prevalence", or "snomed", or must be <code>"shortname"</code></p></dd>
+<dt id="arg-property">property<a class="anchor" aria-label="anchor" href="#arg-property"></a></dt>
+<dd><p>one of the column names of the <a href="microorganisms.html">microorganisms</a> data set: "mo", "fullname", "status", "kingdom", "phylum", "class", "order", "family", "genus", "species", "subspecies", "rank", "ref", "oxygen_tolerance", "source", "lpsn", "lpsn_parent", "lpsn_renamed_to", "mycobank", "mycobank_parent", "mycobank_renamed_to", "gbif", "gbif_parent", "gbif_renamed_to", "prevalence", or "snomed", or must be <code>"shortname"</code></p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
 
 <ul><li><p>An <a href="https://rdrr.io/r/base/integer.html" class="external-link">integer</a> in case of <code>mo_year()</code></p></li>
 <li><p>An <a href="https://rdrr.io/r/base/factor.html" class="external-link">ordered factor</a> in case of <code>mo_pathogenicity()</code></p></li>
@@ -471,19 +373,19 @@
 <p>Determination of intrinsic resistance (<code>mo_is_intrinsic_resistant()</code>) will be based on the <a href="intrinsic_resistant.html">intrinsic_resistant</a> data set, which is based on <a href="https://www.eucast.org/expert_rules_and_expected_phenotypes" class="external-link">'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3</a> (2021). The <code>mo_is_intrinsic_resistant()</code> function can be vectorised over both argument <code>x</code> (input for microorganisms) and <code>ab</code> (input for antibiotics).</p>
 <p>Determination of bacterial oxygen tolerance (<code>mo_oxygen_tolerance()</code>) will be based on BacDive, see <em>Source</em>. The function <code>mo_is_anaerobic()</code> only returns <code>TRUE</code> if the oxygen tolerance is <code>"anaerobe"</code>, indicting an obligate anaerobic species or genus. It always returns <code>FALSE</code> for species outside the taxonomic kingdom of Bacteria.</p>
 <p>The function <code>mo_url()</code> will return the direct URL to the online database entry, which also shows the scientific reference of the concerned species.</p>
-<p>SNOMED codes (<code>mo_snomed()</code>) are from the version of July 1st, 2021. See <em>Source</em> and the <a href="microorganisms.html">microorganisms</a> data set for more info.</p>
+<p>SNOMED codes (<code>mo_snomed()</code>) are from the version of July 16th, 2024. See <em>Source</em> and the <a href="microorganisms.html">microorganisms</a> data set for more info.</p>
 <p>Old taxonomic names (so-called 'synonyms') can be retrieved with <code>mo_synonyms()</code> (which will have the scientific reference as <a href="https://rdrr.io/r/base/names.html" class="external-link">name</a>), the current taxonomic name can be retrieved with <code>mo_current()</code>. Both functions return full names.</p>
 <p>All output <a href="translate.html">will be translated</a> where possible.</p>
     </div>
     <div class="section level2">
     <h2 id="matching-score-for-microorganisms">Matching Score for Microorganisms<a class="anchor" aria-label="anchor" href="#matching-score-for-microorganisms"></a></h2>
-    
+
 
 <p>This function uses <code><a href="as.mo.html">as.mo()</a></code> internally, which uses an advanced algorithm to translate arbitrary user input to valid taxonomy using a so-called matching score. You can read about this public algorithm on the <a href="mo_matching_score.html">MO matching score page</a>.</p>
     </div>
     <div class="section level2">
     <h2 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a></h2>
-    
+
 
 <ol><li><p>Berends MS <em>et al.</em> (2022). <strong>AMR: An R Package for Working with Antimicrobial Resistance Data</strong>. <em>Journal of Statistical Software</em>, 104(3), 1-31; <a href="https://doi.org/10.18637/jss.v104.i03" class="external-link">doi:10.18637/jss.v104.i03</a></p></li>
 <li><p>Becker K <em>et al.</em> (2014). <strong>Coagulase-Negative Staphylococci.</strong> <em>Clin Microbiol Rev.</em> 27(4): 870-926; <a href="https://doi.org/10.1128/CMR.00109-13" class="external-link">doi:10.1128/CMR.00109-13</a></p></li>
@@ -492,17 +394,17 @@
 <li><p>Lancefield RC (1933). <strong>A serological differentiation of human and other groups of hemolytic streptococci.</strong> <em>J Exp Med.</em> 57(4): 571-95; <a href="https://doi.org/10.1084/jem.57.4.571" class="external-link">doi:10.1084/jem.57.4.571</a></p></li>
 <li><p>Berends MS <em>et al.</em> (2022). <strong>Trends in Occurrence and Phenotypic Resistance of Coagulase-Negative Staphylococci (CoNS) Found in Human Blood in the Northern Netherlands between 2013 and 2019/</strong> <em>Micro.rganisms</em> 10(9), 1801; <a href="https://doi.org/10.3390/microorganisms10091801" class="external-link">doi:10.3390/microorganisms10091801</a></p></li>
 <li><p>Parte, AC <em>et al.</em> (2020). <strong>List of Prokaryotic names with Standing in Nomenclature (LPSN) moves to the DSMZ.</strong> International Journal of Systematic and Evolutionary Microbiology, 70, 5607-5612; <a href="https://doi.org/10.1099/ijsem.0.004332" class="external-link">doi:10.1099/ijsem.0.004332</a>
-. Accessed from <a href="https://lpsn.dsmz.de" class="external-link">https://lpsn.dsmz.de</a> on December 11th, 2022.</p></li>
+. Accessed from <a href="https://lpsn.dsmz.de" class="external-link">https://lpsn.dsmz.de</a> on June 24th, 2024.</p></li>
 <li><p>GBIF Secretariat (2023). GBIF Backbone Taxonomy. Checklist dataset <a href="https://doi.org/10.15468/39omei" class="external-link">doi:10.15468/39omei</a>
-. Accessed from <a href="https://www.gbif.org" class="external-link">https://www.gbif.org</a> on January 8th, 2024.</p></li>
+. Accessed from <a href="https://www.gbif.org" class="external-link">https://www.gbif.org</a> on June 24th, 2024.</p></li>
 <li><p>Reimer, LC <em>et al.</em> (2022). <strong><em>BacDive</em> in 2022: the knowledge base for standardized bacterial and archaeal data.</strong> Nucleic Acids Res., 50(D1):D741-D74; <a href="https://doi.org/10.1093/nar/gkab961" class="external-link">doi:10.1093/nar/gkab961</a>
-. Accessed from <a href="https://bacdive.dsmz.de" class="external-link">https://bacdive.dsmz.de</a> on May 12th, 2023.</p></li>
+. Accessed from <a href="https://bacdive.dsmz.de" class="external-link">https://bacdive.dsmz.de</a> on July 16th, 2024.</p></li>
 <li><p>Public Health Information Network Vocabulary Access and Distribution System (PHIN VADS). US Edition of SNOMED CT from 1 September 2020. Value Set Name 'Microorganism', OID 2.16.840.1.114222.4.11.1009 (v12). URL: <a href="https://phinvads.cdc.gov" class="external-link">https://phinvads.cdc.gov</a></p></li>
 <li><p>Bartlett A <em>et al.</em> (2022). <strong>A comprehensive list of bacterial pathogens infecting humans</strong> <em>Microbiology</em> 168:001269; <a href="https://doi.org/10.1099/mic.0.001269" class="external-link">doi:10.1099/mic.0.001269</a></p></li>
 </ol></div>
     <div class="section level2">
     <h2 id="reference-data-publicly-available">Reference Data Publicly Available<a class="anchor" aria-label="anchor" href="#reference-data-publicly-available"></a></h2>
-    
+
 
 <p>All data sets in this <code>AMR</code> package (about microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) are publicly and freely available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. We also provide tab-separated plain text files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please visit <a href="https://msberends.github.io/AMR/articles/datasets.html">our website for the download links</a>. The actual files are of course available on <a href="https://github.com/msberends/AMR/tree/main/data-raw" class="external-link">our GitHub repository</a>.</p>
     </div>
@@ -563,7 +465,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span>                                Klebsiella pneumoniae </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> "https://lpsn.dsmz.de/species/klebsiella-pneumoniae" </span>
 <span class="r-in"><span><span class="fu">mo_is_yeast</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Candida"</span>, <span class="st">"Trichophyton"</span>, <span class="st">"Klebsiella"</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1]  TRUE FALSE FALSE</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] FALSE FALSE FALSE</span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="fu">mo_group_members</span><span class="op">(</span><span class="st">"Streptococcus group A"</span><span class="op">)</span></span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] "Streptococcus pyogenes"</span>
@@ -604,6 +506,8 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] "777146"</span>
 <span class="r-in"><span><span class="fu">mo_gbif</span><span class="op">(</span><span class="st">"Klebsiella aerogenes"</span><span class="op">)</span></span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] "9281703"</span>
+<span class="r-in"><span><span class="fu">mo_mycobank</span><span class="op">(</span><span class="st">"Candida albicans"</span><span class="op">)</span></span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] "256187"</span>
 <span class="r-in"><span><span class="fu">mo_synonyms</span><span class="op">(</span><span class="st">"Klebsiella aerogenes"</span><span class="op">)</span></span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   Hormaeche et al., 1960     Bascomb et al., 1971 </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> "Enterobacter aerogenes"     "Klebsiella mobilis" </span>
@@ -818,7 +722,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] "Gram-negative"</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> $oxygen_tolerance</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] "aerobe"</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] "facultative anaerobe"</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> $url</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] "https://lpsn.dsmz.de/species/klebsiella-pneumoniae"</span>
@@ -842,7 +746,7 @@
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -856,9 +760,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/mo_rank.html b/reference/mo_rank.html
new file mode 100644
index 000000000..32a922060
--- /dev/null
+++ b/reference/mo_rank.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mo_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/mo_property.html">
+  </head>
+</html>
+
diff --git a/reference/mo_ref.html b/reference/mo_ref.html
new file mode 100644
index 000000000..32a922060
--- /dev/null
+++ b/reference/mo_ref.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mo_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/mo_property.html">
+  </head>
+</html>
+
diff --git a/reference/mo_renamed.html b/reference/mo_renamed.html
new file mode 100644
index 000000000..e68bf46d9
--- /dev/null
+++ b/reference/mo_renamed.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/as.mo.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/as.mo.html">
+  </head>
+</html>
+
diff --git a/reference/mo_reset_session.html b/reference/mo_reset_session.html
new file mode 100644
index 000000000..e68bf46d9
--- /dev/null
+++ b/reference/mo_reset_session.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/as.mo.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/as.mo.html">
+  </head>
+</html>
+
diff --git a/reference/mo_shortname.html b/reference/mo_shortname.html
new file mode 100644
index 000000000..32a922060
--- /dev/null
+++ b/reference/mo_shortname.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mo_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/mo_property.html">
+  </head>
+</html>
+
diff --git a/reference/mo_snomed.html b/reference/mo_snomed.html
new file mode 100644
index 000000000..32a922060
--- /dev/null
+++ b/reference/mo_snomed.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mo_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/mo_property.html">
+  </head>
+</html>
+
diff --git a/reference/mo_source.html b/reference/mo_source.html
index 0a8c0b629..42ab6872b 100644
--- a/reference/mo_source.html
+++ b/reference/mo_source.html
@@ -1,163 +1,57 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="These functions can be used to predefine your own reference to be used in as.mo() and consequently all mo_* functions (such as mo_genus() and mo_gramstain()).
-This is the fastest way to have your organisation (or analysis) specific codes picked up and translated by this package, since you don't have to bother about it again after setting it up once."><title>User-Defined Reference Data Set for Microorganisms — mo_source • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="User-Defined Reference Data Set for Microorganisms — mo_source"><meta property="og:description" content="These functions can be used to predefine your own reference to be used in as.mo() and consequently all mo_* functions (such as mo_genus() and mo_gramstain()).
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+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
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 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>User-Defined Reference Data Set for Microorganisms</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/mo_source.R" class="external-link"><code>R/mo_source.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/mo_source.R" class="external-link"><code>R/mo_source.R</code></a></small>
       <div class="d-none name"><code>mo_source.Rd</code></div>
     </div>
 
@@ -178,11 +72,13 @@ This is the fastest way to have your organisation (or analysis) specific codes p
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>path</dt>
+
+
+<dl><dt id="arg-path">path<a class="anchor" aria-label="anchor" href="#arg-path"></a></dt>
 <dd><p>location of your reference file, this can be any text file (comma-, tab- or pipe-separated) or an Excel file (see <em>Details</em>). Can also be <code>""</code>, <code>NULL</code> or <code>FALSE</code> to delete the reference file.</p></dd>
 
 
-<dt>destination</dt>
+<dt id="arg-destination">destination<a class="anchor" aria-label="anchor" href="#arg-destination"></a></dt>
 <dd><p>destination of the compressed data file - the default is the user's home directory.</p></dd>
 
 </dl></div>
@@ -196,7 +92,7 @@ This is the fastest way to have your organisation (or analysis) specific codes p
     </div>
     <div class="section level2">
     <h2 id="how-to-setup">How to Setup<a class="anchor" aria-label="anchor" href="#how-to-setup"></a></h2>
-    
+
 
 
 <p>Imagine this data on a sheet of an Excel file. The first column contains the organisation specific codes, the second column contains valid taxonomic names:</p>
@@ -250,7 +146,7 @@ This is the fastest way to have your organisation (or analysis) specific codes p
 <p>If the original file (in the previous case an Excel file) is moved or deleted, the <code>mo_source.rds</code> file will be removed upon the next use of <code><a href="as.mo.html">as.mo()</a></code> or any <code><a href="mo_property.html">mo_*</a></code> function.</p>
     </div>
 
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -264,9 +160,9 @@ This is the fastest way to have your organisation (or analysis) specific codes p
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/mo_species.html b/reference/mo_species.html
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+++ b/reference/mo_species.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mo_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/mo_property.html">
+  </head>
+</html>
+
diff --git a/reference/mo_status.html b/reference/mo_status.html
new file mode 100644
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--- /dev/null
+++ b/reference/mo_status.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mo_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/mo_property.html">
+  </head>
+</html>
+
diff --git a/reference/mo_subspecies.html b/reference/mo_subspecies.html
new file mode 100644
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+++ b/reference/mo_subspecies.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mo_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/mo_property.html">
+  </head>
+</html>
+
diff --git a/reference/mo_synonyms.html b/reference/mo_synonyms.html
new file mode 100644
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+++ b/reference/mo_synonyms.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mo_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/mo_property.html">
+  </head>
+</html>
+
diff --git a/reference/mo_taxonomy.html b/reference/mo_taxonomy.html
new file mode 100644
index 000000000..32a922060
--- /dev/null
+++ b/reference/mo_taxonomy.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mo_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/mo_property.html">
+  </head>
+</html>
+
diff --git a/reference/mo_type.html b/reference/mo_type.html
new file mode 100644
index 000000000..32a922060
--- /dev/null
+++ b/reference/mo_type.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mo_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/mo_property.html">
+  </head>
+</html>
+
diff --git a/reference/mo_uncertainties.html b/reference/mo_uncertainties.html
new file mode 100644
index 000000000..e68bf46d9
--- /dev/null
+++ b/reference/mo_uncertainties.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/as.mo.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/as.mo.html">
+  </head>
+</html>
+
diff --git a/reference/mo_url.html b/reference/mo_url.html
new file mode 100644
index 000000000..32a922060
--- /dev/null
+++ b/reference/mo_url.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mo_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/mo_property.html">
+  </head>
+</html>
+
diff --git a/reference/mo_year.html b/reference/mo_year.html
new file mode 100644
index 000000000..32a922060
--- /dev/null
+++ b/reference/mo_year.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mo_property.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/mo_property.html">
+  </head>
+</html>
+
diff --git a/reference/mrgn.html b/reference/mrgn.html
new file mode 100644
index 000000000..9ccef1b51
--- /dev/null
+++ b/reference/mrgn.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/mdro.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/mdro.html">
+  </head>
+</html>
+
diff --git a/reference/n_sir.html b/reference/n_sir.html
new file mode 100644
index 000000000..c15e60ab1
--- /dev/null
+++ b/reference/n_sir.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/count.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/count.html">
+  </head>
+</html>
+
diff --git a/reference/nitrofurans.html b/reference/nitrofurans.html
new file mode 100644
index 000000000..07f8b21e2
--- /dev/null
+++ b/reference/nitrofurans.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html">
+  </head>
+</html>
+
diff --git a/reference/not_intrinsic_resistant.html b/reference/not_intrinsic_resistant.html
new file mode 100644
index 000000000..07f8b21e2
--- /dev/null
+++ b/reference/not_intrinsic_resistant.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html">
+  </head>
+</html>
+
diff --git a/reference/oxazolidinones.html b/reference/oxazolidinones.html
new file mode 100644
index 000000000..07f8b21e2
--- /dev/null
+++ b/reference/oxazolidinones.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html">
+  </head>
+</html>
+
diff --git a/reference/pca.html b/reference/pca.html
index 864059a83..ed6ddd5ce 100644
--- a/reference/pca.html
+++ b/reference/pca.html
@@ -1,161 +1,55 @@
 <!DOCTYPE html>
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+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
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   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Principal Component Analysis (for AMR)</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/pca.R" class="external-link"><code>R/pca.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/pca.R" class="external-link"><code>R/pca.R</code></a></small>
       <div class="d-none name"><code>pca.Rd</code></div>
     </div>
 
@@ -178,27 +72,29 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> containing <a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a> columns</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>columns of <code>x</code> to be selected for PCA, can be unquoted since it supports quasiquotation.</p></dd>
 
 
-<dt>retx</dt>
+<dt id="arg-retx">retx<a class="anchor" aria-label="anchor" href="#arg-retx"></a></dt>
 <dd><p>a logical value indicating whether the rotated variables
     should be returned.</p></dd>
 
 
-<dt>center</dt>
+<dt id="arg-center">center<a class="anchor" aria-label="anchor" href="#arg-center"></a></dt>
 <dd><p>a logical value indicating whether the variables
     should be shifted to be zero centered. Alternately, a vector of
     length equal the number of columns of <code>x</code> can be supplied.
     The value is passed to <code>scale</code>.</p></dd>
 
 
-<dt>scale.</dt>
+<dt id="arg-scale-">scale.<a class="anchor" aria-label="anchor" href="#arg-scale-"></a></dt>
 <dd><p>a logical value indicating whether the variables should
     be scaled to have unit variance before the analysis takes
     place.  The default is <code>FALSE</code> for consistency with S, but
@@ -207,7 +103,7 @@
     value is passed to <code><a href="https://rdrr.io/r/base/scale.html" class="external-link">scale</a></code>.</p></dd>
 
 
-<dt>tol</dt>
+<dt id="arg-tol">tol<a class="anchor" aria-label="anchor" href="#arg-tol"></a></dt>
 <dd><p>a value indicating the magnitude below which components
     should be omitted. (Components are omitted if their
     standard deviations are less than or equal to <code>tol</code> times the
@@ -218,7 +114,7 @@
     would omit essentially constant components.</p></dd>
 
 
-<dt>rank.</dt>
+<dt id="arg-rank-">rank.<a class="anchor" aria-label="anchor" href="#arg-rank-"></a></dt>
 <dd><p>optionally, a number specifying the maximal rank, i.e.,
     maximal number of principal components to be used.  Can be set as
     alternative or in addition to <code>tol</code>, useful notably when the
@@ -227,11 +123,7 @@
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>An object of classes pca and <a href="https://rdrr.io/r/stats/prcomp.html" class="external-link">prcomp</a></p>
-
-
+    <p>An object of classes pca and <a href="https://rdrr.io/r/stats/prcomp.html" class="external-link">prcomp</a></p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -292,7 +184,7 @@
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -306,9 +198,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/penicillins.html b/reference/penicillins.html
new file mode 100644
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@@ -0,0 +1,8 @@
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diff --git a/reference/plot.antibiogram.html b/reference/plot.antibiogram.html
new file mode 100644
index 000000000..4748f41b8
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+++ b/reference/plot.antibiogram.html
@@ -0,0 +1,8 @@
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new file mode 100644
index 000000000..934dc99fb
--- /dev/null
+++ b/reference/plot.disk.html
@@ -0,0 +1,8 @@
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diff --git a/reference/plot.html b/reference/plot.html
index a90a79ac9..cd5da2663 100644
--- a/reference/plot.html
+++ b/reference/plot.html
@@ -1,163 +1,57 @@
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-Especially the scale_*_mic() functions are relevant wrappers to plot MIC values for ggplot2. They allows custom MIC ranges and to plot intermediate log2 levels for missing MIC values."><title>Plotting for Classes sir, mic and disk — plot • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Plotting for Classes sir, mic and disk — plot"><meta property="og:description" content="Functions to plot classes sir, mic and disk, with support for base R and ggplot2.
-Especially the scale_*_mic() functions are relevant wrappers to plot MIC values for ggplot2. They allows custom MIC ranges and to plot intermediate log2 levels for missing MIC values."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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+Especially the scale_*_mic() functions are relevant wrappers to plot MIC values for ggplot2. They allows custom MIC ranges and to plot intermediate log2 levels for missing MIC values."><meta property="og:description" content="Functions to plot classes sir, mic and disk, with support for base R and ggplot2.
+Especially the scale_*_mic() functions are relevant wrappers to plot MIC values for ggplot2. They allows custom MIC ranges and to plot intermediate log2 levels for missing MIC values."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"></head><body>
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   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Plotting for Classes <code>sir</code>, <code>mic</code> and <code>disk</code></h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/plot.R" class="external-link"><code>R/plot.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/plot.R" class="external-link"><code>R/plot.R</code></a></small>
       <div class="d-none name"><code>plot.Rd</code></div>
     </div>
 
@@ -176,7 +70,7 @@ Especially the scale_*_mic() functions are relevant wrappers to plot MIC values
 <span></span>
 <span><span class="fu">scale_fill_mic</span><span class="op">(</span>keep_operators <span class="op">=</span> <span class="st">"edges"</span>, mic_range <span class="op">=</span> <span class="cn">NULL</span>, drop <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for mic</span></span>
+<span><span class="co"># S3 method for class 'mic'</span></span>
 <span><span class="fu">plot</span><span class="op">(</span></span>
 <span>  <span class="va">x</span>,</span>
 <span>  mo <span class="op">=</span> <span class="cn">NULL</span>,</span>
@@ -193,7 +87,7 @@ Especially the scale_*_mic() functions are relevant wrappers to plot MIC values
 <span>  <span class="va">...</span></span>
 <span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for mic</span></span>
+<span><span class="co"># S3 method for class 'mic'</span></span>
 <span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span></span>
 <span>  <span class="va">object</span>,</span>
 <span>  mo <span class="op">=</span> <span class="cn">NULL</span>,</span>
@@ -210,10 +104,10 @@ Especially the scale_*_mic() functions are relevant wrappers to plot MIC values
 <span>  <span class="va">...</span></span>
 <span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for mic</span></span>
+<span><span class="co"># S3 method for class 'mic'</span></span>
 <span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/fortify.html" class="external-link">fortify</a></span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for disk</span></span>
+<span><span class="co"># S3 method for class 'disk'</span></span>
 <span><span class="fu">plot</span><span class="op">(</span></span>
 <span>  <span class="va">x</span>,</span>
 <span>  main <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/deparse.html" class="external-link">deparse</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/substitute.html" class="external-link">substitute</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span><span class="op">)</span>,</span>
@@ -230,7 +124,7 @@ Especially the scale_*_mic() functions are relevant wrappers to plot MIC values
 <span>  <span class="va">...</span></span>
 <span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for disk</span></span>
+<span><span class="co"># S3 method for class 'disk'</span></span>
 <span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span></span>
 <span>  <span class="va">object</span>,</span>
 <span>  mo <span class="op">=</span> <span class="cn">NULL</span>,</span>
@@ -247,10 +141,10 @@ Especially the scale_*_mic() functions are relevant wrappers to plot MIC values
 <span>  <span class="va">...</span></span>
 <span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for disk</span></span>
+<span><span class="co"># S3 method for class 'disk'</span></span>
 <span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/fortify.html" class="external-link">fortify</a></span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for sir</span></span>
+<span><span class="co"># S3 method for class 'sir'</span></span>
 <span><span class="fu">plot</span><span class="op">(</span></span>
 <span>  <span class="va">x</span>,</span>
 <span>  ylab <span class="op">=</span> <span class="fu"><a href="translate.html">translate_AMR</a></span><span class="op">(</span><span class="st">"Percentage"</span>, language <span class="op">=</span> <span class="va">language</span><span class="op">)</span>,</span>
@@ -260,7 +154,7 @@ Especially the scale_*_mic() functions are relevant wrappers to plot MIC values
 <span>  <span class="va">...</span></span>
 <span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for sir</span></span>
+<span><span class="co"># S3 method for class 'sir'</span></span>
 <span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span></span>
 <span>  <span class="va">object</span>,</span>
 <span>  title <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/deparse.html" class="external-link">deparse</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/substitute.html" class="external-link">substitute</a></span><span class="op">(</span><span class="va">object</span><span class="op">)</span><span class="op">)</span>,</span>
@@ -271,79 +165,77 @@ Especially the scale_*_mic() functions are relevant wrappers to plot MIC values
 <span>  <span class="va">...</span></span>
 <span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for sir</span></span>
+<span><span class="co"># S3 method for class 'sir'</span></span>
 <span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/fortify.html" class="external-link">fortify</a></span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
     </div>
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>keep_operators</dt>
+
+
+<dl><dt id="arg-keep-operators">keep_operators<a class="anchor" aria-label="anchor" href="#arg-keep-operators"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> specifying how to handle operators (such as <code>&gt;</code> and <code>&lt;=</code>) in the input. Accepts one of three values: <code>"all"</code> (or <code>TRUE</code>) to keep all operators, <code>"none"</code> (or <code>FALSE</code>) to remove all operators, or <code>"edges"</code> to keep operators only at both ends of the range.</p></dd>
 
 
-<dt>mic_range</dt>
+<dt id="arg-mic-range">mic_range<a class="anchor" aria-label="anchor" href="#arg-mic-range"></a></dt>
 <dd><p>a manual range to limit the MIC values, e.g., <code>mic_range = c(0.001, 32)</code>. Use <code>NA</code> to set no limit on one side, e.g., <code>mic_range = c(NA, 32)</code>.</p></dd>
 
 
-<dt>drop</dt>
+<dt id="arg-drop">drop<a class="anchor" aria-label="anchor" href="#arg-drop"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to remove intermediate MIC values, defaults to <code>FALSE</code></p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>arguments passed on to methods</p></dd>
 
 
-<dt>x, object</dt>
+<dt id="arg-x-object">x, object<a class="anchor" aria-label="anchor" href="#arg-x-object"></a></dt>
 <dd><p>values created with <code><a href="as.mic.html">as.mic()</a></code>, <code><a href="as.disk.html">as.disk()</a></code> or <code><a href="as.sir.html">as.sir()</a></code> (or their <code>random_*</code> variants, such as <code><a href="random.html">random_mic()</a></code>)</p></dd>
 
 
-<dt>mo</dt>
+<dt id="arg-mo">mo<a class="anchor" aria-label="anchor" href="#arg-mo"></a></dt>
 <dd><p>any (vector of) text that can be coerced to a valid microorganism code with <code><a href="as.mo.html">as.mo()</a></code></p></dd>
 
 
-<dt>ab</dt>
+<dt id="arg-ab">ab<a class="anchor" aria-label="anchor" href="#arg-ab"></a></dt>
 <dd><p>any (vector of) text that can be coerced to a valid antimicrobial drug code with <code><a href="as.ab.html">as.ab()</a></code></p></dd>
 
 
-<dt>guideline</dt>
+<dt id="arg-guideline">guideline<a class="anchor" aria-label="anchor" href="#arg-guideline"></a></dt>
 <dd><p>interpretation guideline to use - the default is the latest included EUCAST guideline, see <em>Details</em></p></dd>
 
 
-<dt>main, title</dt>
+<dt id="arg-main-title">main, title<a class="anchor" aria-label="anchor" href="#arg-main-title"></a></dt>
 <dd><p>title of the plot</p></dd>
 
 
-<dt>xlab, ylab</dt>
+<dt id="arg-xlab-ylab">xlab, ylab<a class="anchor" aria-label="anchor" href="#arg-xlab-ylab"></a></dt>
 <dd><p>axis title</p></dd>
 
 
-<dt>colours_SIR</dt>
+<dt id="arg-colours-sir">colours_SIR<a class="anchor" aria-label="anchor" href="#arg-colours-sir"></a></dt>
 <dd><p>colours to use for filling in the bars, must be a vector of three values (in the order S, I and R). The default colours are colour-blind friendly.</p></dd>
 
 
-<dt>language</dt>
+<dt id="arg-language">language<a class="anchor" aria-label="anchor" href="#arg-language"></a></dt>
 <dd><p>language to be used to translate 'Susceptible', 'Increased exposure'/'Intermediate' and 'Resistant' - the default is system language (see <code><a href="translate.html">get_AMR_locale()</a></code>) and can be overwritten by setting the <a href="AMR-options.html">package option</a> <code><a href="AMR-options.html">AMR_locale</a></code>, e.g. <code>options(AMR_locale = "de")</code>, see <a href="translate.html">translate</a>. Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></dd>
 
 
-<dt>expand</dt>
+<dt id="arg-expand">expand<a class="anchor" aria-label="anchor" href="#arg-expand"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether the range on the x axis should be expanded between the lowest and highest value. For MIC values, intermediate values will be factors of 2 starting from the highest MIC value. For disk diameters, the whole diameter range will be filled.</p></dd>
 
 
-<dt>include_PKPD</dt>
+<dt id="arg-include-pkpd">include_PKPD<a class="anchor" aria-label="anchor" href="#arg-include-pkpd"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate that PK/PD clinical breakpoints must be applied as a last resort - the default is <code>TRUE</code>. Can also be set with the <a href="AMR-options.html">package option</a> <code><a href="AMR-options.html">AMR_include_PKPD</a></code>.</p></dd>
 
 
-<dt>breakpoint_type</dt>
+<dt id="arg-breakpoint-type">breakpoint_type<a class="anchor" aria-label="anchor" href="#arg-breakpoint-type"></a></dt>
 <dd><p>the type of breakpoints to use, either "ECOFF", "animal", or "human". ECOFF stands for Epidemiological Cut-Off values. The default is <code>"human"</code>, which can also be set with the <a href="AMR-options.html">package option</a> <code><a href="AMR-options.html">AMR_breakpoint_type</a></code>. If <code>host</code> is set to values of veterinary species, this will automatically be set to <code>"animal"</code>.</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>The <code><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot()</a></code> functions return a <code><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></code> model that is extendible with any <code>ggplot2</code> function.</p>
-
-
+    <p>The <code><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot()</a></code> functions return a <code><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></code> model that is extendible with any <code>ggplot2</code> function.</p>
 <p>The <code><a href="https://ggplot2.tidyverse.org/reference/fortify.html" class="external-link">fortify()</a></code> functions return a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> as an extension for usage in the <code><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot2::ggplot()</a></code> function.</p>
     </div>
     <div class="section level2">
@@ -420,7 +312,7 @@ Especially the scale_*_mic() functions are relevant wrappers to plot MIC values
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -434,9 +326,9 @@ Especially the scale_*_mic() functions are relevant wrappers to plot MIC values
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/plot.mic.html b/reference/plot.mic.html
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+++ b/reference/plot.mic.html
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new file mode 100644
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new file mode 100644
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diff --git a/reference/polymyxins.html b/reference/polymyxins.html
new file mode 100644
index 000000000..07f8b21e2
--- /dev/null
+++ b/reference/polymyxins.html
@@ -0,0 +1,8 @@
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+  <head>
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+
diff --git a/reference/portion.html b/reference/portion.html
new file mode 100644
index 000000000..887064d0e
--- /dev/null
+++ b/reference/portion.html
@@ -0,0 +1,8 @@
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diff --git a/reference/proportion.html b/reference/proportion.html
index a0684abbc..90a059fb6 100644
--- a/reference/proportion.html
+++ b/reference/proportion.html
@@ -1,163 +1,57 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="These functions can be used to calculate the (co-)resistance or susceptibility of microbial isolates (i.e. percentage of S, SI, I, IR or R). All functions support quasiquotation with pipes, can be used in summarise() from the dplyr package and also support grouped variables, see Examples.
-resistance() should be used to calculate resistance, susceptibility() should be used to calculate susceptibility."><title>Calculate Antimicrobial Resistance — proportion • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Calculate Antimicrobial Resistance — proportion"><meta property="og:description" content="These functions can be used to calculate the (co-)resistance or susceptibility of microbial isolates (i.e. percentage of S, SI, I, IR or R). All functions support quasiquotation with pipes, can be used in summarise() from the dplyr package and also support grouped variables, see Examples.
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+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-how-to" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true"><span class="fa fa-question-circle"></span> How to</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to"><li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
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+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul></li>
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
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 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Calculate Antimicrobial Resistance</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/proportion.R" class="external-link"><code>R/proportion.R</code></a>, <a href="https://github.com/msberends/AMR/blob/HEAD/R/sir_df.R" class="external-link"><code>R/sir_df.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/proportion.R" class="external-link"><code>R/proportion.R</code></a>, <a href="https://github.com/msberends/AMR/blob/main/R/sir_df.R" class="external-link"><code>R/sir_df.R</code></a></small>
       <div class="d-none name"><code>proportion.Rd</code></div>
     </div>
 
@@ -220,59 +114,59 @@ resistance() should be used to calculate resistance, susceptibility() should be
     </div>
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>...</dt>
+
+
+<dl><dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with <code><a href="as.sir.html">as.sir()</a></code> if needed. Use multiple columns to calculate (the lack of) co-resistance: the probability where one of two drugs have a resistant or susceptible result. See <em>Examples</em>.</p></dd>
 
 
-<dt>minimum</dt>
+<dt id="arg-minimum">minimum<a class="anchor" aria-label="anchor" href="#arg-minimum"></a></dt>
 <dd><p>the minimum allowed number of available (tested) isolates. Any isolate count lower than <code>minimum</code> will return <code>NA</code> with a warning. The default number of <code>30</code> isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see <em>Source</em>.</p></dd>
 
 
-<dt>as_percent</dt>
+<dt id="arg-as-percent">as_percent<a class="anchor" aria-label="anchor" href="#arg-as-percent"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether the output must be returned as a hundred fold with % sign (a character). A value of <code>0.123456</code> will then be returned as <code>"12.3%"</code>.</p></dd>
 
 
-<dt>only_all_tested</dt>
+<dt id="arg-only-all-tested">only_all_tested<a class="anchor" aria-label="anchor" href="#arg-only-all-tested"></a></dt>
 <dd><p>(for combination therapies, i.e. using more than one variable for <code>...</code>): a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate that isolates must be tested for all antibiotics, see section <em>Combination Therapy</em> below</p></dd>
 
 
-<dt>ab_result</dt>
+<dt id="arg-ab-result">ab_result<a class="anchor" aria-label="anchor" href="#arg-ab-result"></a></dt>
 <dd><p>antibiotic results to test against, must be one or more values of "S", "I", or "R"</p></dd>
 
 
-<dt>confidence_level</dt>
+<dt id="arg-confidence-level">confidence_level<a class="anchor" aria-label="anchor" href="#arg-confidence-level"></a></dt>
 <dd><p>the confidence level for the returned confidence interval. For the calculation, the number of S or SI isolates, and R isolates are compared with the total number of available isolates with R, S, or I by using <code><a href="https://rdrr.io/r/stats/binom.test.html" class="external-link">binom.test()</a></code>, i.e., the Clopper-Pearson method.</p></dd>
 
 
-<dt>side</dt>
+<dt id="arg-side">side<a class="anchor" aria-label="anchor" href="#arg-side"></a></dt>
 <dd><p>the side of the confidence interval to return. The default is <code>"both"</code> for a length 2 vector, but can also be (abbreviated as) <code>"min"</code>/<code>"left"</code>/<code>"lower"</code>/<code>"less"</code> or <code>"max"</code>/<code>"right"</code>/<code>"higher"</code>/<code>"greater"</code>.</p></dd>
 
 
-<dt>collapse</dt>
+<dt id="arg-collapse">collapse<a class="anchor" aria-label="anchor" href="#arg-collapse"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether the output values should be 'collapsed', i.e. be merged together into one value, or a character value to use for collapsing</p></dd>
 
 
-<dt>data</dt>
+<dt id="arg-data">data<a class="anchor" aria-label="anchor" href="#arg-data"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> containing columns with class <code><a href="as.sir.html">sir</a></code> (see <code><a href="as.sir.html">as.sir()</a></code>)</p></dd>
 
 
-<dt>translate_ab</dt>
+<dt id="arg-translate-ab">translate_ab<a class="anchor" aria-label="anchor" href="#arg-translate-ab"></a></dt>
 <dd><p>a column name of the <a href="antibiotics.html">antibiotics</a> data set to translate the antibiotic abbreviations to, using <code><a href="ab_property.html">ab_property()</a></code></p></dd>
 
 
-<dt>language</dt>
+<dt id="arg-language">language<a class="anchor" aria-label="anchor" href="#arg-language"></a></dt>
 <dd><p>language of the returned text - the default is the current system language (see <code><a href="translate.html">get_AMR_locale()</a></code>) and can also be set with the <a href="AMR-options.html">package option</a> <code><a href="AMR-options.html">AMR_locale</a></code>. Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></dd>
 
 
-<dt>combine_SI</dt>
+<dt id="arg-combine-si">combine_SI<a class="anchor" aria-label="anchor" href="#arg-combine-si"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether all values of S and I must be merged into one, so the output only consists of S+I vs. R (susceptible vs. resistant) - the default is <code>TRUE</code></p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A <a href="https://rdrr.io/r/base/double.html" class="external-link">double</a> or, when <code>as_percent = TRUE</code>, a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a>.</p>
+    <p>A <a href="https://rdrr.io/r/base/double.html" class="external-link">double</a> or, when <code>as_percent = TRUE</code>, a <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a>.</p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -284,7 +178,7 @@ resistance() should be used to calculate resistance, susceptibility() should be
     </div>
     <div class="section level2">
     <h2 id="combination-therapy">Combination Therapy<a class="anchor" aria-label="anchor" href="#combination-therapy"></a></h2>
-    
+
 
 <p>When using more than one variable for <code>...</code> (= combination therapy), use <code>only_all_tested</code> to only count isolates that are tested for all antibiotics/variables that you test them for. See this example for two antibiotics, Drug A and Drug B, about how <code>susceptibility()</code> works to calculate the %SI:</p>
 <p></p><div class="sourceCode"><pre><code><span id="cb1-1"><a href="#cb1-1" tabindex="-1"></a><span class="sc">--------------------------------------------------------------------</span></span>
@@ -313,7 +207,7 @@ resistance() should be used to calculate resistance, susceptibility() should be
     </div>
     <div class="section level2">
     <h2 id="interpretation-of-sir">Interpretation of SIR<a class="anchor" aria-label="anchor" href="#interpretation-of-sir"></a></h2>
-    
+
 
 <p>In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories S, I, and R as shown below (<a href="https://www.eucast.org/newsiandr" class="external-link">https://www.eucast.org/newsiandr</a>):</p><ul><li><p><strong>S - Susceptible, standard dosing regimen</strong><br>
 A microorganism is categorised as "Susceptible, standard dosing regimen", when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.</p></li>
@@ -535,7 +429,7 @@ A microorganism is categorised as "Resistant" when there is a high likelihood of
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -549,9 +443,9 @@ A microorganism is categorised as "Resistant" when there is a high likelihood of
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/proportion_I.html b/reference/proportion_I.html
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+++ b/reference/proportion_I.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/proportion.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/proportion.html">
+  </head>
+</html>
+
diff --git a/reference/proportion_IR.html b/reference/proportion_IR.html
new file mode 100644
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--- /dev/null
+++ b/reference/proportion_IR.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/proportion.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/proportion.html">
+  </head>
+</html>
+
diff --git a/reference/proportion_R.html b/reference/proportion_R.html
new file mode 100644
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+++ b/reference/proportion_R.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/proportion.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/proportion.html">
+  </head>
+</html>
+
diff --git a/reference/proportion_S.html b/reference/proportion_S.html
new file mode 100644
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+++ b/reference/proportion_S.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/proportion.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/proportion.html">
+  </head>
+</html>
+
diff --git a/reference/proportion_SI.html b/reference/proportion_SI.html
new file mode 100644
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+++ b/reference/proportion_SI.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/proportion.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/proportion.html">
+  </head>
+</html>
+
diff --git a/reference/proportion_df.html b/reference/proportion_df.html
new file mode 100644
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--- /dev/null
+++ b/reference/proportion_df.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/proportion.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/proportion.html">
+  </head>
+</html>
+
diff --git a/reference/quinolones.html b/reference/quinolones.html
new file mode 100644
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--- /dev/null
+++ b/reference/quinolones.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html">
+  </head>
+</html>
+
diff --git a/reference/random.html b/reference/random.html
index 08bd370b1..b01d0e754 100644
--- a/reference/random.html
+++ b/reference/random.html
@@ -1,161 +1,55 @@
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   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Random MIC Values/Disk Zones/SIR Generation</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/random.R" class="external-link"><code>R/random.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/random.R" class="external-link"><code>R/random.R</code></a></small>
       <div class="d-none name"><code>random.Rd</code></div>
     </div>
 
@@ -174,31 +68,31 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>size</dt>
+
+
+<dl><dt id="arg-size">size<a class="anchor" aria-label="anchor" href="#arg-size"></a></dt>
 <dd><p>desired size of the returned vector. If used in a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> call or <code>dplyr</code> verb, will get the current (group) size if left blank.</p></dd>
 
 
-<dt>mo</dt>
+<dt id="arg-mo">mo<a class="anchor" aria-label="anchor" href="#arg-mo"></a></dt>
 <dd><p>any <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> that can be coerced to a valid microorganism code with <code><a href="as.mo.html">as.mo()</a></code></p></dd>
 
 
-<dt>ab</dt>
+<dt id="arg-ab">ab<a class="anchor" aria-label="anchor" href="#arg-ab"></a></dt>
 <dd><p>any <a href="https://rdrr.io/r/base/character.html" class="external-link">character</a> that can be coerced to a valid antimicrobial drug code with <code><a href="as.ab.html">as.ab()</a></code></p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>ignored, only in place to allow future extensions</p></dd>
 
 
-<dt>prob_SIR</dt>
+<dt id="arg-prob-sir">prob_SIR<a class="anchor" aria-label="anchor" href="#arg-prob-sir"></a></dt>
 <dd><p>a vector of length 3: the probabilities for "S" (1st value), "I" (2nd value) and "R" (3rd value)</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>class <code>mic</code> for <code>random_mic()</code> (see <code><a href="as.mic.html">as.mic()</a></code>) and class <code>disk</code> for <code>random_disk()</code> (see <code><a href="as.disk.html">as.disk()</a></code>)</p>
+    <p>class <code>mic</code> for <code>random_mic()</code> (see <code><a href="as.mic.html">as.mic()</a></code>) and class <code>disk</code> for <code>random_disk()</code> (see <code><a href="as.disk.html">as.disk()</a></code>)</p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -249,7 +143,7 @@
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -263,9 +157,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/random_disk.html b/reference/random_disk.html
new file mode 100644
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--- /dev/null
+++ b/reference/random_disk.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/random.html" />
+    <meta name="robots" content="noindex">
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+
diff --git a/reference/random_mic.html b/reference/random_mic.html
new file mode 100644
index 000000000..c2a117cf8
--- /dev/null
+++ b/reference/random_mic.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/random.html" />
+    <meta name="robots" content="noindex">
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+</html>
+
diff --git a/reference/random_sir.html b/reference/random_sir.html
new file mode 100644
index 000000000..c2a117cf8
--- /dev/null
+++ b/reference/random_sir.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/random.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/random.html">
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+</html>
+
diff --git a/reference/rescale_mic.html b/reference/rescale_mic.html
new file mode 100644
index 000000000..977eb978a
--- /dev/null
+++ b/reference/rescale_mic.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/as.mic.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/as.mic.html">
+  </head>
+</html>
+
diff --git a/reference/reset_AMR_locale.html b/reference/reset_AMR_locale.html
new file mode 100644
index 000000000..b4dcf12f0
--- /dev/null
+++ b/reference/reset_AMR_locale.html
@@ -0,0 +1,8 @@
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diff --git a/reference/resistance.html b/reference/resistance.html
new file mode 100644
index 000000000..887064d0e
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diff --git a/reference/resistance_predict.html b/reference/resistance_predict.html
index 6a3df5371..196e9b6ed 100644
--- a/reference/resistance_predict.html
+++ b/reference/resistance_predict.html
@@ -1,161 +1,55 @@
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-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Create a prediction model to predict antimicrobial resistance for the next years on statistical solid ground. Standard errors (SE) will be returned as columns se_min and se_max. See Examples for a real live example."><title>Predict Antimicrobial Resistance — resistance_predict • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Predict Antimicrobial Resistance — resistance_predict"><meta property="og:description" content="Create a prediction model to predict antimicrobial resistance for the next years on statistical solid ground. Standard errors (SE) will be returned as columns se_min and se_max. See Examples for a real live example."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Predict Antimicrobial Resistance</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/resistance_predict.R" class="external-link"><code>R/resistance_predict.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/resistance_predict.R" class="external-link"><code>R/resistance_predict.R</code></a></small>
       <div class="d-none name"><code>resistance_predict.Rd</code></div>
     </div>
 
@@ -195,7 +89,7 @@
 <span>  <span class="va">...</span></span>
 <span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for resistance_predict</span></span>
+<span><span class="co"># S3 method for class 'resistance_predict'</span></span>
 <span><span class="fu"><a href="plot.html">plot</a></span><span class="op">(</span><span class="va">x</span>, main <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"Resistance Prediction of"</span>, <span class="va">x_name</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span>
 <span></span>
 <span><span class="fu">ggplot_sir_predict</span><span class="op">(</span></span>
@@ -205,7 +99,7 @@
 <span>  <span class="va">...</span></span>
 <span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for resistance_predict</span></span>
+<span><span class="co"># S3 method for class 'resistance_predict'</span></span>
 <span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span></span>
 <span>  <span class="va">object</span>,</span>
 <span>  main <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"Resistance Prediction of"</span>, <span class="va">x_name</span><span class="op">)</span>,</span>
@@ -216,71 +110,71 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> containing isolates. Can be left blank for automatic determination, see <em>Examples</em>.</p></dd>
 
 
-<dt>col_ab</dt>
+<dt id="arg-col-ab">col_ab<a class="anchor" aria-label="anchor" href="#arg-col-ab"></a></dt>
 <dd><p>column name of <code>x</code> containing antimicrobial interpretations (<code>"R"</code>, <code>"I"</code> and <code>"S"</code>)</p></dd>
 
 
-<dt>col_date</dt>
+<dt id="arg-col-date">col_date<a class="anchor" aria-label="anchor" href="#arg-col-date"></a></dt>
 <dd><p>column name of the date, will be used to calculate years if this column doesn't consist of years already - the default is the first column of with a date class</p></dd>
 
 
-<dt>year_min</dt>
+<dt id="arg-year-min">year_min<a class="anchor" aria-label="anchor" href="#arg-year-min"></a></dt>
 <dd><p>lowest year to use in the prediction model, dafaults to the lowest year in <code>col_date</code></p></dd>
 
 
-<dt>year_max</dt>
+<dt id="arg-year-max">year_max<a class="anchor" aria-label="anchor" href="#arg-year-max"></a></dt>
 <dd><p>highest year to use in the prediction model - the default is 10 years after today</p></dd>
 
 
-<dt>year_every</dt>
+<dt id="arg-year-every">year_every<a class="anchor" aria-label="anchor" href="#arg-year-every"></a></dt>
 <dd><p>unit of sequence between lowest year found in the data and <code>year_max</code></p></dd>
 
 
-<dt>minimum</dt>
+<dt id="arg-minimum">minimum<a class="anchor" aria-label="anchor" href="#arg-minimum"></a></dt>
 <dd><p>minimal amount of available isolates per year to include. Years containing less observations will be estimated by the model.</p></dd>
 
 
-<dt>model</dt>
+<dt id="arg-model">model<a class="anchor" aria-label="anchor" href="#arg-model"></a></dt>
 <dd><p>the statistical model of choice. This could be a generalised linear regression model with binomial distribution (i.e. using <code>glm(..., family = binomial)</code>, assuming that a period of zero resistance was followed by a period of increasing resistance leading slowly to more and more resistance. See <em>Details</em> for all valid options.</p></dd>
 
 
-<dt>I_as_S</dt>
+<dt id="arg-i-as-s">I_as_S<a class="anchor" aria-label="anchor" href="#arg-i-as-s"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether values <code>"I"</code> should be treated as <code>"S"</code> (will otherwise be treated as <code>"R"</code>). The default, <code>TRUE</code>, follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section <em>Interpretation of S, I and R</em> below.</p></dd>
 
 
-<dt>preserve_measurements</dt>
+<dt id="arg-preserve-measurements">preserve_measurements<a class="anchor" aria-label="anchor" href="#arg-preserve-measurements"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether predictions of years that are actually available in the data should be overwritten by the original data. The standard errors of those years will be <code>NA</code>.</p></dd>
 
 
-<dt>info</dt>
+<dt id="arg-info">info<a class="anchor" aria-label="anchor" href="#arg-info"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether textual analysis should be printed with the name and <code><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary()</a></code> of the statistical model.</p></dd>
 
 
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
 <dd><p>arguments passed on to functions</p></dd>
 
 
-<dt>main</dt>
+<dt id="arg-main">main<a class="anchor" aria-label="anchor" href="#arg-main"></a></dt>
 <dd><p>title of the plot</p></dd>
 
 
-<dt>ribbon</dt>
+<dt id="arg-ribbon">ribbon<a class="anchor" aria-label="anchor" href="#arg-ribbon"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether a ribbon should be shown (default) or error bars</p></dd>
 
 
-<dt>object</dt>
+<dt id="arg-object">object<a class="anchor" aria-label="anchor" href="#arg-object"></a></dt>
 <dd><p>model data to be plotted</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    
-
-<p>A <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with extra class <code>resistance_predict</code> with columns:</p><ul><li><p><code>year</code></p></li>
+    <p>A <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with extra class <code>resistance_predict</code> with columns:</p><ul><li><p><code>year</code></p></li>
 <li><p><code>value</code>, the same as <code>estimated</code> when <code>preserve_measurements = FALSE</code>, and a combination of <code>observed</code> and <code>estimated</code> otherwise</p></li>
 <li><p><code>se_min</code>, the lower bound of the standard error with a minimum of <code>0</code> (so the standard error will never go below 0%)</p></li>
 <li><p><code>se_max</code> the upper bound of the standard error with a maximum of <code>1</code> (so the standard error will never go above 100%)</p></li>
@@ -297,7 +191,7 @@
 </ul></div>
     <div class="section level2">
     <h2 id="interpretation-of-sir">Interpretation of SIR<a class="anchor" aria-label="anchor" href="#interpretation-of-sir"></a></h2>
-    
+
 
 <p>In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories S, I, and R as shown below (<a href="https://www.eucast.org/newsiandr" class="external-link">https://www.eucast.org/newsiandr</a>):</p><ul><li><p><strong>S - Susceptible, standard dosing regimen</strong><br>
 A microorganism is categorised as "Susceptible, standard dosing regimen", when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.</p></li>
@@ -379,7 +273,7 @@ A microorganism is categorised as "Resistant" when there is a high likelihood of
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -393,9 +287,9 @@ A microorganism is categorised as "Resistant" when there is a high likelihood of
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
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new file mode 100644
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index 36bd814a0..a4be3a969 100644
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-When negative ('left-skewed'): the left tail is longer; the mass of the distribution is concentrated on the right of a histogram. When positive ('right-skewed'): the right tail is longer; the mass of the distribution is concentrated on the left of a histogram. A normal distribution has a skewness of 0."><title>Skewness of the Sample — skewness • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.9/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.9/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Skewness of the Sample — skewness"><meta property="og:description" content="Skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean.
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+When negative ('left-skewed'): the left tail is longer; the mass of the distribution is concentrated on the right of a histogram. When positive ('right-skewed'): the right tail is longer; the mass of the distribution is concentrated on the left of a histogram. A normal distribution has a skewness of 0."><meta property="og:description" content="Skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean.
+When negative ('left-skewed'): the left tail is longer; the mass of the distribution is concentrated on the right of a histogram. When positive ('right-skewed'): the right tail is longer; the mass of the distribution is concentrated on the left of a histogram. A normal distribution has a skewness of 0."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"></head><body>
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   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Skewness of the Sample</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/skewness.R" class="external-link"><code>R/skewness.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/skewness.R" class="external-link"><code>R/skewness.R</code></a></small>
       <div class="d-none name"><code>skewness.Rd</code></div>
     </div>
 
@@ -170,23 +64,25 @@ When negative ('left-skewed'): the left tail is longer; the mass of the distribu
     <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">skewness</span><span class="op">(</span><span class="va">x</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for default</span></span>
+<span><span class="co"># Default S3 method</span></span>
 <span><span class="fu">skewness</span><span class="op">(</span><span class="va">x</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for matrix</span></span>
+<span><span class="co"># S3 method for class 'matrix'</span></span>
 <span><span class="fu">skewness</span><span class="op">(</span><span class="va">x</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for data.frame</span></span>
+<span><span class="co"># S3 method for class 'data.frame'</span></span>
 <span><span class="fu">skewness</span><span class="op">(</span><span class="va">x</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div>
     </div>
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>x</dt>
+
+
+<dl><dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>a vector of values, a <a href="https://rdrr.io/r/base/matrix.html" class="external-link">matrix</a> or a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></p></dd>
 
 
-<dt>na.rm</dt>
+<dt id="arg-na-rm">na.rm<a class="anchor" aria-label="anchor" href="#arg-na-rm"></a></dt>
 <dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> value indicating whether <code>NA</code> values should be stripped before the computation proceeds</p></dd>
 
 </dl></div>
@@ -201,7 +97,7 @@ When negative ('left-skewed'): the left tail is longer; the mass of the distribu
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] -0.03310027</span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -215,9 +111,9 @@ When negative ('left-skewed'): the left tail is longer; the mass of the distribu
 
     </footer></div>
 
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diff --git a/reference/skewness.matrix.html b/reference/skewness.matrix.html
new file mode 100644
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+++ b/reference/skewness.matrix.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
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+
diff --git a/reference/streptogramins.html b/reference/streptogramins.html
new file mode 100644
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+++ b/reference/streptogramins.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
+    <meta name="robots" content="noindex">
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+</html>
+
diff --git a/reference/susceptibility.html b/reference/susceptibility.html
new file mode 100644
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--- /dev/null
+++ b/reference/susceptibility.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/proportion.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/proportion.html">
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+
diff --git a/reference/tetracyclines.html b/reference/tetracyclines.html
new file mode 100644
index 000000000..07f8b21e2
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+++ b/reference/tetracyclines.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html">
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diff --git a/reference/theme_sir.html b/reference/theme_sir.html
new file mode 100644
index 000000000..9e142046a
--- /dev/null
+++ b/reference/theme_sir.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/ggplot_sir.html" />
+    <meta name="robots" content="noindex">
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diff --git a/reference/translate.html b/reference/translate.html
index 1317e6f58..54acc39f4 100644
--- a/reference/translate.html
+++ b/reference/translate.html
@@ -1,161 +1,55 @@
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     <a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9061</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9063</small>
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-      Generate Antibiogram (Trad./Syndromic/WISCA)
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-      Get Properties of an Antiviral Drug
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-how-to"><li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
+    <li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
+    <li><a class="dropdown-item" href="../articles/resistance_predict.html"><span class="fa fa-dice"></span> Predict Antimicrobial Resistance</a></li>
+    <li><a class="dropdown-item" href="../articles/datasets.html"><span class="fa fa-database"></span> Download Data Sets for Own Use</a></li>
+    <li><a class="dropdown-item" href="../reference/AMR-options.html"><span class="fa fa-gear"></span> Set User- Or Team-specific Package Settings</a></li>
+    <li><a class="dropdown-item" href="../articles/PCA.html"><span class="fa fa-compress"></span> Conduct Principal Component Analysis for AMR</a></li>
+    <li><a class="dropdown-item" href="../articles/MDR.html"><span class="fa fa-skull-crossbones"></span> Determine Multi-Drug Resistance (MDR)</a></li>
+    <li><a class="dropdown-item" href="../articles/WHONET.html"><span class="fa fa-globe-americas"></span> Work with WHONET Data</a></li>
+    <li><a class="dropdown-item" href="../articles/EUCAST.html"><span class="fa fa-exchange-alt"></span> Apply Eucast Rules</a></li>
+    <li><a class="dropdown-item" href="../reference/mo_property.html"><span class="fa fa-bug"></span> Get Taxonomy of a Microorganism</a></li>
+    <li><a class="dropdown-item" href="../reference/ab_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antibiotic Drug</a></li>
+    <li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
+  </ul></li>
 <li class="nav-item dropdown">
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-    <a class="dropdown-item" href="../articles/other_pkg.html">
-      <span class="fa fa-layer-group"></span>
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-      AMR &amp; dplyr/tidyverse
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-    <a class="dropdown-item" href="../articles/other_pkg.html">
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-      AMR &amp; data.table
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-      AMR &amp; tidymodels
-    </a>
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-      AMR &amp; base R
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-    Authors
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+  <ul class="dropdown-menu" aria-labelledby="dropdown-with-other-pkgs"><li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; data.table</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; tidymodels</a></li>
+    <li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; base R</a></li>
+  </ul></li>
+<li class="active nav-item"><a class="nav-link" href="../reference/index.html"><span class="fa fa-book-open"></span> Manual</a></li>
+<li class="nav-item"><a class="nav-link" href="../authors.html"><span class="fa fa-users"></span> Authors</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><a class="nav-link" href="../news/index.html"><span class="fa far fa-newspaper"></span> Changelog</a></li>
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       </ul></div>
 
-    
+
   </div>
 </nav><div class="container template-reference-topic">
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Translate Strings from the AMR Package</h1>
-      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/translate.R" class="external-link"><code>R/translate.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/translate.R" class="external-link"><code>R/translate.R</code></a></small>
       <div class="d-none name"><code>translate.Rd</code></div>
     </div>
 
@@ -176,11 +70,13 @@
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
-    <dl><dt>language</dt>
+
+
+<dl><dt id="arg-language">language<a class="anchor" aria-label="anchor" href="#arg-language"></a></dt>
 <dd><p>language to choose. Use one of these supported language names or ISO-639-1 codes: English (en), Chinese (zh), Czech (cs), Danish (da), Dutch (nl), Finnish (fi), French (fr), German (de), Greek (el), Italian (it), Japanese (ja), Norwegian (no), Polish (pl), Portuguese (pt), Romanian (ro), Russian (ru), Spanish (es), Swedish (sv), Turkish (tr), or Ukrainian (uk).</p></dd>
 
 
-<dt>x</dt>
+<dt id="arg-x">x<a class="anchor" aria-label="anchor" href="#arg-x"></a></dt>
 <dd><p>text to translate</p></dd>
 
 </dl></div>
@@ -249,7 +145,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] "Amoxicillin/clavulanic acid"</span>
 </code></pre></div>
     </div>
-  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
     </nav></aside></div>
 
 
@@ -263,9 +159,9 @@
 
     </footer></div>
 
-  
 
-  
+
+
 
   </body></html>
 
diff --git a/reference/translate_AMR.html b/reference/translate_AMR.html
new file mode 100644
index 000000000..b4dcf12f0
--- /dev/null
+++ b/reference/translate_AMR.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/translate.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/translate.html">
+  </head>
+</html>
+
diff --git a/reference/trimethoprims.html b/reference/trimethoprims.html
new file mode 100644
index 000000000..07f8b21e2
--- /dev/null
+++ b/reference/trimethoprims.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html">
+  </head>
+</html>
+
diff --git a/reference/ureidopenicillins.html b/reference/ureidopenicillins.html
new file mode 100644
index 000000000..07f8b21e2
--- /dev/null
+++ b/reference/ureidopenicillins.html
@@ -0,0 +1,8 @@
+<html>
+  <head>
+    <meta http-equiv="refresh" content="0;URL=https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html" />
+    <meta name="robots" content="noindex">
+    <link rel="canonical" href="https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html">
+  </head>
+</html>
+
diff --git a/search.json b/search.json
index 4fcce6a62..21cf9d8df 100644
--- a/search.json
+++ b/search.json
@@ -1 +1 @@
-[{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"How to conduct AMR data analysis","text":"Conducting AMR data analysis unfortunately requires -depth knowledge different scientific fields, makes hard right. least, requires: Good questions (always start !) reliable data thorough understanding (clinical) epidemiology, understand clinical epidemiological relevance possible bias results thorough understanding (clinical) microbiology/infectious diseases, understand microorganisms causal infections implications pharmaceutical treatment, well understanding intrinsic acquired microbial resistance Experience data analysis microbiological tests results, understand determination limitations MIC values interpretations SIR values Availability biological taxonomy microorganisms probably normalisation factors pharmaceuticals, defined daily doses (DDD) Available (inter-)national guidelines, profound methods apply course, instantly provide knowledge experience. AMR package, aimed providing (1) tools simplify antimicrobial resistance data cleaning, transformation analysis, (2) methods easily incorporate international guidelines (3) scientifically reliable reference data, including requirements mentioned . AMR package enables standardised reproducible AMR data analysis, application evidence-based rules, determination first isolates, translation various codes microorganisms antimicrobial agents, determination (multi-drug) resistant microorganisms, calculation antimicrobial resistance, prevalence future trends.","code":""},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"preparation","dir":"Articles","previous_headings":"","what":"Preparation","title":"How to conduct AMR data analysis","text":"tutorial, create fake demonstration data work . can skip Cleaning data already data ready. start analysis, try make structure data generally look like :","code":""},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"needed-r-packages","dir":"Articles","previous_headings":"Preparation","what":"Needed R packages","title":"How to conduct AMR data analysis","text":"many uses R, need additional packages AMR data analysis. package works closely together tidyverse packages dplyr ggplot2 RStudio. tidyverse tremendously improves way conduct data science - allows natural way writing syntaxes creating beautiful plots R. also use cleaner package, can used cleaning data creating frequency tables. AMR package contains data set example_isolates_unclean, might look data users extracted laboratory systems: AMR data analysis, like microorganism column contain valid, --date taxonomy, antibiotic columns cleaned SIR values well.","code":"library(dplyr) library(ggplot2) library(AMR)  # (if not yet installed, install with:) # install.packages(c(\"dplyr\", \"ggplot2\", \"AMR\")) example_isolates_unclean #> # A tibble: 3,000 × 8 #>    patient_id hospital date       bacteria      AMX   AMC   CIP   GEN   #>    <chr>      <chr>    <date>     <chr>         <chr> <chr> <chr> <chr> #>  1 J3         A        2012-11-21 E. coli       R     I     S     S     #>  2 R7         A        2018-04-03 K. pneumoniae R     I     S     S     #>  3 P3         A        2014-09-19 E. coli       R     S     S     S     #>  4 P10        A        2015-12-10 E. coli       S     I     S     S     #>  5 B7         A        2015-03-02 E. coli       S     S     S     S     #>  6 W3         A        2018-03-31 S. aureus     R     S     R     S     #>  7 J8         A        2016-06-14 E. coli       R     S     S     S     #>  8 M3         A        2015-10-25 E. coli       R     S     S     S     #>  9 J3         A        2019-06-19 E. coli       S     S     S     S     #> 10 G6         A        2015-04-27 S. aureus     S     S     S     S     #> # ℹ 2,990 more rows # we will use 'our_data' as the data set name for this tutorial our_data <- example_isolates_unclean"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"taxonomy-of-microorganisms","dir":"Articles","previous_headings":"Preparation","what":"Taxonomy of microorganisms","title":"How to conduct AMR data analysis","text":".mo(), users can transform arbitrary microorganism names codes current taxonomy. AMR package contains --date taxonomic data. specific, currently included data retrieved 11 Dec 2022. codes AMR packages come .mo() short, still human readable. importantly, .mo() supports kinds input: first character codes denote taxonomic kingdom, Bacteria (B), Fungi (F), Protozoa (P). AMR package also contain functions directly retrieve taxonomic properties, name, genus, species, family, order, even Gram-stain. start mo_ use .mo() internally, still arbitrary user input can used: Now can thus clean data: Apparently, uncertainty translation taxonomic codes. Let’s check : ’s good.","code":"as.mo(\"Klebsiella pneumoniae\") #> Class 'mo' #> [1] B_KLBSL_PNMN as.mo(\"K. pneumoniae\") #> Class 'mo' #> [1] B_KLBSL_PNMN as.mo(\"KLEPNE\") #> Class 'mo' #> [1] B_KLBSL_PNMN as.mo(\"KLPN\") #> Class 'mo' #> [1] B_KLBSL_PNMN mo_family(\"K. pneumoniae\") #> [1] \"Enterobacteriaceae\" mo_genus(\"K. pneumoniae\") #> [1] \"Klebsiella\" mo_species(\"K. pneumoniae\") #> [1] \"pneumoniae\" mo_gramstain(\"Klebsiella pneumoniae\") #> [1] \"Gram-negative\" mo_ref(\"K. pneumoniae\") #> [1] \"Trevisan, 1887\" mo_snomed(\"K. pneumoniae\") #> [[1]] #> [1] \"1098101000112102\" \"446870005\"        \"1098201000112108\" \"409801009\"        #> [5] \"56415008\"         \"714315002\"        \"713926009\" our_data$bacteria <- as.mo(our_data$bacteria, info = TRUE) #> ℹ Microorganism translation was uncertain for four microorganisms. Run #>   mo_uncertainties() to review these uncertainties, or use #>   add_custom_microorganisms() to add custom entries. mo_uncertainties() #> Matching scores are based on the resemblance between the input and the full #> taxonomic name, and the pathogenicity in humans. See ?mo_matching_score. #>  #> -------------------------------------------------------------------------------- #> \"E. coli\" -> Escherichia coli (B_ESCHR_COLI, 0.688) #> Also matched: Enterobacter cowanii (0.600), Eubacterium combesii #>               (0.600), Eggerthia catenaformis (0.591), Eubacterium callanderi #>               (0.591), Enterocloster citroniae (0.587), Eubacterium cylindroides #>               (0.583), Enterococcus casseliflavus (0.577), Enterobacter cloacae #>               cloacae (0.571), Enterobacter cloacae complex (0.571), and Ehrlichia #>               canis (0.567) #> -------------------------------------------------------------------------------- #> \"K. pneumoniae\" -> Klebsiella pneumoniae (B_KLBSL_PNMN, 0.786) #> Also matched: Klebsiella pneumoniae ozaenae (0.707), Klebsiella #>               pneumoniae pneumoniae (0.688), Klebsiella pneumoniae rhinoscleromatis #>               (0.658), Klebsiella pasteurii (0.500), Klebsiella planticola (0.500), #>               Kingella potus (0.400), Kosakonia pseudosacchari (0.361), Kaistella #>               palustris (0.333), Kocuria palustris (0.333), and Kocuria pelophila #>               (0.333) #> -------------------------------------------------------------------------------- #> \"S. aureus\" -> Staphylococcus aureus (B_STPHY_AURS, 0.690) #> Also matched: Staphylococcus aureus aureus (0.643), Staphylococcus #>               argenteus (0.625), Staphylococcus aureus anaerobius (0.625), Salmonella #>               Aurelianis (0.595), Salmonella Aarhus (0.588), Salmonella Amounderness #>               (0.587), Selenomonas artemidis (0.571), Salmonella choleraesuis #>               arizonae (0.562), Streptococcus anginosus anginosus (0.561), and #>               Salmonella Abaetetuba (0.548) #> -------------------------------------------------------------------------------- #> \"S. pneumoniae\" -> Streptococcus pneumoniae (B_STRPT_PNMN, 0.750) #> Also matched: Streptococcus pseudopneumoniae (0.700), Serratia #>               proteamaculans quinovora (0.545), Streptococcus pseudoporcinus (0.536), #>               Staphylococcus pseudintermedius (0.532), Serratia proteamaculans #>               proteamaculans (0.526), Salmonella Portanigra (0.524), Sphingomonas #>               paucimobilis (0.520), Streptococcus pluranimalium (0.519), #>               Streptococcus constellatus pharyngis (0.514), and Salmonella Pakistan #>               (0.500) #>  #> Only the first 10 other matches of each record are shown. Run #> print(mo_uncertainties(), n = ...) to view more entries, or save #> mo_uncertainties() to an object."},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"antibiotic-results","dir":"Articles","previous_headings":"Preparation","what":"Antibiotic results","title":"How to conduct AMR data analysis","text":"column antibiotic test results must also cleaned. AMR package comes three new data types work test results: mic minimal inhibitory concentrations (MIC), disk disk diffusion diameters, sir SIR data interpreted already. package can also determine SIR values based MIC disk diffusion values, read .sir() page. now, just clean SIR columns data using dplyr: basically cleaning, time start data inclusion.","code":"# method 1, be explicit about the columns: our_data <- our_data %>%   mutate_at(vars(AMX:GEN), as.sir)  # method 2, let the AMR package determine the eligible columns our_data <- our_data %>%   mutate_if(is_sir_eligible, as.sir)  # result: our_data #> # A tibble: 3,000 × 8 #>    patient_id hospital date       bacteria     AMX   AMC   CIP   GEN   #>    <chr>      <chr>    <date>     <mo>         <sir> <sir> <sir> <sir> #>  1 J3         A        2012-11-21 B_ESCHR_COLI R     I     S     S     #>  2 R7         A        2018-04-03 B_KLBSL_PNMN R     I     S     S     #>  3 P3         A        2014-09-19 B_ESCHR_COLI R     S     S     S     #>  4 P10        A        2015-12-10 B_ESCHR_COLI S     I     S     S     #>  5 B7         A        2015-03-02 B_ESCHR_COLI S     S     S     S     #>  6 W3         A        2018-03-31 B_STPHY_AURS R     S     R     S     #>  7 J8         A        2016-06-14 B_ESCHR_COLI R     S     S     S     #>  8 M3         A        2015-10-25 B_ESCHR_COLI R     S     S     S     #>  9 J3         A        2019-06-19 B_ESCHR_COLI S     S     S     S     #> 10 G6         A        2015-04-27 B_STPHY_AURS S     S     S     S     #> # ℹ 2,990 more rows"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"first-isolates","dir":"Articles","previous_headings":"Preparation","what":"First isolates","title":"How to conduct AMR data analysis","text":"need know isolates can actually use analysis without repetition bias. conduct analysis antimicrobial resistance, must include first isolate every patient per episode (Hindler et al., Clin Infect Dis. 2007). , easily get overestimate underestimate resistance antibiotic. Imagine patient admitted MRSA found 5 different blood cultures following weeks (yes, countries like Netherlands blood drawing policies). resistance percentage oxacillin isolates overestimated, included MRSA . clearly selection bias. Clinical Laboratory Standards Institute (CLSI) appoints follows: (…) preparing cumulative antibiogram guide clinical decisions empirical antimicrobial therapy initial infections, first isolate given species per patient, per analysis period (eg, one year) included, irrespective body site, antimicrobial susceptibility profile, phenotypical characteristics (eg, biotype). first isolate easily identified, cumulative antimicrobial susceptibility test data prepared using first isolate generally comparable cumulative antimicrobial susceptibility test data calculated methods, providing duplicate isolates excluded. M39-A4 Analysis Presentation Cumulative Antimicrobial Susceptibility Test Data, 4th Edition. CLSI, 2014. Chapter 6.4 AMR package includes methodology first_isolate() function able apply four different methods defined Hindler et al. 2007: phenotype-based, episode-based, patient-based, isolate-based. right method depends goals analysis, default phenotype-based method case method properly correct duplicate isolates. Read methods first_isolate() page. outcome function can easily added data: 90% suitable resistance analysis! can now filter filter() function, also dplyr package: future use, two syntaxes can shortened: end 2 712 isolates analysis. Now data looks like: Time analysis.","code":"our_data <- our_data %>%   mutate(first = first_isolate(info = TRUE)) #> ℹ Determining first isolates using an episode length of 365 days #> ℹ Using column 'bacteria' as input for col_mo. #> ℹ Using column 'date' as input for col_date. #> ℹ Using column 'patient_id' as input for col_patient_id. #> ℹ Basing inclusion on all antimicrobial results, using a points threshold #>   of 2 #> => Found 2,712 'phenotype-based' first isolates (90.4% of total where a #>    microbial ID was available) our_data_1st <- our_data %>%   filter(first == TRUE) our_data_1st <- our_data %>%   filter_first_isolate() our_data_1st #> # A tibble: 2,712 × 9 #>    patient_id hospital date       bacteria     AMX   AMC   CIP   GEN   first #>    <chr>      <chr>    <date>     <mo>         <sir> <sir> <sir> <sir> <lgl> #>  1 J3         A        2012-11-21 B_ESCHR_COLI R     I     S     S     TRUE  #>  2 R7         A        2018-04-03 B_KLBSL_PNMN R     I     S     S     TRUE  #>  3 P10        A        2015-12-10 B_ESCHR_COLI S     I     S     S     TRUE  #>  4 B7         A        2015-03-02 B_ESCHR_COLI S     S     S     S     TRUE  #>  5 W3         A        2018-03-31 B_STPHY_AURS R     S     R     S     TRUE  #>  6 M3         A        2015-10-25 B_ESCHR_COLI R     S     S     S     TRUE  #>  7 J3         A        2019-06-19 B_ESCHR_COLI S     S     S     S     TRUE  #>  8 G6         A        2015-04-27 B_STPHY_AURS S     S     S     S     TRUE  #>  9 P4         A        2011-06-21 B_ESCHR_COLI S     S     S     S     TRUE  #> 10 Z1         A        2014-09-05 B_ESCHR_COLI S     S     S     S     TRUE  #> # ℹ 2,702 more rows"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"analysing-the-data","dir":"Articles","previous_headings":"","what":"Analysing the data","title":"How to conduct AMR data analysis","text":"base R summary() function gives good first impression, comes support new mo sir classes now data set:","code":"summary(our_data_1st) #>   patient_id          hospital              date            #>  Length:2712        Length:2712        Min.   :2011-01-01   #>  Class :character   Class :character   1st Qu.:2013-05-03   #>  Mode  :character   Mode  :character   Median :2015-06-16   #>                                        Mean   :2015-06-21   #>                                        3rd Qu.:2017-08-24   #>                                        Max.   :2019-12-27   #>    bacteria               AMX                    AMC                 #>  Class :mo             Class:sir              Class:sir              #>  <NA>  :0              %S   :41.0% (n=1112)   %S   :52.0% (n=1409)   #>  Unique:4              %SDD : 0.0% (n=0)      %SDD : 0.0% (n=0)      #>  #1    :B_ESCHR_COLI   %I   :16.1% (n=437)    %I   :12.0% (n=325)    #>  #2    :B_STPHY_AURS   %R   :42.9% (n=1163)   %R   :36.1% (n=978)    #>  #3    :B_STRPT_PNMN   %NI  : 0.0% (n=0)      %NI  : 0.0% (n=0)      #>     CIP                    GEN                  first         #>  Class:sir              Class:sir              Mode:logical   #>  %S   :51.5% (n=1396)   %S   :59.6% (n=1616)   TRUE:2712      #>  %SDD : 0.0% (n=0)      %SDD : 0.0% (n=0)                     #>  %I   : 6.6% (n=178)    %I   : 3.1% (n=85)                    #>  %R   :42.0% (n=1138)   %R   :37.3% (n=1011)                  #>  %NI  : 0.0% (n=0)      %NI  : 0.0% (n=0) glimpse(our_data_1st) #> Rows: 2,712 #> Columns: 9 #> $ patient_id <chr> \"J3\", \"R7\", \"P10\", \"B7\", \"W3\", \"M3\", \"J3\", \"G6\", \"P4\", \"Z1\"… #> $ hospital   <chr> \"A\", \"A\", \"A\", \"A\", \"A\", \"A\", \"A\", \"A\", \"A\", \"A\", \"A\", \"A\",… #> $ date       <date> 2012-11-21, 2018-04-03, 2015-12-10, 2015-03-02, 2018-03-31… #> $ bacteria   <mo> \"B_ESCHR_COLI\", \"B_KLBSL_PNMN\", \"B_ESCHR_COLI\", \"B_ESCHR_COL… #> $ AMX        <sir> R, R, S, S, R, R, S, S, S, S, R, S, S, S, R, R, R, R, S, R,… #> $ AMC        <sir> I, I, I, S, S, S, S, S, S, S, S, S, I, S, S, S, S, R, S, S,… #> $ CIP        <sir> S, S, S, S, R, S, S, S, S, S, S, S, S, S, S, S, S, S, S, S,… #> $ GEN        <sir> S, S, S, S, S, S, S, S, S, S, R, S, S, S, S, S, S, S, S, S,… #> $ first      <lgl> TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,… # number of unique values per column: sapply(our_data_1st, n_distinct) #> patient_id   hospital       date   bacteria        AMX        AMC        CIP  #>        260          3       1852          4          3          3          3  #>        GEN      first  #>          3          1"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"availability-of-species","dir":"Articles","previous_headings":"Analysing the data","what":"Availability of species","title":"How to conduct AMR data analysis","text":"just get idea species distributed, create frequency table count() based name microorganisms:","code":"our_data %>%   count(mo_name(bacteria), sort = TRUE) #> # A tibble: 4 × 2 #>   `mo_name(bacteria)`          n #>   <chr>                    <int> #> 1 Escherichia coli          1518 #> 2 Staphylococcus aureus      730 #> 3 Streptococcus pneumoniae   426 #> 4 Klebsiella pneumoniae      326 our_data_1st %>%   count(mo_name(bacteria), sort = TRUE) #> # A tibble: 4 × 2 #>   `mo_name(bacteria)`          n #>   <chr>                    <int> #> 1 Escherichia coli          1319 #> 2 Staphylococcus aureus      676 #> 3 Streptococcus pneumoniae   400 #> 4 Klebsiella pneumoniae      317"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"select-and-filter-with-antibiotic-selectors","dir":"Articles","previous_headings":"Analysing the data","what":"Select and filter with antibiotic selectors","title":"How to conduct AMR data analysis","text":"Using -called antibiotic class selectors, can select filter columns based antibiotic class antibiotic results :","code":"our_data_1st %>%   select(date, aminoglycosides()) #> ℹ For aminoglycosides() using column 'GEN' (gentamicin) #> # A tibble: 2,712 × 2 #>    date       GEN   #>    <date>     <sir> #>  1 2012-11-21 S     #>  2 2018-04-03 S     #>  3 2015-12-10 S     #>  4 2015-03-02 S     #>  5 2018-03-31 S     #>  6 2015-10-25 S     #>  7 2019-06-19 S     #>  8 2015-04-27 S     #>  9 2011-06-21 S     #> 10 2014-09-05 S     #> # ℹ 2,702 more rows our_data_1st %>%   select(bacteria, betalactams()) #> ℹ For betalactams() using columns 'AMX' (amoxicillin) and 'AMC' #>   (amoxicillin/clavulanic acid) #> # A tibble: 2,712 × 3 #>    bacteria     AMX   AMC   #>    <mo>         <sir> <sir> #>  1 B_ESCHR_COLI R     I     #>  2 B_KLBSL_PNMN R     I     #>  3 B_ESCHR_COLI S     I     #>  4 B_ESCHR_COLI S     S     #>  5 B_STPHY_AURS R     S     #>  6 B_ESCHR_COLI R     S     #>  7 B_ESCHR_COLI S     S     #>  8 B_STPHY_AURS S     S     #>  9 B_ESCHR_COLI S     S     #> 10 B_ESCHR_COLI S     S     #> # ℹ 2,702 more rows our_data_1st %>%   select(bacteria, where(is.sir)) #> # A tibble: 2,712 × 5 #>    bacteria     AMX   AMC   CIP   GEN   #>    <mo>         <sir> <sir> <sir> <sir> #>  1 B_ESCHR_COLI R     I     S     S     #>  2 B_KLBSL_PNMN R     I     S     S     #>  3 B_ESCHR_COLI S     I     S     S     #>  4 B_ESCHR_COLI S     S     S     S     #>  5 B_STPHY_AURS R     S     R     S     #>  6 B_ESCHR_COLI R     S     S     S     #>  7 B_ESCHR_COLI S     S     S     S     #>  8 B_STPHY_AURS S     S     S     S     #>  9 B_ESCHR_COLI S     S     S     S     #> 10 B_ESCHR_COLI S     S     S     S     #> # ℹ 2,702 more rows # filtering using AB selectors is also possible: our_data_1st %>%   filter(any(aminoglycosides() == \"R\")) #> ℹ For aminoglycosides() using column 'GEN' (gentamicin) #> # A tibble: 1,011 × 9 #>    patient_id hospital date       bacteria     AMX   AMC   CIP   GEN   first #>    <chr>      <chr>    <date>     <mo>         <sir> <sir> <sir> <sir> <lgl> #>  1 J5         A        2017-12-25 B_STRPT_PNMN R     S     S     R     TRUE  #>  2 X1         A        2017-07-04 B_STPHY_AURS R     S     S     R     TRUE  #>  3 B3         A        2016-07-24 B_ESCHR_COLI S     S     S     R     TRUE  #>  4 V7         A        2012-04-03 B_ESCHR_COLI S     S     S     R     TRUE  #>  5 C9         A        2017-03-23 B_ESCHR_COLI S     S     S     R     TRUE  #>  6 R1         A        2018-06-10 B_STPHY_AURS S     S     S     R     TRUE  #>  7 S2         A        2013-07-19 B_STRPT_PNMN S     S     S     R     TRUE  #>  8 P5         A        2019-03-09 B_STPHY_AURS S     S     S     R     TRUE  #>  9 Q8         A        2019-08-10 B_STPHY_AURS S     S     S     R     TRUE  #> 10 K5         A        2013-03-15 B_STRPT_PNMN S     S     S     R     TRUE  #> # ℹ 1,001 more rows our_data_1st %>%   filter(all(betalactams() == \"R\")) #> ℹ For betalactams() using columns 'AMX' (amoxicillin) and 'AMC' #>   (amoxicillin/clavulanic acid) #> # A tibble: 483 × 9 #>    patient_id hospital date       bacteria     AMX   AMC   CIP   GEN   first #>    <chr>      <chr>    <date>     <mo>         <sir> <sir> <sir> <sir> <lgl> #>  1 M7         A        2013-07-22 B_STRPT_PNMN R     R     S     S     TRUE  #>  2 R10        A        2013-12-20 B_STPHY_AURS R     R     S     S     TRUE  #>  3 R7         A        2015-10-25 B_STPHY_AURS R     R     S     S     TRUE  #>  4 R8         A        2019-10-25 B_STPHY_AURS R     R     S     S     TRUE  #>  5 B6         A        2016-11-20 B_ESCHR_COLI R     R     R     R     TRUE  #>  6 I7         A        2015-08-19 B_ESCHR_COLI R     R     S     S     TRUE  #>  7 N3         A        2014-12-29 B_STRPT_PNMN R     R     R     S     TRUE  #>  8 Q2         A        2019-09-22 B_ESCHR_COLI R     R     S     S     TRUE  #>  9 X7         A        2011-03-20 B_ESCHR_COLI R     R     S     R     TRUE  #> 10 V1         A        2018-08-07 B_STPHY_AURS R     R     S     S     TRUE  #> # ℹ 473 more rows # even works in base R (since R 3.0): our_data_1st[all(betalactams() == \"R\"), ] #> ℹ For betalactams() using columns 'AMX' (amoxicillin) and 'AMC' #>   (amoxicillin/clavulanic acid) #> # A tibble: 483 × 9 #>    patient_id hospital date       bacteria     AMX   AMC   CIP   GEN   first #>    <chr>      <chr>    <date>     <mo>         <sir> <sir> <sir> <sir> <lgl> #>  1 M7         A        2013-07-22 B_STRPT_PNMN R     R     S     S     TRUE  #>  2 R10        A        2013-12-20 B_STPHY_AURS R     R     S     S     TRUE  #>  3 R7         A        2015-10-25 B_STPHY_AURS R     R     S     S     TRUE  #>  4 R8         A        2019-10-25 B_STPHY_AURS R     R     S     S     TRUE  #>  5 B6         A        2016-11-20 B_ESCHR_COLI R     R     R     R     TRUE  #>  6 I7         A        2015-08-19 B_ESCHR_COLI R     R     S     S     TRUE  #>  7 N3         A        2014-12-29 B_STRPT_PNMN R     R     R     S     TRUE  #>  8 Q2         A        2019-09-22 B_ESCHR_COLI R     R     S     S     TRUE  #>  9 X7         A        2011-03-20 B_ESCHR_COLI R     R     S     R     TRUE  #> 10 V1         A        2018-08-07 B_STPHY_AURS R     R     S     S     TRUE  #> # ℹ 473 more rows"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"generate-antibiograms","dir":"Articles","previous_headings":"Analysing the data","what":"Generate antibiograms","title":"How to conduct AMR data analysis","text":"Since AMR v2.0 (March 2023), easy create different types antibiograms, support 20 different languages. four antibiogram types, proposed Klinker et al. (2021, DOI 10.1177/20499361211011373), supported new antibiogram() function: Traditional Antibiogram (TA) e.g, susceptibility Pseudomonas aeruginosa piperacillin/tazobactam (TZP) Combination Antibiogram (CA) e.g, sdditional susceptibility Pseudomonas aeruginosa TZP + tobramycin versus TZP alone Syndromic Antibiogram (SA) e.g, susceptibility Pseudomonas aeruginosa TZP among respiratory specimens (obtained among ICU patients ) Weighted-Incidence Syndromic Combination Antibiogram (WISCA) e.g, susceptibility Pseudomonas aeruginosa TZP among respiratory specimens (obtained among ICU patients ) male patients age >=65 years heart failure section, show use antibiogram() function create antibiogram types. starters, included example_isolates data set looks like:","code":"example_isolates #> # A tibble: 2,000 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-03 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  3 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  4 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  5 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  6 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  7 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  8 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  9 2002-01-16 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #> 10 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R     NA    S     NA    #> # ℹ 1,990 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, …"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"traditional-antibiogram","dir":"Articles","previous_headings":"Analysing the data > Generate antibiograms","what":"Traditional Antibiogram","title":"How to conduct AMR data analysis","text":"create traditional antibiogram, simply state antibiotics used. antibiotics argument antibiogram() function supports (combination) previously mentioned antibiotic class selectors: Notice antibiogram() function automatically prints right format using Quarto R Markdown (page), even applies italics taxonomic names (using italicise_taxonomy() internally). also uses language OS either English, Chinese, Czech, Danish, Dutch, Finnish, French, German, Greek, Italian, Japanese, Norwegian, Polish, Portuguese, Romanian, Russian, Spanish, Swedish, Turkish, Ukrainian. next example, force language Spanish using language argument:","code":"antibiogram(example_isolates,             antibiotics = c(aminoglycosides(), carbapenems())) #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) antibiogram(example_isolates,             mo_transform = \"gramstain\",             antibiotics = aminoglycosides(),             ab_transform = \"name\",             language = \"es\") #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin)"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"combined-antibiogram","dir":"Articles","previous_headings":"Analysing the data > Generate antibiograms","what":"Combined Antibiogram","title":"How to conduct AMR data analysis","text":"create combined antibiogram, use antibiotic codes names plus + character like :","code":"antibiogram(example_isolates,             antibiotics = c(\"TZP\", \"TZP+TOB\", \"TZP+GEN\"))"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"syndromic-antibiogram","dir":"Articles","previous_headings":"Analysing the data > Generate antibiograms","what":"Syndromic Antibiogram","title":"How to conduct AMR data analysis","text":"create syndromic antibiogram, syndromic_group argument must used. can column data, e.g. ifelse() calculations based certain columns:","code":"antibiogram(example_isolates,             antibiotics = c(aminoglycosides(), carbapenems()),             syndromic_group = \"ward\") #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem)"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"weighted-incidence-syndromic-combination-antibiogram-wisca","dir":"Articles","previous_headings":"Analysing the data > Generate antibiograms","what":"Weighted-Incidence Syndromic Combination Antibiogram (WISCA)","title":"How to conduct AMR data analysis","text":"create WISCA, must state combination therapy antibiotics argument (similar Combination Antibiogram), define syndromic group syndromic_group argument (similar Syndromic Antibiogram) cases predefined based clinical demographic characteristics (e.g., endocarditis 75+ females). next example simplification without clinical characteristics, just gives idea WISCA can created:","code":"wisca <- antibiogram(example_isolates,                      antibiotics = c(\"AMC\", \"AMC+CIP\", \"TZP\", \"TZP+TOB\"),                      mo_transform = \"gramstain\",                      minimum = 10, # this should be >= 30, but now just as example                      syndromic_group = ifelse(example_isolates$age >= 65 &                                                 example_isolates$gender == \"M\",                                               \"WISCA Group 1\", \"WISCA Group 2\")) wisca"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"plotting-antibiograms","dir":"Articles","previous_headings":"Analysing the data > Generate antibiograms","what":"Plotting antibiograms","title":"How to conduct AMR data analysis","text":"Antibiograms can plotted using autoplot() ggplot2 packages, since AMR package provides extension function:  calculate antimicrobial resistance sensible way, also correcting results, use resistance() susceptibility() functions.","code":"autoplot(wisca)"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"resistance-percentages","dir":"Articles","previous_headings":"Analysing the data","what":"Resistance percentages","title":"How to conduct AMR data analysis","text":"functions resistance() susceptibility() can used calculate antimicrobial resistance susceptibility. specific analyses, functions proportion_S(), proportion_SI(), proportion_I(), proportion_IR() proportion_R() can used determine proportion specific antimicrobial outcome. functions contain minimum argument, denoting minimum required number test results returning value. functions otherwise return NA. default minimum = 30, following CLSI M39-A4 guideline applying microbial epidemiology. per EUCAST guideline 2019, calculate resistance proportion R (proportion_R(), equal resistance()) susceptibility proportion S (proportion_SI(), equal susceptibility()). functions can used : can used conjunction group_by() summarise(), dplyr package: Author: Dr. Matthijs Berends, 26th Feb 2023","code":"our_data_1st %>% resistance(AMX) #> [1] 0.4288348 our_data_1st %>%   group_by(hospital) %>%   summarise(amoxicillin = resistance(AMX)) #> # A tibble: 3 × 2 #>   hospital amoxicillin #>   <chr>          <dbl> #> 1 A              0.342 #> 2 B              0.564 #> 3 C              0.372"},{"path":"https://msberends.github.io/AMR/articles/EUCAST.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"How to apply EUCAST rules","text":"EUCAST rules? European Committee Antimicrobial Susceptibility Testing (EUCAST) states website: EUCAST expert rules tabulated collection expert knowledge intrinsic resistances, exceptional resistance phenotypes interpretive rules may applied antimicrobial susceptibility testing order reduce errors make appropriate recommendations reporting particular resistances. Europe, lot medical microbiological laboratories already apply rules (Brown et al., 2015). package features latest insights intrinsic resistance unusual phenotypes (v3.1, 2016). Moreover, eucast_rules() function use purpose can also apply additional rules, like forcing ampicillin = R isolates amoxicillin/clavulanic acid = R.","code":""},{"path":"https://msberends.github.io/AMR/articles/EUCAST.html","id":"examples","dir":"Articles","previous_headings":"","what":"Examples","title":"How to apply EUCAST rules","text":"rules can used discard impossible bug-drug combinations data. example, Klebsiella produces beta-lactamase prevents ampicillin (amoxicillin) working . words, practically every strain Klebsiella resistant ampicillin. Sometimes, laboratory data can still contain strains ampicillin susceptible ampicillin. antibiogram available identification available, antibiogram re-interpreted based identification (namely, Klebsiella). EUCAST expert rules solve , can applied using eucast_rules(): convenient function mo_is_intrinsic_resistant() uses guideline, allows check one specific microorganisms antibiotics: EUCAST rules can used correction, can also used filling known resistance susceptibility based results antimicrobials drugs. process called interpretive reading, basically form imputation, part eucast_rules() function well:","code":"oops <- data.frame(   mo = c(     \"Klebsiella\",     \"Escherichia\"   ),   ampicillin = \"S\" ) oops #>            mo ampicillin #> 1  Klebsiella          S #> 2 Escherichia          S eucast_rules(oops, info = FALSE) #>            mo ampicillin #> 1  Klebsiella          R #> 2 Escherichia          S mo_is_intrinsic_resistant(   c(\"Klebsiella\", \"Escherichia\"),   \"ampicillin\" ) #> [1]  TRUE FALSE mo_is_intrinsic_resistant(   \"Klebsiella\",   c(\"ampicillin\", \"kanamycin\") ) #> [1]  TRUE FALSE data <- data.frame(   mo = c(     \"Staphylococcus aureus\",     \"Enterococcus faecalis\",     \"Escherichia coli\",     \"Klebsiella pneumoniae\",     \"Pseudomonas aeruginosa\"   ),   VAN = \"-\", # Vancomycin   AMX = \"-\", # Amoxicillin   COL = \"-\", # Colistin   CAZ = \"-\", # Ceftazidime   CXM = \"-\", # Cefuroxime   PEN = \"S\", # Benzylenicillin   FOX = \"S\", # Cefoxitin   stringsAsFactors = FALSE ) data eucast_rules(data)"},{"path":"https://msberends.github.io/AMR/articles/MDR.html","id":"type-of-input","dir":"Articles","previous_headings":"","what":"Type of input","title":"How to determine multi-drug resistance (MDR)","text":"mdro() function takes data set input, regular data.frame. tries automatically determine right columns info isolates, name species columns results antimicrobial agents. See help page info set right settings data command ?mdro. WHONET data (data), settings automatically set correctly.","code":""},{"path":"https://msberends.github.io/AMR/articles/MDR.html","id":"guidelines","dir":"Articles","previous_headings":"","what":"Guidelines","title":"How to determine multi-drug resistance (MDR)","text":"mdro() function support multiple guidelines. can select guideline guideline parameter. Currently supported guidelines (case-insensitive): guideline = \"CMI2012\" (default) Magiorakos AP, Srinivasan et al. “Multidrug-resistant, extensively drug-resistant pandrug-resistant bacteria: international expert proposal interim standard definitions acquired resistance.” Clinical Microbiology Infection (2012) (link) guideline = \"EUCAST3.2\" (simply guideline = \"EUCAST\") European international guideline - EUCAST Expert Rules Version 3.2 “Intrinsic Resistance Unusual Phenotypes” (link) guideline = \"EUCAST3.1\" European international guideline - EUCAST Expert Rules Version 3.1 “Intrinsic Resistance Exceptional Phenotypes Tables” (link) guideline = \"TB\" international guideline multi-drug resistant tuberculosis - World Health Organization “Companion handbook guidelines programmatic management drug-resistant tuberculosis” (link) guideline = \"MRGN\" German national guideline - Mueller et al. (2015) Antimicrobial Resistance Infection Control 4:7. DOI: 10.1186/s13756-015-0047-6 guideline = \"BRMO\" Dutch national guideline - Rijksinstituut voor Volksgezondheid en Milieu “WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen) (ZKH)” (link) Please suggest (country-specific) guidelines letting us know: https://github.com/msberends/AMR/issues/new.","code":""},{"path":"https://msberends.github.io/AMR/articles/MDR.html","id":"custom-guidelines","dir":"Articles","previous_headings":"Guidelines","what":"Custom Guidelines","title":"How to determine multi-drug resistance (MDR)","text":"can also use custom guideline. Custom guidelines can set custom_mdro_guideline() function. great importance custom rules determine MDROs hospital, e.g., rules dependent ward, state contact isolation variables data. familiar case_when() dplyr package, recognise input method set rules. Rules must set using R considers ‘formula notation’: row/isolate matches first rule, value first ~ (case ‘Elderly Type ’) set MDRO value. Otherwise, second rule tried . maximum number rules unlimited. can print rules set console overview. Colours help reading console supports colours. outcome function can used guideline argument mdro() function: rules set (custom object case) exported shared file location using saveRDS() collaborate multiple users. custom rules set imported using readRDS().","code":"custom <- custom_mdro_guideline(   CIP == \"R\" & age > 60 ~ \"Elderly Type A\",   ERY == \"R\" & age > 60 ~ \"Elderly Type B\" ) custom #> A set of custom MDRO rules: #>   1. If CIP is \"R\" and age is higher than 60 then: Elderly Type A #>   2. If ERY is \"R\" and age is higher than 60 then: Elderly Type B #>   3. Otherwise: Negative #>  #> Unmatched rows will return NA. #> Results will be of class 'factor', with ordered levels: Negative < Elderly Type A < Elderly Type B x <- mdro(example_isolates, guideline = custom) table(x) #> x #>       Negative Elderly Type A Elderly Type B  #>           1070            198            732"},{"path":"https://msberends.github.io/AMR/articles/MDR.html","id":"examples","dir":"Articles","previous_headings":"","what":"Examples","title":"How to determine multi-drug resistance (MDR)","text":"mdro() function always returns ordered factor predefined guidelines. example, output default guideline Magiorakos et al. returns factor levels ‘Negative’, ‘MDR’, ‘XDR’ ‘PDR’ order. next example uses example_isolates data set. data set included package contains full antibiograms 2,000 microbial isolates. reflects reality can used practise AMR data analysis. test MDR/XDR/PDR guideline data set, get: Frequency table Class: factor > ordered (numeric) Length: 2,000 Levels: 4: Negative < Multi-drug-resistant (MDR) < Extensively drug-resistant … Available: 1,729 (86.45%, NA: 271 = 13.55%) Unique: 2 another example, create data set determine multi-drug resistant TB: column names automatically verified valid drug names codes, worked exactly way: data set now looks like : can now add interpretation MDR-TB data set. can use: shortcut mdr_tb(): Create frequency table results: Frequency table Class: factor > ordered (numeric) Length: 5,000 Levels: 5: Negative < Mono-resistant < Poly-resistant < Multi-drug-resistant <… Available: 5,000 (100%, NA: 0 = 0%) Unique: 5","code":"library(dplyr) # to support pipes: %>% library(cleaner) # to create frequency tables example_isolates %>%   mdro() %>%   freq() # show frequency table of the result #> Warning: in mdro(): NA introduced for isolates where the available percentage of #> antimicrobial classes was below 50% (set with pct_required_classes) # random_sir() is a helper function to generate # a random vector with values S, I and R my_TB_data <- data.frame(   rifampicin = random_sir(5000),   isoniazid = random_sir(5000),   gatifloxacin = random_sir(5000),   ethambutol = random_sir(5000),   pyrazinamide = random_sir(5000),   moxifloxacin = random_sir(5000),   kanamycin = random_sir(5000) ) my_TB_data <- data.frame(   RIF = random_sir(5000),   INH = random_sir(5000),   GAT = random_sir(5000),   ETH = random_sir(5000),   PZA = random_sir(5000),   MFX = random_sir(5000),   KAN = random_sir(5000) ) head(my_TB_data) #>   rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin #> 1          I         R            S          S            S            S #> 2          S         S            I          R            R            S #> 3          R         I            I          I            R            I #> 4          I         S            S          S            S            S #> 5          I         I            I          S            I            S #> 6          R         S            R          S            I            I #>   kanamycin #> 1         R #> 2         I #> 3         S #> 4         I #> 5         I #> 6         I mdro(my_TB_data, guideline = \"TB\") my_TB_data$mdr <- mdr_tb(my_TB_data) #> ℹ No column found as input for col_mo, assuming all rows contain #>   Mycobacterium tuberculosis. freq(my_TB_data$mdr)"},{"path":[]},{"path":"https://msberends.github.io/AMR/articles/PCA.html","id":"transforming","dir":"Articles","previous_headings":"","what":"Transforming","title":"How to conduct principal component analysis (PCA) for AMR","text":"PCA, need transform AMR data first. example_isolates data set package looks like: Now transform data set resistance percentages per taxonomic order genus:","code":"library(AMR) library(dplyr) glimpse(example_isolates) #> Rows: 2,000 #> Columns: 46 #> $ date    <date> 2002-01-02, 2002-01-03, 2002-01-07, 2002-01-07, 2002-01-13, 2… #> $ patient <chr> \"A77334\", \"A77334\", \"067927\", \"067927\", \"067927\", \"067927\", \"4… #> $ age     <dbl> 65, 65, 45, 45, 45, 45, 78, 78, 45, 79, 67, 67, 71, 71, 75, 50… #> $ gender  <chr> \"F\", \"F\", \"F\", \"F\", \"F\", \"F\", \"M\", \"M\", \"F\", \"F\", \"M\", \"M\", \"M… #> $ ward    <chr> \"Clinical\", \"Clinical\", \"ICU\", \"ICU\", \"ICU\", \"ICU\", \"Clinical\"… #> $ mo      <mo> \"B_ESCHR_COLI\", \"B_ESCHR_COLI\", \"B_STPHY_EPDR\", \"B_STPHY_EPDR\",… #> $ PEN     <sir> R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, S,… #> $ OXA     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ FLC     <sir> NA, NA, R, R, R, R, S, S, R, S, S, S, NA, NA, NA, NA, NA, R, R… #> $ AMX     <sir> NA, NA, NA, NA, NA, NA, R, R, NA, NA, NA, NA, NA, NA, R, NA, N… #> $ AMC     <sir> I, I, NA, NA, NA, NA, S, S, NA, NA, S, S, I, I, R, I, I, NA, N… #> $ AMP     <sir> NA, NA, NA, NA, NA, NA, R, R, NA, NA, NA, NA, NA, NA, R, NA, N… #> $ TZP     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ CZO     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, NA,… #> $ FEP     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ CXM     <sir> I, I, R, R, R, R, S, S, R, S, S, S, S, S, NA, S, S, R, R, S, S… #> $ FOX     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, NA,… #> $ CTX     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, S, S, NA, S, S… #> $ CAZ     <sir> NA, NA, R, R, R, R, R, R, R, R, R, R, NA, NA, NA, S, S, R, R, … #> $ CRO     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, S, S, NA, S, S… #> $ GEN     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ TOB     <sir> NA, NA, NA, NA, NA, NA, S, S, NA, NA, NA, NA, S, S, NA, NA, NA… #> $ AMK     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ KAN     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ TMP     <sir> R, R, S, S, R, R, R, R, S, S, NA, NA, S, S, S, S, S, R, R, R, … #> $ SXT     <sir> R, R, S, S, NA, NA, NA, NA, S, S, NA, NA, S, S, S, S, S, NA, N… #> $ NIT     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R,… #> $ FOS     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ LNZ     <sir> R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R, R, R, N… #> $ CIP     <sir> NA, NA, NA, NA, NA, NA, NA, NA, S, S, NA, NA, NA, NA, NA, S, S… #> $ MFX     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ VAN     <sir> R, R, S, S, S, S, S, S, S, S, NA, NA, R, R, R, R, R, S, S, S, … #> $ TEC     <sir> R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R, R, R, N… #> $ TCY     <sir> R, R, S, S, S, S, S, S, S, I, S, S, NA, NA, I, R, R, S, I, R, … #> $ TGC     <sir> NA, NA, S, S, S, S, S, S, S, NA, S, S, NA, NA, NA, R, R, S, NA… #> $ DOX     <sir> NA, NA, S, S, S, S, S, S, S, NA, S, S, NA, NA, NA, R, R, S, NA… #> $ ERY     <sir> R, R, R, R, R, R, S, S, R, S, S, S, R, R, R, R, R, R, R, R, S,… #> $ CLI     <sir> R, R, NA, NA, NA, R, NA, NA, NA, NA, NA, NA, R, R, R, R, R, NA… #> $ AZM     <sir> R, R, R, R, R, R, S, S, R, S, S, S, R, R, R, R, R, R, R, R, S,… #> $ IPM     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, S, S, NA, S, S… #> $ MEM     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ MTR     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ CHL     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ COL     <sir> NA, NA, R, R, R, R, R, R, R, R, R, R, NA, NA, NA, R, R, R, R, … #> $ MUP     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ RIF     <sir> R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R, R, R, N… resistance_data <- example_isolates %>%   group_by(     order = mo_order(mo), # group on anything, like order     genus = mo_genus(mo)   ) %>% #  and genus as we do here   summarise_if(is.sir, resistance) %>% # then get resistance of all drugs   select(     order, genus, AMC, CXM, CTX,     CAZ, GEN, TOB, TMP, SXT   ) # and select only relevant columns  head(resistance_data) #> # A tibble: 6 × 10 #> # Groups:   order [5] #>   order             genus          AMC   CXM   CTX   CAZ   GEN   TOB   TMP   SXT #>   <chr>             <chr>        <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 (unknown order)   (unknown ge…    NA    NA    NA    NA    NA    NA    NA    NA #> 2 Actinomycetales   Schaalia        NA    NA    NA    NA    NA    NA    NA    NA #> 3 Bacteroidales     Bacteroides     NA    NA    NA    NA    NA    NA    NA    NA #> 4 Campylobacterales Campylobact…    NA    NA    NA    NA    NA    NA    NA    NA #> 5 Caryophanales     Gemella         NA    NA    NA    NA    NA    NA    NA    NA #> 6 Caryophanales     Listeria        NA    NA    NA    NA    NA    NA    NA    NA"},{"path":"https://msberends.github.io/AMR/articles/PCA.html","id":"perform-principal-component-analysis","dir":"Articles","previous_headings":"","what":"Perform principal component analysis","title":"How to conduct principal component analysis (PCA) for AMR","text":"new pca() function automatically filter rows contain numeric values selected variables, now need : result can reviewed good old summary() function: Good news. first two components explain total 93.3% variance (see PC1 PC2 values Proportion Variance. can create -called biplot base R biplot() function, see antimicrobial resistance per drug explain difference per microorganism.","code":"pca_result <- pca(resistance_data) #> ℹ Columns selected for PCA: \"AMC\", \"CAZ\", \"CTX\", \"CXM\", \"GEN\", \"SXT\", #>   \"TMP\", and \"TOB\". Total observations available: 7. summary(pca_result) #> Groups (n=4, named as 'order'): #> [1] \"Caryophanales\"    \"Enterobacterales\" \"Lactobacillales\"  \"Pseudomonadales\" #> Importance of components: #>                           PC1    PC2    PC3     PC4     PC5     PC6       PC7 #> Standard deviation     2.1539 1.6807 0.6138 0.33879 0.20808 0.03140 1.232e-16 #> Proportion of Variance 0.5799 0.3531 0.0471 0.01435 0.00541 0.00012 0.000e+00 #> Cumulative Proportion  0.5799 0.9330 0.9801 0.99446 0.99988 1.00000 1.000e+00 #> Groups (n=4, named as 'order'): #> [1] \"Caryophanales\"    \"Enterobacterales\" \"Lactobacillales\"  \"Pseudomonadales\""},{"path":"https://msberends.github.io/AMR/articles/PCA.html","id":"plotting-the-results","dir":"Articles","previous_headings":"","what":"Plotting the results","title":"How to conduct principal component analysis (PCA) for AMR","text":"can’t see explanation points. Perhaps works better new ggplot_pca() function, automatically adds right labels even groups:  can also print ellipse per group, edit appearance:","code":"biplot(pca_result) ggplot_pca(pca_result) ggplot_pca(pca_result, ellipse = TRUE) +   ggplot2::labs(title = \"An AMR/PCA biplot!\")"},{"path":"https://msberends.github.io/AMR/articles/WHONET.html","id":"import-of-data","dir":"Articles","previous_headings":"","what":"Import of data","title":"How to work with WHONET data","text":"tutorial assumes already imported WHONET data e.g. readxl package. RStudio, can done using menu button ‘Import Dataset’ tab ‘Environment’. Choose option ‘Excel’ select exported file. Make sure date fields imported correctly. example syntax look like : package comes example data set WHONET. use analysis.","code":"library(readxl) data <- read_excel(path = \"path/to/your/file.xlsx\")"},{"path":"https://msberends.github.io/AMR/articles/WHONET.html","id":"preparation","dir":"Articles","previous_headings":"","what":"Preparation","title":"How to work with WHONET data","text":"First, load relevant packages yet . use tidyverse analyses. . don’t know yet, suggest read website: https://www.tidyverse.org/. transform variables simplify automate analysis: Microorganisms transformed microorganism codes (called mo) using Catalogue Life reference data set, contains ~70,000 microorganisms taxonomic kingdoms Bacteria, Fungi Protozoa. tranformation .mo(). function also recognises almost WHONET abbreviations microorganisms. Antimicrobial results interpretations clean valid. words, contain values \"S\", \"\" \"R\". exactly .sir() function . errors warnings, values transformed succesfully. also created package dedicated data cleaning checking, called cleaner package. freq() function can used create frequency tables. let’s check data, couple frequency tables: Frequency table Class: character Length: 500 Available: 500 (100%, NA: 0 = 0%) Unique: 38 Shortest: 11 Longest: 40 (omitted 28 entries, n = 57 [11.4%]) Frequency table Class: factor > ordered > sir (numeric) Length: 500 Levels: 5: S < SDD < < R < NI Available: 481 (96.2%, NA: 19 = 3.8%) Unique: 3 Drug: Amoxicillin/clavulanic acid (AMC, J01CR02) Drug group: Beta-lactams/penicillins %SI: 78.59%","code":"library(dplyr) # part of tidyverse library(ggplot2) # part of tidyverse library(AMR) # this package library(cleaner) # to create frequency tables # transform variables data <- WHONET %>%   # get microbial ID based on given organism   mutate(mo = as.mo(Organism)) %>%   # transform everything from \"AMP_ND10\" to \"CIP_EE\" to the new `sir` class   mutate_at(vars(AMP_ND10:CIP_EE), as.sir) # our newly created `mo` variable, put in the mo_name() function data %>% freq(mo_name(mo), nmax = 10) # our transformed antibiotic columns # amoxicillin/clavulanic acid (J01CR02) as an example data %>% freq(AMC_ND2)"},{"path":"https://msberends.github.io/AMR/articles/WHONET.html","id":"a-first-glimpse-at-results","dir":"Articles","previous_headings":"","what":"A first glimpse at results","title":"How to work with WHONET data","text":"easy ggplot already give lot information, using included ggplot_sir() function:","code":"data %>%   group_by(Country) %>%   select(Country, AMP_ND2, AMC_ED20, CAZ_ED10, CIP_ED5) %>%   ggplot_sir(translate_ab = \"ab\", facet = \"Country\", datalabels = FALSE)"},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"microorganisms-full-microbial-taxonomy","dir":"Articles","previous_headings":"","what":"microorganisms: Full Microbial Taxonomy","title":"Data sets for download / own use","text":"data set 52 171 rows 23 columns, containing following column names:mo, fullname, status, kingdom, phylum, class, order, family, genus, species, subspecies, rank, ref, oxygen_tolerance, source, lpsn, lpsn_parent, lpsn_renamed_to, gbif, gbif_parent, gbif_renamed_to, prevalence, snomed. data set R available microorganisms, load AMR package. last updated 14 July 2023 08:49:06 UTC. Find info structure data set . Direct download links: Download original R Data Structure (RDS) file (1.2 MB) Download tab-separated text file (11.7 MB) Download Microsoft Excel workbook (5.2 MB) Download Apache Feather file (5.5 MB) Download Apache Parquet file (2.6 MB) Download SAS transport (XPT) file (48.6 MB) Download IBM SPSS Statistics data file (17.8 MB) Download Stata DTA file (48.6 MB) NOTE: exported files SAS, SPSS Stata contain first 50 SNOMED codes per record, file size otherwise exceed 100 MB; file size limit GitHub. file structures compression techniques inefficient. Advice? Use R instead. ’s free much better many ways. tab-separated text file Microsoft Excel workbook contain SNOMED codes comma separated values.","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"source","dir":"Articles","previous_headings":"microorganisms: Full Microbial Taxonomy","what":"Source","title":"Data sets for download / own use","text":"data set contains full microbial taxonomy five kingdoms List Prokaryotic names Standing Nomenclature (LPSN) Global Biodiversity Information Facility (GBIF): Parte, AC et al. (2020). List Prokaryotic names Standing Nomenclature (LPSN) moves DSMZ. International Journal Systematic Evolutionary Microbiology, 70, 5607-5612; . Accessed https://lpsn.dsmz.de December 11th, 2022. GBIF Secretariat (2023). GBIF Backbone Taxonomy. Checklist dataset . Accessed https://www.gbif.org January 8th, 2024. Public Health Information Network Vocabulary Access Distribution System (PHIN VADS). US Edition SNOMED CT 1 September 2020. Value Set Name ‘Microorganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: https://phinvads.cdc.gov","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"example-content","dir":"Articles","previous_headings":"microorganisms: Full Microbial Taxonomy","what":"Example content","title":"Data sets for download / own use","text":"Included (sub)species per taxonomic kingdom: Example rows filtering genus Escherichia:","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"antibiotics-antibiotic-antifungal-drugs","dir":"Articles","previous_headings":"","what":"antibiotics: Antibiotic (+Antifungal) Drugs","title":"Data sets for download / own use","text":"data set 485 rows 14 columns, containing following column names:ab, cid, name, group, atc, atc_group1, atc_group2, abbreviations, synonyms, oral_ddd, oral_units, iv_ddd, iv_units, loinc. data set R available antibiotics, load AMR package. last updated 14 June 2024 20:39:01 UTC. Find info structure data set . Direct download links: Download original R Data Structure (RDS) file (44 kB) Download tab-separated text file (0.1 MB) Download Microsoft Excel workbook (73 kB) Download Apache Feather file (0.2 MB) Download Apache Parquet file (0 kB) Download SAS transport (XPT) file (1.5 MB) Download IBM SPSS Statistics data file (0.4 MB) Download Stata DTA file (0.5 MB) tab-separated text file Microsoft Excel workbook, SAS, SPSS Stata files contain ATC codes, common abbreviations, trade names LOINC codes comma separated values.","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"source-1","dir":"Articles","previous_headings":"antibiotics: Antibiotic (+Antifungal) Drugs","what":"Source","title":"Data sets for download / own use","text":"data set contains EARS-Net ATC codes gathered WHONET, compound IDs PubChem. also contains brand names (synonyms) found PubChem Defined Daily Doses (DDDs) oral parenteral administration. ATC/DDD index Collaborating Centre Drug Statistics Methodology (note: may used commercial purposes, freely available CC website personal use) PubChem US National Library Medicine WHONET software 2019 LOINC (Logical Observation Identifiers Names Codes)","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"antivirals-antiviral-drugs","dir":"Articles","previous_headings":"","what":"antivirals: Antiviral Drugs","title":"Data sets for download / own use","text":"data set 120 rows 11 columns, containing following column names:av, name, atc, cid, atc_group, synonyms, oral_ddd, oral_units, iv_ddd, iv_units, loinc. data set R available antivirals, load AMR package. last updated 20 October 2023 12:51:48 UTC. Find info structure data set . Direct download links: Download original R Data Structure (RDS) file (6 kB) Download tab-separated text file (17 kB) Download Microsoft Excel workbook (16 kB) Download Apache Feather file (16 kB) Download Apache Parquet file (13 kB) Download SAS transport (XPT) file (73 kB) Download IBM SPSS Statistics data file (32 kB) Download Stata DTA file (78 kB) tab-separated text file Microsoft Excel workbook, SAS, SPSS Stata files contain trade names LOINC codes comma separated values.","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"source-2","dir":"Articles","previous_headings":"antivirals: Antiviral Drugs","what":"Source","title":"Data sets for download / own use","text":"data set contains ATC codes gathered compound IDs PubChem. also contains brand names (synonyms) found PubChem Defined Daily Doses (DDDs) oral parenteral administration. ATC/DDD index Collaborating Centre Drug Statistics Methodology (note: may used commercial purposes, freely available CC website personal use) PubChem US National Library Medicine LOINC (Logical Observation Identifiers Names Codes)","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"clinical_breakpoints-interpretation-from-mic-values-disk-diameters-to-sir","dir":"Articles","previous_headings":"","what":"clinical_breakpoints: Interpretation from MIC values & disk diameters to SIR","title":"Data sets for download / own use","text":"data set 34 063 rows 14 columns, containing following column names:guideline, type, host, method, site, mo, rank_index, ab, ref_tbl, disk_dose, breakpoint_S, breakpoint_R, uti, is_SDD. data set R available clinical_breakpoints, load AMR package. last updated 19 June 2024 13:08:23 UTC. Find info structure data set . Direct download links: Download original R Data Structure (RDS) file (70 kB) Download tab-separated text file (3.1 MB) Download Microsoft Excel workbook (1.7 MB) Download Apache Feather file (4.9 MB) Download Apache Parquet file (0 kB) Download SAS transport (XPT) file (9.6 MB) Download IBM SPSS Statistics data file (5.6 MB) Download Stata DTA file (9.3 MB)","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"source-3","dir":"Articles","previous_headings":"clinical_breakpoints: Interpretation from MIC values & disk diameters to SIR","what":"Source","title":"Data sets for download / own use","text":"data set contains interpretation rules MIC values disk diffusion diameters. Included guidelines CLSI (2011-2024) EUCAST (2011-2024). Clinical breakpoints package validated imported WHONET, free desktop Windows application developed supported Collaborating Centre Surveillance Antimicrobial Resistance. can read website. developers WHONET AMR package contact sharing work. highly appreciate development WHONET software. CEO CLSI chairman EUCAST endorsed work public use AMR package (consequently use breakpoints) June 2023, future development distributing clinical breakpoints discussed meeting CLSI, EUCAST, , developers WHONET AMR package. NOTE: AMR package (WHONET software well) contains internal methods apply guidelines, rather complex. example, breakpoints must applied certain species groups (case package available microorganisms.groups data set). important considered using breakpoints use.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"intrinsic_resistant-intrinsic-bacterial-resistance","dir":"Articles","previous_headings":"","what":"intrinsic_resistant: Intrinsic Bacterial Resistance","title":"Data sets for download / own use","text":"data set 134 634 rows 2 columns, containing following column names:mo ab. data set R available intrinsic_resistant, load AMR package. last updated 16 December 2022 15:10:43 UTC. Find info structure data set . Direct download links: Download original R Data Structure (RDS) file (78 kB) Download tab-separated text file (5.1 MB) Download Microsoft Excel workbook (1.3 MB) Download Apache Feather file (1.2 MB) Download Apache Parquet file (0.2 MB) Download SAS transport (XPT) file (9.5 MB) Download IBM SPSS Statistics data file (7.4 MB) Download Stata DTA file (9.5 MB)","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"source-4","dir":"Articles","previous_headings":"intrinsic_resistant: Intrinsic Bacterial Resistance","what":"Source","title":"Data sets for download / own use","text":"data set contains defined intrinsic resistance EUCAST bug-drug combinations, based ‘EUCAST Expert Rules’ ‘EUCAST Intrinsic Resistance Unusual Phenotypes’ v3.3 (2021).","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"example-content-4","dir":"Articles","previous_headings":"intrinsic_resistant: Intrinsic Bacterial Resistance","what":"Example content","title":"Data sets for download / own use","text":"Example rows filtering Enterobacter cloacae:","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"dosage-dosage-guidelines-from-eucast","dir":"Articles","previous_headings":"","what":"dosage: Dosage Guidelines from EUCAST","title":"Data sets for download / own use","text":"data set 503 rows 9 columns, containing following column names:ab, name, type, dose, dose_times, administration, notes, original_txt, eucast_version. data set R available dosage, load AMR package. last updated 22 June 2023 13:10:59 UTC. Find info structure data set . Direct download links: Download original R Data Structure (RDS) file (3 kB) Download tab-separated text file (43 kB) Download Microsoft Excel workbook (25 kB) Download Apache Feather file (21 kB) Download Apache Parquet file (9 kB) Download SAS transport (XPT) file (0.1 MB) Download IBM SPSS Statistics data file (64 kB) Download Stata DTA file (0.1 MB)","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"source-5","dir":"Articles","previous_headings":"dosage: Dosage Guidelines from EUCAST","what":"Source","title":"Data sets for download / own use","text":"EUCAST breakpoints used package based dosages data set. Currently included dosages data set meant :  (), ‘EUCAST Clinical Breakpoint Tables’ v11.0 (2021), ‘EUCAST Clinical Breakpoint Tables’ v12.0 (2022).","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"example_isolates-example-data-for-practice","dir":"Articles","previous_headings":"","what":"example_isolates: Example Data for Practice","title":"Data sets for download / own use","text":"data set 2 000 rows 46 columns, containing following column names:date, patient, age, gender, ward, mo, PEN, OXA, FLC, AMX, AMC, AMP, TZP, CZO, FEP, CXM, FOX, CTX, CAZ, CRO, GEN, TOB, AMK, KAN, TMP, SXT, NIT, FOS, LNZ, CIP, MFX, VAN, TEC, TCY, TGC, DOX, ERY, CLI, AZM, IPM, MEM, MTR, CHL, COL, MUP, RIF. data set R available example_isolates, load AMR package. last updated 15 June 2024 13:33:49 UTC. Find info structure data set .","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"source-6","dir":"Articles","previous_headings":"example_isolates: Example Data for Practice","what":"Source","title":"Data sets for download / own use","text":"data set contains randomised fictitious data, reflects reality can used practise AMR data analysis.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"example_isolates_unclean-example-data-for-practice","dir":"Articles","previous_headings":"","what":"example_isolates_unclean: Example Data for Practice","title":"Data sets for download / own use","text":"data set 3 000 rows 8 columns, containing following column names:patient_id, hospital, date, bacteria, AMX, AMC, CIP, GEN. data set R available example_isolates_unclean, load AMR package. last updated 27 August 2022 18:49:37 UTC. Find info structure data set .","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"source-7","dir":"Articles","previous_headings":"example_isolates_unclean: Example Data for Practice","what":"Source","title":"Data sets for download / own use","text":"data set contains randomised fictitious data, reflects reality can used practise AMR data analysis.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"microorganisms-groups-species-groups-and-microbiological-complexes","dir":"Articles","previous_headings":"","what":"microorganisms.groups: Species Groups and Microbiological Complexes","title":"Data sets for download / own use","text":"data set 521 rows 4 columns, containing following column names:mo_group, mo, mo_group_name, mo_name. data set R available microorganisms.groups, load AMR package. last updated 14 July 2023 08:49:06 UTC. Find info structure data set . Direct download links: Download original R Data Structure (RDS) file (6 kB) Download tab-separated text file (49 kB) Download Microsoft Excel workbook (20 kB) Download Apache Feather file (19 kB) Download Apache Parquet file (13 kB) Download SAS transport (XPT) file (0 kB) Download IBM SPSS Statistics data file (64 kB) Download Stata DTA file (81 kB)","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"source-8","dir":"Articles","previous_headings":"microorganisms.groups: Species Groups and Microbiological Complexes","what":"Source","title":"Data sets for download / own use","text":"data set contains species groups microbiological complexes, used clinical_breakpoints data set.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"microorganisms-codes-common-laboratory-codes","dir":"Articles","previous_headings":"","what":"microorganisms.codes: Common Laboratory Codes","title":"Data sets for download / own use","text":"data set 4 971 rows 2 columns, containing following column names:code mo. data set R available microorganisms.codes, load AMR package. last updated 16 June 2024 09:28:56 UTC. Find info structure data set . Direct download links: Download original R Data Structure (RDS) file (22 kB) Download tab-separated text file (0.1 MB) Download Microsoft Excel workbook (91 kB) Download Apache Feather file (0.1 MB) Download Apache Parquet file (0 kB) Download SAS transport (XPT) file (0 kB) Download IBM SPSS Statistics data file (0.1 MB) Download Stata DTA file (0.1 MB)","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"source-9","dir":"Articles","previous_headings":"microorganisms.codes: Common Laboratory Codes","what":"Source","title":"Data sets for download / own use","text":"data set contains commonly used codes microorganisms, laboratory systems WHONET.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/articles/resistance_predict.html","id":"needed-r-packages","dir":"Articles","previous_headings":"","what":"Needed R packages","title":"How to predict antimicrobial resistance","text":"many uses R, need additional packages AMR data analysis. package works closely together tidyverse packages dplyr ggplot2. tidyverse tremendously improves way conduct data science - allows natural way writing syntaxes creating beautiful plots R. AMR package depends packages even extends use functions.","code":"library(dplyr) library(ggplot2) library(AMR)  # (if not yet installed, install with:) # install.packages(c(\"tidyverse\", \"AMR\"))"},{"path":"https://msberends.github.io/AMR/articles/resistance_predict.html","id":"prediction-analysis","dir":"Articles","previous_headings":"","what":"Prediction analysis","title":"How to predict antimicrobial resistance","text":"package contains function resistance_predict(), takes input functions AMR data analysis. Based date column, calculates cases per year uses regression model predict antimicrobial resistance. basically easy : function look date column col_date set. running commands, summary regression model printed unless using resistance_predict(..., info = FALSE). text printed summary - actual result (output) function data.frame containing year: number observations, actual observed resistance, estimated resistance standard error estimation: function plot available base R, can extended packages depend output based type input. extended function cope resistance predictions:  fastest way plot result. automatically adds right axes, error bars, titles, number available observations type model. also support ggplot2 package custom function ggplot_sir_predict() create appealing plots:","code":"# resistance prediction of piperacillin/tazobactam (TZP): resistance_predict(tbl = example_isolates, col_date = \"date\", col_ab = \"TZP\", model = \"binomial\")  # or: example_isolates %>%   resistance_predict(     col_ab = \"TZP\",     model = \"binomial\"   )  # to bind it to object 'predict_TZP' for example: predict_TZP <- example_isolates %>%   resistance_predict(     col_ab = \"TZP\",     model = \"binomial\"   ) predict_TZP #> # A tibble: 33 × 7 #>     year  value se_min se_max observations observed estimated #>  * <dbl>  <dbl>  <dbl>  <dbl>        <int>    <dbl>     <dbl> #>  1  2002 0.2        NA     NA           15   0.2       0.0562 #>  2  2003 0.0625     NA     NA           32   0.0625    0.0616 #>  3  2004 0.0854     NA     NA           82   0.0854    0.0676 #>  4  2005 0.05       NA     NA           60   0.05      0.0741 #>  5  2006 0.0508     NA     NA           59   0.0508    0.0812 #>  6  2007 0.121      NA     NA           66   0.121     0.0889 #>  7  2008 0.0417     NA     NA           72   0.0417    0.0972 #>  8  2009 0.0164     NA     NA           61   0.0164    0.106  #>  9  2010 0.0566     NA     NA           53   0.0566    0.116  #> 10  2011 0.183      NA     NA           93   0.183     0.127  #> # ℹ 23 more rows plot(predict_TZP) ggplot_sir_predict(predict_TZP) # choose for error bars instead of a ribbon ggplot_sir_predict(predict_TZP, ribbon = FALSE)"},{"path":"https://msberends.github.io/AMR/articles/resistance_predict.html","id":"choosing-the-right-model","dir":"Articles","previous_headings":"Prediction analysis","what":"Choosing the right model","title":"How to predict antimicrobial resistance","text":"Resistance easily predicted; look vancomycin resistance Gram-positive bacteria, spread (.e. standard error) enormous:  Vancomycin resistance 100% ten years, might remain low. can define model model parameter. model chosen generalised linear regression model using binomial distribution, assuming period zero resistance followed period increasing resistance leading slowly resistance. Valid values : vancomycin resistance Gram-positive bacteria, linear model might appropriate:  model also available object, attribute:","code":"example_isolates %>%   filter(mo_gramstain(mo, language = NULL) == \"Gram-positive\") %>%   resistance_predict(col_ab = \"VAN\", year_min = 2010, info = FALSE, model = \"binomial\") %>%   ggplot_sir_predict() example_isolates %>%   filter(mo_gramstain(mo, language = NULL) == \"Gram-positive\") %>%   resistance_predict(col_ab = \"VAN\", year_min = 2010, info = FALSE, model = \"linear\") %>%   ggplot_sir_predict() model <- attributes(predict_TZP)$model  summary(model)$family #>  #> Family: binomial  #> Link function: logit summary(model)$coefficients #>                  Estimate  Std. Error   z value     Pr(>|z|) #> (Intercept) -200.67944891 46.17315349 -4.346237 1.384932e-05 #> year           0.09883005  0.02295317  4.305725 1.664395e-05"},{"path":"https://msberends.github.io/AMR/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Matthijs S. Berends. Author, maintainer. Dennis Souverein. Author, contributor. Erwin E. . Hassing. Author, contributor. Casper J. Albers. Thesis advisor. Peter Dutey-Magni. Contributor. Judith M. Fonville. Contributor. Alex W. Friedrich. Thesis advisor. Corinna Glasner. Thesis advisor. Eric H. L. C. M. Hazenberg. Contributor. Gwen Knight. Contributor. Annick Lenglet. Contributor. Christian F. Luz. Contributor. Bart C. Meijer. Contributor. Dmytro Mykhailenko. Contributor. Anton Mymrikov. Contributor. Andrew P. Norgan. Contributor. Sofia Ny. Contributor. Matthew Saab. Contributor. Jonas Salm. Contributor. Javier Sanchez. Contributor. Rogier P. Schade. Contributor. Bhanu N. M. Sinha. Thesis advisor. Jason Stull. Contributor. Anthony Underwood. Contributor. Anita Williams. Contributor.","code":""},{"path":"https://msberends.github.io/AMR/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C (2022). “AMR: R Package Working Antimicrobial Resistance Data.” Journal Statistical Software, 104(3), 1–31. doi:10.18637/jss.v104.i03.","code":"@Article{,   title = {{AMR}: An {R} Package for Working with Antimicrobial Resistance Data},   author = {Matthijs S. Berends and Christian F. Luz and Alexander W. Friedrich and Bhanu N. M. Sinha and Casper J. Albers and Corinna Glasner},   journal = {Journal of Statistical Software},   year = {2022},   volume = {104},   number = {3},   pages = {1--31},   doi = {10.18637/jss.v104.i03}, }"},{"path":"https://msberends.github.io/AMR/index.html","id":"the-amr-package-for-r-","dir":"","previous_headings":"","what":"Antimicrobial Resistance Data Analysis","title":"Antimicrobial Resistance Data Analysis","text":"Provides --one solution antimicrobial resistance (AMR) data analysis One Health approach Used 175 countries, available 20 languages Generates antibiograms - traditional, combined, syndromic, even WISCA Provides full microbiological taxonomy extensive info antimicrobial drugs Applies recent CLSI EUCAST clinical veterinary breakpoints MICs disk zones Corrects duplicate isolates, calculates predicts AMR per antibiotic class Integrates WHONET, ATC, EARS-Net, PubChem, LOINC, SNOMED CT, NCBI 100% free costs dependencies, highly suitable places limited resources https://msberends.github.io/AMR https://doi.org/10.18637/jss.v104.i03","code":""},{"path":"https://msberends.github.io/AMR/index.html","id":"introduction","dir":"","previous_headings":"","what":"Introduction","title":"Antimicrobial Resistance Data Analysis","text":"AMR package free open-source R package zero dependencies simplify analysis prediction Antimicrobial Resistance (AMR) work microbial antimicrobial data properties, using evidence-based methods. aim provide standard clean reproducible AMR data analysis, can therefore empower epidemiological analyses continuously enable surveillance treatment evaluation setting. Many different researchers around globe continually helping us make successful durable project! work published Journal Statistical Software (Volume 104(3); DOI 10.18637/jss.v104.i03) formed basis two PhD theses (DOI 10.33612/diss.177417131 DOI 10.33612/diss.192486375). installing package, R knows ~52,000 distinct microbial species (updated December 2022) ~600 antibiotic, antimycotic antiviral drugs name code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC SNOMED CT), knows valid SIR MIC values. integral clinical breakpoint guidelines CLSI EUCAST included, even epidemiological cut-(ECOFF) values. supports can read data format, including WHONET data. package works Windows, macOS Linux versions R since R-3.0 (April 2013). designed work setting, including limited resources. created routine data analysis academic research Faculty Medical Sciences University Groningen, collaboration non-profit organisations Certe Medical Diagnostics Advice Foundation University Medical Center Groningen.","code":""},{"path":"https://msberends.github.io/AMR/index.html","id":"used-in-over-175-countries-available-in-20-languages","dir":"","previous_headings":"Introduction","what":"Used in over 175 countries, available in 20 languages","title":"Antimicrobial Resistance Data Analysis","text":"Since first public release early 2018, R package used almost countries world. Click map enlarge see country names. help contributors corners world, AMR package available  English,  Czech,  Chinese,  Danish,  Dutch,  Finnish,  French,  German,  Greek,  Italian,  Japanese,  Norwegian,  Polish,  Portuguese,  Romanian,  Russian,  Spanish,  Swedish,  Turkish,  Ukrainian. Antimicrobial drug (group) names colloquial microorganism names provided languages.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/index.html","id":"filtering-and-selecting-data","dir":"","previous_headings":"Practical examples","what":"Filtering and selecting data","title":"Antimicrobial Resistance Data Analysis","text":"One powerful functions package, aside calculating plotting AMR, selecting filtering based antibiotic columns. can done using -called antibiotic class selectors work base R, dplyr data.table: defined row filter Gram-negative bacteria intrinsic resistance cefotaxime (mo_is_gram_negative() mo_is_intrinsic_resistant()) column selection two antibiotic groups (aminoglycosides() carbapenems()), reference data microorganisms antibiotics AMR package make sure get meant: base R equivalent : base R code work version R since April 2013 (R-3.0). Moreover, code works identically data.table package, starting :","code":"# AMR works great with dplyr, but it's not required or neccesary library(AMR) library(dplyr)  example_isolates %>%   mutate(bacteria = mo_fullname()) %>%   # filtering functions for microorganisms:   filter(mo_is_gram_negative(),          mo_is_intrinsic_resistant(ab = \"cefotax\")) %>%   # antibiotic selectors:   select(bacteria,          aminoglycosides(),          carbapenems()) library(AMR) example_isolates$bacteria <- mo_fullname(example_isolates$mo) example_isolates[which(mo_is_gram_negative() &                          mo_is_intrinsic_resistant(ab = \"cefotax\")),                  c(\"bacteria\", aminoglycosides(), carbapenems())] example_isolates <- data.table::as.data.table(example_isolates)"},{"path":"https://msberends.github.io/AMR/index.html","id":"generating-antibiograms","dir":"","previous_headings":"Practical examples","what":"Generating antibiograms","title":"Antimicrobial Resistance Data Analysis","text":"AMR package supports generating traditional, combined, syndromic, even weighted-incidence syndromic combination antibiograms (WISCA). used inside R Markdown Quarto, table printed right output format automatically (markdown, LaTeX, HTML, etc.). combination antibiograms, clear combined antibiotics yield higher empiric coverage: Like many functions package, antibiogram() comes support 20 languages often detected automatically based system language:","code":"antibiogram(example_isolates,             antibiotics = c(aminoglycosides(), carbapenems())) antibiogram(example_isolates,             antibiotics = c(\"TZP\", \"TZP+TOB\", \"TZP+GEN\"),             mo_transform = \"gramstain\") antibiogram(example_isolates,             antibiotics = c(\"cipro\", \"tobra\", \"genta\"), # any arbitrary name or code will work             mo_transform = \"gramstain\",             ab_transform = \"name\",             language = \"uk\") # Ukrainian"},{"path":"https://msberends.github.io/AMR/index.html","id":"calculating-resistance-per-group","dir":"","previous_headings":"Practical examples","what":"Calculating resistance per group","title":"Antimicrobial Resistance Data Analysis","text":"manual approach, can use resistance susceptibility() function: use antibiotic class selectors select series antibiotic columns:","code":"example_isolates %>%   # group by ward:   group_by(ward) %>%   # calculate AMR using resistance() for gentamicin and tobramycin   # and get their 95% confidence intervals using sir_confidence_interval():   summarise(across(c(GEN, TOB),                    list(total_R = resistance,                         conf_int = function(x) sir_confidence_interval(x, collapse = \"-\")))) library(AMR) library(dplyr)  out <- example_isolates %>%   # group by ward:   group_by(ward) %>%   # calculate AMR using resistance(), over all aminoglycosides and polymyxins:   summarise(across(c(aminoglycosides(), polymyxins()),             resistance)) out # transform the antibiotic columns to names: out %>% set_ab_names() # transform the antibiotic column to ATC codes: out %>% set_ab_names(property = \"atc\")"},{"path":"https://msberends.github.io/AMR/index.html","id":"what-else-can-you-do-with-this-package","dir":"","previous_headings":"","what":"What else can you do with this package?","title":"Antimicrobial Resistance Data Analysis","text":"package intended comprehensive toolbox integrated AMR data analysis. package can used : Reference taxonomy microorganisms, since package contains microbial (sub)species List Prokaryotic names Standing Nomenclature (LPSN) Global Biodiversity Information Facility (GBIF) (manual) Interpreting raw MIC disk diffusion values, based CLSI EUCAST guideline (manual) Retrieving antimicrobial drug names, doses forms administration clinical health care records (manual) Determining first isolates used AMR data analysis (manual) Calculating antimicrobial resistance (tutorial) Determining multi-drug resistance (MDR) / multi-drug resistant organisms (MDRO) (tutorial) Calculating (empirical) susceptibility mono therapy combination therapies (tutorial) Predicting future antimicrobial resistance using regression models (tutorial) Getting properties microorganism (like Gram stain, species, genus family) (manual) Getting properties antibiotic (like name, code EARS-Net/ATC/LOINC/PubChem, defined daily dose trade name) (manual) Plotting antimicrobial resistance (tutorial) Applying EUCAST expert rules (manual) Getting SNOMED codes microorganism, getting properties microorganism based SNOMED code (manual) Getting LOINC codes antibiotic, getting properties antibiotic based LOINC code (manual) Machine reading EUCAST CLSI guidelines 2011-2021 translate MIC values disk diffusion diameters SIR (link) Principal component analysis AMR (tutorial)","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/index.html","id":"latest-official-version","dir":"","previous_headings":"Get this package","what":"Latest official version","title":"Antimicrobial Resistance Data Analysis","text":"package available official R network (CRAN). Install package R CRAN using command: downloaded installed automatically. RStudio, click menu Tools > Install Packages… type “AMR” press Install. Note: functions website may available latest release. use functions data sets mentioned website, install latest development version.","code":"install.packages(\"AMR\")"},{"path":"https://msberends.github.io/AMR/index.html","id":"latest-development-version","dir":"","previous_headings":"Get this package","what":"Latest development version","title":"Antimicrobial Resistance Data Analysis","text":"Please read Developer Guideline . latest unpublished development version can installed GitHub two ways: Manually, using: Automatically, using rOpenSci R-universe platform, adding R-universe address list repositories (‘repos’): , can install update AMR package like official release (e.g., using install.packages(\"AMR\") RStudio via Tools > Check Package Updates…).","code":"install.packages(\"remotes\") # if you haven't already remotes::install_github(\"msberends/AMR\") options(repos = c(getOption(\"repos\"),                   msberends = \"https://msberends.r-universe.dev\"))"},{"path":"https://msberends.github.io/AMR/index.html","id":"get-started","dir":"","previous_headings":"","what":"Get started","title":"Antimicrobial Resistance Data Analysis","text":"find conduct AMR data analysis, please continue reading get started click link ‘’ menu.","code":""},{"path":"https://msberends.github.io/AMR/index.html","id":"partners","dir":"","previous_headings":"","what":"Partners","title":"Antimicrobial Resistance Data Analysis","text":"development package part , related , made possible following non-profit organisations initiatives:","code":""},{"path":"https://msberends.github.io/AMR/index.html","id":"copyright","dir":"","previous_headings":"","what":"Copyright","title":"Antimicrobial Resistance Data Analysis","text":"R package free, open-source software licensed GNU General Public License v2.0 (GPL-2). nutshell, means package: May used commercial purposes May used private purposes May used patent purposes May modified, although: Modifications must released license distributing package Changes made code must documented May distributed, although: Source code must made available package distributed copy license copyright notice must included package. Comes LIMITATION liability Comes warranty","code":""},{"path":"https://msberends.github.io/AMR/reference/AMR-options.html","id":null,"dir":"Reference","previous_headings":"","what":"Options for the AMR package — AMR-options","title":"Options for the AMR package — AMR-options","text":"overview package-specific options() can set AMR package.","code":""},{"path":"https://msberends.github.io/AMR/reference/AMR-options.html","id":"options","dir":"Reference","previous_headings":"","what":"Options","title":"Options for the AMR package — AMR-options","text":"AMR_breakpoint_type  character use .sir(), indicate breakpoint type use. must either \"ECOFF\", \"animal\", \"human\". AMR_cleaning_regex  regular expression (case-insensitive) use .mo() mo_* functions, clean user input. default outcome mo_cleaning_regex(), removes texts brackets texts \"species\" \"serovar\". AMR_custom_ab  file location RDS file, use custom antimicrobial drugs package. explained add_custom_antimicrobials(). AMR_custom_mo  file location RDS file, use custom microorganisms package. explained add_custom_microorganisms(). AMR_eucastrules  character set default types rules eucast_rules() function, must one : \"breakpoints\", \"expert\", \"\", \"custom\", \"\", defaults c(\"breakpoints\", \"expert\"). AMR_guideline  character set default guideline interpreting MIC values disk diffusion diameters .sir(). Can guideline name (e.g., \"CLSI\") name year (e.g. \"CLSI 2019\"). default latest implemented EUCAST guideline, currently \"EUCAST 2024\". Supported guideline currently EUCAST (2011-2024) CLSI (2011-2024). AMR_ignore_pattern  regular expression ignore (.e., make NA) match given .mo() mo_* functions. AMR_include_PKPD  logical use .sir(), indicate PK/PD clinical breakpoints must applied last resort - default TRUE. AMR_include_screening  logical use .sir(), indicate clinical breakpoints screening allowed - default FALSE. AMR_keep_synonyms  logical use .mo() mo_* functions, indicate old, previously valid taxonomic names must preserved corrected currently accepted names. default FALSE. AMR_locale  character set language AMR package, can one supported language names ISO-639-1 codes: English (en), Chinese (zh), Czech (cs), Danish (da), Dutch (nl), Finnish (fi), French (fr), German (de), Greek (el), Italian (), Japanese (ja), Norwegian (), Polish (pl), Portuguese (pt), Romanian (ro), Russian (ru), Spanish (es), Swedish (sv), Turkish (tr), Ukrainian (uk). default current system language (supported, English otherwise). AMR_mo_source  file location manual code list used .mo() mo_* functions. explained set_mo_source().","code":""},{"path":"https://msberends.github.io/AMR/reference/AMR-options.html","id":"saving-settings-between-sessions","dir":"Reference","previous_headings":"","what":"Saving Settings Between Sessions","title":"Options for the AMR package — AMR-options","text":"Settings R saved globally thus lost R exited. can save options .Rprofile file, user-specific file. can edit using:   file, can set options ...   ...add Portuguese language support antibiotics, allow PK/PD rules interpreting MIC values .sir().","code":"utils::file.edit(\"~/.Rprofile\") options(AMR_locale = \"pt\")  options(AMR_include_PKPD = TRUE)"},{"path":"https://msberends.github.io/AMR/reference/AMR-options.html","id":"share-options-within-team","dir":"Reference","previous_headings":"","what":"Share Options Within Team","title":"Options for the AMR package — AMR-options","text":"global approach, e.g. within (data) team, save options file remote file location, shared network drive, user read file automatically start-. work way: Save plain text file e.g. \"X:/team_folder/R_options.R\" fill preferred settings. user, open .Rprofile file using utils::file.edit(\"~/.Rprofile\") put :   Reload R/RStudio check settings getOption(), e.g. getOption(\"AMR_locale\") set value. Now team settings configured one place, can maintained .","code":"source(\"X:/team_folder/R_options.R\")"},{"path":"https://msberends.github.io/AMR/reference/AMR.html","id":null,"dir":"Reference","previous_headings":"","what":"The AMR Package — AMR","title":"The AMR Package — AMR","text":"Welcome AMR package. AMR package free open-source R package zero dependencies simplify analysis prediction Antimicrobial Resistance (AMR) work microbial antimicrobial data properties, using evidence-based methods. aim provide standard clean reproducible AMR data analysis, can therefore empower epidemiological analyses continuously enable surveillance treatment evaluation setting. Many different researchers around globe continually helping us make successful durable project! work published Journal Statistical Software (Volume 104(3); doi:10.18637/jss.v104.i03 ) formed basis two PhD theses (doi:10.33612/diss.177417131  doi:10.33612/diss.192486375 ). installing package, R knows ~52 000 microorganisms (updated January 2024) ~600 antibiotic, antimycotic antiviral drugs name code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC SNOMED CT), knows valid SIR MIC values. integral clinical breakpoint guidelines CLSI EUCAST included, even epidemiological cut-(ECOFF) values. supports can read data format, including WHONET data. package works Windows, macOS Linux versions R since R-3.0 (April 2013). designed work setting, including limited resources. created routine data analysis academic research Faculty Medical Sciences public University Groningen, collaboration non-profit organisations Certe Medical Diagnostics Advice Foundation University Medical Center Groningen. AMR package available English, Chinese, Czech, Danish, Dutch, Finnish, French, German, Greek, Italian, Japanese, Norwegian, Polish, Portuguese, Romanian, Russian, Spanish, Swedish, Turkish, Ukrainian. Antimicrobial drug (group) names colloquial microorganism names provided languages.","code":""},{"path":"https://msberends.github.io/AMR/reference/AMR.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"The AMR Package — AMR","text":"cite AMR publications use: Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C (2022). \"AMR: R Package Working Antimicrobial Resistance Data.\" Journal Statistical Software, 104(3), 1-31. doi:10.18637/jss.v104.i03 BibTeX entry LaTeX users :","code":"@Article{,   title = {{AMR}: An {R} Package for Working with Antimicrobial Resistance Data},   author = {Matthijs S. Berends and Christian F. Luz and Alexander W. Friedrich and Bhanu N. M. Sinha and Casper J. Albers and Corinna Glasner},   journal = {Journal of Statistical Software},   year = {2022},   volume = {104},   number = {3},   pages = {1--31},   doi = {10.18637/jss.v104.i03}, }"},{"path":"https://msberends.github.io/AMR/reference/AMR.html","id":"reference-data-publicly-available","dir":"Reference","previous_headings":"","what":"Reference Data Publicly Available","title":"The AMR Package — AMR","text":"data sets AMR package (microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) publicly freely available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. also provide tab-separated plain text files machine-readable suitable input software program, laboratory information systems. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/AMR.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"The AMR Package — AMR","text":"Maintainer: Matthijs S. Berends m.s.berends@umcg.nl (ORCID) Authors: Dennis Souverein (ORCID) [contributor] Erwin E. . Hassing [contributor] contributors: Casper J. Albers (ORCID) [thesis advisor] Peter Dutey-Magni (ORCID) [contributor] Judith M. Fonville [contributor] Alex W. Friedrich (ORCID) [thesis advisor] Corinna Glasner (ORCID) [thesis advisor] Eric H. L. C. M. Hazenberg [contributor] Gwen Knight (ORCID) [contributor] Annick Lenglet (ORCID) [contributor] Christian F. Luz (ORCID) [contributor] Bart C. Meijer [contributor] Dmytro Mykhailenko [contributor] Anton Mymrikov [contributor] Andrew P. Norgan (ORCID) [contributor] Sofia Ny (ORCID) [contributor] Matthew Saab [contributor] Jonas Salm [contributor] Javier Sanchez (ORCID) [contributor] Rogier P. Schade [contributor] Bhanu N. M. Sinha (ORCID) [thesis advisor] Jason Stull (ORCID) [contributor] Anthony Underwood (ORCID) [contributor] Anita Williams (ORCID) [contributor]","code":""},{"path":"https://msberends.github.io/AMR/reference/WHOCC.html","id":null,"dir":"Reference","previous_headings":"","what":"WHOCC: WHO Collaborating Centre for Drug Statistics Methodology — WHOCC","title":"WHOCC: WHO Collaborating Centre for Drug Statistics Methodology — WHOCC","text":"antimicrobial drugs official names, ATC codes, ATC groups defined daily dose (DDD) included package, using Collaborating Centre Drug Statistics Methodology.","code":""},{"path":"https://msberends.github.io/AMR/reference/WHOCC.html","id":"whocc","dir":"Reference","previous_headings":"","what":"WHOCC","title":"WHOCC: WHO Collaborating Centre for Drug Statistics Methodology — WHOCC","text":"package contains ~550 antibiotic, antimycotic antiviral drugs Anatomical Therapeutic Chemical (ATC) codes, ATC groups Defined Daily Dose (DDD) World Health Organization Collaborating Centre Drug Statistics Methodology (WHOCC, https://atcddd.fhi.) Pharmaceuticals Community Register European Commission (https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm). become gold standard international drug utilisation monitoring research. WHOCC located Oslo Norwegian Institute Public Health funded Norwegian government. European Commission executive European Union promotes general interest. NOTE: WHOCC copyright allow use commercial purposes, unlike info package. See https://atcddd.fhi./copyright_disclaimer/.","code":""},{"path":"https://msberends.github.io/AMR/reference/WHOCC.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"WHOCC: WHO Collaborating Centre for Drug Statistics Methodology — WHOCC","text":"","code":"as.ab(\"meropenem\") #> Class 'ab' #> [1] MEM ab_name(\"J01DH02\") #> [1] \"Meropenem\"  ab_tradenames(\"flucloxacillin\") #>  [1] \"culpen\"               \"floxacillin\"          \"floxacillin sodium\"   #>  [4] \"floxapen\"             \"floxapen sodium salt\" \"fluclox\"              #>  [7] \"flucloxacilina\"       \"flucloxacillin\"       \"flucloxacilline\"      #> [10] \"flucloxacillinum\"     \"fluorochloroxacillin\" \"staphylex\""},{"path":"https://msberends.github.io/AMR/reference/WHONET.html","id":null,"dir":"Reference","previous_headings":"","what":"Data Set with 500 Isolates - WHONET Example — WHONET","title":"Data Set with 500 Isolates - WHONET Example — WHONET","text":"example data set exact structure export file WHONET. files can used package, example data set shows. antibiotic results example_isolates data set. patient names created using online surname generators place practice purposes.","code":""},{"path":"https://msberends.github.io/AMR/reference/WHONET.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Data Set with 500 Isolates - WHONET Example — WHONET","text":"","code":"WHONET"},{"path":"https://msberends.github.io/AMR/reference/WHONET.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data Set with 500 Isolates - WHONET Example — WHONET","text":"tibble 500 observations 53 variables: Identification number ID sample Specimen number ID specimen Organism Name microorganism. analysis, transform valid microbial class, using .mo(). Country Country origin Laboratory Name laboratory Last name Fictitious last name patient First name Fictitious initial patient Sex Fictitious gender patient Age Fictitious age patient Age category Age group, can also looked using age_groups() Date admissionDate hospital admission Specimen dateDate specimen received laboratory Specimen type Specimen type group Specimen type (Numeric) Translation \"Specimen type\" Reason Reason request Differential Diagnosis Isolate number ID isolate Organism type Type microorganism, can also looked using mo_type() Serotype Serotype microorganism Beta-lactamase Microorganism produces beta-lactamase? ESBL Microorganism produces extended spectrum beta-lactamase? Carbapenemase Microorganism produces carbapenemase? MRSA screening test Microorganism possible MRSA? Inducible clindamycin resistance Clindamycin can induced? Comment comments Date data entryDate data entered WHONET AMP_ND10:CIP_EE 28 different antibiotics. can lookup abbreviations antibiotics data set, use e.g. ab_name(\"AMP\") get official name immediately. analysis, transform valid antibiotic class, using .sir().","code":""},{"path":"https://msberends.github.io/AMR/reference/WHONET.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Data Set with 500 Isolates - WHONET Example — WHONET","text":"Like data sets package, data set publicly available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":"https://msberends.github.io/AMR/reference/WHONET.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Data Set with 500 Isolates - WHONET Example — WHONET","text":"","code":"WHONET #> # A tibble: 500 × 53 #>    `Identification number` `Specimen number` Organism Country         Laboratory #>    <chr>                               <int> <chr>    <chr>           <chr>      #>  1 fe41d7bafa                           1748 SPN      Belgium         National … #>  2 91f175ec37                           1767 eco      The Netherlands National … #>  3 cc4015056e                           1343 eco      The Netherlands National … #>  4 e864b692f5                           1894 MAP      Denmark         National … #>  5 3d051fe345                           1739 PVU      Belgium         National … #>  6 c80762a08d                           1846 103      The Netherlands National … #>  7 8022d3727c                           1628 103      Denmark         National … #>  8 f3dc5f553d                           1493 eco      The Netherlands National … #>  9 15add38f6c                           1847 eco      France          National … #> 10 fd41248def                           1458 eco      Germany         National … #> # ℹ 490 more rows #> # ℹ 48 more variables: `Last name` <chr>, `First name` <chr>, Sex <chr>, #> #   Age <dbl>, `Age category` <chr>, `Date of admission` <date>, #> #   `Specimen date` <date>, `Specimen type` <chr>, #> #   `Specimen type (Numeric)` <dbl>, Reason <chr>, `Isolate number` <int>, #> #   `Organism type` <chr>, Serotype <chr>, `Beta-lactamase` <lgl>, ESBL <lgl>, #> #   Carbapenemase <lgl>, `MRSA screening test` <lgl>, …"},{"path":"https://msberends.github.io/AMR/reference/ab_from_text.html","id":null,"dir":"Reference","previous_headings":"","what":"Retrieve Antimicrobial Drug Names and Doses from Clinical Text — ab_from_text","title":"Retrieve Antimicrobial Drug Names and Doses from Clinical Text — ab_from_text","text":"Use function e.g. clinical texts health care records. returns list antimicrobial drugs, doses forms administration found texts.","code":""},{"path":"https://msberends.github.io/AMR/reference/ab_from_text.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Retrieve Antimicrobial Drug Names and Doses from Clinical Text — ab_from_text","text":"","code":"ab_from_text(   text,   type = c(\"drug\", \"dose\", \"administration\"),   collapse = NULL,   translate_ab = FALSE,   thorough_search = NULL,   info = interactive(),   ... )"},{"path":"https://msberends.github.io/AMR/reference/ab_from_text.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Retrieve Antimicrobial Drug Names and Doses from Clinical Text — ab_from_text","text":"text text analyse type type property search , either \"drug\", \"dose\" \"administration\", see Examples collapse character pass paste(, collapse = ...) return one character per element text, see Examples translate_ab type = \"drug\": column name antibiotics data set translate antibiotic abbreviations , using ab_property(). default FALSE. Using TRUE equal using \"name\". thorough_search logical indicate whether input must extensively searched misspelling faulty input values. Setting TRUE take considerably time using FALSE. default, turn TRUE input elements contain maximum three words. info logical indicate whether progress bar printed - default TRUE interactive mode ... arguments passed .ab()","code":""},{"path":"https://msberends.github.io/AMR/reference/ab_from_text.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Retrieve Antimicrobial Drug Names and Doses from Clinical Text — ab_from_text","text":"list,  character collapse NULL","code":""},{"path":"https://msberends.github.io/AMR/reference/ab_from_text.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Retrieve Antimicrobial Drug Names and Doses from Clinical Text — ab_from_text","text":"function also internally used .ab(), although searches first drug name throw note drug names returned. Note: .ab() function may use long regular expression match brand names antimicrobial drugs. may fail systems.","code":""},{"path":"https://msberends.github.io/AMR/reference/ab_from_text.html","id":"argument-type","dir":"Reference","previous_headings":"","what":"Argument type","title":"Retrieve Antimicrobial Drug Names and Doses from Clinical Text — ab_from_text","text":"default, function search antimicrobial drug names. text elements searched official names, ATC codes brand names. uses .ab() internally, correct misspelling. type = \"dose\" (similar, like \"dosing\", \"doses\"), text elements searched numeric values higher 100 resemble years. output numeric. supports unit (g, mg, IE, etc.) multiple values one clinical text, see Examples. type = \"administration\" (abbreviations, like \"admin\", \"adm\"), text elements searched form drug administration. supports following forms (including common abbreviations): buccal, implant, inhalation, instillation, intravenous, nasal, oral, parenteral, rectal, sublingual, transdermal vaginal. Abbreviations oral ('po', 'per os') become \"oral\", values intravenous ('iv', 'intraven') become \"iv\". supports multiple values one clinical text, see Examples.","code":""},{"path":"https://msberends.github.io/AMR/reference/ab_from_text.html","id":"argument-collapse","dir":"Reference","previous_headings":"","what":"Argument collapse","title":"Retrieve Antimicrobial Drug Names and Doses from Clinical Text — ab_from_text","text":"Without using collapse, function return list. can convenient use e.g. inside mutate()):df %>% mutate(abx = ab_from_text(clinical_text)) returned AB codes can transformed official names, groups, etc. ab_* functions ab_name() ab_group(), using translate_ab argument. using collapse, function return character:df %>% mutate(abx = ab_from_text(clinical_text, collapse = \"|\"))","code":""},{"path":"https://msberends.github.io/AMR/reference/ab_from_text.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Retrieve Antimicrobial Drug Names and Doses from Clinical Text — ab_from_text","text":"","code":"# mind the bad spelling of amoxicillin in this line, # straight from a true health care record: ab_from_text(\"28/03/2020 regular amoxicilliin 500mg po tid\") #> [[1]] #> Class 'ab' #> [1] AMX #>   ab_from_text(\"500 mg amoxi po and 400mg cipro iv\") #> [[1]] #> Class 'ab' #> [1] AMX CIP #>  ab_from_text(\"500 mg amoxi po and 400mg cipro iv\", type = \"dose\") #> [[1]] #> [1] 500 400 #>  ab_from_text(\"500 mg amoxi po and 400mg cipro iv\", type = \"admin\") #> [[1]] #> [1] \"oral\" \"iv\"   #>   ab_from_text(\"500 mg amoxi po and 400mg cipro iv\", collapse = \", \") #> [1] \"AMX, CIP\" # \\donttest{ # if you want to know which antibiotic groups were administered, do e.g.: abx <- ab_from_text(\"500 mg amoxi po and 400mg cipro iv\") ab_group(abx[[1]]) #> [1] \"Beta-lactams/penicillins\" \"Quinolones\"                if (require(\"dplyr\")) {   tibble(clinical_text = c(     \"given 400mg cipro and 500 mg amox\",     \"started on doxy iv today\"   )) %>%     mutate(       abx_codes = ab_from_text(clinical_text),       abx_doses = ab_from_text(clinical_text, type = \"doses\"),       abx_admin = ab_from_text(clinical_text, type = \"admin\"),       abx_coll = ab_from_text(clinical_text, collapse = \"|\"),       abx_coll_names = ab_from_text(clinical_text,         collapse = \"|\",         translate_ab = \"name\"       ),       abx_coll_doses = ab_from_text(clinical_text,         type = \"doses\",         collapse = \"|\"       ),       abx_coll_admin = ab_from_text(clinical_text,         type = \"admin\",         collapse = \"|\"       )     ) } #> Loading required package: dplyr #>  #> Attaching package: ‘dplyr’ #> The following objects are masked from ‘package:stats’: #>  #>     filter, lag #> The following objects are masked from ‘package:base’: #>  #>     intersect, setdiff, setequal, union #> # A tibble: 2 × 8 #>   clinical_text            abx_codes abx_doses abx_admin abx_coll abx_coll_names #>   <chr>                    <list>    <list>    <list>    <chr>    <chr>          #> 1 given 400mg cipro and 5… <ab [2]>  <dbl [2]> <chr [1]> CIP|AMX  Ciprofloxacin… #> 2 started on doxy iv today <ab [1]>  <dbl [1]> <chr [1]> DOX      Doxycycline    #> # ℹ 2 more variables: abx_coll_doses <chr>, abx_coll_admin <chr> # }"},{"path":"https://msberends.github.io/AMR/reference/ab_property.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Properties of an Antibiotic — ab_property","title":"Get Properties of an Antibiotic — ab_property","text":"Use functions return specific property antibiotic antibiotics data set. input values evaluated internally .ab().","code":""},{"path":"https://msberends.github.io/AMR/reference/ab_property.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Properties of an Antibiotic — ab_property","text":"","code":"ab_name(x, language = get_AMR_locale(), tolower = FALSE, ...)  ab_cid(x, ...)  ab_synonyms(x, ...)  ab_tradenames(x, ...)  ab_group(x, language = get_AMR_locale(), ...)  ab_atc(x, only_first = FALSE, ...)  ab_atc_group1(x, language = get_AMR_locale(), ...)  ab_atc_group2(x, language = get_AMR_locale(), ...)  ab_loinc(x, ...)  ab_ddd(x, administration = \"oral\", ...)  ab_ddd_units(x, administration = \"oral\", ...)  ab_info(x, language = get_AMR_locale(), ...)  ab_url(x, open = FALSE, ...)  ab_property(x, property = \"name\", language = get_AMR_locale(), ...)  set_ab_names(   data,   ...,   property = \"name\",   language = get_AMR_locale(),   snake_case = NULL )"},{"path":"https://msberends.github.io/AMR/reference/ab_property.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Properties of an Antibiotic — ab_property","text":"x (vector ) text can coerced valid antibiotic drug code .ab() language language returned text - default current system language (see get_AMR_locale()) can also set package option AMR_locale. Use language = NULL language = \"\" prevent translation. tolower logical indicate whether first character every output transformed lower case character. lead e.g. \"polymyxin B\" \"polymyxin b\". ... case set_ab_names() data data.frame: columns select (supports tidy selection column1:column4), otherwise arguments passed .ab() only_first logical indicate whether first ATC code must returned, giving preference J0-codes (.e., antimicrobial drug group) administration way administration, either \"oral\" \"iv\" open browse URL using utils::browseURL() property one column names one antibiotics data set: vector_or(colnames(antibiotics), sort = FALSE). data data.frame columns need renamed, character vector column names snake_case logical indicate whether names -called snake case: lower case spaces/slashes replaced underscore (_)","code":""},{"path":"https://msberends.github.io/AMR/reference/ab_property.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Properties of an Antibiotic — ab_property","text":"integer case ab_cid() named list case ab_info() multiple ab_atc()/ab_synonyms()/ab_tradenames() double case ab_ddd() data.frame case set_ab_names() character cases","code":""},{"path":"https://msberends.github.io/AMR/reference/ab_property.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get Properties of an Antibiotic — ab_property","text":"output translated possible. function ab_url() return direct URL official website. warning returned required ATC code available. function set_ab_names() special column renaming function data.frames. renames columns names resemble antimicrobial drugs. always makes sure new column names unique. property = \"atc\" set, preference given ATC codes J-group.","code":""},{"path":"https://msberends.github.io/AMR/reference/ab_property.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get Properties of an Antibiotic — ab_property","text":"World Health Organization () Collaborating Centre Drug Statistics Methodology: https://atcddd.fhi./atc_ddd_index/ European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm","code":""},{"path":"https://msberends.github.io/AMR/reference/ab_property.html","id":"reference-data-publicly-available","dir":"Reference","previous_headings":"","what":"Reference Data Publicly Available","title":"Get Properties of an Antibiotic — ab_property","text":"data sets AMR package (microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) publicly freely available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. also provide tab-separated plain text files machine-readable suitable input software program, laboratory information systems. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/ab_property.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Properties of an Antibiotic — ab_property","text":"","code":"# all properties: ab_name(\"AMX\") #> [1] \"Amoxicillin\" ab_atc(\"AMX\") #> [1] \"J01CA04\" ab_cid(\"AMX\") #> [1] 33613 ab_synonyms(\"AMX\") #>  [1] \"actimoxi\"            \"amoclen\"             \"amolin\"              #>  [4] \"amopen\"              \"amopenixin\"          \"amoxibiotic\"         #>  [7] \"amoxicaps\"           \"amoxicilina\"         \"amoxicillin\"         #> [10] \"amoxicillin hydrate\" \"amoxicilline\"        \"amoxicillinum\"       #> [13] \"amoxiden\"            \"amoxil\"              \"amoxivet\"            #> [16] \"amoxy\"               \"amoxycillin\"         \"amoxyke\"             #> [19] \"anemolin\"            \"aspenil\"             \"atoksilin\"           #> [22] \"biomox\"              \"bristamox\"           \"cemoxin\"             #> [25] \"clamoxyl\"            \"damoxy\"              \"delacillin\"          #> [28] \"demoksil\"            \"dispermox\"           \"efpenix\"             #> [31] \"flemoxin\"            \"hiconcil\"            \"histocillin\"         #> [34] \"hydroxyampicillin\"   \"ibiamox\"             \"imacillin\"           #> [37] \"lamoxy\"              \"largopen\"            \"metafarma capsules\"  #> [40] \"metifarma capsules\"  \"moksilin\"            \"moxacin\"             #> [43] \"moxatag\"             \"ospamox\"             \"pamoxicillin\"        #> [46] \"piramox\"             \"promoxil\"            \"remoxil\"             #> [49] \"robamox\"             \"sawamox pm\"          \"tolodina\"            #> [52] \"topramoxin\"          \"unicillin\"           \"utimox\"              #> [55] \"vetramox\"            ab_tradenames(\"AMX\") #>  [1] \"actimoxi\"            \"amoclen\"             \"amolin\"              #>  [4] \"amopen\"              \"amopenixin\"          \"amoxibiotic\"         #>  [7] \"amoxicaps\"           \"amoxicilina\"         \"amoxicillin\"         #> [10] \"amoxicillin hydrate\" \"amoxicilline\"        \"amoxicillinum\"       #> [13] \"amoxiden\"            \"amoxil\"              \"amoxivet\"            #> [16] \"amoxy\"               \"amoxycillin\"         \"amoxyke\"             #> [19] \"anemolin\"            \"aspenil\"             \"atoksilin\"           #> [22] \"biomox\"              \"bristamox\"           \"cemoxin\"             #> [25] \"clamoxyl\"            \"damoxy\"              \"delacillin\"          #> [28] \"demoksil\"            \"dispermox\"           \"efpenix\"             #> [31] \"flemoxin\"            \"hiconcil\"            \"histocillin\"         #> [34] \"hydroxyampicillin\"   \"ibiamox\"             \"imacillin\"           #> [37] \"lamoxy\"              \"largopen\"            \"metafarma capsules\"  #> [40] \"metifarma capsules\"  \"moksilin\"            \"moxacin\"             #> [43] \"moxatag\"             \"ospamox\"             \"pamoxicillin\"        #> [46] \"piramox\"             \"promoxil\"            \"remoxil\"             #> [49] \"robamox\"             \"sawamox pm\"          \"tolodina\"            #> [52] \"topramoxin\"          \"unicillin\"           \"utimox\"              #> [55] \"vetramox\"            ab_group(\"AMX\") #> [1] \"Beta-lactams/penicillins\" ab_atc_group1(\"AMX\") #> [1] \"Beta-lactam antibacterials, penicillins\" ab_atc_group2(\"AMX\") #> [1] \"Penicillins with extended spectrum\" ab_url(\"AMX\") #>                                                             Amoxicillin  #> \"https://atcddd.fhi.no/atc_ddd_index//?code=J01CA04&showdescription=no\"   # smart lowercase transformation ab_name(x = c(\"AMC\", \"PLB\")) #> [1] \"Amoxicillin/clavulanic acid\" \"Polymyxin B\"                 ab_name(x = c(\"AMC\", \"PLB\"), tolower = TRUE) #> [1] \"amoxicillin/clavulanic acid\" \"polymyxin B\"                  # defined daily doses (DDD) ab_ddd(\"AMX\", \"oral\") #> [1] 1.5 ab_ddd_units(\"AMX\", \"oral\") #> [1] \"g\" ab_ddd(\"AMX\", \"iv\") #> [1] 3 ab_ddd_units(\"AMX\", \"iv\") #> [1] \"g\"  ab_info(\"AMX\") # all properties as a list #> $ab #> [1] \"AMX\" #>  #> $cid #> [1] 33613 #>  #> $name #> [1] \"Amoxicillin\" #>  #> $group #> [1] \"Beta-lactams/penicillins\" #>  #> $atc #> [1] \"J01CA04\" #>  #> $atc_group1 #> [1] \"Beta-lactam antibacterials, penicillins\" #>  #> $atc_group2 #> [1] \"Penicillins with extended spectrum\" #>  #> $tradenames #>  [1] \"actimoxi\"            \"amoclen\"             \"amolin\"              #>  [4] \"amopen\"              \"amopenixin\"          \"amoxibiotic\"         #>  [7] \"amoxicaps\"           \"amoxicilina\"         \"amoxicillin\"         #> [10] \"amoxicillin hydrate\" \"amoxicilline\"        \"amoxicillinum\"       #> [13] \"amoxiden\"            \"amoxil\"              \"amoxivet\"            #> [16] \"amoxy\"               \"amoxycillin\"         \"amoxyke\"             #> [19] \"anemolin\"            \"aspenil\"             \"atoksilin\"           #> [22] \"biomox\"              \"bristamox\"           \"cemoxin\"             #> [25] \"clamoxyl\"            \"damoxy\"              \"delacillin\"          #> [28] \"demoksil\"            \"dispermox\"           \"efpenix\"             #> [31] \"flemoxin\"            \"hiconcil\"            \"histocillin\"         #> [34] \"hydroxyampicillin\"   \"ibiamox\"             \"imacillin\"           #> [37] \"lamoxy\"              \"largopen\"            \"metafarma capsules\"  #> [40] \"metifarma capsules\"  \"moksilin\"            \"moxacin\"             #> [43] \"moxatag\"             \"ospamox\"             \"pamoxicillin\"        #> [46] \"piramox\"             \"promoxil\"            \"remoxil\"             #> [49] \"robamox\"             \"sawamox pm\"          \"tolodina\"            #> [52] \"topramoxin\"          \"unicillin\"           \"utimox\"              #> [55] \"vetramox\"            #>  #> $loinc #>  [1] \"101498-4\" \"15-8\"     \"16-6\"     \"16365-9\"  \"17-4\"     \"18-2\"     #>  [7] \"18861-5\"  \"18862-3\"  \"19-0\"     \"20-8\"     \"21-6\"     \"22-4\"     #> [13] \"25274-2\"  \"25310-4\"  \"3344-9\"   \"55614-2\"  \"55615-9\"  \"55616-7\"  #> [19] \"6976-5\"   \"6977-3\"   \"80133-2\"  #>  #> $ddd #> $ddd$oral #> $ddd$oral$amount #> [1] 1.5 #>  #> $ddd$oral$units #> [1] \"g\" #>  #>  #> $ddd$iv #> $ddd$iv$amount #> [1] 3 #>  #> $ddd$iv$units #> [1] \"g\" #>  #>  #>   # all ab_* functions use as.ab() internally, so you can go from 'any' to 'any': ab_atc(\"AMP\") #> [1] \"J01CA01\" \"S01AA19\" ab_group(\"J01CA01\") #> [1] \"Beta-lactams/penicillins\" ab_loinc(\"ampicillin\") #>  [1] \"101477-8\" \"101478-6\" \"18864-9\"  \"18865-6\"  \"20374-5\"  \"21066-6\"  #>  [7] \"23618-2\"  \"27-3\"     \"28-1\"     \"29-9\"     \"30-7\"     \"31-5\"     #> [13] \"32-3\"     \"33-1\"     \"3355-5\"   \"33562-0\"  \"33919-2\"  \"34-9\"     #> [19] \"43883-8\"  \"43884-6\"  \"6979-9\"   \"6980-7\"   \"87604-5\"  ab_name(\"21066-6\") #> [1] \"Ampicillin\" ab_name(6249) #> [1] \"Ampicillin\" ab_name(\"J01CA01\") #> [1] \"Ampicillin\"  # spelling from different languages and dyslexia are no problem ab_atc(\"ceftriaxon\") #> [1] \"J01DD04\" ab_atc(\"cephtriaxone\") #> [1] \"J01DD04\" ab_atc(\"cephthriaxone\") #> [1] \"J01DD04\" ab_atc(\"seephthriaaksone\") #> [1] \"J01DD04\"  # use set_ab_names() for renaming columns colnames(example_isolates) #>  [1] \"date\"    \"patient\" \"age\"     \"gender\"  \"ward\"    \"mo\"      \"PEN\"     #>  [8] \"OXA\"     \"FLC\"     \"AMX\"     \"AMC\"     \"AMP\"     \"TZP\"     \"CZO\"     #> [15] \"FEP\"     \"CXM\"     \"FOX\"     \"CTX\"     \"CAZ\"     \"CRO\"     \"GEN\"     #> [22] \"TOB\"     \"AMK\"     \"KAN\"     \"TMP\"     \"SXT\"     \"NIT\"     \"FOS\"     #> [29] \"LNZ\"     \"CIP\"     \"MFX\"     \"VAN\"     \"TEC\"     \"TCY\"     \"TGC\"     #> [36] \"DOX\"     \"ERY\"     \"CLI\"     \"AZM\"     \"IPM\"     \"MEM\"     \"MTR\"     #> [43] \"CHL\"     \"COL\"     \"MUP\"     \"RIF\"     colnames(set_ab_names(example_isolates)) #>  [1] \"date\"                          \"patient\"                       #>  [3] \"age\"                           \"gender\"                        #>  [5] \"ward\"                          \"mo\"                            #>  [7] \"benzylpenicillin\"              \"oxacillin\"                     #>  [9] \"flucloxacillin\"                \"amoxicillin\"                   #> [11] \"amoxicillin_clavulanic_acid\"   \"ampicillin\"                    #> [13] \"piperacillin_tazobactam\"       \"cefazolin\"                     #> [15] \"cefepime\"                      \"cefuroxime\"                    #> [17] \"cefoxitin\"                     \"cefotaxime\"                    #> [19] \"ceftazidime\"                   \"ceftriaxone\"                   #> [21] \"gentamicin\"                    \"tobramycin\"                    #> [23] \"amikacin\"                      \"kanamycin\"                     #> [25] \"trimethoprim\"                  \"trimethoprim_sulfamethoxazole\" #> [27] \"nitrofurantoin\"                \"fosfomycin\"                    #> [29] \"linezolid\"                     \"ciprofloxacin\"                 #> [31] \"moxifloxacin\"                  \"vancomycin\"                    #> [33] \"teicoplanin\"                   \"tetracycline\"                  #> [35] \"tigecycline\"                   \"doxycycline\"                   #> [37] \"erythromycin\"                  \"clindamycin\"                   #> [39] \"azithromycin\"                  \"imipenem\"                      #> [41] \"meropenem\"                     \"metronidazole\"                 #> [43] \"chloramphenicol\"               \"colistin\"                      #> [45] \"mupirocin\"                     \"rifampicin\"                    colnames(set_ab_names(example_isolates, NIT:VAN)) #>  [1] \"date\"           \"patient\"        \"age\"            \"gender\"         #>  [5] \"ward\"           \"mo\"             \"PEN\"            \"OXA\"            #>  [9] \"FLC\"            \"AMX\"            \"AMC\"            \"AMP\"            #> [13] \"TZP\"            \"CZO\"            \"FEP\"            \"CXM\"            #> [17] \"FOX\"            \"CTX\"            \"CAZ\"            \"CRO\"            #> [21] \"GEN\"            \"TOB\"            \"AMK\"            \"KAN\"            #> [25] \"TMP\"            \"SXT\"            \"nitrofurantoin\" \"fosfomycin\"     #> [29] \"linezolid\"      \"ciprofloxacin\"  \"moxifloxacin\"   \"vancomycin\"     #> [33] \"TEC\"            \"TCY\"            \"TGC\"            \"DOX\"            #> [37] \"ERY\"            \"CLI\"            \"AZM\"            \"IPM\"            #> [41] \"MEM\"            \"MTR\"            \"CHL\"            \"COL\"            #> [45] \"MUP\"            \"RIF\"            # \\donttest{ if (require(\"dplyr\")) {   example_isolates %>%     set_ab_names()    # this does the same:   example_isolates %>%     rename_with(set_ab_names)    # set_ab_names() works with any AB property:   example_isolates %>%     set_ab_names(property = \"atc\")    example_isolates %>%     set_ab_names(where(is.sir)) %>%     colnames()    example_isolates %>%     set_ab_names(NIT:VAN) %>%     colnames() } #>  [1] \"date\"           \"patient\"        \"age\"            \"gender\"         #>  [5] \"ward\"           \"mo\"             \"PEN\"            \"OXA\"            #>  [9] \"FLC\"            \"AMX\"            \"AMC\"            \"AMP\"            #> [13] \"TZP\"            \"CZO\"            \"FEP\"            \"CXM\"            #> [17] \"FOX\"            \"CTX\"            \"CAZ\"            \"CRO\"            #> [21] \"GEN\"            \"TOB\"            \"AMK\"            \"KAN\"            #> [25] \"TMP\"            \"SXT\"            \"nitrofurantoin\" \"fosfomycin\"     #> [29] \"linezolid\"      \"ciprofloxacin\"  \"moxifloxacin\"   \"vancomycin\"     #> [33] \"TEC\"            \"TCY\"            \"TGC\"            \"DOX\"            #> [37] \"ERY\"            \"CLI\"            \"AZM\"            \"IPM\"            #> [41] \"MEM\"            \"MTR\"            \"CHL\"            \"COL\"            #> [45] \"MUP\"            \"RIF\"            # }"},{"path":"https://msberends.github.io/AMR/reference/add_custom_antimicrobials.html","id":null,"dir":"Reference","previous_headings":"","what":"Add Custom Antimicrobials — add_custom_antimicrobials","title":"Add Custom Antimicrobials — add_custom_antimicrobials","text":"add_custom_antimicrobials() can add custom antimicrobial drug names codes.","code":""},{"path":"https://msberends.github.io/AMR/reference/add_custom_antimicrobials.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add Custom Antimicrobials — add_custom_antimicrobials","text":"","code":"add_custom_antimicrobials(x)  clear_custom_antimicrobials()"},{"path":"https://msberends.github.io/AMR/reference/add_custom_antimicrobials.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add Custom Antimicrobials — add_custom_antimicrobials","text":"x data.frame resembling antibiotics data set, least containing columns \"ab\" \"name\"","code":""},{"path":"https://msberends.github.io/AMR/reference/add_custom_antimicrobials.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Add Custom Antimicrobials — add_custom_antimicrobials","text":"Important: Due R works, add_custom_antimicrobials() function run every R session - added antimicrobials stored sessions thus lost R exited. two ways circumvent automate process adding antimicrobials: Method 1: Using package option AMR_custom_ab, preferred method. use method: Create data set structure antibiotics data set (containing least columns \"ab\" \"name\") save saveRDS() location choice, e.g. \"~/my_custom_ab.rds\", remote location. Set file location package option AMR_custom_ab: options(AMR_custom_ab = \"~/my_custom_ab.rds\"). can even remote file location, https URL. Since options saved R sessions, best save option .Rprofile file loaded start-R. , open .Rprofile file using e.g. utils::file.edit(\"~/.Rprofile\"), add text save file:   Upon package load, file loaded run add_custom_antimicrobials() function. Method 2: Loading antimicrobial additions directly .Rprofile file. Note definitions stored user-specific R file, suboptimal workflow. use method: Edit .Rprofile file using e.g. utils::file.edit(\"~/.Rprofile\"). Add text like save file:   Use clear_custom_antimicrobials() clear previously added antimicrobials.","code":"# Add custom antimicrobial codes: options(AMR_custom_ab = \"~/my_custom_ab.rds\") # Add custom antibiotic drug codes:  AMR::add_custom_antimicrobials(    data.frame(ab = \"TESTAB\",               name = \"Test Antibiotic\",               group = \"Test Group\")  )"},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/add_custom_antimicrobials.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add Custom Antimicrobials — add_custom_antimicrobials","text":"","code":"# \\donttest{  # returns NA and throws a warning (which is suppressed here): suppressWarnings(   as.ab(\"testab\") ) #> Class 'ab' #> [1] <NA>  # now add a custom entry - it will be considered by as.ab() and # all ab_*() functions add_custom_antimicrobials(   data.frame(     ab = \"TESTAB\",     name = \"Test Antibiotic\",     # you can add any property present in the     # 'antibiotics' data set, such as 'group':     group = \"Test Group\"   ) ) #> ℹ Added one record to the internal antibiotics data set.  # \"testab\" is now a new antibiotic: as.ab(\"testab\") #> Class 'ab' #> [1] TESTAB ab_name(\"testab\") #> [1] \"Test Antibiotic\" ab_group(\"testab\") #> [1] \"Test Group\"  ab_info(\"testab\") #> $ab #> [1] \"TESTAB\" #>  #> $cid #> [1] NA #>  #> $name #> [1] \"Test Antibiotic\" #>  #> $group #> [1] \"Test Group\" #>  #> $atc #> [1] NA #>  #> $atc_group1 #> [1] NA #>  #> $atc_group2 #> [1] NA #>  #> $tradenames #> [1] NA #>  #> $loinc #> [1] NA #>  #> $ddd #> $ddd$oral #> $ddd$oral$amount #> [1] NA #>  #> $ddd$oral$units #> [1] NA #>  #>  #> $ddd$iv #> $ddd$iv$amount #> [1] NA #>  #> $ddd$iv$units #> [1] NA #>  #>  #>    # Add Co-fluampicil, which is one of the many J01CR50 codes, see # https://atcddd.fhi.no/ddd/list_of_ddds_combined_products/ add_custom_antimicrobials(   data.frame(     ab = \"COFLU\",     name = \"Co-fluampicil\",     atc = \"J01CR50\",     group = \"Beta-lactams/penicillins\"   ) ) #> ℹ Added one record to the internal antibiotics data set. ab_atc(\"Co-fluampicil\") #> [1] \"J01CR50\" ab_name(\"J01CR50\") #> [1] \"Co-fluampicil\"  # even antibiotic selectors work x <- data.frame(   random_column = \"some value\",   coflu = as.sir(\"S\"),   ampicillin = as.sir(\"R\") ) x #>   random_column coflu ampicillin #> 1    some value     S          R x[, betalactams()] #> ℹ For betalactams() using columns 'coflu' (co-fluampicil) and #>   'ampicillin' #>   coflu ampicillin #> 1     S          R # }"},{"path":"https://msberends.github.io/AMR/reference/add_custom_microorganisms.html","id":null,"dir":"Reference","previous_headings":"","what":"Add Custom Microorganisms — add_custom_microorganisms","title":"Add Custom Microorganisms — add_custom_microorganisms","text":"add_custom_microorganisms() can add custom microorganisms, non-taxonomic outcome laboratory analysis.","code":""},{"path":"https://msberends.github.io/AMR/reference/add_custom_microorganisms.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add Custom Microorganisms — add_custom_microorganisms","text":"","code":"add_custom_microorganisms(x)  clear_custom_microorganisms()"},{"path":"https://msberends.github.io/AMR/reference/add_custom_microorganisms.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add Custom Microorganisms — add_custom_microorganisms","text":"x data.frame resembling microorganisms data set, least containing column \"genus\" (case-insensitive)","code":""},{"path":"https://msberends.github.io/AMR/reference/add_custom_microorganisms.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Add Custom Microorganisms — add_custom_microorganisms","text":"function fill missing taxonomy , specific taxonomic columns missing, see Examples. Important: Due R works, add_custom_microorganisms() function run every R session - added microorganisms stored sessions thus lost R exited. two ways circumvent automate process adding microorganisms: Method 1: Using package option AMR_custom_mo, preferred method. use method: Create data set structure microorganisms data set (containing least column \"genus\") save saveRDS() location choice, e.g. \"~/my_custom_mo.rds\", remote location. Set file location package option AMR_custom_mo: options(AMR_custom_mo = \"~/my_custom_mo.rds\"). can even remote file location, https URL. Since options saved R sessions, best save option .Rprofile file loaded start-R. , open .Rprofile file using e.g. utils::file.edit(\"~/.Rprofile\"), add text save file:   Upon package load, file loaded run add_custom_microorganisms() function. Method 2: Loading microorganism directly .Rprofile file. Note definitions stored user-specific R file, suboptimal workflow. use method: Edit .Rprofile file using e.g. utils::file.edit(\"~/.Rprofile\"). Add text like save file:   Use clear_custom_microorganisms() clear previously added microorganisms.","code":"# Add custom microorganism codes: options(AMR_custom_mo = \"~/my_custom_mo.rds\") # Add custom antibiotic drug codes:  AMR::add_custom_microorganisms(    data.frame(genus = \"Enterobacter\",               species = \"asburiae/cloacae\")  )"},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/add_custom_microorganisms.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add Custom Microorganisms — add_custom_microorganisms","text":"","code":"# \\donttest{ # a combination of species is not formal taxonomy, so # this will result in \"Enterobacter cloacae cloacae\", # since it resembles the input best: mo_name(\"Enterobacter asburiae/cloacae\") #> [1] \"Enterobacter asburiae\"  # now add a custom entry - it will be considered by as.mo() and # all mo_*() functions add_custom_microorganisms(   data.frame(     genus = \"Enterobacter\",     species = \"asburiae/cloacae\"   ) ) #> ℹ Added Enterobacter asburiae/cloacae to the internal microorganisms data #>   set.  # E. asburiae/cloacae is now a new microorganism: mo_name(\"Enterobacter asburiae/cloacae\") #> [1] \"Enterobacter asburiae/cloacae\"  # its code: as.mo(\"Enterobacter asburiae/cloacae\") #> Class 'mo' #> [1] CUSTOM1_ENTRB_ASB/  # all internal algorithms will work as well: mo_name(\"Ent asburia cloacae\") #> [1] \"Enterobacter asburiae/cloacae\"  # and even the taxonomy was added based on the genus! mo_family(\"E. asburiae/cloacae\") #> [1] \"Enterobacteriaceae\" mo_gramstain(\"Enterobacter asburiae/cloacae\") #> [1] \"Gram-negative\"  mo_info(\"Enterobacter asburiae/cloacae\") #> $mo #> [1] \"CUSTOM1_ENTRB_ASB/\" #>  #> $kingdom #> [1] \"Bacteria\" #>  #> $phylum #> [1] \"Pseudomonadota\" #>  #> $class #> [1] \"Gammaproteobacteria\" #>  #> $order #> [1] \"Enterobacterales\" #>  #> $family #> [1] \"Enterobacteriaceae\" #>  #> $genus #> [1] \"Enterobacter\" #>  #> $species #> [1] \"asburiae/cloacae\" #>  #> $subspecies #> [1] \"\" #>  #> $status #> [1] \"accepted\" #>  #> $synonyms #> NULL #>  #> $gramstain #> [1] \"Gram-negative\" #>  #> $oxygen_tolerance #> [1] NA #>  #> $url #> [1] \"\" #>  #> $ref #> [1] \"Self-added, 2024\" #>  #> $snomed #> [1] NA #>  #> $lpsn #> [1] NA #>  #> $gbif #> [1] NA #>  #> $group_members #> character(0) #>    # the function tries to be forgiving: add_custom_microorganisms(   data.frame(     GENUS = \"BACTEROIDES / PARABACTEROIDES SLASHLINE\",     SPECIES = \"SPECIES\"   ) ) #> ℹ Added Bacteroides/Parabacteroides to the internal microorganisms data #>   set. mo_name(\"BACTEROIDES / PARABACTEROIDES\") #> [1] \"Bacteroides/Parabacteroides\" mo_rank(\"BACTEROIDES / PARABACTEROIDES\") #> [1] \"genus\"  # taxonomy still works, even though a slashline genus was given as input: mo_family(\"Bacteroides/Parabacteroides\") #> [1] \"Bacteroidaceae\"   # for groups and complexes, set them as species or subspecies: add_custom_microorganisms(   data.frame(     genus = \"Citrobacter\",     species = c(\"freundii\", \"braakii complex\"),     subspecies = c(\"complex\", \"\")   ) ) #> ℹ Added Citrobacter braakii complex and Citrobacter freundii complex to the #>   internal microorganisms data set. mo_name(c(\"C. freundii complex\", \"C. braakii complex\")) #> [1] \"Citrobacter freundii complex\" \"Citrobacter braakii complex\"  mo_species(c(\"C. freundii complex\", \"C. braakii complex\")) #> [1] \"freundii complex\" \"braakii complex\"  mo_gramstain(c(\"C. freundii complex\", \"C. braakii complex\")) #> [1] \"Gram-negative\" \"Gram-negative\" # }"},{"path":"https://msberends.github.io/AMR/reference/age.html","id":null,"dir":"Reference","previous_headings":"","what":"Age in Years of Individuals — age","title":"Age in Years of Individuals — age","text":"Calculates age years based reference date, system date default.","code":""},{"path":"https://msberends.github.io/AMR/reference/age.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Age in Years of Individuals — age","text":"","code":"age(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...)"},{"path":"https://msberends.github.io/AMR/reference/age.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Age in Years of Individuals — age","text":"x date(s), character (vectors) coerced .POSIXlt() reference reference date(s) (default today), character (vectors) coerced .POSIXlt() exact logical indicate whether age calculation exact, .e. decimals. divides number days year--date (YTD) x number days year reference (either 365 366). na.rm logical indicate whether missing values removed ... arguments passed .POSIXlt(), origin","code":""},{"path":"https://msberends.github.io/AMR/reference/age.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Age in Years of Individuals — age","text":"integer (decimals) exact = FALSE, double (decimals) otherwise","code":""},{"path":"https://msberends.github.io/AMR/reference/age.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Age in Years of Individuals — age","text":"Ages 0 returned NA warning. Ages 120 give warning. function vectorises x reference, meaning either can length 1 argument larger length.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/age.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Age in Years of Individuals — age","text":"","code":"# 10 random pre-Y2K birth dates df <- data.frame(birth_date = as.Date(\"2000-01-01\") - runif(10) * 25000)  # add ages df$age <- age(df$birth_date)  # add exact ages df$age_exact <- age(df$birth_date, exact = TRUE)  # add age at millenium switch df$age_at_y2k <- age(df$birth_date, \"2000-01-01\")  df #>    birth_date age age_exact age_at_y2k #> 1  1965-12-05  58  58.54918         34 #> 2  1980-03-01  44  44.31148         19 #> 3  1949-11-01  74  74.64208         50 #> 4  1947-02-14  77  77.35519         52 #> 5  1940-02-19  84  84.34153         59 #> 6  1988-01-10  36  36.45082         11 #> 7  1997-08-27  26  26.82240          2 #> 8  1978-01-26  46  46.40710         21 #> 9  1972-06-17  52  52.01639         27 #> 10 1986-08-10  37  37.86885         13"},{"path":"https://msberends.github.io/AMR/reference/age_groups.html","id":null,"dir":"Reference","previous_headings":"","what":"Split Ages into Age Groups — age_groups","title":"Split Ages into Age Groups — age_groups","text":"Split ages age groups defined split argument. allows easier demographic (antimicrobial resistance) analysis.","code":""},{"path":"https://msberends.github.io/AMR/reference/age_groups.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Split Ages into Age Groups — age_groups","text":"","code":"age_groups(x, split_at = c(12, 25, 55, 75), na.rm = FALSE)"},{"path":"https://msberends.github.io/AMR/reference/age_groups.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Split Ages into Age Groups — age_groups","text":"x age, e.g. calculated age() split_at values split x - default age groups 0-11, 12-24, 25-54, 55-74 75+. See Details. na.rm logical indicate whether missing values removed","code":""},{"path":"https://msberends.github.io/AMR/reference/age_groups.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Split Ages into Age Groups — age_groups","text":"Ordered factor","code":""},{"path":"https://msberends.github.io/AMR/reference/age_groups.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Split Ages into Age Groups — age_groups","text":"split ages, input split_at argument can : numeric vector. value e.g. c(10, 20) split x 0-9, 10-19 20+. value 50 split x 0-49 50+. default split young children (0-11), youth (12-24), young adults (25-54), middle-aged adults (55-74) elderly (75+). character: \"children\" \"kids\", equivalent : c(0, 1, 2, 4, 6, 13, 18). split 0, 1, 2-3, 4-5, 6-12, 13-17 18+. \"elderly\" \"seniors\", equivalent : c(65, 75, 85). split 0-64, 65-74, 75-84, 85+. \"fives\", equivalent : 1:20 * 5. split 0-4, 5-9, ..., 95-99, 100+. \"tens\", equivalent : 1:10 * 10. split 0-9, 10-19, ..., 90-99, 100+.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/age_groups.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Split Ages into Age Groups — age_groups","text":"","code":"ages <- c(3, 8, 16, 54, 31, 76, 101, 43, 21)  # split into 0-49 and 50+ age_groups(ages, 50) #> [1] 0-49 0-49 0-49 50+  0-49 50+  50+  0-49 0-49 #> Levels: 0-49 < 50+  # split into 0-19, 20-49 and 50+ age_groups(ages, c(20, 50)) #> [1] 0-19  0-19  0-19  50+   20-49 50+   50+   20-49 20-49 #> Levels: 0-19 < 20-49 < 50+  # split into groups of ten years age_groups(ages, 1:10 * 10) #> [1] 0-9   0-9   10-19 50-59 30-39 70-79 100+  40-49 20-29 #> 11 Levels: 0-9 < 10-19 < 20-29 < 30-39 < 40-49 < 50-59 < 60-69 < ... < 100+ age_groups(ages, split_at = \"tens\") #> [1] 0-9   0-9   10-19 50-59 30-39 70-79 100+  40-49 20-29 #> 11 Levels: 0-9 < 10-19 < 20-29 < 30-39 < 40-49 < 50-59 < 60-69 < ... < 100+  # split into groups of five years age_groups(ages, 1:20 * 5) #> [1] 0-4   5-9   15-19 50-54 30-34 75-79 100+  40-44 20-24 #> 21 Levels: 0-4 < 5-9 < 10-14 < 15-19 < 20-24 < 25-29 < 30-34 < ... < 100+ age_groups(ages, split_at = \"fives\") #> [1] 0-4   5-9   15-19 50-54 30-34 75-79 100+  40-44 20-24 #> 21 Levels: 0-4 < 5-9 < 10-14 < 15-19 < 20-24 < 25-29 < 30-34 < ... < 100+  # split specifically for children age_groups(ages, c(1, 2, 4, 6, 13, 18)) #> [1] 2-3   6-12  13-17 18+   18+   18+   18+   18+   18+   #> Levels: 0 < 1 < 2-3 < 4-5 < 6-12 < 13-17 < 18+ age_groups(ages, \"children\") #> [1] 2-3   6-12  13-17 18+   18+   18+   18+   18+   18+   #> Levels: 0 < 1 < 2-3 < 4-5 < 6-12 < 13-17 < 18+  # \\donttest{ # resistance of ciprofloxacin per age group if (require(\"dplyr\") && require(\"ggplot2\")) {   example_isolates %>%     filter_first_isolate() %>%     filter(mo == as.mo(\"Escherichia coli\")) %>%     group_by(age_group = age_groups(age)) %>%     select(age_group, CIP) %>%     ggplot_sir(       x = \"age_group\",       minimum = 0,       x.title = \"Age Group\",       title = \"Ciprofloxacin resistance per age group\"     ) } #> Loading required package: ggplot2  # }"},{"path":"https://msberends.github.io/AMR/reference/antibiogram.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted-Incidence Syndromic Combination (WISCA) — antibiogram","title":"Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted-Incidence Syndromic Combination (WISCA) — antibiogram","text":"Generate antibiogram, communicate results plots tables. functions follow logic Klinker et al. Barbieri et al. (see Source), allow reporting e.g. R Markdown Quarto well.","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiogram.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted-Incidence Syndromic Combination (WISCA) — antibiogram","text":"","code":"antibiogram(   x,   antibiotics = where(is.sir),   mo_transform = \"shortname\",   ab_transform = NULL,   syndromic_group = NULL,   add_total_n = TRUE,   only_all_tested = FALSE,   digits = 0,   col_mo = NULL,   language = get_AMR_locale(),   minimum = 30,   combine_SI = TRUE,   sep = \" + \",   info = interactive() )  # S3 method for antibiogram plot(x, ...)  # S3 method for antibiogram autoplot(object, ...)  # S3 method for antibiogram knit_print(   x,   italicise = TRUE,   na = getOption(\"knitr.kable.NA\", default = \"\"),   ... )"},{"path":"https://msberends.github.io/AMR/reference/antibiogram.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted-Incidence Syndromic Combination (WISCA) — antibiogram","text":"Klinker KP et al. (2021). Antimicrobial stewardship antibiograms: importance moving beyond traditional antibiograms. Therapeutic Advances Infectious Disease, May 5;8:20499361211011373; doi:10.1177/20499361211011373 Barbieri E et al. (2021). Development Weighted-Incidence Syndromic Combination Antibiogram (WISCA) guide choice empiric antibiotic treatment urinary tract infection paediatric patients: Bayesian approach Antimicrobial Resistance & Infection Control May 1;10(1):74; doi:10.1186/s13756-021-00939-2 M39 Analysis Presentation Cumulative Antimicrobial Susceptibility Test Data, 5th Edition, 2022, Clinical Laboratory Standards Institute (CLSI). https://clsi.org/standards/products/microbiology/documents/m39/.","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiogram.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted-Incidence Syndromic Combination (WISCA) — antibiogram","text":"x data.frame containing least column microorganisms columns antibiotic results (class 'sir', see .sir()) antibiotics vector antibiotic name code (evaluated .ab(), column name x, (combinations ) antibiotic selectors aminoglycosides() carbapenems(). combination antibiograms, can also set values separated \"+\", \"TZP+TOB\" \"cipro + genta\", given columns resembling antibiotics exist x. See Examples. mo_transform character transform microorganism input - must \"name\", \"shortname\", \"gramstain\", one column names microorganisms data set: \"mo\", \"fullname\", \"status\", \"kingdom\", \"phylum\", \"class\", \"order\", \"family\", \"genus\", \"species\", \"subspecies\", \"rank\", \"ref\", \"oxygen_tolerance\", \"source\", \"lpsn\", \"lpsn_parent\", \"lpsn_renamed_to\", \"gbif\", \"gbif_parent\", \"gbif_renamed_to\", \"prevalence\", \"snomed\". Can also NULL transform input. ab_transform character transform antibiotic input - must one column names antibiotics data set: \"ab\", \"cid\", \"name\", \"group\", \"atc\", \"atc_group1\", \"atc_group2\", \"abbreviations\", \"synonyms\", \"oral_ddd\", \"oral_units\", \"iv_ddd\", \"iv_units\", \"loinc\". Can also NULL transform input. syndromic_group column name x, values calculated split rows x, e.g. using ifelse() case_when(). See Examples. add_total_n logical indicate whether total available numbers per pathogen added table (default TRUE). add lowest highest number available isolate per antibiotic (e.g, E. coli 200 isolates available ciprofloxacin 150 amoxicillin, returned number \"150-200\"). only_all_tested (combination antibiograms): logical indicate isolates must tested antibiotics, see Details digits number digits use rounding col_mo column name names codes microorganisms (see .mo()) - default first column class mo. Values coerced using .mo(). language language translate text, defaults system language (see get_AMR_locale()) minimum minimum allowed number available (tested) isolates. isolate count lower minimum return NA warning. default number 30 isolates advised Clinical Laboratory Standards Institute (CLSI) best practice, see Source. combine_SI logical indicate whether susceptibility determined results either S , instead S (default TRUE) sep separating character antibiotic columns combination antibiograms info logical indicate info printed - default TRUE interactive mode ... used R Markdown Quarto: arguments passed knitr::kable() (otherwise, use) object antibiogram() object italicise logical indicate whether microorganism names knitr table made italic, using italicise_taxonomy(). na character use showing NA values","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiogram.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted-Incidence Syndromic Combination (WISCA) — antibiogram","text":"function returns table values 0 100 susceptibility, resistance. Remember filter data let contain first isolates! needed exclude duplicates reduce selection bias. Use first_isolate() determine data set one four available algorithms. types antibiograms listed can plotted (using ggplot2::autoplot() base R plot()/barplot()). antibiogram object can also used directly R Markdown / Quarto (.e., knitr) reports. case, knitr::kable() applied automatically microorganism names even printed italics default (see argument italicise). can also use functions specific 'table reporting' packages transform output antibiogram() needs, e.g. flextable::as_flextable() gt::gt().","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiogram.html","id":"antibiogram-types","dir":"Reference","previous_headings":"","what":"Antibiogram Types","title":"Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted-Incidence Syndromic Combination (WISCA) — antibiogram","text":"four antibiogram types, proposed Klinker et al. (2021, doi:10.1177/20499361211011373 ), supported antibiogram(): Traditional Antibiogram Case example: Susceptibility Pseudomonas aeruginosa piperacillin/tazobactam (TZP) Code example:   Combination Antibiogram Case example: Additional susceptibility Pseudomonas aeruginosa TZP + tobramycin versus TZP alone Code example:   Syndromic Antibiogram Case example: Susceptibility Pseudomonas aeruginosa TZP among respiratory specimens (obtained among ICU patients ) Code example:   Weighted-Incidence Syndromic Combination Antibiogram (WISCA) Case example: Susceptibility Pseudomonas aeruginosa TZP among respiratory specimens (obtained among ICU patients ) male patients age >=65 years heart failure Code example:   Note combination antibiograms, important realise susceptibility can calculated two ways, can set only_all_tested argument (default FALSE). See example two antibiotics, Drug Drug B, antibiogram() works calculate %SI:","code":"antibiogram(your_data,             antibiotics = \"TZP\") antibiogram(your_data,             antibiotics = c(\"TZP\", \"TZP+TOB\", \"TZP+GEN\")) antibiogram(your_data,             antibiotics = penicillins(),             syndromic_group = \"ward\") library(dplyr) your_data %>%   filter(ward == \"ICU\" & specimen_type == \"Respiratory\") %>%   antibiogram(antibiotics = c(\"TZP\", \"TZP+TOB\", \"TZP+GEN\"),               syndromic_group = ifelse(.$age >= 65 &                                          .$gender == \"Male\" &                                          .$condition == \"Heart Disease\",                                        \"Study Group\", \"Control Group\")) --------------------------------------------------------------------                     only_all_tested = FALSE  only_all_tested = TRUE                     -----------------------  -----------------------  Drug A    Drug B   include as  include as   include as  include as                     numerator   denominator  numerator   denominator --------  --------  ----------  -----------  ----------  -----------  S or I    S or I       X            X            X            X    R       S or I       X            X            X            X   <NA>     S or I       X            X            -            -  S or I      R          X            X            X            X    R         R          -            X            -            X   <NA>       R          -            -            -            -  S or I     <NA>        X            X            -            -    R        <NA>        -            -            -            -   <NA>      <NA>        -            -            -            - --------------------------------------------------------------------"},{"path":"https://msberends.github.io/AMR/reference/antibiogram.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted-Incidence Syndromic Combination (WISCA) — antibiogram","text":"","code":"# example_isolates is a data set available in the AMR package. # run ?example_isolates for more info. example_isolates #> # A tibble: 2,000 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-03 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  3 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  4 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  5 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  6 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  7 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  8 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  9 2002-01-16 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #> 10 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R     NA    S     NA    #> # ℹ 1,990 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, …  # \\donttest{ # Traditional antibiogram ----------------------------------------------  antibiogram(example_isolates,   antibiotics = c(aminoglycosides(), carbapenems()) ) #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> # A tibble: 10 × 7 #>    `Pathogen (N min-max)`   AMK   GEN   IPM   KAN   MEM   TOB #>  * <chr>                  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #>  1 CoNS (43-309)              0    86    52     0    52    22 #>  2 E. coli (0-462)          100    98   100    NA   100    97 #>  3 E. faecalis (0-39)         0     0   100     0    NA     0 #>  4 K. pneumoniae (0-58)      NA    90   100    NA   100    90 #>  5 P. aeruginosa (17-30)     NA   100    NA     0    NA   100 #>  6 P. mirabilis (0-34)       NA    94    94    NA    NA    94 #>  7 S. aureus (2-233)         NA    99    NA    NA    NA    98 #>  8 S. epidermidis (8-163)     0    79    NA     0    NA    51 #>  9 S. hominis (3-80)         NA    92    NA    NA    NA    85 #> 10 S. pneumoniae (11-117)     0     0    NA     0    NA     0  antibiogram(example_isolates,   antibiotics = aminoglycosides(),   ab_transform = \"atc\",   mo_transform = \"gramstain\" ) #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> # A tibble: 2 × 5 #>   `Pathogen (N min-max)`   J01GB01 J01GB03 J01GB04 J01GB06 #> * <chr>                      <dbl>   <dbl>   <dbl>   <dbl> #> 1 Gram-negative (35-686)        96      96       0      98 #> 2 Gram-positive (436-1170)      34      63       0       0  antibiogram(example_isolates,   antibiotics = carbapenems(),   ab_transform = \"name\",   mo_transform = \"name\" ) #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> # A tibble: 5 × 3 #>   `Pathogen (N min-max)`                           Imipenem Meropenem #> * <chr>                                               <dbl>     <dbl> #> 1 Coagulase-negative Staphylococcus (CoNS) (48-48)       52        52 #> 2 Enterococcus faecalis (0-38)                          100        NA #> 3 Escherichia coli (418-422)                            100       100 #> 4 Klebsiella pneumoniae (51-53)                         100       100 #> 5 Proteus mirabilis (27-32)                              94        NA   # Combined antibiogram -------------------------------------------------  # combined antibiotics yield higher empiric coverage antibiogram(example_isolates,   antibiotics = c(\"TZP\", \"TZP+TOB\", \"TZP+GEN\"),   mo_transform = \"gramstain\" ) #> # A tibble: 2 × 4 #>   `Pathogen (N min-max)`     TZP `TZP + GEN` `TZP + TOB` #> * <chr>                    <dbl>       <dbl>       <dbl> #> 1 Gram-negative (641-693)     88          99          98 #> 2 Gram-positive (345-1044)    86          98          95  # names of antibiotics do not need to resemble columns exactly: antibiogram(example_isolates,   antibiotics = c(\"Cipro\", \"cipro + genta\"),   mo_transform = \"gramstain\",   ab_transform = \"name\",   sep = \" & \" ) #> # A tibble: 2 × 3 #>   `Pathogen (N min-max)`  Ciprofloxacin `Ciprofloxacin & Gentamicin` #> * <chr>                           <dbl>                        <dbl> #> 1 Gram-negative (684-694)            91                           99 #> 2 Gram-positive (724-847)            77                           93   # Syndromic antibiogram ------------------------------------------------  # the data set could contain a filter for e.g. respiratory specimens antibiogram(example_isolates,   antibiotics = c(aminoglycosides(), carbapenems()),   syndromic_group = \"ward\" ) #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> # A tibble: 14 × 8 #>    `Syndromic Group` `Pathogen (N min-max)`   AMK   GEN   IPM   KAN   MEM   TOB #>  * <chr>             <chr>                  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #>  1 Clinical          CoNS (23-205)             NA    89    57    NA    57    26 #>  2 ICU               CoNS (10-73)              NA    79    NA    NA    NA    NA #>  3 Outpatient        CoNS (3-31)               NA    84    NA    NA    NA    NA #>  4 Clinical          E. coli (0-299)          100    98   100    NA   100    98 #>  5 ICU               E. coli (0-137)          100    99   100    NA   100    96 #>  6 Clinical          K. pneumoniae (0-51)      NA    92   100    NA   100    92 #>  7 Clinical          P. mirabilis (0-30)       NA   100    NA    NA    NA   100 #>  8 Clinical          S. aureus (2-150)         NA    99    NA    NA    NA    97 #>  9 ICU               S. aureus (0-66)          NA   100    NA    NA    NA    NA #> 10 Clinical          S. epidermidis (4-79)     NA    82    NA    NA    NA    55 #> 11 ICU               S. epidermidis (4-75)     NA    72    NA    NA    NA    41 #> 12 Clinical          S. hominis (1-45)         NA    96    NA    NA    NA    94 #> 13 Clinical          S. pneumoniae (5-78)       0     0    NA     0    NA     0 #> 14 ICU               S. pneumoniae (5-30)       0     0    NA     0    NA     0  # now define a data set with only E. coli ex1 <- example_isolates[which(mo_genus() == \"Escherichia\"), ] #> ℹ Using column 'mo' as input for mo_genus()  # with a custom language, though this will be determined automatically # (i.e., this table will be in Spanish on Spanish systems) antibiogram(ex1,   antibiotics = aminoglycosides(),   ab_transform = \"name\",   syndromic_group = ifelse(ex1$ward == \"ICU\",     \"UCI\", \"No UCI\"   ),   language = \"es\" ) #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> # A tibble: 2 × 5 #>   `Grupo sindrómico` `Patógeno (N min-max)` Amikacina Gentamicina Tobramicina #> * <chr>              <chr>                      <dbl>       <dbl>       <dbl> #> 1 No UCI             E. coli (0-325)              100          98          98 #> 2 UCI                E. coli (0-137)              100          99          96   # Weighted-incidence syndromic combination antibiogram (WISCA) ---------  # the data set could contain a filter for e.g. respiratory specimens/ICU antibiogram(example_isolates,   antibiotics = c(\"AMC\", \"AMC+CIP\", \"TZP\", \"TZP+TOB\"),   mo_transform = \"gramstain\",   minimum = 10, # this should be >=30, but now just as example   syndromic_group = ifelse(example_isolates$age >= 65 &     example_isolates$gender == \"M\",   \"WISCA Group 1\", \"WISCA Group 2\"   ) ) #> # A tibble: 4 × 6 #>   `Syndromic Group` `Pathogen (N min-max)`    AMC `AMC + CIP`   TZP `TZP + TOB` #> * <chr>             <chr>                   <dbl>       <dbl> <dbl>       <dbl> #> 1 WISCA Group 1     Gram-negative (261-285)    76          95    89          99 #> 2 WISCA Group 2     Gram-negative (380-442)    76          98    88          98 #> 3 WISCA Group 1     Gram-positive (123-406)    76          89    81          95 #> 4 WISCA Group 2     Gram-positive (222-732)    76          89    88          95   # Print the output for R Markdown / Quarto -----------------------------  ureido <- antibiogram(example_isolates,   antibiotics = ureidopenicillins(),   ab_transform = \"name\" ) #> ℹ For ureidopenicillins() using column 'TZP' (piperacillin/tazobactam)  # in an Rmd file, you would just need to return `ureido` in a chunk, # but to be explicit here: if (requireNamespace(\"knitr\")) {   cat(knitr::knit_print(ureido)) } #>  #>  #> |Pathogen (N)          | Piperacillin/tazobactam| #> |:---------------------|-----------------------:| #> |CoNS (33)             |                      30| #> |*E. coli* (416)       |                      94| #> |*K. pneumoniae* (53)  |                      89| #> |*S. pneumoniae* (112) |                     100|   # Generate plots with ggplot2 or base R --------------------------------  ab1 <- antibiogram(example_isolates,   antibiotics = c(\"AMC\", \"CIP\", \"TZP\", \"TZP+TOB\"),   mo_transform = \"gramstain\" ) ab2 <- antibiogram(example_isolates,   antibiotics = c(\"AMC\", \"CIP\", \"TZP\", \"TZP+TOB\"),   mo_transform = \"gramstain\",   syndromic_group = \"ward\" )  if (requireNamespace(\"ggplot2\")) {   ggplot2::autoplot(ab1) }  if (requireNamespace(\"ggplot2\")) {   ggplot2::autoplot(ab2) }   plot(ab1)  plot(ab2)  # }"},{"path":"https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html","id":null,"dir":"Reference","previous_headings":"","what":"Antibiotic Selectors — antibiotic_class_selectors","title":"Antibiotic Selectors — antibiotic_class_selectors","text":"functions allow filtering rows selecting columns based antibiotic test results specific antibiotic class group (according antibiotics data set), without need define columns antibiotic abbreviations. short, column name resembles antimicrobial drug, picked functions matches pharmaceutical class: \"cefazolin\", \"kefzol\", \"CZO\" \"J01DB04\" picked cephalosporins().","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Antibiotic Selectors — antibiotic_class_selectors","text":"","code":"ab_class(ab_class, only_sir_columns = FALSE, only_treatable = TRUE, ...)  ab_selector(filter, only_sir_columns = FALSE, only_treatable = TRUE, ...)  aminoglycosides(only_sir_columns = FALSE, only_treatable = TRUE, ...)  aminopenicillins(only_sir_columns = FALSE, ...)  antifungals(only_sir_columns = FALSE, ...)  antimycobacterials(only_sir_columns = FALSE, ...)  betalactams(only_sir_columns = FALSE, only_treatable = TRUE, ...)  carbapenems(only_sir_columns = FALSE, only_treatable = TRUE, ...)  cephalosporins(only_sir_columns = FALSE, ...)  cephalosporins_1st(only_sir_columns = FALSE, ...)  cephalosporins_2nd(only_sir_columns = FALSE, ...)  cephalosporins_3rd(only_sir_columns = FALSE, ...)  cephalosporins_4th(only_sir_columns = FALSE, ...)  cephalosporins_5th(only_sir_columns = FALSE, ...)  fluoroquinolones(only_sir_columns = FALSE, ...)  glycopeptides(only_sir_columns = FALSE, ...)  lincosamides(only_sir_columns = FALSE, only_treatable = TRUE, ...)  lipoglycopeptides(only_sir_columns = FALSE, ...)  macrolides(only_sir_columns = FALSE, ...)  nitrofurans(only_sir_columns = FALSE, ...)  oxazolidinones(only_sir_columns = FALSE, ...)  penicillins(only_sir_columns = FALSE, ...)  polymyxins(only_sir_columns = FALSE, only_treatable = TRUE, ...)  quinolones(only_sir_columns = FALSE, ...)  rifamycins(only_sir_columns = FALSE, ...)  streptogramins(only_sir_columns = FALSE, ...)  tetracyclines(only_sir_columns = FALSE, ...)  trimethoprims(only_sir_columns = FALSE, ...)  ureidopenicillins(only_sir_columns = FALSE, ...)  administrable_per_os(only_sir_columns = FALSE, ...)  administrable_iv(only_sir_columns = FALSE, ...)  not_intrinsic_resistant(   only_sir_columns = FALSE,   col_mo = NULL,   version_expertrules = 3.3,   ... )"},{"path":"https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Antibiotic Selectors — antibiotic_class_selectors","text":"ab_class antimicrobial class part , \"carba\" \"carbapenems\". columns group, atc_group1 atc_group2 antibiotics data set searched (case-insensitive) value. only_sir_columns logical indicate whether columns class sir must selected (default FALSE), see .sir() only_treatable logical indicate whether antimicrobial drugs excluded laboratory tests (default TRUE), gentamicin-high (GEH) imipenem/EDTA (IPE) ... ignored, place allow future extensions filter expression evaluated antibiotics data set, name %like% \"trim\" col_mo column name names codes microorganisms (see .mo()) - default first column class mo. Values coerced using .mo(). version_expertrules version number use EUCAST Expert Rules Intrinsic Resistance guideline. Can \"3.3\", \"3.2\", \"3.1\".","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Antibiotic Selectors — antibiotic_class_selectors","text":"(internally) character vector column names, additional class \"ab_selector\"","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Antibiotic Selectors — antibiotic_class_selectors","text":"functions can used data set calls selecting columns filtering rows. work base R, Tidyverse, data.table. heavily inspired Tidyverse selection helpers everything(), limited dplyr verbs. Nonetheless, convenient use dplyr functions select(), filter() summarise(), see Examples. columns data functions called searched known antibiotic names, abbreviations, brand names, codes (ATC, EARS-Net, , etc.) according antibiotics data set. means selector aminoglycosides() pick column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc. ab_class() function can used filter/select manually defined antibiotic class. searches results antibiotics data set within columns group, atc_group1 atc_group2. ab_selector() function can used internally filter antibiotics data set results, see Examples. allows filtering (part ) certain name, /group name even minimum DDDs oral treatment. function yields highest flexibility, also least user-friendly, since requires hard-coded filter set. administrable_per_os() administrable_iv() functions also rely antibiotics data set - antibiotic columns matched DDD (defined daily dose) resp. oral IV treatment available antibiotics data set. not_intrinsic_resistant() function can used select antibiotic columns pose intrinsic resistance microorganisms data set. example, data set contains microorganism codes names E. coli K. pneumoniae contains column \"vancomycin\", column removed (rather, unselected) using function. currently applies 'EUCAST Expert Rules' 'EUCAST Intrinsic Resistance Unusual Phenotypes' v3.3 (2021) determine intrinsic resistance, using eucast_rules() function internally. determination, function quite slow terms performance.","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html","id":"full-list-of-supported-antibiotic-classes","dir":"Reference","previous_headings":"","what":"Full list of supported (antibiotic) classes","title":"Antibiotic Selectors — antibiotic_class_selectors","text":"aminoglycosides() can select:  amikacin (AMK), amikacin/fosfomycin (AKF), apramycin (APR), arbekacin (ARB), astromicin (AST), bekanamycin (BEK), dibekacin (DKB), framycetin (FRM), gentamicin (GEN), gentamicin-high (GEH), habekacin (HAB), hygromycin (HYG), isepamicin (ISE), kanamycin (KAN), kanamycin-high (KAH), kanamycin/cephalexin (KAC), micronomicin (MCR), neomycin (NEO), netilmicin (NET), pentisomicin (PIM), plazomicin (PLZ), propikacin (PKA), ribostamycin (RST), sisomicin (SIS), streptoduocin (STR), streptomycin (STR1), streptomycin-high (STH), tobramycin (TOB), tobramycin-high (TOH) aminopenicillins() can select:  amoxicillin (AMX) ampicillin (AMP) antifungals() can select:  amorolfine (AMO), amphotericin B (AMB), amphotericin B-high (AMH), anidulafungin (ANI), butoconazole (), caspofungin (CAS), ciclopirox (CIX), clotrimazole (CTR), econazole (ECO), fluconazole (FLU), flucytosine (FCT), fosfluconazole (FFL), griseofulvin (GRI), hachimycin (HCH), ibrexafungerp (IBX), isavuconazole (ISV), isoconazole (ISO), itraconazole (ITR), ketoconazole (KET), manogepix (MGX), micafungin (MIF), miconazole (MCZ), nystatin (NYS), oteseconazole (OTE), pimaricin (PMR), posaconazole (POS), rezafungin (RZF), ribociclib (RBC), sulconazole (SUC), terbinafine (TRB), terconazole (TRC), voriconazole (VOR) antimycobacterials() can select:  4-aminosalicylic acid (AMA), calcium aminosalicylate (CLA), capreomycin (CAP), clofazimine (CLF), delamanid (DLM), enviomycin (ENV), ethambutol (ETH), ethambutol/isoniazid (ETI), ethionamide (ETI1), isoniazid (INH), isoniazid/sulfamethoxazole/trimethoprim/pyridoxine (IST), morinamide (MRN), p-aminosalicylic acid (PAS), pretomanid (PMD), protionamide (PTH), pyrazinamide (PZA), rifabutin (RIB), rifampicin (RIF), rifampicin/ethambutol/isoniazid (REI), rifampicin/isoniazid (RFI), rifampicin/pyrazinamide/ethambutol/isoniazid (RPEI), rifampicin/pyrazinamide/isoniazid (RPI), rifamycin (RFM), rifapentine (RFP), simvastatin/fenofibrate (SMF), sodium aminosalicylate (SDA), streptomycin/isoniazid (STI), terizidone (TRZ), thioacetazone (TAT), thioacetazone/isoniazid (THI1), tiocarlide (TCR), viomycin (VIO) betalactams() can select:  amoxicillin (AMX), amoxicillin/clavulanic acid (AMC), amoxicillin/sulbactam (AXS), ampicillin (AMP), ampicillin/sulbactam (SAM), apalcillin (APL), aspoxicillin (APX), avibactam (AVB), azidocillin (AZD), azlocillin (AZL), aztreonam (ATM), aztreonam/avibactam (AZA), aztreonam/nacubactam (ANC), bacampicillin (BAM), benzathine benzylpenicillin (BNB), benzathine phenoxymethylpenicillin (BNP), benzylpenicillin (PEN), biapenem (BIA), carbenicillin (CRB), carindacillin (CRN), cefacetrile (CAC), cefaclor (CEC), cefadroxil (CFR), cefalexin (LEX), cefaloridine (RID), cefalotin (CEP), cefamandole (MAN), cefapirin (HAP), cefatrizine (CTZ), cefazedone (CZD), cefazolin (CZO), cefcapene (CCP), cefcapene pivoxil (CCX), cefdinir (CDR), cefditoren (DIT), cefditoren pivoxil (DIX), cefepime (FEP), cefepime/clavulanic acid (CPC), cefepime/nacubactam (FNC), cefepime/tazobactam (FPT), cefetamet (CAT), cefetamet pivoxil (CPI), cefetecol (CCL), cefetrizole (CZL), cefixime (CFM), cefmenoxime (CMX), cefmetazole (CMZ), cefodizime (DIZ), cefonicid (CID), cefoperazone (CFP), cefoperazone/sulbactam (CSL), ceforanide (CND), cefoselis (CSE), cefotaxime (CTX), cefotaxime/clavulanic acid (CTC), cefotaxime/sulbactam (CTS), cefotetan (CTT), cefotiam (CTF), cefotiam hexetil (CHE), cefovecin (FOV), cefoxitin (FOX), cefoxitin screening (FOX1), cefozopran (ZOP), cefpimizole (CFZ), cefpiramide (CPM), cefpirome (CPO), cefpodoxime (CPD), cefpodoxime proxetil (CPX), cefpodoxime/clavulanic acid (CDC), cefprozil (CPR), cefquinome (CEQ), cefroxadine (CRD), cefsulodin (CFS), cefsumide (CSU), ceftaroline (CPT), ceftaroline/avibactam (CPA), ceftazidime (CAZ), ceftazidime/avibactam (CZA), ceftazidime/clavulanic acid (CCV), cefteram (CEM), cefteram pivoxil (CPL), ceftezole (CTL), ceftibuten (CTB), ceftiofur (TIO), ceftizoxime (CZX), ceftizoxime alapivoxil (CZP), ceftobiprole (BPR), ceftobiprole medocaril (CFM1), ceftolozane/tazobactam (CZT), ceftriaxone (CRO), ceftriaxone/beta-lactamase inhibitor (CEB), cefuroxime (CXM), cefuroxime axetil (CXA), cephradine (CED), ciclacillin (CIC), clometocillin (CLM), cloxacillin (CLO), dicloxacillin (DIC), doripenem (DOR), epicillin (EPC), ertapenem (ETP), flucloxacillin (FLC), hetacillin (HET), imipenem (IPM), imipenem/EDTA (IPE), imipenem/relebactam (IMR), latamoxef (LTM), lenampicillin (LEN), loracarbef (LOR), mecillinam (MEC), meropenem (MEM), meropenem/nacubactam (MNC), meropenem/vaborbactam (MEV), metampicillin (MTM), meticillin (MET), mezlocillin (MEZ), mezlocillin/sulbactam (MSU), nacubactam (NAC), nafcillin (NAF), oxacillin (OXA), panipenem (PAN), penamecillin (PNM), penicillin/novobiocin (PNO), penicillin/sulbactam (PSU), pheneticillin (PHE), phenoxymethylpenicillin (PHN), piperacillin (PIP), piperacillin/sulbactam (PIS), piperacillin/tazobactam (TZP), piridicillin (PRC), pivampicillin (PVM), pivmecillinam (PME), procaine benzylpenicillin (PRB), propicillin (PRP), razupenem (RZM), ritipenem (RIT), ritipenem acoxil (RIA), sarmoxicillin (SRX), sulbactam (SUL), sulbenicillin (SBC), sultamicillin (SLT6), talampicillin (TAL), tazobactam (TAZ), tebipenem (TBP), temocillin (TEM), ticarcillin (TIC), ticarcillin/clavulanic acid (TCC) carbapenems() can select:  biapenem (BIA), doripenem (DOR), ertapenem (ETP), imipenem (IPM), imipenem/EDTA (IPE), imipenem/relebactam (IMR), meropenem (MEM), meropenem/nacubactam (MNC), meropenem/vaborbactam (MEV), panipenem (PAN), razupenem (RZM), ritipenem (RIT), ritipenem acoxil (RIA), tebipenem (TBP) cephalosporins() can select:  cefacetrile (CAC), cefaclor (CEC), cefadroxil (CFR), cefalexin (LEX), cefaloridine (RID), cefalotin (CEP), cefamandole (MAN), cefapirin (HAP), cefatrizine (CTZ), cefazedone (CZD), cefazolin (CZO), cefcapene (CCP), cefcapene pivoxil (CCX), cefdinir (CDR), cefditoren (DIT), cefditoren pivoxil (DIX), cefepime (FEP), cefepime/clavulanic acid (CPC), cefepime/tazobactam (FPT), cefetamet (CAT), cefetamet pivoxil (CPI), cefetecol (CCL), cefetrizole (CZL), cefixime (CFM), cefmenoxime (CMX), cefmetazole (CMZ), cefodizime (DIZ), cefonicid (CID), cefoperazone (CFP), cefoperazone/sulbactam (CSL), ceforanide (CND), cefoselis (CSE), cefotaxime (CTX), cefotaxime/clavulanic acid (CTC), cefotaxime/sulbactam (CTS), cefotetan (CTT), cefotiam (CTF), cefotiam hexetil (CHE), cefovecin (FOV), cefoxitin (FOX), cefoxitin screening (FOX1), cefozopran (ZOP), cefpimizole (CFZ), cefpiramide (CPM), cefpirome (CPO), cefpodoxime (CPD), cefpodoxime proxetil (CPX), cefpodoxime/clavulanic acid (CDC), cefprozil (CPR), cefquinome (CEQ), cefroxadine (CRD), cefsulodin (CFS), cefsumide (CSU), ceftaroline (CPT), ceftaroline/avibactam (CPA), ceftazidime (CAZ), ceftazidime/avibactam (CZA), ceftazidime/clavulanic acid (CCV), cefteram (CEM), cefteram pivoxil (CPL), ceftezole (CTL), ceftibuten (CTB), ceftiofur (TIO), ceftizoxime (CZX), ceftizoxime alapivoxil (CZP), ceftobiprole (BPR), ceftobiprole medocaril (CFM1), ceftolozane/tazobactam (CZT), ceftriaxone (CRO), ceftriaxone/beta-lactamase inhibitor (CEB), cefuroxime (CXM), cefuroxime axetil (CXA), cephradine (CED), latamoxef (LTM), loracarbef (LOR) cephalosporins_1st() can select:  cefacetrile (CAC), cefadroxil (CFR), cefalexin (LEX), cefaloridine (RID), cefalotin (CEP), cefapirin (HAP), cefatrizine (CTZ), cefazedone (CZD), cefazolin (CZO), cefroxadine (CRD), ceftezole (CTL), cephradine (CED) cephalosporins_2nd() can select:  cefaclor (CEC), cefamandole (MAN), cefmetazole (CMZ), cefonicid (CID), ceforanide (CND), cefotetan (CTT), cefotiam (CTF), cefoxitin (FOX), cefoxitin screening (FOX1), cefprozil (CPR), cefuroxime (CXM), cefuroxime axetil (CXA), loracarbef (LOR) cephalosporins_3rd() can select:  cefcapene (CCP), cefcapene pivoxil (CCX), cefdinir (CDR), cefditoren (DIT), cefditoren pivoxil (DIX), cefetamet (CAT), cefetamet pivoxil (CPI), cefixime (CFM), cefmenoxime (CMX), cefodizime (DIZ), cefoperazone (CFP), cefoperazone/sulbactam (CSL), cefotaxime (CTX), cefotaxime/clavulanic acid (CTC), cefotaxime/sulbactam (CTS), cefotiam hexetil (CHE), cefovecin (FOV), cefpimizole (CFZ), cefpiramide (CPM), cefpodoxime (CPD), cefpodoxime proxetil (CPX), cefpodoxime/clavulanic acid (CDC), cefsulodin (CFS), ceftazidime (CAZ), ceftazidime/avibactam (CZA), ceftazidime/clavulanic acid (CCV), cefteram (CEM), cefteram pivoxil (CPL), ceftibuten (CTB), ceftiofur (TIO), ceftizoxime (CZX), ceftizoxime alapivoxil (CZP), ceftriaxone (CRO), ceftriaxone/beta-lactamase inhibitor (CEB), latamoxef (LTM) cephalosporins_4th() can select:  cefepime (FEP), cefepime/clavulanic acid (CPC), cefepime/tazobactam (FPT), cefetecol (CCL), cefoselis (CSE), cefozopran (ZOP), cefpirome (CPO), cefquinome (CEQ) cephalosporins_5th() can select:  ceftaroline (CPT), ceftaroline/avibactam (CPA), ceftobiprole (BPR), ceftobiprole medocaril (CFM1), ceftolozane/tazobactam (CZT) fluoroquinolones() can select:  besifloxacin (BES), ciprofloxacin (CIP), clinafloxacin (CLX), danofloxacin (DAN), delafloxacin (DFX), difloxacin (DIF), enoxacin (ENX), enrofloxacin (ENR), finafloxacin (FIN), fleroxacin (FLE), garenoxacin (GRN), gatifloxacin (GAT), gemifloxacin (GEM), grepafloxacin (GRX), lascufloxacin (LSC), levofloxacin (LVX), levonadifloxacin (LND), lomefloxacin (LOM), marbofloxacin (MAR), metioxate (MXT), miloxacin (MIL), moxifloxacin (MFX), nadifloxacin (NAD), nifuroquine (NIF), norfloxacin (), ofloxacin (OFX), orbifloxacin (ORB), pazufloxacin (PAZ), pefloxacin (PEF), pradofloxacin (PRA), premafloxacin (PRX), prulifloxacin (PRU), rufloxacin (RFL), sarafloxacin (SAR), sitafloxacin (SIT), sparfloxacin (SPX), temafloxacin (TMX), tilbroquinol (TBQ), tioxacin (TXC), tosufloxacin (TFX), trovafloxacin (TVA) glycopeptides() can select:  avoparcin (AVO), dalbavancin (DAL), norvancomycin (NVA), oritavancin (ORI), ramoplanin (RAM), teicoplanin (TEC), teicoplanin-macromethod (TCM), telavancin (TLV), vancomycin (VAN), vancomycin-macromethod (VAM) lincosamides() can select:  acetylmidecamycin (ACM), acetylspiramycin (ASP), clindamycin (CLI), clindamycin inducible screening (CLI1), gamithromycin (GAM), kitasamycin (KIT), lincomycin (LIN), meleumycin (MEL), nafithromycin (ZWK), pirlimycin (PRL), primycin (PRM), solithromycin (SOL), tildipirosin (TIP), tilmicosin (TIL), tulathromycin (TUL), tylosin (TYL), tylvalosin (TYL1) lipoglycopeptides() can select:  dalbavancin (DAL), oritavancin (ORI), telavancin (TLV) macrolides() can select:  acetylmidecamycin (ACM), acetylspiramycin (ASP), azithromycin (AZM), clarithromycin (CLR), dirithromycin (DIR), erythromycin (ERY), flurithromycin (FLR1), gamithromycin (GAM), josamycin (JOS), kitasamycin (KIT), meleumycin (MEL), midecamycin (MID), miocamycin (MCM), nafithromycin (ZWK), oleandomycin (OLE), pirlimycin (PRL), primycin (PRM), rokitamycin (ROK), roxithromycin (RXT), solithromycin (SOL), spiramycin (SPI), telithromycin (TLT), tildipirosin (TIP), tilmicosin (TIL), troleandomycin (TRL), tulathromycin (TUL), tylosin (TYL), tylvalosin (TYL1) nitrofurans() can select:  furazidin (FUR), furazolidone (FRZ), nifurtoinol (NFR), nitrofurantoin (NIT), nitrofurazone (NIZ) oxazolidinones() can select:  cadazolid (CDZ), cycloserine (CYC), linezolid (LNZ), tedizolid (TZD), thiacetazone (THA) penicillins() can select:  amoxicillin (AMX), amoxicillin/clavulanic acid (AMC), amoxicillin/sulbactam (AXS), ampicillin (AMP), ampicillin/sulbactam (SAM), apalcillin (APL), aspoxicillin (APX), avibactam (AVB), azidocillin (AZD), azlocillin (AZL), aztreonam (ATM), aztreonam/avibactam (AZA), aztreonam/nacubactam (ANC), bacampicillin (BAM), benzathine benzylpenicillin (BNB), benzathine phenoxymethylpenicillin (BNP), benzylpenicillin (PEN), carbenicillin (CRB), carindacillin (CRN), cefepime/nacubactam (FNC), ciclacillin (CIC), clometocillin (CLM), cloxacillin (CLO), dicloxacillin (DIC), epicillin (EPC), flucloxacillin (FLC), hetacillin (HET), lenampicillin (LEN), mecillinam (MEC), metampicillin (MTM), meticillin (MET), mezlocillin (MEZ), mezlocillin/sulbactam (MSU), nacubactam (NAC), nafcillin (NAF), oxacillin (OXA), penamecillin (PNM), penicillin/novobiocin (PNO), penicillin/sulbactam (PSU), pheneticillin (PHE), phenoxymethylpenicillin (PHN), piperacillin (PIP), piperacillin/sulbactam (PIS), piperacillin/tazobactam (TZP), piridicillin (PRC), pivampicillin (PVM), pivmecillinam (PME), procaine benzylpenicillin (PRB), propicillin (PRP), sarmoxicillin (SRX), sulbactam (SUL), sulbenicillin (SBC), sultamicillin (SLT6), talampicillin (TAL), tazobactam (TAZ), temocillin (TEM), ticarcillin (TIC), ticarcillin/clavulanic acid (TCC) polymyxins() can select:  colistin (COL), polymyxin B (PLB), polymyxin B/polysorbate 80 (POP) quinolones() can select:  besifloxacin (BES), cinoxacin (CIN), ciprofloxacin (CIP), ciprofloxacin/metronidazole (CIM), ciprofloxacin/ornidazole (CIO), ciprofloxacin/tinidazole (CIT), clinafloxacin (CLX), danofloxacin (DAN), delafloxacin (DFX), difloxacin (DIF), enoxacin (ENX), enrofloxacin (ENR), finafloxacin (FIN), fleroxacin (FLE), flumequine (FLM), garenoxacin (GRN), gatifloxacin (GAT), gemifloxacin (GEM), grepafloxacin (GRX), lascufloxacin (LSC), levofloxacin (LVX), levonadifloxacin (LND), lomefloxacin (LOM), marbofloxacin (MAR), metioxate (MXT), miloxacin (MIL), moxifloxacin (MFX), nadifloxacin (NAD), nalidixic acid (NAL), nemonoxacin (NEM), nifuroquine (NIF), nitroxoline (NTR), norfloxacin (), ofloxacin (OFX), orbifloxacin (ORB), oxolinic acid (OXO), pazufloxacin (PAZ), pefloxacin (PEF), pipemidic acid (PPA), piromidic acid (PIR), pradofloxacin (PRA), premafloxacin (PRX), prulifloxacin (PRU), rosoxacin (ROS), rufloxacin (RFL), sarafloxacin (SAR), sitafloxacin (SIT), sparfloxacin (SPX), temafloxacin (TMX), tilbroquinol (TBQ), tioxacin (TXC), tosufloxacin (TFX), trovafloxacin (TVA) rifamycins() can select:  rifabutin (RIB), rifampicin (RIF), rifampicin/ethambutol/isoniazid (REI), rifampicin/isoniazid (RFI), rifampicin/pyrazinamide/ethambutol/isoniazid (RPEI), rifampicin/pyrazinamide/isoniazid (RPI), rifamycin (RFM), rifapentine (RFP) streptogramins() can select:  pristinamycin (PRI) quinupristin/dalfopristin (QDA) tetracyclines() can select:  cetocycline (CTO), chlortetracycline (CTE), clomocycline (CLM1), demeclocycline (DEM), doxycycline (DOX), eravacycline (ERV), lymecycline (LYM), metacycline (MTC), minocycline (MNO), omadacycline (OMC), oxytetracycline (OXY), penimepicycline (PNM1), rolitetracycline (RLT), sarecycline (SRC), tetracycline (TCY), tigecycline (TGC) trimethoprims() can select:  brodimoprim (BDP), sulfadiazine (SDI), sulfadiazine/tetroxoprim (SLT), sulfadiazine/trimethoprim (SLT1), sulfadimethoxine (SUD), sulfadimidine (SDM), sulfadimidine/trimethoprim (SLT2), sulfafurazole (SLF), sulfaisodimidine (SLF1), sulfalene (SLF2), sulfamazone (SZO), sulfamerazine (SLF3), sulfamerazine/trimethoprim (SLT3), sulfamethizole (SLF4), sulfamethoxazole (SMX), sulfamethoxypyridazine (SLF5), sulfametomidine (SLF6), sulfametoxydiazine (SLF7), sulfametrole/trimethoprim (SLT4), sulfamoxole (SLF8), sulfamoxole/trimethoprim (SLT5), sulfanilamide (SLF9), sulfaperin (SLF10), sulfaphenazole (SLF11), sulfapyridine (SLF12), sulfathiazole (SUT), sulfathiourea (SLF13), trimethoprim (TMP), trimethoprim/sulfamethoxazole (SXT) ureidopenicillins() can select:  azlocillin (AZL), mezlocillin (MEZ), piperacillin (PIP), piperacillin/tazobactam (TZP)","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html","id":"reference-data-publicly-available","dir":"Reference","previous_headings":"","what":"Reference Data Publicly Available","title":"Antibiotic Selectors — antibiotic_class_selectors","text":"data sets AMR package (microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) publicly freely available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. also provide tab-separated plain text files machine-readable suitable input software program, laboratory information systems. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Antibiotic Selectors — antibiotic_class_selectors","text":"","code":"# `example_isolates` is a data set available in the AMR package. # See ?example_isolates. example_isolates #> # A tibble: 2,000 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-03 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  3 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  4 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  5 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  6 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  7 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  8 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  9 2002-01-16 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #> 10 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R     NA    S     NA    #> # ℹ 1,990 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, …   # Examples sections below are split into 'dplyr', 'base R', and 'data.table':  # \\donttest{ # dplyr -------------------------------------------------------------------  if (require(\"dplyr\")) {   example_isolates %>% select(carbapenems()) } #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> # A tibble: 2,000 × 2 #>    IPM   MEM   #>    <sir> <sir> #>  1 NA    NA    #>  2 NA    NA    #>  3 NA    NA    #>  4 NA    NA    #>  5 NA    NA    #>  6 NA    NA    #>  7 NA    NA    #>  8 NA    NA    #>  9 NA    NA    #> 10 NA    NA    #> # ℹ 1,990 more rows  if (require(\"dplyr\")) {   # select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB'   example_isolates %>% select(mo, aminoglycosides()) } #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> # A tibble: 2,000 × 5 #>    mo           GEN   TOB   AMK   KAN   #>    <mo>         <sir> <sir> <sir> <sir> #>  1 B_ESCHR_COLI NA    NA    NA    NA    #>  2 B_ESCHR_COLI NA    NA    NA    NA    #>  3 B_STPHY_EPDR NA    NA    NA    NA    #>  4 B_STPHY_EPDR NA    NA    NA    NA    #>  5 B_STPHY_EPDR NA    NA    NA    NA    #>  6 B_STPHY_EPDR NA    NA    NA    NA    #>  7 B_STPHY_AURS NA    S     NA    NA    #>  8 B_STPHY_AURS NA    S     NA    NA    #>  9 B_STPHY_EPDR NA    NA    NA    NA    #> 10 B_STPHY_EPDR NA    NA    NA    NA    #> # ℹ 1,990 more rows  if (require(\"dplyr\")) {   # select only antibiotic columns with DDDs for oral treatment   example_isolates %>% select(administrable_per_os()) } #> ℹ For administrable_per_os() using columns 'OXA' (oxacillin), 'FLC' #>   (flucloxacillin), 'AMX' (amoxicillin), 'AMC' (amoxicillin/clavulanic acid), #>   'AMP' (ampicillin), 'CXM' (cefuroxime), 'KAN' (kanamycin), 'TMP' #>   (trimethoprim), 'NIT' (nitrofurantoin), 'FOS' (fosfomycin), 'LNZ' #>   (linezolid), 'CIP' (ciprofloxacin), 'MFX' (moxifloxacin), 'VAN' #>   (vancomycin), 'TCY' (tetracycline), 'DOX' (doxycycline), 'ERY' #>   (erythromycin), 'CLI' (clindamycin), 'AZM' (azithromycin), 'MTR' #>   (metronidazole), 'CHL' (chloramphenicol), 'COL' (colistin), and 'RIF' #>   (rifampicin) #> # A tibble: 2,000 × 23 #>    OXA   FLC   AMX   AMC   AMP   CXM   KAN   TMP   NIT   FOS   LNZ   CIP   MFX   #>    <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> #>  1 NA    NA    NA    I     NA    I     NA    R     NA    NA    R     NA    NA    #>  2 NA    NA    NA    I     NA    I     NA    R     NA    NA    R     NA    NA    #>  3 NA    R     NA    NA    NA    R     NA    S     NA    NA    NA    NA    NA    #>  4 NA    R     NA    NA    NA    R     NA    S     NA    NA    NA    NA    NA    #>  5 NA    R     NA    NA    NA    R     NA    R     NA    NA    NA    NA    NA    #>  6 NA    R     NA    NA    NA    R     NA    R     NA    NA    NA    NA    NA    #>  7 NA    S     R     S     R     S     NA    R     NA    NA    NA    NA    NA    #>  8 NA    S     R     S     R     S     NA    R     NA    NA    NA    NA    NA    #>  9 NA    R     NA    NA    NA    R     NA    S     NA    NA    NA    S     NA    #> 10 NA    S     NA    NA    NA    S     NA    S     NA    NA    NA    S     NA    #> # ℹ 1,990 more rows #> # ℹ 10 more variables: VAN <sir>, TCY <sir>, DOX <sir>, ERY <sir>, CLI <sir>, #> #   AZM <sir>, MTR <sir>, CHL <sir>, COL <sir>, RIF <sir>  if (require(\"dplyr\")) {   # get AMR for all aminoglycosides e.g., per ward:   example_isolates %>%     group_by(ward) %>%     summarise(across(aminoglycosides(),                      resistance)) } #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> Warning: There was 1 warning in `summarise()`. #> ℹ In argument: `across(aminoglycosides(), resistance)`. #> ℹ In group 3: `ward = \"Outpatient\"`. #> Caused by warning: #> ! Introducing NA: only 23 results available for KAN in group: ward = #> \"Outpatient\" (minimum = 30). #> # A tibble: 3 × 5 #>   ward         GEN   TOB   AMK   KAN #>   <chr>      <dbl> <dbl> <dbl> <dbl> #> 1 Clinical   0.229 0.315 0.626     1 #> 2 ICU        0.290 0.400 0.662     1 #> 3 Outpatient 0.2   0.368 0.605    NA if (require(\"dplyr\")) {   # You can combine selectors with '&' to be more specific:   example_isolates %>%     select(penicillins() & administrable_per_os()) } #> ℹ For penicillins() using columns 'PEN' (benzylpenicillin), 'OXA' #>   (oxacillin), 'FLC' (flucloxacillin), 'AMX' (amoxicillin), 'AMC' #>   (amoxicillin/clavulanic acid), 'AMP' (ampicillin), and 'TZP' #>   (piperacillin/tazobactam) #> ℹ For administrable_per_os() using columns 'OXA' (oxacillin), 'FLC' #>   (flucloxacillin), 'AMX' (amoxicillin), 'AMC' (amoxicillin/clavulanic acid), #>   'AMP' (ampicillin), 'CXM' (cefuroxime), 'KAN' (kanamycin), 'TMP' #>   (trimethoprim), 'NIT' (nitrofurantoin), 'FOS' (fosfomycin), 'LNZ' #>   (linezolid), 'CIP' (ciprofloxacin), 'MFX' (moxifloxacin), 'VAN' #>   (vancomycin), 'TCY' (tetracycline), 'DOX' (doxycycline), 'ERY' #>   (erythromycin), 'CLI' (clindamycin), 'AZM' (azithromycin), 'MTR' #>   (metronidazole), 'CHL' (chloramphenicol), 'COL' (colistin), and 'RIF' #>   (rifampicin) #> # A tibble: 2,000 × 5 #>    OXA   FLC   AMX   AMC   AMP   #>    <sir> <sir> <sir> <sir> <sir> #>  1 NA    NA    NA    I     NA    #>  2 NA    NA    NA    I     NA    #>  3 NA    R     NA    NA    NA    #>  4 NA    R     NA    NA    NA    #>  5 NA    R     NA    NA    NA    #>  6 NA    R     NA    NA    NA    #>  7 NA    S     R     S     R     #>  8 NA    S     R     S     R     #>  9 NA    R     NA    NA    NA    #> 10 NA    S     NA    NA    NA    #> # ℹ 1,990 more rows if (require(\"dplyr\")) {   # get AMR for only drugs that matter - no intrinsic resistance:   example_isolates %>%     filter(mo_genus() %in% c(\"Escherichia\", \"Klebsiella\")) %>%     group_by(ward) %>%     summarise_at(not_intrinsic_resistant(),                  resistance) } #> ℹ Using column 'mo' as input for mo_genus() #> ℹ For not_intrinsic_resistant() removing columns 'PEN' #>   (benzylpenicillin), 'LNZ' (linezolid), 'VAN' (vancomycin), 'TEC' #>   (teicoplanin), 'ERY' (erythromycin), 'CLI' (clindamycin), 'AZM' #>   (azithromycin), and 'RIF' (rifampicin) #> Warning: There were 52 warnings in `summarise()`. #> The first warning was: #> ℹ In argument: `OXA = (function (..., minimum = 30, as_percent = FALSE, #>   only_all_tested = FALSE) ...`. #> ℹ In group 1: `ward = \"Clinical\"`. #> Caused by warning: #> ! Introducing NA: no results available for OXA in group: ward = \"Clinical\" #> (minimum = 30). #> ℹ Run `dplyr::last_dplyr_warnings()` to see the 51 remaining warnings. #> # A tibble: 3 × 33 #>   ward    OXA   FLC    AMX    AMC    AMP     TZP     CZO     FEP     CXM     FOX #>   <chr> <dbl> <dbl>  <dbl>  <dbl>  <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl> #> 1 Clin…    NA    NA  0.606  0.121  0.606  0.0504  0.0656  0.0159  0.0622  0.0648 #> 2 ICU      NA    NA  0.535  0.172  0.535  0.119  NA       0.0722  0.0828  0.0992 #> 3 Outp…    NA    NA NA     NA     NA     NA      NA      NA      NA      NA      #> # ℹ 22 more variables: CTX <dbl>, CAZ <dbl>, CRO <dbl>, GEN <dbl>, TOB <dbl>, #> #   AMK <dbl>, KAN <dbl>, TMP <dbl>, SXT <dbl>, NIT <dbl>, FOS <dbl>, #> #   CIP <dbl>, MFX <dbl>, TCY <dbl>, TGC <dbl>, DOX <dbl>, IPM <dbl>, #> #   MEM <dbl>, MTR <dbl>, CHL <dbl>, COL <dbl>, MUP <dbl> if (require(\"dplyr\")) {   # get susceptibility for antibiotics whose name contains \"trim\":   example_isolates %>%     filter(first_isolate()) %>%     group_by(ward) %>%     summarise(across(ab_selector(name %like% \"trim\"), susceptibility)) } #> ℹ For ab_selector(name %like% \"trim\") using columns 'TMP' (trimethoprim) #>   and 'SXT' (trimethoprim/sulfamethoxazole) #> # A tibble: 3 × 3 #>   ward         TMP   SXT #>   <chr>      <dbl> <dbl> #> 1 Clinical   0.627 0.807 #> 2 ICU        0.551 0.780 #> 3 Outpatient 0.667 0.821 if (require(\"dplyr\")) {   # this will select columns 'IPM' (imipenem) and 'MEM' (meropenem):   example_isolates %>%     select(carbapenems()) } #> # A tibble: 2,000 × 2 #>    IPM   MEM   #>    <sir> <sir> #>  1 NA    NA    #>  2 NA    NA    #>  3 NA    NA    #>  4 NA    NA    #>  5 NA    NA    #>  6 NA    NA    #>  7 NA    NA    #>  8 NA    NA    #>  9 NA    NA    #> 10 NA    NA    #> # ℹ 1,990 more rows if (require(\"dplyr\")) {   # this will select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB':   example_isolates %>%     select(mo, aminoglycosides()) } #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> # A tibble: 2,000 × 5 #>    mo           GEN   TOB   AMK   KAN   #>    <mo>         <sir> <sir> <sir> <sir> #>  1 B_ESCHR_COLI NA    NA    NA    NA    #>  2 B_ESCHR_COLI NA    NA    NA    NA    #>  3 B_STPHY_EPDR NA    NA    NA    NA    #>  4 B_STPHY_EPDR NA    NA    NA    NA    #>  5 B_STPHY_EPDR NA    NA    NA    NA    #>  6 B_STPHY_EPDR NA    NA    NA    NA    #>  7 B_STPHY_AURS NA    S     NA    NA    #>  8 B_STPHY_AURS NA    S     NA    NA    #>  9 B_STPHY_EPDR NA    NA    NA    NA    #> 10 B_STPHY_EPDR NA    NA    NA    NA    #> # ℹ 1,990 more rows if (require(\"dplyr\")) {   # any() and all() work in dplyr's filter() too:   example_isolates %>%     filter(       any(aminoglycosides() == \"R\"),       all(cephalosporins_2nd() == \"R\")     ) } #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> ℹ For cephalosporins_2nd() using columns 'CXM' (cefuroxime) and 'FOX' #>   (cefoxitin) #> # A tibble: 112 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-02-21 4FC193     69 M      Clinical B_ENTRC_FACM NA    NA    NA    NA    #>  2 2002-03-16 4FC193     69 M      Clinical B_PSDMN_AERG R     NA    NA    R     #>  3 2002-04-08 130252     78 M      ICU      B_ENTRC_FCLS NA    NA    NA    NA    #>  4 2002-06-23 798871     82 M      Clinical B_ENTRC_FCLS NA    NA    NA    NA    #>  5 2002-06-23 798871     82 M      Clinical B_ENTRC_FCLS NA    NA    NA    NA    #>  6 2002-07-21 955940     82 F      Clinical B_PSDMN_AERG R     NA    NA    R     #>  7 2002-07-21 955940     82 F      Clinical B_PSDMN_AERG R     NA    NA    R     #>  8 2003-08-13 F35553     52 M      ICU      B_ENTRC_FCLS NA    NA    NA    NA    #>  9 2003-09-05 F35553     52 M      ICU      B_ENTRC_FCLS NA    NA    NA    NA    #> 10 2004-06-09 529296     69 M      ICU      B_ENTRC_FACM NA    NA    NA    NA    #> # ℹ 102 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, … if (require(\"dplyr\")) {   # also works with c():   example_isolates %>%     filter(any(c(carbapenems(), aminoglycosides()) == \"R\")) } #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> # A tibble: 531 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-02-21 4FC193     69 M      Clinical B_ENTRC_FACM NA    NA    NA    NA    #>  2 2002-03-16 4FC193     69 M      Clinical B_PSDMN_AERG R     NA    NA    R     #>  3 2002-03-17 B30560     78 M      Clinical B_STPHY_CONS R     NA    R     R     #>  4 2002-04-04 E61143     67 M      Clinical B_STRPT_SNGN S     NA    NA    S     #>  5 2002-04-08 130252     78 M      ICU      B_ENTRC_FCLS NA    NA    NA    NA    #>  6 2002-04-14 F30196     73 M      Outpati… B_STRPT_GRPB S     NA    S     S     #>  7 2002-05-07 D91570     83 M      Clinical B_STPHY_CONS R     NA    R     R     #>  8 2002-05-07 D91570     83 M      Clinical B_STPHY_CONS R     NA    R     R     #>  9 2002-05-14 077552     86 F      Clinical B_STRPT_PNMN S     NA    NA    S     #> 10 2002-05-14 077552     86 F      Clinical B_STRPT_PNMN S     NA    NA    S     #> # ℹ 521 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, … if (require(\"dplyr\")) {   # not setting any/all will automatically apply all():   example_isolates %>%     filter(aminoglycosides() == \"R\") } #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> ℹ Assuming a filter on all 4 aminoglycosides. Wrap around all() or #>   any() to prevent this note. #> # A tibble: 427 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-02-21 4FC193     69 M      Clinical B_ENTRC_FACM NA    NA    NA    NA    #>  2 2002-03-17 B30560     78 M      Clinical B_STPHY_CONS R     NA    R     R     #>  3 2002-04-04 E61143     67 M      Clinical B_STRPT_SNGN S     NA    NA    S     #>  4 2002-04-08 130252     78 M      ICU      B_ENTRC_FCLS NA    NA    NA    NA    #>  5 2002-04-14 F30196     73 M      Outpati… B_STRPT_GRPB S     NA    S     S     #>  6 2002-05-07 D91570     83 M      Clinical B_STPHY_CONS R     NA    R     R     #>  7 2002-05-07 D91570     83 M      Clinical B_STPHY_CONS R     NA    R     R     #>  8 2002-05-14 077552     86 F      Clinical B_STRPT_PNMN S     NA    NA    S     #>  9 2002-05-14 077552     86 F      Clinical B_STRPT_PNMN S     NA    NA    S     #> 10 2002-05-16 D25302     65 F      ICU      B_STRPT_ANGN S     NA    NA    S     #> # ℹ 417 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, … if (require(\"dplyr\")) {   # this will select columns 'mo' and all antimycobacterial drugs ('RIF'):   example_isolates %>%     select(mo, ab_class(\"mycobact\")) } #> ℹ For ab_class(\"mycobact\") using column 'RIF' (rifampicin) #> # A tibble: 2,000 × 2 #>    mo           RIF   #>    <mo>         <sir> #>  1 B_ESCHR_COLI R     #>  2 B_ESCHR_COLI R     #>  3 B_STPHY_EPDR NA    #>  4 B_STPHY_EPDR NA    #>  5 B_STPHY_EPDR NA    #>  6 B_STPHY_EPDR NA    #>  7 B_STPHY_AURS NA    #>  8 B_STPHY_AURS NA    #>  9 B_STPHY_EPDR NA    #> 10 B_STPHY_EPDR NA    #> # ℹ 1,990 more rows if (require(\"dplyr\")) {   # get bug/drug combinations for only glycopeptides in Gram-positives:   example_isolates %>%     filter(mo_is_gram_positive()) %>%     select(mo, glycopeptides()) %>%     bug_drug_combinations() %>%     format() } #> ℹ Using column 'mo' as input for mo_is_gram_positive() #> ℹ For glycopeptides() using columns 'VAN' (vancomycin) and 'TEC' #>   (teicoplanin) #> # A tibble: 2 × 8 #>   Group      Drug  CoNS  `E. faecalis` `S. aureus` `S. epidermidis` `S. hominis` #>   <chr>      <chr> <chr> <chr>         <chr>       <chr>            <chr>        #> 1 \"Glycopep… Teic… \"\"    \"\"            \" 0.0% (0/… \"64.1% (25/39)\"  \" 6.8% (4/5… #> 2 \"\"         Vanc… \" 0.… \" 0.0% (0/39… \" 0.0% (0/… \" 0.0% (0/171)\"  \" 0.0% (0/8… #> # ℹ 1 more variable: `S. pneumoniae` <chr> if (require(\"dplyr\")) {   data.frame(     some_column = \"some_value\",     J01CA01 = \"S\"   ) %>% # ATC code of ampicillin     select(penicillins()) # only the 'J01CA01' column will be selected } #> ℹ For penicillins() using column 'J01CA01' (ampicillin) #>   J01CA01 #> 1       S if (require(\"dplyr\")) {   # with recent versions of dplyr, this is all equal:   x <- example_isolates[carbapenems() == \"R\", ]   y <- example_isolates %>% filter(carbapenems() == \"R\")   z <- example_isolates %>% filter(if_all(carbapenems(), ~ .x == \"R\"))   identical(x, y) && identical(y, z) } #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> ℹ Assuming a filter on all 2 carbapenems. Wrap around all() or any() to #>   prevent this note. #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> ℹ Assuming a filter on all 2 carbapenems. Wrap around all() or any() to #>   prevent this note. #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> [1] TRUE   # base R ------------------------------------------------------------------  # select columns 'IPM' (imipenem) and 'MEM' (meropenem) example_isolates[, carbapenems()] #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> # A tibble: 2,000 × 2 #>    IPM   MEM   #>    <sir> <sir> #>  1 NA    NA    #>  2 NA    NA    #>  3 NA    NA    #>  4 NA    NA    #>  5 NA    NA    #>  6 NA    NA    #>  7 NA    NA    #>  8 NA    NA    #>  9 NA    NA    #> 10 NA    NA    #> # ℹ 1,990 more rows  # select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB' example_isolates[, c(\"mo\", aminoglycosides())] #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> # A tibble: 2,000 × 5 #>    mo           GEN   TOB   AMK   KAN   #>    <mo>         <sir> <sir> <sir> <sir> #>  1 B_ESCHR_COLI NA    NA    NA    NA    #>  2 B_ESCHR_COLI NA    NA    NA    NA    #>  3 B_STPHY_EPDR NA    NA    NA    NA    #>  4 B_STPHY_EPDR NA    NA    NA    NA    #>  5 B_STPHY_EPDR NA    NA    NA    NA    #>  6 B_STPHY_EPDR NA    NA    NA    NA    #>  7 B_STPHY_AURS NA    S     NA    NA    #>  8 B_STPHY_AURS NA    S     NA    NA    #>  9 B_STPHY_EPDR NA    NA    NA    NA    #> 10 B_STPHY_EPDR NA    NA    NA    NA    #> # ℹ 1,990 more rows  # select only antibiotic columns with DDDs for oral treatment example_isolates[, administrable_per_os()] #> ℹ For administrable_per_os() using columns 'OXA' (oxacillin), 'FLC' #>   (flucloxacillin), 'AMX' (amoxicillin), 'AMC' (amoxicillin/clavulanic acid), #>   'AMP' (ampicillin), 'CXM' (cefuroxime), 'KAN' (kanamycin), 'TMP' #>   (trimethoprim), 'NIT' (nitrofurantoin), 'FOS' (fosfomycin), 'LNZ' #>   (linezolid), 'CIP' (ciprofloxacin), 'MFX' (moxifloxacin), 'VAN' #>   (vancomycin), 'TCY' (tetracycline), 'DOX' (doxycycline), 'ERY' #>   (erythromycin), 'CLI' (clindamycin), 'AZM' (azithromycin), 'MTR' #>   (metronidazole), 'CHL' (chloramphenicol), 'COL' (colistin), and 'RIF' #>   (rifampicin) #> # A tibble: 2,000 × 23 #>    OXA   FLC   AMX   AMC   AMP   CXM   KAN   TMP   NIT   FOS   LNZ   CIP   MFX   #>    <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> #>  1 NA    NA    NA    I     NA    I     NA    R     NA    NA    R     NA    NA    #>  2 NA    NA    NA    I     NA    I     NA    R     NA    NA    R     NA    NA    #>  3 NA    R     NA    NA    NA    R     NA    S     NA    NA    NA    NA    NA    #>  4 NA    R     NA    NA    NA    R     NA    S     NA    NA    NA    NA    NA    #>  5 NA    R     NA    NA    NA    R     NA    R     NA    NA    NA    NA    NA    #>  6 NA    R     NA    NA    NA    R     NA    R     NA    NA    NA    NA    NA    #>  7 NA    S     R     S     R     S     NA    R     NA    NA    NA    NA    NA    #>  8 NA    S     R     S     R     S     NA    R     NA    NA    NA    NA    NA    #>  9 NA    R     NA    NA    NA    R     NA    S     NA    NA    NA    S     NA    #> 10 NA    S     NA    NA    NA    S     NA    S     NA    NA    NA    S     NA    #> # ℹ 1,990 more rows #> # ℹ 10 more variables: VAN <sir>, TCY <sir>, DOX <sir>, ERY <sir>, CLI <sir>, #> #   AZM <sir>, MTR <sir>, CHL <sir>, COL <sir>, RIF <sir>  # filter using any() or all() example_isolates[any(carbapenems() == \"R\"), ] #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> # A tibble: 55 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2004-06-09 529296     69 M      ICU      B_ENTRC_FACM NA    NA    NA    NA    #>  2 2004-06-09 529296     69 M      ICU      B_ENTRC_FACM NA    NA    NA    NA    #>  3 2004-11-03 D65308     80 F      ICU      B_STNTR_MLTP R     NA    NA    R     #>  4 2005-04-21 452212     82 F      ICU      B_ENTRC      NA    NA    NA    NA    #>  5 2005-04-22 452212     82 F      ICU      B_ENTRC      NA    NA    NA    NA    #>  6 2005-04-22 452212     82 F      ICU      B_ENTRC_FACM NA    NA    NA    NA    #>  7 2007-02-21 8BBC46     61 F      Clinical B_ENTRC_FACM NA    NA    NA    NA    #>  8 2007-12-15 401043     72 M      Clinical B_ENTRC_FACM NA    NA    NA    NA    #>  9 2008-01-22 1710B8     82 M      Clinical B_PROTS_MRBL R     NA    NA    NA    #> 10 2008-01-22 1710B8     82 M      Clinical B_PROTS_MRBL R     NA    NA    NA    #> # ℹ 45 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, … subset(example_isolates, any(carbapenems() == \"R\")) #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> # A tibble: 55 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2004-06-09 529296     69 M      ICU      B_ENTRC_FACM NA    NA    NA    NA    #>  2 2004-06-09 529296     69 M      ICU      B_ENTRC_FACM NA    NA    NA    NA    #>  3 2004-11-03 D65308     80 F      ICU      B_STNTR_MLTP R     NA    NA    R     #>  4 2005-04-21 452212     82 F      ICU      B_ENTRC      NA    NA    NA    NA    #>  5 2005-04-22 452212     82 F      ICU      B_ENTRC      NA    NA    NA    NA    #>  6 2005-04-22 452212     82 F      ICU      B_ENTRC_FACM NA    NA    NA    NA    #>  7 2007-02-21 8BBC46     61 F      Clinical B_ENTRC_FACM NA    NA    NA    NA    #>  8 2007-12-15 401043     72 M      Clinical B_ENTRC_FACM NA    NA    NA    NA    #>  9 2008-01-22 1710B8     82 M      Clinical B_PROTS_MRBL R     NA    NA    NA    #> 10 2008-01-22 1710B8     82 M      Clinical B_PROTS_MRBL R     NA    NA    NA    #> # ℹ 45 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, …  # filter on any or all results in the carbapenem columns (i.e., IPM, MEM): example_isolates[any(carbapenems()), ] #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> ℹ Filtering any of columns 'IPM' and 'MEM' to contain value \"S\", \"I\" or \"R\" #> # A tibble: 962 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-19 738003     71 M      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-19 738003     71 M      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  3 2002-01-22 F35553     50 M      ICU      B_PROTS_MRBL R     NA    NA    NA    #>  4 2002-01-22 F35553     50 M      ICU      B_PROTS_MRBL R     NA    NA    NA    #>  5 2002-02-05 067927     45 F      ICU      B_SERRT_MRCS R     NA    NA    R     #>  6 2002-02-05 067927     45 F      ICU      B_SERRT_MRCS R     NA    NA    R     #>  7 2002-02-05 067927     45 F      ICU      B_SERRT_MRCS R     NA    NA    R     #>  8 2002-02-27 066895     85 F      Clinical B_KLBSL_PNMN R     NA    NA    R     #>  9 2002-02-27 066895     85 F      Clinical B_KLBSL_PNMN R     NA    NA    R     #> 10 2002-03-08 4FC193     69 M      Clinical B_ESCHR_COLI R     NA    NA    R     #> # ℹ 952 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, … example_isolates[all(carbapenems()), ] #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> ℹ Filtering all of columns 'IPM' and 'MEM' to contain value \"S\", \"I\" or \"R\" #> # A tibble: 756 × 46 #>    date       patient   age gender ward    mo            PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>   <mo>          <sir> <sir> <sir> <sir> #>  1 2002-04-14 F30196     73 M      Outpat… B_STRPT_GRPB  S     NA    S     S     #>  2 2003-04-08 114570     74 M      ICU     B_STRPT_PYGN  S     NA    S     S     #>  3 2003-04-08 114570     74 M      ICU     B_STRPT_GRPA  S     NA    S     S     #>  4 2003-04-08 114570     74 M      ICU     B_STRPT_GRPA  S     NA    S     S     #>  5 2003-08-14 F71508      0 F      Clinic… B_STRPT_GRPB  S     NA    S     S     #>  6 2003-10-16 650870     63 F      ICU     B_ESCHR_COLI  R     NA    NA    R     #>  7 2003-10-20 F35553     52 M      ICU     B_ENTRBC_CLOC R     NA    NA    R     #>  8 2003-10-20 F35553     52 M      ICU     B_ENTRBC_CLOC R     NA    NA    R     #>  9 2003-11-04 2FC253     87 F      ICU     B_ESCHR_COLI  R     NA    NA    NA    #> 10 2003-11-04 2FC253     87 F      ICU     B_ESCHR_COLI  R     NA    NA    NA    #> # ℹ 746 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, …  # filter with multiple antibiotic selectors using c() example_isolates[all(c(carbapenems(), aminoglycosides()) == \"R\"), ] #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> # A tibble: 26 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2004-11-03 D65308     80 F      ICU      B_STNTR_MLTP R     NA    NA    R     #>  2 2005-04-22 452212     82 F      ICU      B_ENTRC_FACM NA    NA    NA    NA    #>  3 2007-02-21 8BBC46     61 F      Clinical B_ENTRC_FACM NA    NA    NA    NA    #>  4 2007-12-15 401043     72 M      Clinical B_ENTRC_FACM NA    NA    NA    NA    #>  5 2008-12-06 501361     43 F      Clinical B_STNTR_MLTP R     NA    NA    R     #>  6 2011-05-09 207325     82 F      ICU      B_ENTRC_FACM NA    NA    NA    NA    #>  7 2012-03-12 582258     80 M      ICU      B_STPHY_CONS R     R     R     R     #>  8 2012-05-19 C25552     89 F      Outpati… B_STPHY_CONS R     R     R     R     #>  9 2012-07-17 F05015     83 M      ICU      B_STPHY_CONS R     R     R     R     #> 10 2012-07-20 404299     66 F      Clinical B_STPHY_CONS R     R     R     R     #> # ℹ 16 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, …  # filter + select in one go: get penicillins in carbapenem-resistant strains example_isolates[any(carbapenems() == \"R\"), penicillins()] #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> ℹ For penicillins() using columns 'PEN' (benzylpenicillin), 'OXA' #>   (oxacillin), 'FLC' (flucloxacillin), 'AMX' (amoxicillin), 'AMC' #>   (amoxicillin/clavulanic acid), 'AMP' (ampicillin), and 'TZP' #>   (piperacillin/tazobactam) #> # A tibble: 55 × 7 #>    PEN   OXA   FLC   AMX   AMC   AMP   TZP   #>    <sir> <sir> <sir> <sir> <sir> <sir> <sir> #>  1 NA    NA    NA    NA    NA    NA    NA    #>  2 NA    NA    NA    NA    NA    NA    NA    #>  3 R     NA    NA    R     R     R     R     #>  4 NA    NA    NA    NA    NA    NA    R     #>  5 NA    NA    NA    NA    NA    NA    R     #>  6 NA    NA    NA    NA    NA    NA    R     #>  7 NA    NA    NA    NA    NA    NA    R     #>  8 NA    NA    NA    NA    NA    NA    R     #>  9 R     NA    NA    NA    S     NA    S     #> 10 R     NA    NA    NA    S     NA    S     #> # ℹ 45 more rows  # You can combine selectors with '&' to be more specific. For example, # penicillins() would select benzylpenicillin ('peni G') and # administrable_per_os() would select erythromycin. Yet, when combined these # drugs are both omitted since benzylpenicillin is not administrable per os # and erythromycin is not a penicillin: example_isolates[, penicillins() & administrable_per_os()] #> ℹ For penicillins() using columns 'PEN' (benzylpenicillin), 'OXA' #>   (oxacillin), 'FLC' (flucloxacillin), 'AMX' (amoxicillin), 'AMC' #>   (amoxicillin/clavulanic acid), 'AMP' (ampicillin), and 'TZP' #>   (piperacillin/tazobactam) #> ℹ For administrable_per_os() using columns 'OXA' (oxacillin), 'FLC' #>   (flucloxacillin), 'AMX' (amoxicillin), 'AMC' (amoxicillin/clavulanic acid), #>   'AMP' (ampicillin), 'CXM' (cefuroxime), 'KAN' (kanamycin), 'TMP' #>   (trimethoprim), 'NIT' (nitrofurantoin), 'FOS' (fosfomycin), 'LNZ' #>   (linezolid), 'CIP' (ciprofloxacin), 'MFX' (moxifloxacin), 'VAN' #>   (vancomycin), 'TCY' (tetracycline), 'DOX' (doxycycline), 'ERY' #>   (erythromycin), 'CLI' (clindamycin), 'AZM' (azithromycin), 'MTR' #>   (metronidazole), 'CHL' (chloramphenicol), 'COL' (colistin), and 'RIF' #>   (rifampicin) #> # A tibble: 2,000 × 5 #>    OXA   FLC   AMX   AMC   AMP   #>    <sir> <sir> <sir> <sir> <sir> #>  1 NA    NA    NA    I     NA    #>  2 NA    NA    NA    I     NA    #>  3 NA    R     NA    NA    NA    #>  4 NA    R     NA    NA    NA    #>  5 NA    R     NA    NA    NA    #>  6 NA    R     NA    NA    NA    #>  7 NA    S     R     S     R     #>  8 NA    S     R     S     R     #>  9 NA    R     NA    NA    NA    #> 10 NA    S     NA    NA    NA    #> # ℹ 1,990 more rows  # ab_selector() applies a filter in the `antibiotics` data set and is thus # very flexible. For instance, to select antibiotic columns with an oral DDD # of at least 1 gram: example_isolates[, ab_selector(oral_ddd > 1 & oral_units == \"g\")] #> ℹ For ab_selector(oral_ddd > 1 & oral_units == \"g\") using columns 'OXA' #>   (oxacillin), 'FLC' (flucloxacillin), 'AMX' (amoxicillin), 'AMC' #>   (amoxicillin/clavulanic acid), 'AMP' (ampicillin), 'KAN' (kanamycin), 'FOS' #>   (fosfomycin), 'LNZ' (linezolid), 'VAN' (vancomycin), 'ERY' (erythromycin), #>   'CLI' (clindamycin), 'MTR' (metronidazole), and 'CHL' (chloramphenicol) #> # A tibble: 2,000 × 13 #>    OXA   FLC   AMX   AMC   AMP   KAN   FOS   LNZ   VAN   ERY   CLI   MTR   CHL   #>    <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> #>  1 NA    NA    NA    I     NA    NA    NA    R     R     R     R     NA    NA    #>  2 NA    NA    NA    I     NA    NA    NA    R     R     R     R     NA    NA    #>  3 NA    R     NA    NA    NA    NA    NA    NA    S     R     NA    NA    NA    #>  4 NA    R     NA    NA    NA    NA    NA    NA    S     R     NA    NA    NA    #>  5 NA    R     NA    NA    NA    NA    NA    NA    S     R     NA    NA    NA    #>  6 NA    R     NA    NA    NA    NA    NA    NA    S     R     R     NA    NA    #>  7 NA    S     R     S     R     NA    NA    NA    S     S     NA    NA    NA    #>  8 NA    S     R     S     R     NA    NA    NA    S     S     NA    NA    NA    #>  9 NA    R     NA    NA    NA    NA    NA    NA    S     R     NA    NA    NA    #> 10 NA    S     NA    NA    NA    NA    NA    NA    S     S     NA    NA    NA    #> # ℹ 1,990 more rows   # data.table --------------------------------------------------------------  # data.table is supported as well, just use it in the same way as with # base R, but add `with = FALSE` if using a single AB selector.  if (require(\"data.table\")) {   dt <- as.data.table(example_isolates)    # this does not work, it returns column *names*   dt[, carbapenems()] } #> Loading required package: data.table #>  #> Attaching package: ‘data.table’ #> The following objects are masked from ‘package:dplyr’: #>  #>     between, first, last #> The following objects are masked from ‘package:AMR’: #>  #>     %like%, like #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> Warning: It should never be needed to print an antibiotic selector class. Are you #> using data.table? Then add the argument with = FALSE, see our examples at #> ?ab_selector. #> Class 'ab_selector' #> [1] IPM MEM if (require(\"data.table\")) {   # so `with = FALSE` is required   dt[, carbapenems(), with = FALSE] } #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #>         IPM   MEM #>       <sir> <sir> #>    1:  <NA>  <NA> #>    2:  <NA>  <NA> #>    3:  <NA>  <NA> #>    4:  <NA>  <NA> #>    5:  <NA>  <NA> #>   ---             #> 1996:  <NA>  <NA> #> 1997:     S     S #> 1998:     S     S #> 1999:     S     S #> 2000:     S     S  # for multiple selections or AB selectors, `with = FALSE` is not needed: if (require(\"data.table\")) {   dt[, c(\"mo\", aminoglycosides())] } #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #>                 mo   GEN   TOB   AMK   KAN #>               <mo> <sir> <sir> <sir> <sir> #>    1: B_ESCHR_COLI  <NA>  <NA>  <NA>  <NA> #>    2: B_ESCHR_COLI  <NA>  <NA>  <NA>  <NA> #>    3: B_STPHY_EPDR  <NA>  <NA>  <NA>  <NA> #>    4: B_STPHY_EPDR  <NA>  <NA>  <NA>  <NA> #>    5: B_STPHY_EPDR  <NA>  <NA>  <NA>  <NA> #>   ---                                      #> 1996: B_STRPT_PNMN     R     R     R     R #> 1997: B_ESCHR_COLI     S     S     S  <NA> #> 1998: B_STPHY_CONS     S  <NA>  <NA>  <NA> #> 1999: B_ESCHR_COLI     S     S  <NA>  <NA> #> 2000: B_KLBSL_PNMN     S     S  <NA>  <NA> if (require(\"data.table\")) {   dt[, c(carbapenems(), aminoglycosides())] } #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #>         IPM   MEM   GEN   TOB   AMK   KAN #>       <sir> <sir> <sir> <sir> <sir> <sir> #>    1:  <NA>  <NA>  <NA>  <NA>  <NA>  <NA> #>    2:  <NA>  <NA>  <NA>  <NA>  <NA>  <NA> #>    3:  <NA>  <NA>  <NA>  <NA>  <NA>  <NA> #>    4:  <NA>  <NA>  <NA>  <NA>  <NA>  <NA> #>    5:  <NA>  <NA>  <NA>  <NA>  <NA>  <NA> #>   ---                                     #> 1996:  <NA>  <NA>     R     R     R     R #> 1997:     S     S     S     S     S  <NA> #> 1998:     S     S     S  <NA>  <NA>  <NA> #> 1999:     S     S     S     S  <NA>  <NA> #> 2000:     S     S     S     S  <NA>  <NA>  # row filters are also supported: if (require(\"data.table\")) {   dt[any(carbapenems() == \"S\"), ] } #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #>            date patient   age gender       ward           mo   PEN   OXA   FLC #>          <Date>  <char> <num> <char>     <char>         <mo> <sir> <sir> <sir> #>   1: 2002-01-19  738003    71      M   Clinical B_ESCHR_COLI     R  <NA>  <NA> #>   2: 2002-01-19  738003    71      M   Clinical B_ESCHR_COLI     R  <NA>  <NA> #>   3: 2002-01-22  F35553    50      M        ICU B_PROTS_MRBL     R  <NA>  <NA> #>   4: 2002-01-22  F35553    50      M        ICU B_PROTS_MRBL     R  <NA>  <NA> #>   5: 2002-02-05  067927    45      F        ICU B_SERRT_MRCS     R  <NA>  <NA> #>  ---                                                                           #> 905: 2005-04-12  D71461    70      M        ICU B_ESCHR_COLI     R  <NA>  <NA> #> 906: 2009-11-12  650870    69      F Outpatient B_ESCHR_COLI     R  <NA>  <NA> #> 907: 2012-06-14  8CBCF2    41      F   Clinical B_STPHY_CONS     R     S     S #> 908: 2012-10-11  175532    78      M   Clinical B_ESCHR_COLI     R  <NA>  <NA> #> 909: 2013-11-23  A97263    77      M   Clinical B_KLBSL_PNMN     R  <NA>  <NA> #>        AMX   AMC   AMP   TZP   CZO   FEP   CXM   FOX   CTX   CAZ   CRO   GEN #>      <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> #>   1:  <NA>     I  <NA>  <NA>  <NA>  <NA>     S  <NA>     S  <NA>     S  <NA> #>   2:  <NA>     I  <NA>  <NA>  <NA>  <NA>     S  <NA>     S  <NA>     S  <NA> #>   3:  <NA>     I  <NA>  <NA>  <NA>  <NA>     S  <NA>     S     S     S  <NA> #>   4:  <NA>     I  <NA>  <NA>  <NA>  <NA>     S  <NA>     S     S     S  <NA> #>   5:     R     R     R  <NA>     R  <NA>     R     R  <NA>  <NA>  <NA>  <NA> #>  ---                                                                         #> 905:     S     S     S     S  <NA>     S     S     S     S     S     S     S #> 906:     S     S     S     S     S     S     S     S     S     S     S     S #> 907:  <NA>     S  <NA>  <NA>     S     S     S     S     S     R     S     S #> 908:     R     S     R     S  <NA>     S     R     R     S     S     S     S #> 909:     R     S     R     S  <NA>     S     S     S     S     S     S     S #>        TOB   AMK   KAN   TMP   SXT   NIT   FOS   LNZ   CIP   MFX   VAN   TEC #>      <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> #>   1:     S  <NA>  <NA>     S     S  <NA>  <NA>     R  <NA>  <NA>     R     R #>   2:     S  <NA>  <NA>     S     S  <NA>  <NA>     R  <NA>  <NA>     R     R #>   3:  <NA>  <NA>  <NA>     S     S     R  <NA>     R     S  <NA>     R     R #>   4:  <NA>  <NA>  <NA>     S     S     R  <NA>     R     S  <NA>     R     R #>   5:  <NA>  <NA>  <NA>     S     S     R  <NA>     R     S  <NA>     R     R #>  ---                                                                         #> 905:     S     S  <NA>  <NA>     S     S  <NA>     R     S  <NA>     R     R #> 906:     S     S  <NA>     S     S     S  <NA>     R     S  <NA>     R     R #> 907:  <NA>  <NA>  <NA>     S     S  <NA>  <NA>  <NA>     S  <NA>     S  <NA> #> 908:     S  <NA>  <NA>     R     R     R  <NA>     R     R     R     R     R #> 909:     S  <NA>  <NA>     S     S     S  <NA>     R     S  <NA>     R     R #>        TCY   TGC   DOX   ERY   CLI   AZM   IPM   MEM   MTR   CHL   COL   MUP #>      <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> #>   1:  <NA>  <NA>  <NA>     R     R     R     S  <NA>  <NA>  <NA>  <NA>  <NA> #>   2:  <NA>  <NA>  <NA>     R     R     R     S  <NA>  <NA>  <NA>  <NA>  <NA> #>   3:     R     R     R     R     R     R     S  <NA>  <NA>  <NA>     R  <NA> #>   4:     R     R     R     R     R     R     S  <NA>  <NA>  <NA>     R  <NA> #>   5:     R     R     R     R     R     R     S  <NA>  <NA>  <NA>     R  <NA> #>  ---                                                                         #> 905:  <NA>  <NA>  <NA>     R     R     R     S     S  <NA>  <NA>  <NA>  <NA> #> 906:  <NA>  <NA>  <NA>     R     R     R     S     S  <NA>  <NA>  <NA>  <NA> #> 907:  <NA>  <NA>  <NA>     S     S     S     S     S  <NA>  <NA>     R  <NA> #> 908:  <NA>  <NA>  <NA>     R     R     R     S     S  <NA>  <NA>     S  <NA> #> 909:  <NA>  <NA>  <NA>     R     R     R     S     S  <NA>  <NA>     S  <NA> #>        RIF #>      <sir> #>   1:     R #>   2:     R #>   3:     R #>   4:     R #>   5:     R #>  ---       #> 905:     R #> 906:     R #> 907:  <NA> #> 908:     R #> 909:     R if (require(\"data.table\")) {   dt[any(carbapenems() == \"S\"), penicillins(), with = FALSE] } #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> ℹ For penicillins() using columns 'PEN' (benzylpenicillin), 'OXA' #>   (oxacillin), 'FLC' (flucloxacillin), 'AMX' (amoxicillin), 'AMC' #>   (amoxicillin/clavulanic acid), 'AMP' (ampicillin), and 'TZP' #>   (piperacillin/tazobactam) #>        PEN   OXA   FLC   AMX   AMC   AMP   TZP #>      <sir> <sir> <sir> <sir> <sir> <sir> <sir> #>   1:     R  <NA>  <NA>  <NA>     I  <NA>  <NA> #>   2:     R  <NA>  <NA>  <NA>     I  <NA>  <NA> #>   3:     R  <NA>  <NA>  <NA>     I  <NA>  <NA> #>   4:     R  <NA>  <NA>  <NA>     I  <NA>  <NA> #>   5:     R  <NA>  <NA>     R     R     R  <NA> #>  ---                                           #> 905:     R  <NA>  <NA>     S     S     S     S #> 906:     R  <NA>  <NA>     S     S     S     S #> 907:     R     S     S  <NA>     S  <NA>  <NA> #> 908:     R  <NA>  <NA>     R     S     R     S #> 909:     R  <NA>  <NA>     R     S     R     S # }"},{"path":"https://msberends.github.io/AMR/reference/antibiotics.html","id":null,"dir":"Reference","previous_headings":"","what":"Data Sets with 605 Antimicrobial Drugs — antibiotics","title":"Data Sets with 605 Antimicrobial Drugs — antibiotics","text":"Two data sets containing antibiotics/antimycotics antivirals. Use .ab() one ab_* functions retrieve values antibiotics data set. Three identifiers included data set: antibiotic ID (ab, primarily used package) defined WHONET/EARS-Net, ATC code (atc) defined , Compound ID (cid) found PubChem. properties data set derived one codes. Note drugs multiple ATC codes.","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotics.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Data Sets with 605 Antimicrobial Drugs — antibiotics","text":"","code":"antibiotics  antivirals"},{"path":"https://msberends.github.io/AMR/reference/antibiotics.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data Sets with 605 Antimicrobial Drugs — antibiotics","text":"object class tbl_df (inherits tbl, data.frame) 120 rows 11 columns.","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotics.html","id":"for-the-antibiotics-data-set-a-tibble-with-observations-and-variables-","dir":"Reference","previous_headings":"","what":"For the antibiotics data set: a tibble with 485 observations and 14 variables:","title":"Data Sets with 605 Antimicrobial Drugs — antibiotics","text":"ab Antibiotic ID used package (AMC), using official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes available. unique identifier. cid Compound ID found PubChem. unique identifier. name Official name used WHONET/EARS-Net . unique identifier. group short concise group name, based WHONET WHOCC definitions atc ATC codes (Anatomical Therapeutic Chemical) defined WHOCC, like J01CR02 atc_group1 Official pharmacological subgroup (3rd level ATC code) defined WHOCC, like \"Macrolides, lincosamides streptogramins\" atc_group2 Official chemical subgroup (4th level ATC code) defined WHOCC, like \"Macrolides\" abbr List abbreviations used many countries, also antibiotic susceptibility testing (AST) synonyms Synonyms (often trade names) drug, found PubChem based compound ID oral_ddd Defined Daily Dose (DDD), oral treatment, currently available 179 drugs oral_units Units oral_ddd iv_ddd Defined Daily Dose (DDD), parenteral (intravenous) treatment, currently available 153 drugs iv_units Units iv_ddd loinc codes associated name antimicrobial drug Logical Observation Identifiers Names Codes (LOINC), Version 2.76 (18 September, 2023). Use ab_loinc() retrieve quickly, see ab_property().","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotics.html","id":"for-the-antivirals-data-set-a-tibble-with-observations-and-variables-","dir":"Reference","previous_headings":"","what":"For the antivirals data set: a tibble with 120 observations and 11 variables:","title":"Data Sets with 605 Antimicrobial Drugs — antibiotics","text":"av Antiviral ID used package (ACI), using official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes available. unique identifier. Combinations codes contain + indicate , ATA+COBI atazanavir/cobicistat. name Official name used WHONET/EARS-Net . unique identifier. atc ATC codes (Anatomical Therapeutic Chemical) defined WHOCC cid Compound ID found PubChem. unique identifier. atc_group Official pharmacological subgroup (3rd level ATC code) defined WHOCC synonyms Synonyms (often trade names) drug, found PubChem based compound ID oral_ddd Defined Daily Dose (DDD), oral treatment oral_units Units oral_ddd iv_ddd Defined Daily Dose (DDD), parenteral treatment iv_units Units iv_ddd loinc codes associated name antiviral drug Logical Observation Identifiers Names Codes (LOINC), Version 2.76 (18 September, 2023). Use av_loinc() retrieve quickly, see av_property().","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotics.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data Sets with 605 Antimicrobial Drugs — antibiotics","text":"World Health Organization () Collaborating Centre Drug Statistics Methodology (WHOCC): https://atcddd.fhi./atc_ddd_index/ Logical Observation Identifiers Names Codes (LOINC), Version 2.76 (18 September, 2023). Accessed https://loinc.org October 19th, 2023. European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotics.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Data Sets with 605 Antimicrobial Drugs — antibiotics","text":"Properties based ATC code available ATC available. properties : atc_group1, atc_group2, oral_ddd, oral_units, iv_ddd iv_units. Synonyms (.e. trade names) derived PubChem Compound ID (column cid) consequently available CID available.","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotics.html","id":"direct-download","dir":"Reference","previous_headings":"","what":"Direct download","title":"Data Sets with 605 Antimicrobial Drugs — antibiotics","text":"Like data sets package, data sets publicly available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotics.html","id":"whocc","dir":"Reference","previous_headings":"","what":"WHOCC","title":"Data Sets with 605 Antimicrobial Drugs — antibiotics","text":"package contains ~550 antibiotic, antimycotic antiviral drugs Anatomical Therapeutic Chemical (ATC) codes, ATC groups Defined Daily Dose (DDD) World Health Organization Collaborating Centre Drug Statistics Methodology (WHOCC, https://atcddd.fhi.) Pharmaceuticals Community Register European Commission (https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm). become gold standard international drug utilisation monitoring research. WHOCC located Oslo Norwegian Institute Public Health funded Norwegian government. European Commission executive European Union promotes general interest. NOTE: WHOCC copyright allow use commercial purposes, unlike info package. See https://atcddd.fhi./copyright_disclaimer/.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/antibiotics.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Data Sets with 605 Antimicrobial Drugs — antibiotics","text":"","code":"antibiotics #> # A tibble: 485 × 14 #>    ab        cid name   group atc   atc_group1 atc_group2 abbreviations synonyms #>    <ab>    <dbl> <chr>  <chr> <lis> <chr>      <chr>      <list>        <named > #>  1 AMA      4649 4-ami… Anti… <chr> Drugs for… Aminosali… <chr [1]>     <chr>    #>  2 ACM   6450012 Acety… Macr… <chr> NA         NA         <chr [1]>     <chr>    #>  3 ASP  49787020 Acety… Macr… <chr> NA         NA         <chr [1]>     <chr>    #>  4 ALS      8954 Aldes… Othe… <chr> Drugs for… Drugs for… <chr [1]>     <chr>    #>  5 AMK     37768 Amika… Amin… <chr> Aminoglyc… Other ami… <chr [5]>     <chr>    #>  6 AKF        NA Amika… Amin… <chr> NA         NA         <chr [1]>     <chr>    #>  7 AMO     54260 Amoro… Anti… <chr> Antifunga… Other ant… <chr [1]>     <chr>    #>  8 AMX     33613 Amoxi… Beta… <chr> Beta-lact… Penicilli… <chr [3]>     <chr>    #>  9 AMC  23665637 Amoxi… Beta… <chr> Beta-lact… Combinati… <chr [5]>     <chr>    #> 10 AXS    465441 Amoxi… Beta… <chr> NA         NA         <chr [1]>     <chr>    #> # ℹ 475 more rows #> # ℹ 5 more variables: oral_ddd <dbl>, oral_units <chr>, iv_ddd <dbl>, #> #   iv_units <chr>, loinc <list> antivirals #> # A tibble: 120 × 11 #>    av       name      atc      cid atc_group synonyms oral_ddd oral_units iv_ddd #>    <av>     <chr>     <chr>  <dbl> <chr>     <list>      <dbl> <chr>       <dbl> #>  1 ABA      Abacavir  J05A… 4.41e5 Nucleosi… <chr>         0.6 g              NA #>  2 ACI      Aciclovir J05A… 1.35e8 Nucleosi… <chr>         4   g               4 #>  3 ADD      Adefovir… J05A… 6.09e4 Nucleosi… <chr>        10   mg             NA #>  4 AME      Amenamev… J05A… 1.14e7 Other an… <chr>         0.4 g              NA #>  5 AMP      Amprenav… J05A… 6.50e4 Protease… <chr>         1.2 g              NA #>  6 ASU      Asunapre… J05A… 1.61e7 Antivira… <chr>         0.2 g              NA #>  7 ATA      Atazanav… J05A… 1.48e5 Protease… <chr>         0.3 g              NA #>  8 ATA+COBI Atazanav… J05A… 8.66e7 Antivira… <chr>        NA   NA             NA #>  9 ATA+RIT  Atazanav… J05A… 2.51e7 Antivira… <chr>         0.3 g              NA #> 10 BAM      Baloxavi… J05A… 1.24e8 Other an… <chr>        40   mg             NA #> # ℹ 110 more rows #> # ℹ 2 more variables: iv_units <chr>, loinc <list>"},{"path":"https://msberends.github.io/AMR/reference/as.ab.html","id":null,"dir":"Reference","previous_headings":"","what":"Transform Input to an Antibiotic ID — as.ab","title":"Transform Input to an Antibiotic ID — as.ab","text":"Use function determine antibiotic drug code one antibiotics. data set antibiotics searched abbreviations, official names synonyms (brand names).","code":""},{"path":"https://msberends.github.io/AMR/reference/as.ab.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transform Input to an Antibiotic ID — as.ab","text":"","code":"as.ab(x, flag_multiple_results = TRUE, info = interactive(), ...)  is.ab(x)"},{"path":"https://msberends.github.io/AMR/reference/as.ab.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transform Input to an Antibiotic ID — as.ab","text":"x character vector determine antibiotic ID flag_multiple_results logical indicate whether note printed console probably one antibiotic drug code name can retrieved single input value. info logical indicate whether progress bar printed - default TRUE interactive mode ... arguments passed internal functions","code":""},{"path":"https://msberends.github.io/AMR/reference/as.ab.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transform Input to an Antibiotic ID — as.ab","text":"character  vector additional class ab","code":""},{"path":"https://msberends.github.io/AMR/reference/as.ab.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Transform Input to an Antibiotic ID — as.ab","text":"entries antibiotics data set three different identifiers: human readable EARS-Net code (column ab, used ECDC WHONET), ATC code (column atc, used ), CID code (column cid, Compound ID, used PubChem). data set contains 5,000 official brand names many different countries, found PubChem. drugs contain multiple ATC codes. properties searched user input. .ab() can correct different forms misspelling: Wrong spelling drug names (\"tobramicin\" \"gentamycin\"), corrects audible similarities f/ph, x/ks, c/z/s, t/th, etc. many vowels consonants Switching two characters (\"mreopenem\", often case clinical data, doctors typed fast) Digitalised paper records, leaving artefacts like 0/o/O (zero O's), B/8, n/r, etc. Use ab_* functions get properties based returned antibiotic ID, see Examples. Note: .ab() ab_* functions may use long regular expression match brand names antimicrobial drugs. may fail systems. can add manual codes considered .ab() ab_* functions, see add_custom_antimicrobials().","code":""},{"path":"https://msberends.github.io/AMR/reference/as.ab.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Transform Input to an Antibiotic ID — as.ab","text":"World Health Organization () Collaborating Centre Drug Statistics Methodology: https://atcddd.fhi./atc_ddd_index/ European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm","code":""},{"path":"https://msberends.github.io/AMR/reference/as.ab.html","id":"whocc","dir":"Reference","previous_headings":"","what":"WHOCC","title":"Transform Input to an Antibiotic ID — as.ab","text":"package contains ~550 antibiotic, antimycotic antiviral drugs Anatomical Therapeutic Chemical (ATC) codes, ATC groups Defined Daily Dose (DDD) World Health Organization Collaborating Centre Drug Statistics Methodology (WHOCC, https://atcddd.fhi.) Pharmaceuticals Community Register European Commission (https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm). become gold standard international drug utilisation monitoring research. WHOCC located Oslo Norwegian Institute Public Health funded Norwegian government. European Commission executive European Union promotes general interest. NOTE: WHOCC copyright allow use commercial purposes, unlike info package. See https://atcddd.fhi./copyright_disclaimer/.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.ab.html","id":"reference-data-publicly-available","dir":"Reference","previous_headings":"","what":"Reference Data Publicly Available","title":"Transform Input to an Antibiotic ID — as.ab","text":"data sets AMR package (microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) publicly freely available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. also provide tab-separated plain text files machine-readable suitable input software program, laboratory information systems. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/as.ab.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Transform Input to an Antibiotic ID — as.ab","text":"","code":"# these examples all return \"ERY\", the ID of erythromycin: as.ab(\"J01FA01\") #> Class 'ab' #> [1] ERY as.ab(\"J 01 FA 01\") #> Class 'ab' #> [1] ERY as.ab(\"Erythromycin\") #> Class 'ab' #> [1] ERY as.ab(\"eryt\") #> Class 'ab' #> [1] ERY as.ab(\"   eryt 123\") #> Class 'ab' #> [1] ERY as.ab(\"ERYT\") #> Class 'ab' #> [1] ERY as.ab(\"ERY\") #> Class 'ab' #> [1] ERY as.ab(\"eritromicine\") # spelled wrong, yet works #> Class 'ab' #> [1] ERY as.ab(\"Erythrocin\") # trade name #> Class 'ab' #> [1] ERY as.ab(\"Romycin\") # trade name #> Class 'ab' #> [1] ERY  # spelling from different languages and dyslexia are no problem ab_atc(\"ceftriaxon\") #> [1] \"J01DD04\" ab_atc(\"cephtriaxone\") # small spelling error #> [1] \"J01DD04\" ab_atc(\"cephthriaxone\") # or a bit more severe #> [1] \"J01DD04\" ab_atc(\"seephthriaaksone\") # and even this works #> [1] \"J01DD04\"  # use ab_* functions to get a specific properties (see ?ab_property); # they use as.ab() internally: ab_name(\"J01FA01\") #> [1] \"Erythromycin\" ab_name(\"eryt\") #> [1] \"Erythromycin\"  # \\donttest{ if (require(\"dplyr\")) {   # you can quickly rename 'sir' columns using set_ab_names() with dplyr:   example_isolates %>%     set_ab_names(where(is.sir), property = \"atc\") } #> # A tibble: 2,000 × 46 #>    date       patient   age gender ward     mo           J01CE01 J01CF04 J01CF05 #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir>   <sir>   <sir>   #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R       NA      NA      #>  2 2002-01-03 A77334     65 F      Clinical B_ESCHR_COLI R       NA      NA      #>  3 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R       NA      R       #>  4 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R       NA      R       #>  5 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R       NA      R       #>  6 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R       NA      R       #>  7 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R       NA      S       #>  8 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R       NA      S       #>  9 2002-01-16 067927     45 F      ICU      B_STPHY_EPDR R       NA      R       #> 10 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R       NA      S       #> # ℹ 1,990 more rows #> # ℹ 37 more variables: J01CA04 <sir>, J01CR02 <sir>, J01CA01 <sir>, #> #   J01CR05 <sir>, J01DB04 <sir>, J01DE01 <sir>, J01DC02 <sir>, J01DC01 <sir>, #> #   J01DD01 <sir>, J01DD02 <sir>, J01DD04 <sir>, J01GB03 <sir>, J01GB01 <sir>, #> #   J01GB06 <sir>, J01GB04 <sir>, J01EA01 <sir>, J01EE01 <sir>, J01XE01 <sir>, #> #   J01XX01 <sir>, J01XX08 <sir>, J01MA02 <sir>, J01MA14 <sir>, J01XA01 <sir>, #> #   J01XA02 <sir>, J01AA07 <sir>, J01AA12 <sir>, J01AA02 <sir>, … # }"},{"path":"https://msberends.github.io/AMR/reference/as.av.html","id":null,"dir":"Reference","previous_headings":"","what":"Transform Input to an Antiviral Drug ID — as.av","title":"Transform Input to an Antiviral Drug ID — as.av","text":"Use function determine antiviral drug code one antiviral drugs. data set antivirals searched abbreviations, official names synonyms (brand names).","code":""},{"path":"https://msberends.github.io/AMR/reference/as.av.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transform Input to an Antiviral Drug ID — as.av","text":"","code":"as.av(x, flag_multiple_results = TRUE, info = interactive(), ...)  is.av(x)"},{"path":"https://msberends.github.io/AMR/reference/as.av.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transform Input to an Antiviral Drug ID — as.av","text":"x character vector determine antiviral drug ID flag_multiple_results logical indicate whether note printed console probably one antiviral drug code name can retrieved single input value. info logical indicate whether progress bar printed - default TRUE interactive mode ... arguments passed internal functions","code":""},{"path":"https://msberends.github.io/AMR/reference/as.av.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transform Input to an Antiviral Drug ID — as.av","text":"character  vector additional class ab","code":""},{"path":"https://msberends.github.io/AMR/reference/as.av.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Transform Input to an Antiviral Drug ID — as.av","text":"entries antivirals data set three different identifiers: human readable EARS-Net code (column ab, used ECDC WHONET), ATC code (column atc, used ), CID code (column cid, Compound ID, used PubChem). data set contains 5,000 official brand names many different countries, found PubChem. drugs contain multiple ATC codes. properties searched user input. .av() can correct different forms misspelling: Wrong spelling drug names (\"acyclovir\"), corrects audible similarities f/ph, x/ks, c/z/s, t/th, etc. many vowels consonants Switching two characters (\"aycclovir\", often case clinical data, doctors typed fast) Digitalised paper records, leaving artefacts like 0/o/O (zero O's), B/8, n/r, etc. Use av_* functions get properties based returned antiviral drug ID, see Examples. Note: .av() av_* functions may use long regular expression match brand names antimicrobial drugs. may fail systems.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.av.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Transform Input to an Antiviral Drug ID — as.av","text":"World Health Organization () Collaborating Centre Drug Statistics Methodology: https://atcddd.fhi./atc_ddd_index/ European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm","code":""},{"path":"https://msberends.github.io/AMR/reference/as.av.html","id":"whocc","dir":"Reference","previous_headings":"","what":"WHOCC","title":"Transform Input to an Antiviral Drug ID — as.av","text":"package contains ~550 antibiotic, antimycotic antiviral drugs Anatomical Therapeutic Chemical (ATC) codes, ATC groups Defined Daily Dose (DDD) World Health Organization Collaborating Centre Drug Statistics Methodology (WHOCC, https://atcddd.fhi.) Pharmaceuticals Community Register European Commission (https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm). become gold standard international drug utilisation monitoring research. WHOCC located Oslo Norwegian Institute Public Health funded Norwegian government. European Commission executive European Union promotes general interest. NOTE: WHOCC copyright allow use commercial purposes, unlike info package. See https://atcddd.fhi./copyright_disclaimer/.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.av.html","id":"reference-data-publicly-available","dir":"Reference","previous_headings":"","what":"Reference Data Publicly Available","title":"Transform Input to an Antiviral Drug ID — as.av","text":"data sets AMR package (microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) publicly freely available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. also provide tab-separated plain text files machine-readable suitable input software program, laboratory information systems. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/as.av.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Transform Input to an Antiviral Drug ID — as.av","text":"","code":"# these examples all return \"ACI\", the ID of aciclovir: as.av(\"J05AB01\") #> Class 'av' #> [1] ACI as.av(\"J 05 AB 01\") #> Class 'av' #> [1] ACI as.av(\"Aciclovir\") #> Class 'av' #> [1] ACI as.av(\"aciclo\") #> Class 'av' #> [1] ACI as.av(\"   aciclo 123\") #> Class 'av' #> [1] ACI as.av(\"ACICL\") #> Class 'av' #> [1] ACI as.av(\"ACI\") #> Class 'av' #> [1] ACI as.av(\"Virorax\") # trade name #> Class 'av' #> [1] ACI as.av(\"Zovirax\") # trade name #> Class 'av' #> [1] ACI  as.av(\"acyklofir\") # severe spelling error, yet works #> Class 'av' #> [1] ACI  # use av_* functions to get a specific properties (see ?av_property); # they use as.av() internally: av_name(\"J05AB01\") #> [1] \"Aciclovir\" av_name(\"acicl\") #> [1] \"Aciclovir\""},{"path":"https://msberends.github.io/AMR/reference/as.disk.html","id":null,"dir":"Reference","previous_headings":"","what":"Transform Input to Disk Diffusion Diameters — as.disk","title":"Transform Input to Disk Diffusion Diameters — as.disk","text":"transforms vector new class disk, disk diffusion growth zone size (around antibiotic disk) millimetres 6 50.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.disk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transform Input to Disk Diffusion Diameters — as.disk","text":"","code":"as.disk(x, na.rm = FALSE)  NA_disk_  is.disk(x)"},{"path":"https://msberends.github.io/AMR/reference/as.disk.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Transform Input to Disk Diffusion Diameters — as.disk","text":"object class disk (inherits integer) length 1.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.disk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transform Input to Disk Diffusion Diameters — as.disk","text":"x vector na.rm logical indicating whether missing values removed","code":""},{"path":"https://msberends.github.io/AMR/reference/as.disk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transform Input to Disk Diffusion Diameters — as.disk","text":"integer additional class disk","code":""},{"path":"https://msberends.github.io/AMR/reference/as.disk.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Transform Input to Disk Diffusion Diameters — as.disk","text":"Interpret disk values SIR values .sir(). supports guidelines EUCAST CLSI. Disk diffusion growth zone sizes must 6 50 millimetres. Values higher 50 lower 100 maximised 50. others input values outside 6-50 range return NA. NA_disk_ missing value new disk class.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/as.disk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Transform Input to Disk Diffusion Diameters — as.disk","text":"","code":"# transform existing disk zones to the `disk` class (using base R) df <- data.frame(   microorganism = \"Escherichia coli\",   AMP = 20,   CIP = 14,   GEN = 18,   TOB = 16 ) df[, 2:5] <- lapply(df[, 2:5], as.disk) str(df) #> 'data.frame':\t1 obs. of  5 variables: #>  $ microorganism: chr \"Escherichia coli\" #>  $ AMP          : 'disk' int 20 #>  $ CIP          : 'disk' int 14 #>  $ GEN          : 'disk' int 18 #>  $ TOB          : 'disk' int 16  # \\donttest{ # transforming is easier with dplyr: if (require(\"dplyr\")) {   df %>% mutate(across(AMP:TOB, as.disk)) } #>      microorganism AMP CIP GEN TOB #> 1 Escherichia coli  20  14  18  16 # }  # interpret disk values, see ?as.sir as.sir(   x = as.disk(18),   mo = \"Strep pneu\", # `mo` will be coerced with as.mo()   ab = \"ampicillin\", # and `ab` with as.ab()   guideline = \"EUCAST\" ) #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting disk diffusion zones: 'ampicillin' (AMP), EUCAST 2024... #>  OK  #> Class 'sir' #> [1] R  # interpret whole data set, pretend to be all from urinary tract infections: as.sir(df, uti = TRUE) #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting disk diffusion zones: column 'AMP' (ampicillin), EUCAST #> 2024... #>  OK  #> Interpreting disk diffusion zones: column 'CIP' (ciprofloxacin), EUCAST #> 2024... #>  OK  #> Interpreting disk diffusion zones: column 'GEN' (gentamicin), EUCAST #> 2024... #>  OK  #> Interpreting disk diffusion zones: column 'TOB' (tobramycin), EUCAST #> 2024... #>  OK  #>      microorganism AMP  CIP GEN TOB #> 1 Escherichia coli   S <NA>   S   S"},{"path":"https://msberends.github.io/AMR/reference/as.mic.html","id":null,"dir":"Reference","previous_headings":"","what":"Transform Input to Minimum Inhibitory Concentrations (MIC) — as.mic","title":"Transform Input to Minimum Inhibitory Concentrations (MIC) — as.mic","text":"transforms vectors new class mic, treats input decimal numbers, maintaining operators (\">=\") allowing valid MIC values known field (medical) microbiology.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.mic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transform Input to Minimum Inhibitory Concentrations (MIC) — as.mic","text":"","code":"as.mic(x, na.rm = FALSE, keep_operators = \"all\")  is.mic(x)  NA_mic_  rescale_mic(x, mic_range, keep_operators = \"edges\", as.mic = TRUE)  # S3 method for mic droplevels(x, as.mic = FALSE, ...)"},{"path":"https://msberends.github.io/AMR/reference/as.mic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transform Input to Minimum Inhibitory Concentrations (MIC) — as.mic","text":"x character numeric vector na.rm logical indicating whether missing values removed keep_operators character specifying handle operators (> <=) input. Accepts one three values: \"\" (TRUE) keep operators, \"none\" (FALSE) remove operators, \"edges\" keep operators ends range. mic_range manual range limit MIC values, e.g., mic_range = c(0.001, 32). Use NA set limit one side, e.g., mic_range = c(NA, 32). .mic logical indicate whether mic class kept - default FALSE ... arguments passed methods","code":""},{"path":"https://msberends.github.io/AMR/reference/as.mic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transform Input to Minimum Inhibitory Concentrations (MIC) — as.mic","text":"Ordered factor additional class mic, mathematical operations acts numeric vector. Bear mind outcome mathematical operation MICs return numeric value.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.mic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Transform Input to Minimum Inhibitory Concentrations (MIC) — as.mic","text":"interpret MIC values SIR values, use .sir() MIC values. supports guidelines EUCAST (2011-2024) CLSI (2011-2024). class MIC values quite special data type: formally ordered factor valid MIC values factor levels (make sure valid MIC values retained), mathematical operation acts decimal numbers:   makes possible maintain operators often come MIC values, \">=\" \"<=\", even filtering using numeric values data analysis, e.g.:   -called group generic functions implemented MIC class (!, !=, <, >=, exp(), log2()). functions stats package also implemented (quantile(), median(), fivenum()). Since sd() var() non-generic functions, extended. Use mad() alternative, use e.g. sd(.numeric(x)) x vector MIC values. Using .double() .numeric() MIC values remove operators return numeric vector. use .integer() MIC values R convention factors, return index factor levels (often useless regular users). Use droplevels() drop unused levels. default, return plain factor. Use droplevels(..., .mic = TRUE) maintain mic class. rescale_mic(), existing MIC ranges can limited defined range MIC values. can useful better compare MIC distributions. ggplot2, use one scale_*_mic() functions plot MIC values. allows custom MIC ranges plot intermediate log2 levels missing MIC values. NA_mic_ missing value new mic class, analogous e.g. base R's NA_character_.","code":"x <- random_mic(10) x #> Class 'mic' #>  [1] 16     1      8      8      64     >=128  0.0625 32     32     16  is.factor(x) #> [1] TRUE  x[1] * 2 #> [1] 32  median(x) #> [1] 26 x[x > 4] #> Class 'mic' #> [1] 16    8     8     64    >=128 32    32    16  df <- data.frame(x, hospital = \"A\") subset(df, x > 4) # or with dplyr: df %>% filter(x > 4) #>        x hospital #> 1     16        A #> 5     64        A #> 6  >=128        A #> 8     32        A #> 9     32        A #> 10    16        A"},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/as.mic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Transform Input to Minimum Inhibitory Concentrations (MIC) — as.mic","text":"","code":"mic_data <- as.mic(c(\">=32\", \"1.0\", \"1\", \"1.00\", 8, \"<=0.128\", \"8\", \"16\", \"16\")) mic_data #> Class 'mic' #> [1] >=32    1       1       1       8       <=0.128 8       16      16      is.mic(mic_data) #> [1] TRUE  # this can also coerce combined MIC/SIR values: as.mic(\"<=0.002; S\") #> Class 'mic' #> [1] <=0.002  # mathematical processing treats MICs as numeric values fivenum(mic_data) #> [1]  0.128  1.000  8.000 16.000 32.000 quantile(mic_data) #>     0%    25%    50%    75%   100%  #>  0.128  1.000  8.000 16.000 32.000  all(mic_data < 512) #> [1] TRUE  # limit MICs using rescale_mic() rescale_mic(mic_data, mic_range = c(4, 16)) #> Class 'mic' #> [1] >=16 <=4  <=4  <=4  8    <=4  8    >=16 >=16  # interpret MIC values as.sir(   x = as.mic(2),   mo = as.mo(\"Streptococcus pneumoniae\"),   ab = \"AMX\",   guideline = \"EUCAST\" ) #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'AMX' (amoxicillin), EUCAST 2024... #>  NOTE  #>   • Multiple breakpoints available for amoxicillin (AMX) in Streptococcus pneumoniae - assuming body site 'Meningitis'. #> Class 'sir' #> [1] R as.sir(   x = as.mic(c(0.01, 2, 4, 8)),   mo = as.mo(\"Streptococcus pneumoniae\"),   ab = \"AMX\",   guideline = \"EUCAST\" ) #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'AMX' (amoxicillin), EUCAST 2024... #>  NOTE  #>   • Multiple breakpoints available for amoxicillin (AMX) in Streptococcus pneumoniae - assuming body site 'Meningitis'. #> Class 'sir' #> [1] S R R R  # plot MIC values, see ?plot plot(mic_data)  plot(mic_data, mo = \"E. coli\", ab = \"cipro\")   if (require(\"ggplot2\")) {   autoplot(mic_data, mo = \"E. coli\", ab = \"cipro\") }  if (require(\"ggplot2\")) {   autoplot(mic_data, mo = \"E. coli\", ab = \"cipro\", language = \"nl\") # Dutch }"},{"path":"https://msberends.github.io/AMR/reference/as.mo.html","id":null,"dir":"Reference","previous_headings":"","what":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","title":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","text":"Use function get valid microorganism code (mo) based arbitrary user input. Determination done using intelligent rules complete taxonomic tree kingdoms Animalia, Archaea, Bacteria, Protozoa, microbial species kingdom Fungi (see Source). input can almost anything: full name (like \"Staphylococcus aureus\"), abbreviated name (\"S. aureus\"), abbreviation known field (\"MRSA\"), just genus. See Examples.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.mo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","text":"","code":"as.mo(   x,   Becker = FALSE,   Lancefield = FALSE,   minimum_matching_score = NULL,   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   reference_df = get_mo_source(),   ignore_pattern = getOption(\"AMR_ignore_pattern\", NULL),   cleaning_regex = getOption(\"AMR_cleaning_regex\", mo_cleaning_regex()),   language = get_AMR_locale(),   info = interactive(),   ... )  is.mo(x)  mo_uncertainties()  mo_renamed()  mo_failures()  mo_reset_session()  mo_cleaning_regex()"},{"path":"https://msberends.github.io/AMR/reference/as.mo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","text":"x character vector data.frame one two columns Becker logical indicate whether staphylococci categorised coagulase-negative staphylococci (\"CoNS\") coagulase-positive staphylococci (\"CoPS\") instead species, according Karsten Becker et al. (see Source). Please see Details full list staphylococcal species converted. excludes Staphylococcus aureus default, use Becker = \"\" also categorise S. aureus \"CoPS\". Lancefield logical indicate whether beta-haemolytic Streptococcus categorised Lancefield groups instead species, according Rebecca C. Lancefield (see Source). streptococci categorised first group, e.g. Streptococcus dysgalactiae group C, although officially also categorised groups G L. . Please see Details full list streptococcal species converted. excludes enterococci default (group D), use Lancefield = \"\" also categorise enterococci group D. minimum_matching_score numeric value set lower limit MO matching score. left blank, determined automatically based character length x, taxonomic kingdom human pathogenicity. keep_synonyms logical indicate old, previously valid taxonomic names must preserved corrected currently accepted names. default FALSE, return note old taxonomic names processed. default can set package option AMR_keep_synonyms, .e. options(AMR_keep_synonyms = TRUE) options(AMR_keep_synonyms = FALSE). reference_df data.frame used extra reference translating x valid mo. See set_mo_source() get_mo_source() automate usage codes (e.g. used analysis organisation). ignore_pattern Perl-compatible regular expression (case-insensitive) matches x must return NA. can convenient exclude known non-relevant input can also set package option AMR_ignore_pattern, e.g. options(AMR_ignore_pattern = \"(reported|contaminated flora)\"). cleaning_regex Perl-compatible regular expression (case-insensitive) clean input x. Every matched part x removed. default, outcome mo_cleaning_regex(), removes texts brackets texts \"species\" \"serovar\". default can set package option AMR_cleaning_regex. language language translate text like \"growth\", defaults system language (see get_AMR_locale()) info logical indicate progress bar printed 25 items coerced - default TRUE interactive mode ... arguments passed functions","code":""},{"path":"https://msberends.github.io/AMR/reference/as.mo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","text":"character  vector additional class mo","code":""},{"path":"https://msberends.github.io/AMR/reference/as.mo.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","text":"microorganism (MO) code package (class: mo) human readable typically looks like examples:   Values coerced considered 'unknown' returned MO code UNKNOWN warning. Use mo_* functions get properties based returned code, see Examples. .mo() function uses novel matching score algorithm (see Matching Score Microorganisms ) match input available microbial taxonomy package. lead effect e.g. \"E. coli\" (microorganism highly prevalent humans) return microbial ID Escherichia coli Entamoeba coli (microorganism less prevalent humans), although latter alphabetically come first. Becker = TRUE, following 85 staphylococci converted coagulase-negative group: S. argensis, S. arlettae, S. auricularis, S. borealis, S. caeli, S. caledonicus, S. canis, S. capitis, S. capitis capitis, S. capitis urealyticus, S. capitis ureolyticus, S. caprae, S. carnosus, S. carnosus carnosus, S. carnosus utilis, S. casei, S. caseolyticus, S. chromogenes, S. cohnii, S. cohnii cohnii, S. cohnii urealyticum, S. cohnii urealyticus, S. condimenti, S. croceilyticus, S. debuckii, S. devriesei, S. durrellii, S. edaphicus, S. epidermidis, S. equorum, S. equorum equorum, S. equorum linens, S. felis, S. fleurettii, S. gallinarum, S. haemolyticus, S. hominis, S. hominis hominis, S. hominis novobiosepticus, S. jettensis, S. kloosii, S. lentus, S. lloydii, S. lugdunensis, S. massiliensis, S. microti, S. muscae, S. nepalensis, S. pasteuri, S. petrasii, S. petrasii croceilyticus, S. petrasii jettensis, S. petrasii petrasii, S. petrasii pragensis, S. pettenkoferi, S. piscifermentans, S. pragensis, S. pseudoxylosus, S. pulvereri, S. ratti, S. rostri, S. saccharolyticus, S. saprophyticus, S. saprophyticus bovis, S. saprophyticus saprophyticus, S. schleiferi, S. schleiferi schleiferi, S. sciuri, S. sciuri carnaticus, S. sciuri lentus, S. sciuri rodentium, S. sciuri sciuri, S. simulans, S. stepanovicii, S. succinus, S. succinus casei, S. succinus succinus, S. taiwanensis, S. urealyticus, S. ureilyticus, S. veratri, S. vitulinus, S. vitulus, S. warneri, S. xylosus. following 16 staphylococci converted coagulase-positive group: S. agnetis, S. argenteus, S. coagulans, S. cornubiensis, S. delphini, S. hyicus, S. hyicus chromogenes, S. hyicus hyicus, S. intermedius, S. lutrae, S. pseudintermedius, S. roterodami, S. schleiferi coagulans, S. schweitzeri, S. simiae, S. singaporensis. Lancefield = TRUE, following streptococci converted corresponding Lancefield group: S. agalactiae (Group B), S. anginosus anginosus (Group F), S. anginosus whileyi (Group F), S. anginosus (Group F), S. canis (Group G), S. dysgalactiae dysgalactiae (Group C), S. dysgalactiae equisimilis (Group C), S. dysgalactiae (Group C), S. equi equi (Group C), S. equi ruminatorum (Group C), S. equi zooepidemicus (Group C), S. equi (Group C), S. pyogenes (Group ), S. salivarius salivarius (Group K), S. salivarius thermophilus (Group K), S. salivarius (Group K), S. sanguinis (Group H).","code":"Code               Full name   ---------------    --------------------------------------   B_KLBSL            Klebsiella   B_KLBSL_PNMN       Klebsiella pneumoniae   B_KLBSL_PNMN_RHNS  Klebsiella pneumoniae rhinoscleromatis   |   |    |    |   |   |    |    |   |   |    |    \\---> subspecies, a 3-5 letter acronym   |   |    \\----> species, a 3-6 letter acronym   |   \\----> genus, a 4-8 letter acronym   \\----> taxonomic kingdom: A (Archaea), AN (Animalia), B (Bacteria),                             F (Fungi), PL (Plantae), P (Protozoa)"},{"path":"https://msberends.github.io/AMR/reference/as.mo.html","id":"coping-with-uncertain-results","dir":"Reference","previous_headings":"","what":"Coping with Uncertain Results","title":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","text":"Results non-exact taxonomic input based matching score. lowest allowed score can set minimum_matching_score argument. default determined based character length input, taxonomic kingdom human pathogenicity taxonomic outcome. values matched uncertainty, message shown suggest user evaluate results mo_uncertainties(), returns data.frame specifications. increase quality matching, cleaning_regex argument can used clean input (.e., x). must regular expression matches parts input removed input matched available microbial taxonomy. matched Perl-compatible case-insensitive. default value cleaning_regex outcome helper function mo_cleaning_regex(). three helper functions can run using .mo() function: Use mo_uncertainties() get data.frame prints pretty format taxonomic names guessed. output contains matching score matches (see Matching Score Microorganisms ). Use mo_failures() get character vector values coerced valid value. Use mo_renamed() get data.frame values coerced based old, previously accepted taxonomic names.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.mo.html","id":"microbial-prevalence-of-pathogens-in-humans","dir":"Reference","previous_headings":"","what":"Microbial Prevalence of Pathogens in Humans","title":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","text":"coercion rules consider prevalence microorganisms humans, available prevalence column microorganisms data set. grouping human pathogenic prevalence explained section Matching Score Microorganisms .","code":""},{"path":"https://msberends.github.io/AMR/reference/as.mo.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","text":"Berends MS et al. (2022). AMR: R Package Working Antimicrobial Resistance Data. Journal Statistical Software, 104(3), 1-31; doi:10.18637/jss.v104.i03 Becker K et al. (2014). Coagulase-Negative Staphylococci. Clin Microbiol Rev. 27(4): 870-926; doi:10.1128/CMR.00109-13 Becker K et al. (2019). Implications identifying recently defined members S. aureus complex, S. argenteus S. schweitzeri: position paper members ESCMID Study Group staphylococci Staphylococcal Diseases (ESGS). Clin Microbiol Infect; doi:10.1016/j.cmi.2019.02.028 Becker K et al. (2020). Emergence coagulase-negative staphylococci. Expert Rev Anti Infect Ther. 18(4):349-366; doi:10.1080/14787210.2020.1730813 Lancefield RC (1933). serological differentiation human groups hemolytic streptococci. J Exp Med. 57(4): 571-95; doi:10.1084/jem.57.4.571 Berends MS et al. (2022). Trends Occurrence Phenotypic Resistance Coagulase-Negative Staphylococci (CoNS) Found Human Blood Northern Netherlands 2013 2019/ Micro.rganisms 10(9), 1801; doi:10.3390/microorganisms10091801 Parte, AC et al. (2020). List Prokaryotic names Standing Nomenclature (LPSN) moves DSMZ. International Journal Systematic Evolutionary Microbiology, 70, 5607-5612; doi:10.1099/ijsem.0.004332 . Accessed https://lpsn.dsmz.de December 11th, 2022. GBIF Secretariat (2023). GBIF Backbone Taxonomy. Checklist dataset doi:10.15468/39omei . Accessed https://www.gbif.org January 8th, 2024. Reimer, LC et al. (2022). BacDive 2022: knowledge base standardized bacterial archaeal data. Nucleic Acids Res., 50(D1):D741-D74; doi:10.1093/nar/gkab961 . Accessed https://bacdive.dsmz.de May 12th, 2023. Public Health Information Network Vocabulary Access Distribution System (PHIN VADS). US Edition SNOMED CT 1 September 2020. Value Set Name 'Microorganism', OID 2.16.840.1.114222.4.11.1009 (v12). URL: https://phinvads.cdc.gov Bartlett et al. (2022). comprehensive list bacterial pathogens infecting humans Microbiology 168:001269; doi:10.1099/mic.0.001269","code":""},{"path":"https://msberends.github.io/AMR/reference/as.mo.html","id":"matching-score-for-microorganisms","dir":"Reference","previous_headings":"","what":"Matching Score for Microorganisms","title":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","text":"ambiguous user input .mo() mo_* functions, returned results chosen based matching score using mo_matching_score(). matching score \\(m\\), calculated :  : \\(x\\) user input; \\(n\\) taxonomic name (genus, species, subspecies); \\(l_n\\) length \\(n\\); \\(lev\\) Levenshtein distance function (counting insertion 1, deletion substitution 2) needed change \\(x\\) \\(n\\); \\(p_n\\) human pathogenic prevalence group \\(n\\), described ; \\(k_n\\) taxonomic kingdom \\(n\\), set Bacteria = 1, Fungi = 1.25, Protozoa = 1.5, Archaea = 2, others = 3. grouping human pathogenic prevalence \\(p\\) based recent work Bartlett et al. (2022, doi:10.1099/mic.0.001269 ) extensively studied medical-scientific literature categorise bacterial species groups: Established, taxonomic species infected least three persons three references. records prevalence = 1.0 microorganisms data set; Putative, taxonomic species fewer three known cases. records prevalence = 1.25 microorganisms data set. Furthermore, genus present established list also prevalence = 1.0 microorganisms data set; genus present putative list prevalence = 1.25 microorganisms data set; species subspecies genus present two aforementioned groups, prevalence = 1.5 microorganisms data set; non-bacterial genus, species subspecies genus present following list, prevalence = 1.25 microorganisms data set: Absidia, Acanthamoeba, Acremonium, Aedes, Alternaria, Amoeba, Ancylostoma, Angiostrongylus, Anisakis, Anopheles, Apophysomyces, Arthroderma, Aspergillus, Aureobasidium, Basidiobolus, Beauveria, Blastocystis, Blastomyces, Candida, Capillaria, Chaetomium, Chrysonilia, Chrysosporium, Cladophialophora, Cladosporium, Conidiobolus, Contracaecum, Cordylobia, Cryptococcus, Curvularia, Demodex, Dermatobia, Dientamoeba, Diphyllobothrium, Dirofilaria, Echinostoma, Entamoeba, Enterobius, Exophiala, Exserohilum, Fasciola, Fonsecaea, Fusarium, Geotrichum, Giardia, Haloarcula, Halobacterium, Halococcus, Hendersonula, Heterophyes, Histomonas, Histoplasma, Hymenolepis, Hypomyces, Hysterothylacium, Kloeckera, Kodamaea, Leishmania, Lichtheimia, Lodderomyces, Malassezia, Malbranchea, Metagonimus, Meyerozyma, Microsporidium, Microsporum, Millerozyma, Mortierella, Mucor, Mycocentrospora, Necator, Nectria, Ochroconis, Oesophagostomum, Oidiodendron, Opisthorchis, Paecilomyces, Pediculus, Penicillium, Phlebotomus, Phoma, Pichia, Piedraia, Pithomyces, Pityrosporum, Pneumocystis, Pseudallescheria, Pseudoterranova, Pulex, Rhizomucor, Rhizopus, Rhodotorula, Saccharomyces, Saprochaete, Sarcoptes, Scedosporium, Scolecobasidium, Scopulariopsis, Scytalidium, Spirometra, Sporobolomyces, Sporotrichum, Stachybotrys, Strongyloides, Syngamus, Taenia, Talaromyces, Toxocara, Trichinella, Trichobilharzia, Trichoderma, Trichomonas, Trichophyton, Trichosporon, Trichostrongylus, Trichuris, Tritirachium, Trombicula, Trypanosoma, Tunga, Verticillium, Wuchereria; records prevalence = 2.0 microorganisms data set. calculating matching score, characters \\(x\\) \\(n\\) ignored -Z, -z, 0-9, spaces parentheses. matches sorted descending matching score user input values, top match returned. lead effect e.g., \"E. coli\" return microbial ID Escherichia coli (\\(m = 0.688\\), highly prevalent microorganism found humans) Entamoeba coli (\\(m = 0.381\\), less prevalent microorganism humans), although latter alphabetically come first.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.mo.html","id":"reference-data-publicly-available","dir":"Reference","previous_headings":"","what":"Reference Data Publicly Available","title":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","text":"data sets AMR package (microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) publicly freely available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. also provide tab-separated plain text files machine-readable suitable input software program, laboratory information systems. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/as.mo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","text":"","code":"# \\donttest{ # These examples all return \"B_STPHY_AURS\", the ID of S. aureus: as.mo(c(   \"sau\", # WHONET code   \"stau\",   \"STAU\",   \"staaur\",   \"S. aureus\",   \"S aureus\",   \"Sthafilokkockus aureus\", # handles incorrect spelling   \"Staphylococcus aureus (MRSA)\",   \"MRSA\", # Methicillin Resistant S. aureus   \"VISA\", # Vancomycin Intermediate S. aureus   \"VRSA\", # Vancomycin Resistant S. aureus   115329001 # SNOMED CT code )) #> Class 'mo' #>  [1] B_STPHY_AURS B_STPHY_AURS B_STPHY_AURS B_STPHY_AURS B_STPHY_AURS #>  [6] B_STPHY_AURS B_STPHY_AURS B_STPHY_AURS B_STPHY_AURS B_STPHY_AURS #> [11] B_STPHY_AURS B_STPHY_AURS  # Dyslexia is no problem - these all work: as.mo(c(   \"Ureaplasma urealyticum\",   \"Ureaplasma urealyticus\",   \"Ureaplasmium urealytica\",   \"Ureaplazma urealitycium\" )) #> Class 'mo' #> [1] B_URPLS_URLY B_URPLS_URLY B_URPLS_URLY B_URPLS_URLY  # input will get cleaned up with the input given in the `cleaning_regex` argument, # which defaults to `mo_cleaning_regex()`: cat(mo_cleaning_regex(), \"\\n\") #> ([^A-Za-z- \\(\\)\\[\\]{}]+|([({]|\\[).+([})]|\\])|(^| )(e?spp([^a-z]+|$)|e?ssp([^a-z]+|$)|serogr.?up[a-z]*|e?ss([^a-z]+|$)|e?sp([^a-z]+|$)|var([^a-z]+|$)|serovar[a-z]*|sube?species|biovar[a-z]*|e?species|Ig[ADEGM]|e?subsp|biotype|titer|dummy))   as.mo(\"Streptococcus group A\") #> Class 'mo' #> [1] B_STRPT_GRPA  as.mo(\"S. epidermidis\") # will remain species: B_STPHY_EPDR #> Class 'mo' #> [1] B_STPHY_EPDR as.mo(\"S. epidermidis\", Becker = TRUE) # will not remain species: B_STPHY_CONS #> Class 'mo' #> [1] B_STPHY_CONS  as.mo(\"S. pyogenes\") # will remain species: B_STRPT_PYGN #> Class 'mo' #> [1] B_STRPT_PYGN as.mo(\"S. pyogenes\", Lancefield = TRUE) # will not remain species: B_STRPT_GRPA #> Class 'mo' #> [1] B_STRPT_GRPA  # All mo_* functions use as.mo() internally too (see ?mo_property): mo_genus(\"E. coli\") #> [1] \"Escherichia\" mo_gramstain(\"ESCO\") #> [1] \"Gram-negative\" mo_is_intrinsic_resistant(\"ESCCOL\", ab = \"vanco\") #> ℹ Determining intrinsic resistance based on 'EUCAST Expert Rules' and #>   'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3 (2021). This note #>   will be shown once per session. #> [1] TRUE # }"},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":null,"dir":"Reference","previous_headings":"","what":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"Clean existing SIR values, interpret minimum inhibitory concentration (MIC) values disk diffusion diameters according EUCAST CLSI. .sir() transforms input new class sir, ordered factor containing levels S, SDD, , R, NI. breakpoints currently implemented: clinical microbiology: EUCAST 2011-2024 CLSI 2011-2024; veterinary microbiology: EUCAST 2021-2024 CLSI 2019-2024; ECOFFs (Epidemiological cut-values): EUCAST 2020-2024 CLSI 2022-2024. breakpoints used interpretation available clinical_breakpoints data set.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"","code":"as.sir(x, ...)  NA_sir_  is.sir(x)  is_sir_eligible(x, threshold = 0.05)  # S3 method for default as.sir(   x,   S = \"^(S|U)+$\",   I = \"^(I)+$\",   R = \"^(R)+$\",   NI = \"^(N|NI|V)+$\",   SDD = \"^(SDD|D|H)+$\",   ... )  # S3 method for mic as.sir(   x,   mo = NULL,   ab = deparse(substitute(x)),   guideline = getOption(\"AMR_guideline\", \"EUCAST\"),   uti = NULL,   conserve_capped_values = FALSE,   add_intrinsic_resistance = FALSE,   reference_data = AMR::clinical_breakpoints,   include_screening = getOption(\"AMR_include_screening\", FALSE),   include_PKPD = getOption(\"AMR_include_PKPD\", TRUE),   breakpoint_type = getOption(\"AMR_breakpoint_type\", \"human\"),   host = NULL,   verbose = FALSE,   ... )  # S3 method for disk as.sir(   x,   mo = NULL,   ab = deparse(substitute(x)),   guideline = getOption(\"AMR_guideline\", \"EUCAST\"),   uti = NULL,   add_intrinsic_resistance = FALSE,   reference_data = AMR::clinical_breakpoints,   include_screening = getOption(\"AMR_include_screening\", FALSE),   include_PKPD = getOption(\"AMR_include_PKPD\", TRUE),   breakpoint_type = getOption(\"AMR_breakpoint_type\", \"human\"),   host = NULL,   verbose = FALSE,   ... )  # S3 method for data.frame as.sir(   x,   ...,   col_mo = NULL,   guideline = getOption(\"AMR_guideline\", \"EUCAST\"),   uti = NULL,   conserve_capped_values = FALSE,   add_intrinsic_resistance = FALSE,   reference_data = AMR::clinical_breakpoints,   include_screening = getOption(\"AMR_include_screening\", FALSE),   include_PKPD = getOption(\"AMR_include_PKPD\", TRUE),   breakpoint_type = getOption(\"AMR_breakpoint_type\", \"human\"),   host = NULL,   verbose = FALSE )  sir_interpretation_history(clean = FALSE)"},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"interpretations minimum inhibitory concentration (MIC) values disk diffusion diameters: CLSI M39: Analysis Presentation Cumulative Antimicrobial Susceptibility Test Data, 2011-2024, Clinical Laboratory Standards Institute (CLSI). https://clsi.org/standards/products/microbiology/documents/m39/. CLSI M100: Performance Standard Antimicrobial Susceptibility Testing, 2011-2024, Clinical Laboratory Standards Institute (CLSI). https://clsi.org/standards/products/microbiology/documents/m100/. CLSI VET01: Performance Standards Antimicrobial Disk Dilution Susceptibility Tests Bacteria Isolated Animals, 2019-2024, Clinical Laboratory Standards Institute (CLSI). https://clsi.org/standards/products/veterinary-medicine/documents/vet01//. EUCAST Breakpoint tables interpretation MICs zone diameters, 2011-2024, European Committee Antimicrobial Susceptibility Testing (EUCAST). https://www.eucast.org/clinical_breakpoints. WHONET source machine-reading clinical breakpoints (read ), 1989-2024, Collaborating Centre Surveillance Antimicrobial Resistance. https://whonet.org/.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"x vector values (class mic: MIC values mg/L, class disk: disk diffusion radius millimetres) ... using data.frame: names columns apply .sir() (supports tidy selection column1:column4). Otherwise: arguments passed methods. threshold maximum fraction invalid antimicrobial interpretations x, see Examples S, , R, NI, SDD case-independent regular expression translate input result. regular expression run non-letters whitespaces removed input. mo vector (column name) characters can coerced valid microorganism codes .mo(), can left empty determine automatically ab vector (column name) characters can coerced valid antimicrobial drug code .ab() guideline defaults EUCAST 2024 (latest implemented EUCAST guideline clinical_breakpoints data set), can set package option AMR_guideline. Currently supports EUCAST (2011-2024) CLSI (2011-2024), see Details. uti (Urinary Tract Infection) vector (column name) logicals (TRUE FALSE) specify whether UTI specific interpretation guideline chosen. using .sir() data.frame, can also column containing logicals left blank, data set searched column 'specimen', rows within column containing 'urin' ('urine', 'urina') regarded isolates UTI. See Examples. conserve_capped_values logical indicate MIC values starting \">\" (\">=\") must always return \"R\" , MIC values starting \"<\" (\"<=\") must always return \"S\" add_intrinsic_resistance (useful using EUCAST guideline) logical indicate whether intrinsic antibiotic resistance must also considered applicable bug-drug combinations, meaning e.g. ampicillin always return \"R\" Klebsiella species. Determination based intrinsic_resistant data set, based 'EUCAST Expert Rules' 'EUCAST Intrinsic Resistance Unusual Phenotypes' v3.3 (2021). reference_data data.frame used interpretation, defaults clinical_breakpoints data set. Changing argument allows using interpretation guidelines. argument must contain data set equal structure clinical_breakpoints data set (column names column types). Please note guideline argument ignored reference_data manually set. include_screening logical indicate clinical breakpoints screening allowed - default FALSE. Can also set package option AMR_include_screening. include_PKPD logical indicate PK/PD clinical breakpoints must applied last resort - default TRUE. Can also set package option AMR_include_PKPD. breakpoint_type type breakpoints use, either \"ECOFF\", \"animal\", \"human\". ECOFF stands Epidemiological Cut-values. default \"human\", can also set package option AMR_breakpoint_type. host set values veterinary species, automatically set \"animal\". host vector (column name) characters indicate host. useful veterinary breakpoints, requires breakpoint_type = \"animal\". values can text resembling animal species, even 20 supported languages package. foreign languages, sure set language set_AMR_locale() (though automatically guessed based system language). verbose logical indicate notes printed interpretation MIC values disk diffusion values. col_mo column name names codes microorganisms (see .mo()) - default first column class mo. Values coerced using .mo(). clean logical indicate whether previously stored results forgotten returning 'logbook' results","code":""},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"Ordered factor new class sir","code":""},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"Note: clinical breakpoints package validated , imported , WHONET. public use AMR package endorsed CLSI EUCAST. See clinical_breakpoints information. NA_sir_ missing value new sir class, analogous e.g. base R's NA_character_.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"how-it-works","dir":"Reference","previous_headings":"","what":"How it Works","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":".sir() function can work four ways: cleaning raw / untransformed data. data cleaned contain valid values, namely: S susceptible, intermediate 'susceptible, increased exposure', R resistant, NI non-interpretable, SDD susceptible dose-dependent. can set using regular expression. Furthermore, .sir() try best clean intelligence. example, mixed values SIR interpretations MIC values \"<0.25; S\" coerced \"S\". Combined interpretations multiple test methods (seen laboratory records) \"S; S\" coerced \"S\", value like \"S; \" return NA warning input invalid. interpreting minimum inhibitory concentration (MIC) values according EUCAST CLSI. must clean MIC values first using .mic(), also gives columns new data class mic. Also, sure column microorganism names codes. found automatically, can set manually using mo argument. Using dplyr, SIR interpretation can done easily either:   Operators like \"<=\" stripped interpretation. using conserve_capped_values = TRUE, MIC value e.g. \">2\" always return \"R\", even breakpoint according chosen guideline \">=4\". prevent capped values raw laboratory data treated conservatively. default behaviour (conserve_capped_values = FALSE) considers \">2\" lower \">=4\" might case return \"S\" \"\". interpreting disk diffusion diameters according EUCAST CLSI. must clean disk zones first using .disk(), also gives columns new data class disk. Also, sure column microorganism names codes. found automatically, can set manually using mo argument. Using dplyr, SIR interpretation can done easily either:   interpreting complete data set, automatic determination MIC values, disk diffusion diameters, microorganism names codes, antimicrobial test results. done simply running .sir(your_data). points 2, 3 4: Use sir_interpretation_history() retrieve data.frame (tibble tibble package installed) results last .sir() call.","code":"your_data %>% mutate_if(is.mic, as.sir) your_data %>% mutate(across(where(is.mic), as.sir)) your_data %>% mutate_if(is.mic, as.sir, ab = \"column_with_antibiotics\", mo = \"column_with_microorganisms\") your_data %>% mutate_if(is.mic, as.sir, ab = c(\"cipro\", \"ampicillin\", ...), mo = c(\"E. coli\", \"K. pneumoniae\", ...))  # for veterinary breakpoints, also set `host`: your_data %>% mutate_if(is.mic, as.sir, host = \"column_with_animal_hosts\", guideline = \"CLSI\") your_data %>% mutate_if(is.disk, as.sir) your_data %>% mutate(across(where(is.disk), as.sir)) your_data %>% mutate_if(is.disk, as.sir, ab = \"column_with_antibiotics\", mo = \"column_with_microorganisms\") your_data %>% mutate_if(is.disk, as.sir, ab = c(\"cipro\", \"ampicillin\", ...), mo = c(\"E. coli\", \"K. pneumoniae\", ...))  # for veterinary breakpoints, also set `host`: your_data %>% mutate_if(is.disk, as.sir, host = \"column_with_animal_hosts\", guideline = \"CLSI\")"},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"supported-guidelines","dir":"Reference","previous_headings":"","what":"Supported Guidelines","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"interpreting MIC values well disk diffusion diameters, currently implemented guidelines clinical microbiology: EUCAST 2011-2024 CLSI 2011-2024, veterinary microbiology: EUCAST 2021-2024 CLSI 2019-2024. Thus, guideline argument must set e.g., \"EUCAST 2024\" \"CLSI 2024\". simply using \"EUCAST\" (default) \"CLSI\" input, latest included version guideline automatically selected. can set data set using reference_data argument. guideline argument ignored. can set default guideline package option AMR_guideline (e.g. .Rprofile file), :   veterinary guidelines, might best options:","code":"options(AMR_guideline = \"CLSI\")   options(AMR_guideline = \"CLSI 2018\")   options(AMR_guideline = \"EUCAST 2020\")   # or to reset:   options(AMR_guideline = NULL) options(AMR_guideline = \"CLSI\")   options(AMR_breakpoint_type = \"animal\")"},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"after-interpretation","dir":"Reference","previous_headings":"","what":"After Interpretation","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"using .sir(), can use eucast_rules() defined EUCAST (1) apply inferred susceptibility resistance based results antimicrobials (2) apply intrinsic resistance based taxonomic properties microorganism.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"machine-readable-clinical-breakpoints","dir":"Reference","previous_headings":"","what":"Machine-Readable Clinical Breakpoints","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"repository package contains machine-readable version guidelines. CSV file consisting 34 063 rows 14 columns. file machine-readable, since contains one row every unique combination test method (MIC disk diffusion), antimicrobial drug microorganism. allows easy implementation rules laboratory information systems (LIS). Note contains interpretation guidelines humans - interpretation guidelines CLSI animals removed.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"other","dir":"Reference","previous_headings":"","what":"Other","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"function .sir() detects input contains class sir. input data.frame, iterates columns returns logical vector. base R function .double() can used retrieve quantitative values sir object: \"S\" = 1, \"\"/\"SDD\" = 2, \"R\" = 3. values rendered NA . Note: use .integer(), since (R works internally) return factor level indices, aforementioned quantitative values. function is_sir_eligible() returns TRUE column contains 5% invalid antimicrobial interpretations (S //R /NI /SDD), FALSE otherwise. threshold 5% can set threshold argument. input data.frame, iterates columns returns logical vector.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"interpretation-of-sir","dir":"Reference","previous_headings":"","what":"Interpretation of SIR","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"2019, European Committee Antimicrobial Susceptibility Testing (EUCAST) decided change definitions susceptibility testing categories S, , R shown (https://www.eucast.org/newsiandr): S - Susceptible, standard dosing regimen microorganism categorised \"Susceptible, standard dosing regimen\", high likelihood therapeutic success using standard dosing regimen agent. - Susceptible, increased exposure  microorganism categorised \"Susceptible, Increased exposure\" high likelihood therapeutic success exposure agent increased adjusting dosing regimen concentration site infection. R = Resistant microorganism categorised \"Resistant\" high likelihood therapeutic failure even increased exposure. Exposure function mode administration, dose, dosing interval, infusion time, well distribution excretion antimicrobial agent influence infecting organism site infection. AMR package honours insight. Use susceptibility() (equal proportion_SI()) determine antimicrobial susceptibility count_susceptible() (equal count_SI()) count susceptible isolates.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"reference-data-publicly-available","dir":"Reference","previous_headings":"","what":"Reference Data Publicly Available","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"data sets AMR package (microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) publicly freely available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. also provide tab-separated plain text files machine-readable suitable input software program, laboratory information systems. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"","code":"example_isolates #> # A tibble: 2,000 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-03 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  3 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  4 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  5 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  6 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  7 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  8 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  9 2002-01-16 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #> 10 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R     NA    S     NA    #> # ℹ 1,990 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, … summary(example_isolates) # see all SIR results at a glance #>       date              patient               age           gender          #>  Min.   :2002-01-02   Length:2000        Min.   : 0.00   Length:2000        #>  1st Qu.:2005-07-31   Class :character   1st Qu.:63.00   Class :character   #>  Median :2009-07-31   Mode  :character   Median :74.00   Mode  :character   #>  Mean   :2009-11-20                      Mean   :70.69                      #>  3rd Qu.:2014-05-30                      3rd Qu.:82.00                      #>  Max.   :2017-12-28                      Max.   :97.00                      #>      ward                mo                  PEN                 #>  Length:2000        Class :mo             Class:sir              #>  Class :character   <NA>  :0              %S   :25.6% (n=417)    #>  Mode  :character   Unique:90             %SDD : 0.0% (n=0)      #>                     #1    :B_ESCHR_COLI   %I   : 0.7% (n=11)     #>                     #2    :B_STPHY_CONS   %R   :73.7% (n=1201)   #>                     #3    :B_STPHY_AURS   %NI  : 0.0% (n=0)      #>     OXA                   FLC                   AMX                #>  Class:sir             Class:sir             Class:sir             #>  %S   :68.8% (n=251)   %S   :70.5% (n=665)   %S   :40.2% (n=543)   #>  %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)     #>  %I   : 0.0% (n=0)     %I   : 0.0% (n=0)     %I   : 0.2% (n=3)     #>  %R   :31.2% (n=114)   %R   :29.5% (n=278)   %R   :59.6% (n=804)   #>  %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)     #>     AMC                    AMP                   TZP                #>  Class:sir              Class:sir             Class:sir             #>  %S   :71.4% (n=1342)   %S   :40.2% (n=543)   %S   :86.1% (n=862)   #>  %SDD : 0.0% (n=0)      %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)     #>  %I   : 4.8% (n=91)     %I   : 0.2% (n=3)     %I   : 1.3% (n=13)    #>  %R   :23.7% (n=446)    %R   :59.6% (n=804)   %R   :12.6% (n=126)   #>  %NI  : 0.0% (n=0)      %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)     #>     CZO                   FEP                   CXM                 #>  Class:sir             Class:sir             Class:sir              #>  %S   :54.9% (n=245)   %S   :85.6% (n=620)   %S   :72.5% (n=1297)   #>  %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)      #>  %I   : 0.4% (n=2)     %I   : 0.1% (n=1)     %I   : 1.2% (n=22)     #>  %R   :44.6% (n=199)   %R   :14.2% (n=103)   %R   :26.3% (n=470)    #>  %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)      #>     FOX                   CTX                   CAZ                 #>  Class:sir             Class:sir             Class:sir              #>  %S   :71.6% (n=586)   %S   :84.4% (n=796)   %S   :33.5% (n=607)    #>  %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)      #>  %I   : 1.0% (n=8)     %I   : 0.1% (n=1)     %I   : 0.0% (n=0)      #>  %R   :27.4% (n=224)   %R   :15.5% (n=146)   %R   :66.5% (n=1204)   #>  %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)      #>     CRO                   GEN                    TOB                #>  Class:sir             Class:sir              Class:sir             #>  %S   :84.4% (n=796)   %S   :74.0% (n=1372)   %S   :65.1% (n=879)   #>  %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)      %SDD : 0.0% (n=0)     #>  %I   : 0.1% (n=1)     %I   : 1.5% (n=27)     %I   : 0.5% (n=7)     #>  %R   :15.5% (n=146)   %R   :24.6% (n=456)    %R   :34.4% (n=465)   #>  %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)      %NI  : 0.0% (n=0)     #>     AMK                   KAN                    TMP                #>  Class:sir             Class:sir              Class:sir             #>  %S   :36.3% (n=251)   %S   : 0.0% (n=0)      %S   :61.2% (n=918)   #>  %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)      %SDD : 0.0% (n=0)     #>  %I   : 0.0% (n=0)     %I   : 0.0% (n=0)      %I   : 0.7% (n=10)    #>  %R   :63.7% (n=441)   %R   :100.0% (n=471)   %R   :38.1% (n=571)   #>  %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)      %NI  : 0.0% (n=0)     #>     SXT                    NIT                   FOS                #>  Class:sir              Class:sir             Class:sir             #>  %S   :79.1% (n=1392)   %S   :76.0% (n=565)   %S   :57.8% (n=203)   #>  %SDD : 0.0% (n=0)      %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)     #>  %I   : 0.3% (n=6)      %I   : 6.9% (n=51)    %I   : 0.0% (n=0)     #>  %R   :20.5% (n=361)    %R   :17.1% (n=127)   %R   :42.2% (n=148)   #>  %NI  : 0.0% (n=0)      %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)     #>     LNZ                   CIP                    MFX                #>  Class:sir             Class:sir              Class:sir             #>  %S   :30.7% (n=314)   %S   :78.9% (n=1112)   %S   :64.5% (n=136)   #>  %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)      %SDD : 0.0% (n=0)     #>  %I   : 0.0% (n=0)     %I   : 4.9% (n=69)     %I   : 1.9% (n=4)     #>  %R   :69.3% (n=709)   %R   :16.2% (n=228)    %R   :33.6% (n=71)    #>  %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)      %NI  : 0.0% (n=0)     #>     VAN                    TEC                   TCY                #>  Class:sir              Class:sir             Class:sir             #>  %S   :61.7% (n=1149)   %S   :24.3% (n=237)   %S   :68.3% (n=820)   #>  %SDD : 0.0% (n=0)      %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)     #>  %I   : 0.0% (n=0)      %I   : 0.0% (n=0)     %I   : 1.9% (n=23)    #>  %R   :38.3% (n=712)    %R   :75.7% (n=739)   %R   :29.8% (n=357)   #>  %NI  : 0.0% (n=0)      %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)     #>     TGC                   DOX                   ERY                 #>  Class:sir             Class:sir             Class:sir              #>  %S   :87.3% (n=697)   %S   :71.7% (n=814)   %S   :42.3% (n=801)    #>  %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)      #>  %I   : 0.0% (n=0)     %I   : 0.6% (n=7)     %I   : 0.5% (n=9)      #>  %R   :12.7% (n=101)   %R   :27.7% (n=315)   %R   :57.2% (n=1084)   #>  %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)      #>     CLI                   AZM                    IPM                #>  Class:sir             Class:sir              Class:sir             #>  %S   :38.6% (n=586)   %S   :42.3% (n=801)    %S   :92.7% (n=824)   #>  %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)      %SDD : 0.0% (n=0)     #>  %I   : 0.3% (n=4)     %I   : 0.5% (n=9)      %I   : 1.1% (n=10)    #>  %R   :61.2% (n=930)   %R   :57.2% (n=1084)   %R   : 6.2% (n=55)    #>  %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)      %NI  : 0.0% (n=0)     #>     MEM                   MTR                  CHL                #>  Class:sir             Class:sir            Class:sir             #>  %S   :94.1% (n=780)   %S   :85.3% (n=29)   %S   :78.6% (n=121)   #>  %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)    %SDD : 0.0% (n=0)     #>  %I   : 0.0% (n=0)     %I   : 0.0% (n=0)    %I   : 0.0% (n=0)     #>  %R   : 5.9% (n=49)    %R   :14.7% (n=5)    %R   :21.4% (n=33)    #>  %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)    %NI  : 0.0% (n=0)     #>     COL                    MUP                   RIF                #>  Class:sir              Class:sir             Class:sir             #>  %S   :18.8% (n=309)    %S   :93.0% (n=251)   %S   :30.2% (n=303)   #>  %SDD : 0.0% (n=0)      %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)     #>  %I   : 0.0% (n=0)      %I   : 1.1% (n=3)     %I   : 0.2% (n=2)     #>  %R   :81.2% (n=1331)   %R   : 5.9% (n=16)    %R   :69.6% (n=698)   #>  %NI  : 0.0% (n=0)      %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)      # For INTERPRETING disk diffusion and MIC values -----------------------  # example data sets, with combined MIC values and disk zones df_wide <- data.frame(   microorganism = \"Escherichia coli\",   amoxicillin = as.mic(8),   cipro = as.mic(0.256),   tobra = as.disk(16),   genta = as.disk(18),   ERY = \"R\" ) df_long <- data.frame(   bacteria = rep(\"Escherichia coli\", 4),   antibiotic = c(\"amoxicillin\", \"cipro\", \"tobra\", \"genta\"),   mics = as.mic(c(0.01, 1, 4, 8)),   disks = as.disk(c(6, 10, 14, 18)) )  # \\donttest{ ## Using dplyr ------------------------------------------------- if (require(\"dplyr\")) {   # approaches that all work without additional arguments:   df_wide %>% mutate_if(is.mic, as.sir)   df_wide %>% mutate_if(function(x) is.mic(x) | is.disk(x), as.sir)   df_wide %>% mutate(across(where(is.mic), as.sir))   df_wide %>% mutate_at(vars(amoxicillin:tobra), as.sir)   df_wide %>% mutate(across(amoxicillin:tobra, as.sir))      # approaches that all work with additional arguments:   df_long %>%     # given a certain data type, e.g. MIC values     mutate_if(is.mic, as.sir,               mo = \"bacteria\",               ab = \"antibiotic\",               guideline = \"CLSI\")   df_long %>%     mutate(across(where(is.mic),                   function(x) as.sir(x,                                      mo = \"bacteria\",                                      ab = \"antibiotic\",                                      guideline = \"CLSI\")))   df_wide %>%     # given certain columns, e.g. from 'cipro' to 'genta'     mutate_at(vars(cipro:genta), as.sir,               mo = \"bacteria\",               guideline = \"CLSI\")   df_wide %>%     mutate(across(cipro:genta,                        function(x) as.sir(x,                                           mo = \"bacteria\",                                           guideline = \"CLSI\")))                           # for veterinary breakpoints, add 'host':   df_long$animal_species <- c(\"cats\", \"dogs\", \"horses\", \"cattle\")   df_long %>%     # given a certain data type, e.g. MIC values     mutate_if(is.mic, as.sir,               mo = \"bacteria\",               ab = \"antibiotic\",               host = \"animal_species\",               guideline = \"CLSI\")   df_long %>%     mutate(across(where(is.mic),                   function(x) as.sir(x,                                      mo = \"bacteria\",                                      ab = \"antibiotic\",                                      host = \"animal_species\",                                      guideline = \"CLSI\")))   df_wide %>%     mutate_at(vars(cipro:genta), as.sir,               mo = \"bacteria\",               ab = \"antibiotic\",               host = \"animal_species\",               guideline = \"CLSI\")   df_wide %>%     mutate(across(cipro:genta,                        function(x) as.sir(x,                                           mo = \"bacteria\",                                           host = \"animal_species\",                                           guideline = \"CLSI\")))      # to include information about urinary tract infections (UTI)   data.frame(mo = \"E. coli\",              nitrofuratoin = c(\"<= 2\", 32),              from_the_bladder = c(TRUE, FALSE)) %>%     as.sir(uti = \"from_the_bladder\")    data.frame(mo = \"E. coli\",              nitrofuratoin = c(\"<= 2\", 32),              specimen = c(\"urine\", \"blood\")) %>%     as.sir() # automatically determines urine isolates    df_wide %>%     mutate_at(vars(cipro:genta), as.sir, mo = \"E. coli\", uti = TRUE) } #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'amoxicillin' (AMX) based on column #> 'microorganism', EUCAST 2024... #>  OK  #> Interpreting MIC values: 'cipro' (CIP, ciprofloxacin) based on column #> 'microorganism', EUCAST 2024... #>  NOTE  #>   • Multiple breakpoints available for ciprofloxacin (CIP) in Escherichia coli - assuming body site 'Non-meningitis'. #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'amoxicillin' (AMX) based on column #> 'microorganism', EUCAST 2024... #>  OK  #> Interpreting MIC values: 'cipro' (CIP, ciprofloxacin) based on column #> 'microorganism', EUCAST 2024... #>  NOTE  #>   • Multiple breakpoints available for ciprofloxacin (CIP) in Escherichia coli - assuming body site 'Non-meningitis'. #> Interpreting disk diffusion zones: 'tobra' (TOB, tobramycin) based on #> column 'microorganism', EUCAST 2024... #>  OK  #> Interpreting disk diffusion zones: 'genta' (GEN, gentamicin) based on #> column 'microorganism', EUCAST 2024... #>  OK  #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'amoxicillin' (AMX) based on column #> 'microorganism', EUCAST 2024... #>  OK  #> Interpreting MIC values: 'cipro' (CIP, ciprofloxacin) based on column #> 'microorganism', EUCAST 2024... #>  NOTE  #>   • Multiple breakpoints available for ciprofloxacin (CIP) in Escherichia coli - assuming body site 'Non-meningitis'. #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'amoxicillin' (AMX) based on column #> 'microorganism', EUCAST 2024... #>  OK  #> Interpreting MIC values: 'cipro' (CIP, ciprofloxacin) based on column #> 'microorganism', EUCAST 2024... #>  NOTE  #>   • Multiple breakpoints available for ciprofloxacin (CIP) in Escherichia coli - assuming body site 'Non-meningitis'. #> Interpreting disk diffusion zones: 'tobra' (TOB, tobramycin) based on #> column 'microorganism', EUCAST 2024... #>  OK  #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'amoxicillin' (AMX) based on column #> 'microorganism', EUCAST 2024... #>  OK  #> Interpreting MIC values: 'cipro' (CIP, ciprofloxacin) based on column #> 'microorganism', EUCAST 2024... #>  NOTE  #>   • Multiple breakpoints available for ciprofloxacin (CIP) in Escherichia coli - assuming body site 'Non-meningitis'. #> Interpreting disk diffusion zones: 'tobra' (TOB, tobramycin) based on #> column 'microorganism', EUCAST 2024... #>  OK  #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'amoxicillin' (AMX), 'cipro' (CIP, ciprofloxacin), #> 'tobra' (TOB, tobramycin), and 'genta' (GEN, gentamicin) based on column #> 'bacteria', CLSI 2024... #>  OK  #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'amoxicillin' (AMX), 'cipro' (CIP, ciprofloxacin), #> 'tobra' (TOB, tobramycin), and 'genta' (GEN, gentamicin) based on column #> 'bacteria', CLSI 2024... #>  OK  #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'cipro' (CIP, ciprofloxacin), CLSI 2024... #>  OK  #> Interpreting disk diffusion zones: 'tobra' (TOB, tobramycin), CLSI 2024... #>  OK  #> Interpreting disk diffusion zones: 'genta' (GEN, gentamicin), CLSI 2024... #>  OK  #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'cipro' (CIP, ciprofloxacin), CLSI 2024... #>  OK  #> Interpreting disk diffusion zones: 'tobra' (TOB, tobramycin), CLSI 2024... #>  OK  #> Interpreting disk diffusion zones: 'genta' (GEN, gentamicin), CLSI 2024... #>  OK  #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> ℹ Assuming breakpoint_type = \"animal\", since host is set. #> ℹ Please note that in the absence of specific veterinary breakpoints for #>   certain animal hosts, breakpoints for dogs, cattle, swine, cats, horse, #>   aquatic, and poultry, in that order, are used as substitutes. #> Interpreting MIC values: 'amoxicillin' (AMX), 'cipro' (CIP, ciprofloxacin), #> 'tobra' (TOB, tobramycin), and 'genta' (GEN, gentamicin) based on column #> 'bacteria', CLSI 2024... #>  NOTE  #>   • Using dogs breakpoints since cattle for gentamicin (GEN) in Escherichia coli are not available. #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> ℹ Assuming breakpoint_type = \"animal\", since host is set. #> ℹ Please note that in the absence of specific veterinary breakpoints for #>   certain animal hosts, breakpoints for dogs, cattle, swine, cats, horse, #>   aquatic, and poultry, in that order, are used as substitutes. #> Interpreting MIC values: 'amoxicillin' (AMX), 'cipro' (CIP, ciprofloxacin), #> 'tobra' (TOB, tobramycin), and 'genta' (GEN, gentamicin) based on column #> 'bacteria', CLSI 2024... #>  NOTE  #>   • Using dogs breakpoints since cattle for gentamicin (GEN) in Escherichia coli are not available. #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> ℹ Assuming breakpoint_type = \"animal\", since host is set. #> ℹ The following host(s) are invalid: \"animalspecies\". For missing animal #>   hosts, assuming \"dogs\", since these have the highest breakpoint #>   availability. #> ℹ Please note that in the absence of specific veterinary breakpoints for #>   certain animal hosts, breakpoints for dogs, cattle, swine, cats, horse, #>   aquatic, and poultry, in that order, are used as substitutes. #> Interpreting MIC values: 'antibiotic' (TESTAB, test Antibiotic), CLSI #> 2024... #>  WARNING  #>   • No CLSI 2024 MIC breakpoints available for test Antibiotic (TESTAB). #> Interpreting disk diffusion zones: 'antibiotic' (TESTAB, test Antibiotic), #> CLSI 2024... #>  WARNING  #>   • No CLSI 2024 DISK breakpoints available for test Antibiotic (TESTAB). #> Interpreting disk diffusion zones: 'antibiotic' (TESTAB, test Antibiotic), #> CLSI 2024... #>  WARNING  #>   • No CLSI 2024 DISK breakpoints available for test Antibiotic (TESTAB). #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> ℹ Assuming breakpoint_type = \"animal\", since host is set. #> ℹ The following host(s) are invalid: \"animalspecies\". For missing animal #>   hosts, assuming \"dogs\", since these have the highest breakpoint #>   availability. #> ℹ Please note that in the absence of specific veterinary breakpoints for #>   certain animal hosts, breakpoints for dogs, cattle, swine, cats, horse, #>   aquatic, and poultry, in that order, are used as substitutes. #> Interpreting MIC values: 'cipro' (CIP, ciprofloxacin), CLSI 2024... #>  WARNING  #>   • No CLSI 2024 MIC breakpoints available for ciprofloxacin (CIP). #> Interpreting disk diffusion zones: 'tobra' (TOB, tobramycin), CLSI 2024... #>  OK  #> Interpreting disk diffusion zones: 'genta' (GEN, gentamicin), CLSI 2024... #>  OK  #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: column 'nitrofuratoin' (NIT, nitrofurantoin), #> EUCAST 2024... #>  NOTE  #>   • Breakpoints for nitrofurantoin (NIT) in Escherichia coli are only available for (uncomplicated) urinary tract infections (UTI); assuming uti = TRUE. #> ℹ Assuming value \"urine\" in column 'specimen' reflects a urinary tract #>   infection. #>   Use as.sir(uti = FALSE) to prevent this. #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: column 'nitrofuratoin' (NIT, nitrofurantoin), #> EUCAST 2024... #>  NOTE  #>   • Breakpoints for nitrofurantoin (NIT) in Escherichia coli are only available for (uncomplicated) urinary tract infections (UTI); assuming uti = TRUE. #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'cipro' (CIP, ciprofloxacin), EUCAST 2024... #>  OK  #> Interpreting disk diffusion zones: 'tobra' (TOB, tobramycin), EUCAST #> 2024... #>  OK  #> Interpreting disk diffusion zones: 'genta' (GEN, gentamicin), EUCAST #> 2024... #>  OK  #>      microorganism amoxicillin cipro tobra genta ERY #> 1 Escherichia coli           8  <NA>     S     S   R   ## Using base R ------------------------------------------------  as.sir(df_wide) #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: column 'amoxicillin' (AMX), EUCAST 2024... #>  OK  #> Interpreting MIC values: column 'cipro' (CIP, ciprofloxacin), EUCAST #> 2024... #>  NOTE  #>   • Multiple breakpoints available for ciprofloxacin (CIP) in Escherichia coli - assuming body site 'Non-meningitis'. #> Interpreting disk diffusion zones: column 'tobra' (TOB, tobramycin), EUCAST #> 2024... #>  OK  #> Interpreting disk diffusion zones: column 'genta' (GEN, gentamicin), EUCAST #> 2024... #>  OK  #> Assigning class 'sir' to already clean column 'ERY' (erythromycin)... #>  OK  #>      microorganism amoxicillin cipro tobra genta ERY #> 1 Escherichia coli           S     I     S     S   R  # return a 'logbook' about the results: sir_interpretation_history() #> # A tibble: 59 × 16 #>    datetime            index ab_given mo_given host_given ab   mo               #>  * <dttm>              <int> <chr>    <chr>    <chr>      <ab> <mo>             #>  1 2024-06-23 14:22:38     4 AMX      B_STRPT… human      AMX  B_STRPT_PNMN     #>  2 2024-06-23 14:22:44     4 genta    Escheri… human      GEN  B_[ORD]_ENTRBCTR #>  3 2024-06-23 14:22:44     4 genta    Escheri… human      GEN  B_[ORD]_ENTRBCTR #>  4 2024-06-23 14:22:44     4 genta    Escheri… cattle     GEN  B_[ORD]_ENTRBCTR #>  5 2024-06-23 14:22:45     4 genta    Escheri… cattle     GEN  B_[ORD]_ENTRBCTR #>  6 2024-06-23 14:22:38     3 AMX      B_STRPT… human      AMX  B_STRPT_PNMN     #>  7 2024-06-23 14:22:44     3 tobra    Escheri… human      TOB  B_[ORD]_ENTRBCTR #>  8 2024-06-23 14:22:44     3 tobra    Escheri… human      TOB  B_[ORD]_ENTRBCTR #>  9 2024-06-23 14:22:44     3 tobra    Escheri… horses     TOB  B_ESCHR_COLI     #> 10 2024-06-23 14:22:45     3 tobra    Escheri… horses     TOB  B_ESCHR_COLI     #> # ℹ 49 more rows #> # ℹ 9 more variables: host <chr>, method <chr>, input <dbl>, outcome <sir>, #> #   notes <chr>, guideline <chr>, ref_table <chr>, uti <lgl>, #> #   breakpoint_S_R <chr>  # for single values as.sir(   x = as.mic(2),   mo = as.mo(\"S. pneumoniae\"),   ab = \"AMP\",   guideline = \"EUCAST\" ) #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'AMP' (ampicillin), EUCAST 2024... #>  NOTE  #>   • Multiple breakpoints available for ampicillin (AMP) in Streptococcus pneumoniae - assuming body site 'Non-meningitis'. #> Class 'sir' #> [1] R  as.sir(   x = as.disk(18),   mo = \"Strep pneu\", # `mo` will be coerced with as.mo()   ab = \"ampicillin\", # and `ab` with as.ab()   guideline = \"EUCAST\" ) #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting disk diffusion zones: 'ampicillin' (AMP), EUCAST 2024... #>  OK  #> Class 'sir' #> [1] R   # For CLEANING existing SIR values ------------------------------------  as.sir(c(\"S\", \"SDD\", \"I\", \"R\", \"NI\", \"A\", \"B\", \"C\")) #> Warning: in as.sir(): 3 results in column '30' truncated (38%) that were invalid #> antimicrobial interpretations: \"A\", \"B\", and \"C\" #> Class 'sir' #> [1] S    SDD  I    R    NI   <NA> <NA> <NA> as.sir(\"<= 0.002; S\") # will return \"S\" #> Class 'sir' #> [1] S sir_data <- as.sir(c(rep(\"S\", 474), rep(\"I\", 36), rep(\"R\", 370))) is.sir(sir_data) #> [1] TRUE plot(sir_data) # for percentages  barplot(sir_data) # for frequencies   # as common in R, you can use as.integer() to return factor indices: as.integer(as.sir(c(\"S\", \"SDD\", \"I\", \"R\", \"NI\", NA))) #> [1]  1  2  3  4  5 NA # but for computational use, as.double() will return 1 for S, 2 for I/SDD, and 3 for R: as.double(as.sir(c(\"S\", \"SDD\", \"I\", \"R\", \"NI\", NA))) #> [1]  1  2  2  3 NA NA  # the dplyr way if (require(\"dplyr\")) {   example_isolates %>%     mutate_at(vars(PEN:RIF), as.sir)   # same:   example_isolates %>%     as.sir(PEN:RIF)    # fastest way to transform all columns with already valid AMR results to class `sir`:   example_isolates %>%     mutate_if(is_sir_eligible, as.sir)    # since dplyr 1.0.0, this can also be:   # example_isolates %>%   #   mutate(across(where(is_sir_eligible), as.sir)) } #> # A tibble: 2,000 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-03 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  3 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  4 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  5 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  6 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  7 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  8 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  9 2002-01-16 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #> 10 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R     NA    S     NA    #> # ℹ 1,990 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, … # }"},{"path":"https://msberends.github.io/AMR/reference/atc_online.html","id":null,"dir":"Reference","previous_headings":"","what":"Get ATC Properties from WHOCC Website — atc_online_property","title":"Get ATC Properties from WHOCC Website — atc_online_property","text":"Gets data WHOCC website determine properties Anatomical Therapeutic Chemical (ATC) (e.g. antibiotic), name, defined daily dose (DDD) standard unit.","code":""},{"path":"https://msberends.github.io/AMR/reference/atc_online.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get ATC Properties from WHOCC Website — atc_online_property","text":"","code":"atc_online_property(   atc_code,   property,   administration = \"O\",   url = \"https://atcddd.fhi.no/atc_ddd_index/?code=%s&showdescription=no\",   url_vet = \"https://atcddd.fhi.no/atcvet/atcvet_index/?code=%s&showdescription=no\" )  atc_online_groups(atc_code, ...)  atc_online_ddd(atc_code, ...)  atc_online_ddd_units(atc_code, ...)"},{"path":"https://msberends.github.io/AMR/reference/atc_online.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get ATC Properties from WHOCC Website — atc_online_property","text":"https://atcddd.fhi./atc_ddd_alterations__cumulative/ddd_alterations/abbrevations/","code":""},{"path":"https://msberends.github.io/AMR/reference/atc_online.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get ATC Properties from WHOCC Website — atc_online_property","text":"atc_code character (vector) ATC code(s) antibiotics, coerced .ab() ab_atc() internally valid ATC code property property ATC code. Valid values \"ATC\", \"Name\", \"DDD\", \"U\" (\"unit\"), \"Adm.R\", \"Note\" groups. last option, hierarchical groups ATC code returned, see Examples. administration type administration using property = \"Adm.R\", see Details url url website WHOCC. sign %s can used placeholder ATC codes. url_vet url website WHOCC veterinary medicine. sign %s can used placeholder ATC_vet codes (start \"Q\"). ... arguments pass atc_property","code":""},{"path":"https://msberends.github.io/AMR/reference/atc_online.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get ATC Properties from WHOCC Website — atc_online_property","text":"Options argument administration: \"Implant\" = Implant \"Inhal\" = Inhalation \"Instill\" = Instillation \"N\" = nasal \"O\" = oral \"P\" = parenteral \"R\" = rectal \"SL\" = sublingual/buccal \"TD\" = transdermal \"V\" = vaginal Abbreviations return values using property = \"U\" (unit): \"g\" = gram \"mg\" = milligram \"mcg\" = microgram \"U\" = unit \"TU\" = thousand units \"MU\" = million units \"mmol\" = millimole \"ml\" = millilitre (e.g. eyedrops) N.B. function requires internet connection works following packages installed: curl, rvest, xml2.","code":""},{"path":"https://msberends.github.io/AMR/reference/atc_online.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get ATC Properties from WHOCC Website — atc_online_property","text":"","code":"# \\donttest{ if (requireNamespace(\"curl\") && requireNamespace(\"rvest\") && requireNamespace(\"xml2\")) {   # oral DDD (Defined Daily Dose) of amoxicillin   atc_online_property(\"J01CA04\", \"DDD\", \"O\")   atc_online_ddd(ab_atc(\"amox\"))    # parenteral DDD (Defined Daily Dose) of amoxicillin   atc_online_property(\"J01CA04\", \"DDD\", \"P\")    atc_online_property(\"J01CA04\", property = \"groups\") # search hierarchical groups of amoxicillin } #> Loading required namespace: rvest #> [1] \"ANTIINFECTIVES FOR SYSTEMIC USE\"         #> [2] \"ANTIBACTERIALS FOR SYSTEMIC USE\"         #> [3] \"BETA-LACTAM ANTIBACTERIALS, PENICILLINS\" #> [4] \"Penicillins with extended spectrum\"      # }"},{"path":"https://msberends.github.io/AMR/reference/av_from_text.html","id":null,"dir":"Reference","previous_headings":"","what":"Retrieve Antiviral Drug Names and Doses from Clinical Text — av_from_text","title":"Retrieve Antiviral Drug Names and Doses from Clinical Text — av_from_text","text":"Use function e.g. clinical texts health care records. returns list antiviral drugs, doses forms administration found texts.","code":""},{"path":"https://msberends.github.io/AMR/reference/av_from_text.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Retrieve Antiviral Drug Names and Doses from Clinical Text — av_from_text","text":"","code":"av_from_text(   text,   type = c(\"drug\", \"dose\", \"administration\"),   collapse = NULL,   translate_av = FALSE,   thorough_search = NULL,   info = interactive(),   ... )"},{"path":"https://msberends.github.io/AMR/reference/av_from_text.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Retrieve Antiviral Drug Names and Doses from Clinical Text — av_from_text","text":"text text analyse type type property search , either \"drug\", \"dose\" \"administration\", see Examples collapse character pass paste(, collapse = ...) return one character per element text, see Examples translate_av type = \"drug\": column name antivirals data set translate antibiotic abbreviations , using av_property(). default FALSE. Using TRUE equal using \"name\". thorough_search logical indicate whether input must extensively searched misspelling faulty input values. Setting TRUE take considerably time using FALSE. default, turn TRUE input elements contain maximum three words. info logical indicate whether progress bar printed - default TRUE interactive mode ... arguments passed .av()","code":""},{"path":"https://msberends.github.io/AMR/reference/av_from_text.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Retrieve Antiviral Drug Names and Doses from Clinical Text — av_from_text","text":"list,  character collapse NULL","code":""},{"path":"https://msberends.github.io/AMR/reference/av_from_text.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Retrieve Antiviral Drug Names and Doses from Clinical Text — av_from_text","text":"function also internally used .av(), although searches first drug name throw note drug names returned. Note: .av() function may use long regular expression match brand names antiviral drugs. may fail systems.","code":""},{"path":"https://msberends.github.io/AMR/reference/av_from_text.html","id":"argument-type","dir":"Reference","previous_headings":"","what":"Argument type","title":"Retrieve Antiviral Drug Names and Doses from Clinical Text — av_from_text","text":"default, function search antiviral drug names. text elements searched official names, ATC codes brand names. uses .av() internally, correct misspelling. type = \"dose\" (similar, like \"dosing\", \"doses\"), text elements searched numeric values higher 100 resemble years. output numeric. supports unit (g, mg, IE, etc.) multiple values one clinical text, see Examples. type = \"administration\" (abbreviations, like \"admin\", \"adm\"), text elements searched form drug administration. supports following forms (including common abbreviations): buccal, implant, inhalation, instillation, intravenous, nasal, oral, parenteral, rectal, sublingual, transdermal vaginal. Abbreviations oral ('po', 'per os') become \"oral\", values intravenous ('iv', 'intraven') become \"iv\". supports multiple values one clinical text, see Examples.","code":""},{"path":"https://msberends.github.io/AMR/reference/av_from_text.html","id":"argument-collapse","dir":"Reference","previous_headings":"","what":"Argument collapse","title":"Retrieve Antiviral Drug Names and Doses from Clinical Text — av_from_text","text":"Without using collapse, function return list. can convenient use e.g. inside mutate()):df %>% mutate(avx = av_from_text(clinical_text)) returned AV codes can transformed official names, groups, etc. av_* functions av_name() av_group(), using translate_av argument. using collapse, function return character:df %>% mutate(avx = av_from_text(clinical_text, collapse = \"|\"))","code":""},{"path":"https://msberends.github.io/AMR/reference/av_from_text.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Retrieve Antiviral Drug Names and Doses from Clinical Text — av_from_text","text":"","code":"av_from_text(\"28/03/2020 valaciclovir po tid\") #> [[1]] #> Class 'av' #> [1] VALA #>  av_from_text(\"28/03/2020 valaciclovir po tid\", type = \"admin\") #> [[1]] #> [1] \"oral\" #>"},{"path":"https://msberends.github.io/AMR/reference/av_property.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Properties of an Antiviral Drug — av_property","title":"Get Properties of an Antiviral Drug — av_property","text":"Use functions return specific property antiviral drug antivirals data set. input values evaluated internally .av().","code":""},{"path":"https://msberends.github.io/AMR/reference/av_property.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Properties of an Antiviral Drug — av_property","text":"","code":"av_name(x, language = get_AMR_locale(), tolower = FALSE, ...)  av_cid(x, ...)  av_synonyms(x, ...)  av_tradenames(x, ...)  av_group(x, language = get_AMR_locale(), ...)  av_atc(x, ...)  av_loinc(x, ...)  av_ddd(x, administration = \"oral\", ...)  av_ddd_units(x, administration = \"oral\", ...)  av_info(x, language = get_AMR_locale(), ...)  av_url(x, open = FALSE, ...)  av_property(x, property = \"name\", language = get_AMR_locale(), ...)"},{"path":"https://msberends.github.io/AMR/reference/av_property.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Properties of an Antiviral Drug — av_property","text":"x (vector ) text can coerced valid antiviral drug code .av() language language returned text - default system language (see get_AMR_locale()) can also set package option AMR_locale. Use language = NULL language = \"\" prevent translation. tolower logical indicate whether first character every output transformed lower case character. ... arguments passed .av() administration way administration, either \"oral\" \"iv\" open browse URL using utils::browseURL() property one column names one antivirals data set: vector_or(colnames(antivirals), sort = FALSE).","code":""},{"path":"https://msberends.github.io/AMR/reference/av_property.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Properties of an Antiviral Drug — av_property","text":"integer case av_cid() named list case av_info() multiple av_atc()/av_synonyms()/av_tradenames() double case av_ddd() character cases","code":""},{"path":"https://msberends.github.io/AMR/reference/av_property.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get Properties of an Antiviral Drug — av_property","text":"output translated possible. function av_url() return direct URL official website. warning returned required ATC code available.","code":""},{"path":"https://msberends.github.io/AMR/reference/av_property.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get Properties of an Antiviral Drug — av_property","text":"World Health Organization () Collaborating Centre Drug Statistics Methodology: https://atcddd.fhi./atc_ddd_index/ European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm","code":""},{"path":"https://msberends.github.io/AMR/reference/av_property.html","id":"reference-data-publicly-available","dir":"Reference","previous_headings":"","what":"Reference Data Publicly Available","title":"Get Properties of an Antiviral Drug — av_property","text":"data sets AMR package (microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) publicly freely available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. also provide tab-separated plain text files machine-readable suitable input software program, laboratory information systems. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/av_property.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Properties of an Antiviral Drug — av_property","text":"","code":"# all properties: av_name(\"ACI\") #> [1] \"Aciclovir\" av_atc(\"ACI\") #> [1] \"J05AB01\" av_cid(\"ACI\") #> [1] 135398513 av_synonyms(\"ACI\") #>  [1] \"acicloftal\"        \"aciclovier\"        \"aciclovirum\"       #>  [4] \"activir\"           \"acyclofoam\"        \"acycloguanosine\"   #>  [7] \"acyclovir\"         \"acyclovir lauriad\" \"avaclyr\"           #> [10] \"cargosil\"          \"cyclovir\"          \"genvir\"            #> [13] \"gerpevir\"          \"hascovir\"          \"maynar\"            #> [16] \"novirus\"           \"poviral\"           \"sitavig\"           #> [19] \"sitavir\"           \"vipral\"            \"viropump\"          #> [22] \"virorax\"           \"zovirax\"           \"zyclir\"            av_tradenames(\"ACI\") #>  [1] \"acicloftal\"        \"aciclovier\"        \"aciclovirum\"       #>  [4] \"activir\"           \"acyclofoam\"        \"acycloguanosine\"   #>  [7] \"acyclovir\"         \"acyclovir lauriad\" \"avaclyr\"           #> [10] \"cargosil\"          \"cyclovir\"          \"genvir\"            #> [13] \"gerpevir\"          \"hascovir\"          \"maynar\"            #> [16] \"novirus\"           \"poviral\"           \"sitavig\"           #> [19] \"sitavir\"           \"vipral\"            \"viropump\"          #> [22] \"virorax\"           \"zovirax\"           \"zyclir\"            av_group(\"ACI\") #> [1] \"Nucleosides and nucleotides excl. reverse transcriptase inhibitors\" av_url(\"ACI\") #>                                                              Aciclovir  #> \"https://atcddd.fhi.no/atc_ddd_index/?code=J05AB01&showdescription=no\"   # lowercase transformation av_name(x = c(\"ACI\", \"VALA\")) #> [1] \"Aciclovir\"    \"Valaciclovir\" av_name(x = c(\"ACI\", \"VALA\"), tolower = TRUE) #> [1] \"aciclovir\"    \"valaciclovir\"  # defined daily doses (DDD) av_ddd(\"ACI\", \"oral\") #> [1] 4 av_ddd_units(\"ACI\", \"oral\") #> [1] \"g\" av_ddd(\"ACI\", \"iv\") #> [1] 4 av_ddd_units(\"ACI\", \"iv\") #> [1] \"g\"  av_info(\"ACI\") # all properties as a list #> $av #> [1] \"ACI\" #>  #> $cid #> [1] 135398513 #>  #> $name #> [1] \"Aciclovir\" #>  #> $group #> [1] \"Nucleosides and nucleotides excl. reverse transcriptase inhibitors\" #>  #> $atc #> [1] \"J05AB01\" #>  #> $tradenames #>  [1] \"acicloftal\"        \"aciclovier\"        \"aciclovirum\"       #>  [4] \"activir\"           \"acyclofoam\"        \"acycloguanosine\"   #>  [7] \"acyclovir\"         \"acyclovir lauriad\" \"avaclyr\"           #> [10] \"cargosil\"          \"cyclovir\"          \"genvir\"            #> [13] \"gerpevir\"          \"hascovir\"          \"maynar\"            #> [16] \"novirus\"           \"poviral\"           \"sitavig\"           #> [19] \"sitavir\"           \"vipral\"            \"viropump\"          #> [22] \"virorax\"           \"zovirax\"           \"zyclir\"            #>  #> $loinc #> [1] \"\" #>  #> $ddd #> $ddd$oral #> $ddd$oral$amount #> [1] 4 #>  #> $ddd$oral$units #> [1] \"g\" #>  #>  #> $ddd$iv #> $ddd$iv$amount #> [1] 4 #>  #> $ddd$iv$units #> [1] \"g\" #>  #>  #>   # all av_* functions use as.av() internally, so you can go from 'any' to 'any': av_atc(\"ACI\") #> [1] \"J05AB01\" av_group(\"J05AB01\") #> [1] \"Nucleosides and nucleotides excl. reverse transcriptase inhibitors\" av_loinc(\"abacavir\") #> [1] \"29113-8\" \"30273-7\" \"30287-7\" \"30303-2\" \"78772-1\" \"78773-9\" \"79134-3\" #> [8] \"80118-3\" av_name(\"29113-8\") #> [1] \"Abacavir\" av_name(135398513) #> [1] \"Aciclovir\" av_name(\"J05AB01\") #> [1] \"Aciclovir\""},{"path":"https://msberends.github.io/AMR/reference/availability.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Availability of Columns — availability","title":"Check Availability of Columns — availability","text":"Easy check data availability columns data set. makes easy get idea antimicrobial combinations can used calculation e.g. susceptibility() resistance().","code":""},{"path":"https://msberends.github.io/AMR/reference/availability.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Availability of Columns — availability","text":"","code":"availability(tbl, width = NULL)"},{"path":"https://msberends.github.io/AMR/reference/availability.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Availability of Columns — availability","text":"tbl data.frame list width number characters present visual availability - default filling width console","code":""},{"path":"https://msberends.github.io/AMR/reference/availability.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Availability of Columns — availability","text":"data.frame column names tbl row names","code":""},{"path":"https://msberends.github.io/AMR/reference/availability.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Check Availability of Columns — availability","text":"function returns data.frame columns \"resistant\" \"visual_resistance\". values columns calculated resistance().","code":""},{"path":"https://msberends.github.io/AMR/reference/availability.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check Availability of Columns — availability","text":"","code":"availability(example_isolates) #>         count available     visual_availabilty resistant      visual_resistance #> date     2000    100.0% |####################|                                  #> patient  2000    100.0% |####################|                                  #> age      2000    100.0% |####################|                                  #> gender   2000    100.0% |####################|                                  #> ward     2000    100.0% |####################|                                  #> mo       2000    100.0% |####################|                                  #> PEN      1629     81.5% |################----|     73.7% |##############------| #> OXA       365     18.3% |###-----------------|     31.2% |######--------------| #> FLC       943     47.2% |#########-----------|     29.5% |#####---------------| #> AMX      1350     67.5% |#############-------|     59.6% |###########---------| #> AMC      1879     94.0% |##################--|     23.7% |####----------------| #> AMP      1350     67.5% |#############-------|     59.6% |###########---------| #> TZP      1001     50.0% |##########----------|     12.6% |##------------------| #> CZO       446     22.3% |####----------------|     44.6% |########------------| #> FEP       724     36.2% |#######-------------|     14.2% |##------------------| #> CXM      1789     89.5% |#################---|     26.3% |#####---------------| #> FOX       818     40.9% |########------------|     27.4% |#####---------------| #> CTX       943     47.2% |#########-----------|     15.5% |###-----------------| #> CAZ      1811     90.6% |##################--|     66.5% |#############-------| #> CRO       943     47.2% |#########-----------|     15.5% |###-----------------| #> GEN      1855     92.8% |##################--|     24.6% |####----------------| #> TOB      1351     67.6% |#############-------|     34.4% |######--------------| #> AMK       692     34.6% |######--------------|     63.7% |############--------| #> KAN       471     23.6% |####----------------|    100.0% |####################| #> TMP      1499     75.0% |###############-----|     38.1% |#######-------------| #> SXT      1759     88.0% |#################---|     20.5% |####----------------| #> NIT       743     37.2% |#######-------------|     17.1% |###-----------------| #> FOS       351     17.6% |###-----------------|     42.2% |########------------| #> LNZ      1023     51.2% |##########----------|     69.3% |#############-------| #> CIP      1409     70.5% |#############-------|     16.2% |###-----------------| #> MFX       211     10.6% |##------------------|     33.6% |######--------------| #> VAN      1861     93.1% |##################--|     38.3% |#######-------------| #> TEC       976     48.8% |#########-----------|     75.7% |###############-----| #> TCY      1200     60.0% |###########---------|     29.8% |#####---------------| #> TGC       798     39.9% |########------------|     12.7% |##------------------| #> DOX      1136     56.8% |###########---------|     27.7% |#####---------------| #> ERY      1894     94.7% |##################--|     57.2% |###########---------| #> CLI      1520     76.0% |###############-----|     61.2% |############--------| #> AZM      1894     94.7% |##################--|     57.2% |###########---------| #> IPM       889     44.5% |########------------|      6.2% |#-------------------| #> MEM       829     41.5% |########------------|      5.9% |#-------------------| #> MTR        34      1.7% |--------------------|     14.7% |##------------------| #> CHL       154      7.7% |#-------------------|     21.4% |####----------------| #> COL      1640     82.0% |################----|     81.2% |################----| #> MUP       270     13.5% |##------------------|      5.9% |#-------------------| #> RIF      1003     50.2% |##########----------|     69.6% |#############-------| # \\donttest{ if (require(\"dplyr\")) {   example_isolates %>%     filter(mo == as.mo(\"Escherichia coli\")) %>%     select_if(is.sir) %>%     availability() } #>     count available       visual_availabilty resistant        visual_resistance #> PEN   467    100.0% |######################|    100.0% |######################| #> OXA     0      0.0% |----------------------|                                    #> FLC     0      0.0% |----------------------|                                    #> AMX   392     83.9% |##################----|     50.0% |###########-----------| #> AMC   467    100.0% |######################|     13.1% |##--------------------| #> AMP   392     83.9% |##################----|     50.0% |###########-----------| #> TZP   416     89.1% |###################---|      5.5% |#---------------------| #> CZO    82     17.6% |###-------------------|      2.4% |----------------------| #> FEP   317     67.9% |##############--------|      2.8% |----------------------| #> CXM   465     99.6% |######################|      5.4% |#---------------------| #> FOX   377     80.7% |#################-----|      6.9% |#---------------------| #> CTX   459     98.3% |#####################-|      2.4% |----------------------| #> CAZ   460     98.5% |#####################-|      2.4% |----------------------| #> CRO   459     98.3% |#####################-|      2.4% |----------------------| #> GEN   460     98.5% |#####################-|      2.0% |----------------------| #> TOB   462     98.9% |#####################-|      2.6% |----------------------| #> AMK   171     36.6% |########--------------|      0.0% |----------------------| #> KAN     0      0.0% |----------------------|                                    #> TMP   396     84.8% |##################----|     39.1% |########--------------| #> SXT   465     99.6% |######################|     31.6% |######----------------| #> NIT   458     98.1% |#####################-|      2.8% |----------------------| #> FOS    61     13.1% |##--------------------|      0.0% |----------------------| #> LNZ   467    100.0% |######################|    100.0% |######################| #> CIP   456     97.6% |#####################-|     12.5% |##--------------------| #> MFX    57     12.2% |##--------------------|    100.0% |######################| #> VAN   467    100.0% |######################|    100.0% |######################| #> TEC   467    100.0% |######################|    100.0% |######################| #> TCY     3      0.6% |----------------------|     66.7% |##############--------| #> TGC    68     14.6% |###-------------------|      0.0% |----------------------| #> DOX     0      0.0% |----------------------|                                    #> ERY   467    100.0% |######################|    100.0% |######################| #> CLI   467    100.0% |######################|    100.0% |######################| #> AZM   467    100.0% |######################|    100.0% |######################| #> IPM   422     90.4% |###################---|      0.0% |----------------------| #> MEM   418     89.5% |###################---|      0.0% |----------------------| #> MTR     2      0.4% |----------------------|      0.0% |----------------------| #> CHL     0      0.0% |----------------------|                                    #> COL   240     51.4% |###########-----------|      0.0% |----------------------| #> MUP     0      0.0% |----------------------|                                    #> RIF   467    100.0% |######################|    100.0% |######################| # }"},{"path":"https://msberends.github.io/AMR/reference/bug_drug_combinations.html","id":null,"dir":"Reference","previous_headings":"","what":"Determine Bug-Drug Combinations — bug_drug_combinations","title":"Determine Bug-Drug Combinations — bug_drug_combinations","text":"Determine antimicrobial resistance (AMR) bug-drug combinations data set least 30 (default) isolates available per species. Use format() result prettify publishable/printable format, see Examples.","code":""},{"path":"https://msberends.github.io/AMR/reference/bug_drug_combinations.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Determine Bug-Drug Combinations — bug_drug_combinations","text":"","code":"bug_drug_combinations(x, col_mo = NULL, FUN = mo_shortname, ...)  # S3 method for bug_drug_combinations format(   x,   translate_ab = \"name (ab, atc)\",   language = get_AMR_locale(),   minimum = 30,   combine_SI = TRUE,   add_ab_group = TRUE,   remove_intrinsic_resistant = FALSE,   decimal.mark = getOption(\"OutDec\"),   big.mark = ifelse(decimal.mark == \",\", \".\", \",\"),   ... )"},{"path":"https://msberends.github.io/AMR/reference/bug_drug_combinations.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Determine Bug-Drug Combinations — bug_drug_combinations","text":"x data set antibiotic columns, amox, AMX AMC col_mo column name names codes microorganisms (see .mo()) - default first column class mo. Values coerced using .mo(). FUN function call mo column transform microorganism codes - default mo_shortname() ... arguments passed FUN translate_ab character length 1 containing column names antibiotics data set language language returned text - default current system language (see get_AMR_locale()) can also set package option AMR_locale. Use language = NULL language = \"\" prevent translation. minimum minimum allowed number available (tested) isolates. isolate count lower minimum return NA warning. default number 30 isolates advised Clinical Laboratory Standards Institute (CLSI) best practice, see Source. combine_SI logical indicate whether values S summed, resistance based R - default TRUE add_ab_group logical indicate group antimicrobials must included first column remove_intrinsic_resistant logical indicate rows columns 100% resistance tested antimicrobials must removed table decimal.mark character used indicate numeric     decimal point. big.mark character; empty used mark every     big.interval decimals (hence big)     decimal point.","code":""},{"path":"https://msberends.github.io/AMR/reference/bug_drug_combinations.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Determine Bug-Drug Combinations — bug_drug_combinations","text":"function bug_drug_combinations() returns data.frame columns \"mo\", \"ab\", \"S\", \"SDD\", \"\", \"R\", \"total\".","code":""},{"path":"https://msberends.github.io/AMR/reference/bug_drug_combinations.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Determine Bug-Drug Combinations — bug_drug_combinations","text":"function format() calculates resistance per bug-drug combination returns table ready reporting/publishing. Use combine_SI = TRUE (default) test R vs. S+combine_SI = FALSE test R+vs. S. table can also directly used R Markdown / Quarto without need e.g. knitr::kable().","code":""},{"path":"https://msberends.github.io/AMR/reference/bug_drug_combinations.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Determine Bug-Drug Combinations — bug_drug_combinations","text":"","code":"# example_isolates is a data set available in the AMR package. # run ?example_isolates for more info. example_isolates #> # A tibble: 2,000 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-03 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  3 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  4 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  5 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  6 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  7 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  8 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  9 2002-01-16 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #> 10 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R     NA    S     NA    #> # ℹ 1,990 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, …  # \\donttest{ x <- bug_drug_combinations(example_isolates) head(x) #> # A tibble: 6 × 9 #>   mo                ab        S   SDD     I     R    NI total N     #>   <chr>             <chr> <int> <int> <int> <int> <int> <int> <lgl> #> 1 (unknown species) AMC      15     0     0     0     0    15 NA    #> 2 (unknown species) AMK       0     0     0     0     0     0 NA    #> 3 (unknown species) AMP      15     0     0     1     0    16 NA    #> 4 (unknown species) AMX      15     0     0     1     0    16 NA    #> 5 (unknown species) AZM       3     0     0     3     0     6 NA    #> 6 (unknown species) CAZ       0     0     0     0     0     0 NA    #> Use 'format()' on this result to get a publishable/printable format. format(x, translate_ab = \"name (atc)\") #> # A tibble: 39 × 12 #>    Group     Drug  CoNS  `E. coli` `E. faecalis` `K. pneumoniae` `P. aeruginosa` #>    <chr>     <chr> <chr> <chr>     <chr>         <chr>           <chr>           #>  1 \"Aminogl… Amik… \"100… \"  0.0% … \"100.0% (39/… \"\"              \"\"              #>  2 \"\"        Gent… \" 13… \"  2.0% … \"100.0% (39/… \" 10.3% (6/58)\" \"  0.0% (0/30)\" #>  3 \"\"        Kana… \"100… \"\"        \"100.0% (39/… \"\"              \"100.0% (30/30… #>  4 \"\"        Tobr… \" 78… \"  2.6% … \"100.0% (39/… \" 10.3% (6/58)\" \"  0.0% (0/30)\" #>  5 \"Ampheni… Chlo… \"\"    \"\"        \"\"            \"\"              \"100.0% (30/30… #>  6 \"Antimyc… Rifa… \"\"    \"100.0% … \"\"            \"100.0% (58/58… \"100.0% (30/30… #>  7 \"Beta-la… Amox… \" 93… \" 50.0% … \"\"            \"100.0% (58/58… \"100.0% (30/30… #>  8 \"\"        Amox… \" 42… \" 13.1% … \"\"            \" 10.3% (6/58)\" \"100.0% (30/30… #>  9 \"\"        Ampi… \" 93… \" 50.0% … \"\"            \"100.0% (58/58… \"100.0% (30/30… #> 10 \"\"        Benz… \" 77… \"100.0% … \"\"            \"100.0% (58/58… \"100.0% (30/30… #> # ℹ 29 more rows #> # ℹ 5 more variables: `P. mirabilis` <chr>, `S. aureus` <chr>, #> #   `S. epidermidis` <chr>, `S. hominis` <chr>, `S. pneumoniae` <chr>  # Use FUN to change to transformation of microorganism codes bug_drug_combinations(example_isolates,   FUN = mo_gramstain ) #> # A tibble: 80 × 9 #>    mo            ab        S   SDD     I     R    NI total N     #>  * <chr>         <chr> <int> <int> <int> <int> <int> <int> <lgl> #>  1 Gram-negative AMC     463     0    89   174     0   726 NA    #>  2 Gram-negative AMK     251     0     0     5     0   256 NA    #>  3 Gram-negative AMP     226     0     0   405     0   631 NA    #>  4 Gram-negative AMX     226     0     0   405     0   631 NA    #>  5 Gram-negative AZM       1     0     2   696     0   699 NA    #>  6 Gram-negative CAZ     607     0     0    27     0   634 NA    #>  7 Gram-negative CHL       1     0     0    30     0    31 NA    #>  8 Gram-negative CIP     610     0    11    63     0   684 NA    #>  9 Gram-negative CLI      18     0     1   709     0   728 NA    #> 10 Gram-negative COL     309     0     0    78     0   387 NA    #> # ℹ 70 more rows #> Use 'format()' on this result to get a publishable/printable format.  bug_drug_combinations(example_isolates,   FUN = function(x) {     ifelse(x == as.mo(\"Escherichia coli\"),       \"E. coli\",       \"Others\"     )   } ) #> # A tibble: 80 × 9 #>    mo      ab        S   SDD     I     R    NI total N     #>  * <chr>   <chr> <int> <int> <int> <int> <int> <int> <lgl> #>  1 E. coli AMC     332     0    74    61     0   467 NA    #>  2 E. coli AMK     171     0     0     0     0   171 NA    #>  3 E. coli AMP     196     0     0   196     0   392 NA    #>  4 E. coli AMX     196     0     0   196     0   392 NA    #>  5 E. coli AZM       0     0     0   467     0   467 NA    #>  6 E. coli CAZ     449     0     0    11     0   460 NA    #>  7 E. coli CHL       0     0     0     0     0     0 NA    #>  8 E. coli CIP     398     0     1    57     0   456 NA    #>  9 E. coli CLI       0     0     0   467     0   467 NA    #> 10 E. coli COL     240     0     0     0     0   240 NA    #> # ℹ 70 more rows #> Use 'format()' on this result to get a publishable/printable format. # }"},{"path":"https://msberends.github.io/AMR/reference/clinical_breakpoints.html","id":null,"dir":"Reference","previous_headings":"","what":"Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints","title":"Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints","text":"Data set containing clinical breakpoints interpret MIC disk diffusion SIR values, according international guidelines. dataset contain breakpoints humans, 7 different animal groups, ECOFFs. Currently available breakpoint guidelines clinical microbiology EUCAST 2011-2024 CLSI 2011-2024. Currently available breakpoint guidelines veterinary microbiology EUCAST 2021-2024 CLSI 2019-2024. Use .sir() transform MICs disks measurements SIR values.","code":""},{"path":"https://msberends.github.io/AMR/reference/clinical_breakpoints.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints","text":"","code":"clinical_breakpoints"},{"path":"https://msberends.github.io/AMR/reference/clinical_breakpoints.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints","text":"tibble 34 063 observations 14 variables: guideline Name guideline type Breakpoint type, either \"ECOFF\", \"animal\", \"human\" host Host infectious agent. mostly useful veterinary breakpoints either \"ECOFF\", \"aquatic\", \"cats\", \"cattle\", \"dogs\", \"horse\", \"human\", \"poultry\", \"swine\" method Testing method, either \"DISK\" \"MIC\" site Body site breakpoint must applied, e.g. \"Oral\" \"Respiratory\" mo Microbial ID, see .mo() rank_index Taxonomic rank index mo 1 (subspecies/infraspecies) 5 (unknown microorganism) ab Antibiotic code used package, EARS-Net WHONET, see .ab() ref_tbl Info guideline rule can found disk_dose Dose used disk diffusion method breakpoint_S Lowest MIC value highest number millimetres leads \"S\" breakpoint_R Highest MIC value lowest number millimetres leads \"R\" uti logical value (TRUE/FALSE) indicate whether rule applies urinary tract infection (UTI) is_SDD logical value (TRUE/FALSE) indicate whether intermediate range \"S\" \"R\" interpreted \"SDD\", instead \"\". currently applies 24 breakpoints.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/clinical_breakpoints.html","id":"different-types-of-breakpoints","dir":"Reference","previous_headings":"","what":"Different types of breakpoints","title":"Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints","text":"Supported types breakpoints ECOFF, animal, human. ECOFF (Epidemiological cut-) values used antimicrobial susceptibility testing differentiate wild-type non-wild-type strains bacteria fungi. default \"human\", can also set package option AMR_breakpoint_type. Use .sir(..., breakpoint_type = ...) interpret raw data using specific breakpoint type, e.g. .sir(..., breakpoint_type = \"ECOFF\") use ECOFFs.","code":""},{"path":"https://msberends.github.io/AMR/reference/clinical_breakpoints.html","id":"imported-from-whonet","dir":"Reference","previous_headings":"","what":"Imported from WHONET","title":"Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints","text":"Clinical breakpoints package validated imported WHONET, free desktop Windows application developed supported Collaborating Centre Surveillance Antimicrobial Resistance. can read website. developers WHONET AMR package contact sharing work. highly appreciate great development WHONET software.","code":""},{"path":"https://msberends.github.io/AMR/reference/clinical_breakpoints.html","id":"response-from-clsi-and-eucast","dir":"Reference","previous_headings":"","what":"Response from CLSI and EUCAST","title":"Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints","text":"CEO CLSI chairman EUCAST endorsed work public use AMR package (consequently use breakpoints) June 2023, future development distributing clinical breakpoints discussed meeting CLSI, EUCAST, , developers WHONET software, developers AMR package.","code":""},{"path":"https://msberends.github.io/AMR/reference/clinical_breakpoints.html","id":"download","dir":"Reference","previous_headings":"","what":"Download","title":"Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints","text":"Like data sets package, data set publicly available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. Please visit website download links. actual files course available GitHub repository. allow machine reading EUCAST CLSI guidelines, almost impossible MS Excel PDF files distributed EUCAST CLSI, though initiatives started overcome burdens. NOTE: AMR package (WHONET software well) contains rather complex internal methods apply guidelines. example, breakpoints must applied certain species groups (case package available microorganisms.groups data set). important considered using breakpoints use.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/clinical_breakpoints.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints","text":"","code":"clinical_breakpoints #> # A tibble: 34,063 × 14 #>    guideline   type  host  method site    mo            rank_index ab   ref_tbl  #>    <chr>       <chr> <chr> <chr>  <chr>   <mo>               <dbl> <ab> <chr>    #>  1 EUCAST 2024 human human DISK   NA      B_ACHRMB_XYLS          2 MEM  A. xylo… #>  2 EUCAST 2024 human human MIC    NA      B_ACHRMB_XYLS          2 MEM  A. xylo… #>  3 EUCAST 2024 human human DISK   NA      B_ACHRMB_XYLS          2 SXT  A. xylo… #>  4 EUCAST 2024 human human MIC    NA      B_ACHRMB_XYLS          2 SXT  A. xylo… #>  5 EUCAST 2024 human human DISK   NA      B_ACHRMB_XYLS          2 TZP  A. xylo… #>  6 EUCAST 2024 human human MIC    NA      B_ACHRMB_XYLS          2 TZP  A. xylo… #>  7 EUCAST 2024 human human DISK   NA      B_ACNTB                3 AMK  Acineto… #>  8 EUCAST 2024 human human DISK   Uncomp… B_ACNTB                3 AMK  Acineto… #>  9 EUCAST 2024 human human MIC    NA      B_ACNTB                3 AMK  Acineto… #> 10 EUCAST 2024 human human MIC    Uncomp… B_ACNTB                3 AMK  Acineto… #> # ℹ 34,053 more rows #> # ℹ 5 more variables: disk_dose <chr>, breakpoint_S <dbl>, breakpoint_R <dbl>, #> #   uti <lgl>, is_SDD <lgl>"},{"path":"https://msberends.github.io/AMR/reference/count.html","id":null,"dir":"Reference","previous_headings":"","what":"Count Available Isolates — count","title":"Count Available Isolates — count","text":"functions can used count resistant/susceptible microbial isolates. functions support quasiquotation pipes, can used summarise() dplyr package also support grouped variables, see Examples. count_resistant() used count resistant isolates, count_susceptible() used count susceptible isolates.","code":""},{"path":"https://msberends.github.io/AMR/reference/count.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Count Available Isolates — count","text":"","code":"count_resistant(..., only_all_tested = FALSE)  count_susceptible(..., only_all_tested = FALSE)  count_S(..., only_all_tested = FALSE)  count_SI(..., only_all_tested = FALSE)  count_I(..., only_all_tested = FALSE)  count_IR(..., only_all_tested = FALSE)  count_R(..., only_all_tested = FALSE)  count_all(..., only_all_tested = FALSE)  n_sir(..., only_all_tested = FALSE)  count_df(   data,   translate_ab = \"name\",   language = get_AMR_locale(),   combine_SI = TRUE )"},{"path":"https://msberends.github.io/AMR/reference/count.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Count Available Isolates — count","text":"... one vectors (columns) antibiotic interpretations. transformed internally .sir() needed. only_all_tested (combination therapies, .e. using one variable ...): logical indicate isolates must tested antibiotics, see section Combination Therapy data data.frame containing columns class sir (see .sir()) translate_ab column name antibiotics data set translate antibiotic abbreviations , using ab_property() language language returned text - default current system language (see get_AMR_locale()) can also set package option AMR_locale. Use language = NULL language = \"\" prevent translation. combine_SI logical indicate whether values S must merged one, output consists S+vs. R (susceptible vs. resistant) - default TRUE","code":""},{"path":"https://msberends.github.io/AMR/reference/count.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Count Available Isolates — count","text":"integer","code":""},{"path":"https://msberends.github.io/AMR/reference/count.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Count Available Isolates — count","text":"functions meant count isolates. Use resistance()/susceptibility() functions calculate microbial resistance/susceptibility. function count_resistant() equal function count_R(). function count_susceptible() equal function count_SI(). function n_sir() alias count_all(). can used count available isolates, .e. input antibiotics available result (S, R). use equal n_distinct(). function equal count_susceptible(...) + count_resistant(...). function count_df() takes variable data sir class (created .sir()) counts number S's, 's R's. also supports grouped variables. function sir_df() works exactly like count_df(), adds percentage S, R.","code":""},{"path":"https://msberends.github.io/AMR/reference/count.html","id":"interpretation-of-sir","dir":"Reference","previous_headings":"","what":"Interpretation of SIR","title":"Count Available Isolates — count","text":"2019, European Committee Antimicrobial Susceptibility Testing (EUCAST) decided change definitions susceptibility testing categories S, , R shown (https://www.eucast.org/newsiandr): S - Susceptible, standard dosing regimen microorganism categorised \"Susceptible, standard dosing regimen\", high likelihood therapeutic success using standard dosing regimen agent. - Susceptible, increased exposure  microorganism categorised \"Susceptible, Increased exposure\" high likelihood therapeutic success exposure agent increased adjusting dosing regimen concentration site infection. R = Resistant microorganism categorised \"Resistant\" high likelihood therapeutic failure even increased exposure. Exposure function mode administration, dose, dosing interval, infusion time, well distribution excretion antimicrobial agent influence infecting organism site infection. AMR package honours insight. Use susceptibility() (equal proportion_SI()) determine antimicrobial susceptibility count_susceptible() (equal count_SI()) count susceptible isolates.","code":""},{"path":"https://msberends.github.io/AMR/reference/count.html","id":"combination-therapy","dir":"Reference","previous_headings":"","what":"Combination Therapy","title":"Count Available Isolates — count","text":"using one variable ... (= combination therapy), use only_all_tested count isolates tested antibiotics/variables test . See example two antibiotics, Drug Drug B, susceptibility() works calculate %SI:   Please note , combination therapies, only_all_tested = TRUE applies :   , combination therapies, only_all_tested = FALSE applies :   Using only_all_tested impact using one antibiotic input.","code":"--------------------------------------------------------------------                     only_all_tested = FALSE  only_all_tested = TRUE                     -----------------------  -----------------------  Drug A    Drug B   include as  include as   include as  include as                     numerator   denominator  numerator   denominator --------  --------  ----------  -----------  ----------  -----------  S or I    S or I       X            X            X            X    R       S or I       X            X            X            X   <NA>     S or I       X            X            -            -  S or I      R          X            X            X            X    R         R          -            X            -            X   <NA>       R          -            -            -            -  S or I     <NA>        X            X            -            -    R        <NA>        -            -            -            -   <NA>      <NA>        -            -            -            - -------------------------------------------------------------------- count_S()    +   count_I()    +   count_R()    = count_all()   proportion_S() + proportion_I() + proportion_R() = 1 count_S()    +   count_I()    +   count_R()    >= count_all()   proportion_S() + proportion_I() + proportion_R() >= 1"},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/count.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Count Available Isolates — count","text":"","code":"# example_isolates is a data set available in the AMR package. # run ?example_isolates for more info.  # base R ------------------------------------------------------------ count_resistant(example_isolates$AMX) # counts \"R\" #> [1] 804 count_susceptible(example_isolates$AMX) # counts \"S\" and \"I\" #> [1] 546 count_all(example_isolates$AMX) # counts \"S\", \"I\" and \"R\" #> [1] 1350  # be more specific count_S(example_isolates$AMX) #> Using count_S() is discouraged; use count_susceptible() instead to also #> consider \"I\" and \"SDD\" being susceptible. This note will be shown once for #> this session. #> [1] 543 count_SI(example_isolates$AMX) #> Note that count_SI() will also count dose-dependent susceptibility, #> 'SDD'. This note will be shown once for this session. #> [1] 546 count_I(example_isolates$AMX) #> Note that count_I() will also count dose-dependent susceptibility, 'SDD'. #> This note will be shown once for this session. #> [1] 3 count_IR(example_isolates$AMX) #> Using count_IR() is discouraged; use count_resistant() instead to not #> consider \"I\" and \"SDD\" being resistant. This note will be shown once for #> this session. #> [1] 807 count_R(example_isolates$AMX) #> [1] 804  # Count all available isolates count_all(example_isolates$AMX) #> [1] 1350 n_sir(example_isolates$AMX) #> [1] 1350  # n_sir() is an alias of count_all(). # Since it counts all available isolates, you can # calculate back to count e.g. susceptible isolates. # These results are the same: count_susceptible(example_isolates$AMX) #> [1] 546 susceptibility(example_isolates$AMX) * n_sir(example_isolates$AMX) #> [1] 546  # dplyr ------------------------------------------------------------- # \\donttest{ if (require(\"dplyr\")) {   example_isolates %>%     group_by(ward) %>%     summarise(       R = count_R(CIP),       I = count_I(CIP),       S = count_S(CIP),       n1 = count_all(CIP), # the actual total; sum of all three       n2 = n_sir(CIP), # same - analogous to n_distinct       total = n()     ) # NOT the number of tested isolates!    # Number of available isolates for a whole antibiotic class   # (i.e., in this data set columns GEN, TOB, AMK, KAN)   example_isolates %>%     group_by(ward) %>%     summarise(across(aminoglycosides(), n_sir))    # Count co-resistance between amoxicillin/clav acid and gentamicin,   # so we can see that combination therapy does a lot more than mono therapy.   # Please mind that `susceptibility()` calculates percentages right away instead.   example_isolates %>% count_susceptible(AMC) # 1433   example_isolates %>% count_all(AMC) # 1879    example_isolates %>% count_susceptible(GEN) # 1399   example_isolates %>% count_all(GEN) # 1855    example_isolates %>% count_susceptible(AMC, GEN) # 1764   example_isolates %>% count_all(AMC, GEN) # 1936    # Get number of S+I vs. R immediately of selected columns   example_isolates %>%     select(AMX, CIP) %>%     count_df(translate = FALSE)    # It also supports grouping variables   example_isolates %>%     select(ward, AMX, CIP) %>%     group_by(ward) %>%     count_df(translate = FALSE) } #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> # A tibble: 12 × 4 #>    ward       antibiotic interpretation value #>  * <chr>      <chr>      <ord>          <int> #>  1 Clinical   AMX        SI               357 #>  2 Clinical   AMX        R                487 #>  3 Clinical   CIP        SI               741 #>  4 Clinical   CIP        R                128 #>  5 ICU        AMX        SI               158 #>  6 ICU        AMX        R                270 #>  7 ICU        CIP        SI               362 #>  8 ICU        CIP        R                 85 #>  9 Outpatient AMX        SI                31 #> 10 Outpatient AMX        R                 47 #> 11 Outpatient CIP        SI                78 #> 12 Outpatient CIP        R                 15 # }"},{"path":"https://msberends.github.io/AMR/reference/custom_eucast_rules.html","id":null,"dir":"Reference","previous_headings":"","what":"Define Custom EUCAST Rules — custom_eucast_rules","title":"Define Custom EUCAST Rules — custom_eucast_rules","text":"Define custom EUCAST rules organisation specific analysis use output function eucast_rules().","code":""},{"path":"https://msberends.github.io/AMR/reference/custom_eucast_rules.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Define Custom EUCAST Rules — custom_eucast_rules","text":"","code":"custom_eucast_rules(...)"},{"path":"https://msberends.github.io/AMR/reference/custom_eucast_rules.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Define Custom EUCAST Rules — custom_eucast_rules","text":"... rules formula notation, see instructions, Examples","code":""},{"path":"https://msberends.github.io/AMR/reference/custom_eucast_rules.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Define Custom EUCAST Rules — custom_eucast_rules","text":"list containing custom rules","code":""},{"path":"https://msberends.github.io/AMR/reference/custom_eucast_rules.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Define Custom EUCAST Rules — custom_eucast_rules","text":"organisations adoption EUCAST rules. function can used define custom EUCAST rules used eucast_rules() function.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/custom_eucast_rules.html","id":"basics","dir":"Reference","previous_headings":"","what":"Basics","title":"Define Custom EUCAST Rules — custom_eucast_rules","text":"familiar case_when() function dplyr package, recognise input method set rules. Rules must set using R considers 'formula notation'. rule written tilde (~) consequence rule written tilde:   two custom EUCAST rules: TZP (piperacillin/tazobactam) \"S\", aminopenicillins (ampicillin amoxicillin) must made \"S\", TZP \"R\", aminopenicillins must made \"R\". rules can also printed console, immediately clear work:   rules (part tilde, example TZP == \"S\" TZP == \"R\") must evaluable data set: able run filter data set without errors. means example column TZP must exist. create sample data set test rules set:","code":"x <- custom_eucast_rules(TZP == \"S\" ~ aminopenicillins == \"S\",                          TZP == \"R\" ~ aminopenicillins == \"R\") x #> A set of custom EUCAST rules: #> #>   1. If TZP is \"S\" then set to  S : #>      amoxicillin (AMX), ampicillin (AMP) #> #>   2. If TZP is \"R\" then set to  R : #>      amoxicillin (AMX), ampicillin (AMP) df <- data.frame(mo = c(\"Escherichia coli\", \"Klebsiella pneumoniae\"),                  TZP = as.sir(\"R\"),                  ampi = as.sir(\"S\"),                  cipro = as.sir(\"S\")) df #>                      mo TZP ampi cipro #> 1      Escherichia coli   R    S     S #> 2 Klebsiella pneumoniae   R    S     S  eucast_rules(df, rules = \"custom\", custom_rules = x, info = FALSE) #>                      mo TZP ampi cipro #> 1      Escherichia coli   R    R     S #> 2 Klebsiella pneumoniae   R    R     S"},{"path":"https://msberends.github.io/AMR/reference/custom_eucast_rules.html","id":"using-taxonomic-properties-in-rules","dir":"Reference","previous_headings":"","what":"Using taxonomic properties in rules","title":"Define Custom EUCAST Rules — custom_eucast_rules","text":"one exception columns used rules: column names microorganisms data set can also used, exist data set. column names : \"mo\", \"fullname\", \"status\", \"kingdom\", \"phylum\", \"class\", \"order\", \"family\", \"genus\", \"species\", \"subspecies\", \"rank\", \"ref\", \"oxygen_tolerance\", \"source\", \"lpsn\", \"lpsn_parent\", \"lpsn_renamed_to\", \"gbif\", \"gbif_parent\", \"gbif_renamed_to\", \"prevalence\", \"snomed\". Thus, next example work well, despite fact df data set contain column genus:","code":"y <- custom_eucast_rules(TZP == \"S\" & genus == \"Klebsiella\" ~ aminopenicillins == \"S\",                          TZP == \"R\" & genus == \"Klebsiella\" ~ aminopenicillins == \"R\")  eucast_rules(df, rules = \"custom\", custom_rules = y, info = FALSE) #>                      mo TZP ampi cipro #> 1      Escherichia coli   R    S     S #> 2 Klebsiella pneumoniae   R    R     S"},{"path":"https://msberends.github.io/AMR/reference/custom_eucast_rules.html","id":"usage-of-multiple-antibiotics-and-antibiotic-group-names","dir":"Reference","previous_headings":"","what":"Usage of multiple antibiotics and antibiotic group names","title":"Define Custom EUCAST Rules — custom_eucast_rules","text":"can define antibiotic groups instead single antibiotics rule consequence, part tilde (~). examples , antibiotic group aminopenicillins includes ampicillin amoxicillin. Rules can also applied multiple antibiotics antibiotic groups simultaneously. Use c() function combine multiple antibiotics. instance, following example sets aminopenicillins ureidopenicillins \"R\" column TZP (piperacillin/tazobactam) \"R\":   30 antibiotic groups allowed rules (case-insensitive) can used combination: aminoglycosides(amikacin, amikacin/fosfomycin, apramycin, arbekacin, astromicin, bekanamycin, dibekacin, framycetin, gentamicin, gentamicin-high, habekacin, hygromycin, isepamicin, kanamycin, kanamycin-high, kanamycin/cephalexin, micronomicin, neomycin, netilmicin, pentisomicin, plazomicin, propikacin, ribostamycin, sisomicin, streptoduocin, streptomycin, streptomycin-high, tobramycin, tobramycin-high) aminopenicillins(amoxicillin ampicillin) antifungals(amorolfine, amphotericin B, amphotericin B-high, anidulafungin, butoconazole, caspofungin, ciclopirox, clotrimazole, econazole, fluconazole, flucytosine, fosfluconazole, griseofulvin, hachimycin, ibrexafungerp, isavuconazole, isoconazole, itraconazole, ketoconazole, manogepix, micafungin, miconazole, nystatin, oteseconazole, pimaricin, posaconazole, rezafungin, ribociclib, sulconazole, terbinafine, terconazole, voriconazole) antimycobacterials(4-aminosalicylic acid, calcium aminosalicylate, capreomycin, clofazimine, delamanid, enviomycin, ethambutol, ethambutol/isoniazid, ethionamide, isoniazid, isoniazid/sulfamethoxazole/trimethoprim/pyridoxine, morinamide, p-aminosalicylic acid, pretomanid, protionamide, pyrazinamide, rifabutin, rifampicin, rifampicin/ethambutol/isoniazid, rifampicin/isoniazid, rifampicin/pyrazinamide/ethambutol/isoniazid, rifampicin/pyrazinamide/isoniazid, rifamycin, rifapentine, simvastatin/fenofibrate, sodium aminosalicylate, streptomycin/isoniazid, terizidone, thioacetazone, thioacetazone/isoniazid, tiocarlide, viomycin) betalactams(amoxicillin, amoxicillin/clavulanic acid, amoxicillin/sulbactam, ampicillin, ampicillin/sulbactam, apalcillin, aspoxicillin, avibactam, azidocillin, azlocillin, aztreonam, aztreonam/avibactam, aztreonam/nacubactam, bacampicillin, benzathine benzylpenicillin, benzathine phenoxymethylpenicillin, benzylpenicillin, biapenem, carbenicillin, carindacillin, cefacetrile, cefaclor, cefadroxil, cefalexin, cefaloridine, cefalotin, cefamandole, cefapirin, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/nacubactam, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol, cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/tazobactam, ceftriaxone, ceftriaxone/beta-lactamase inhibitor, cefuroxime, cefuroxime axetil, cephradine, ciclacillin, clometocillin, cloxacillin, dicloxacillin, doripenem, epicillin, ertapenem, flucloxacillin, hetacillin, imipenem, imipenem/EDTA, imipenem/relebactam, latamoxef, lenampicillin, loracarbef, mecillinam, meropenem, meropenem/nacubactam, meropenem/vaborbactam, metampicillin, meticillin, mezlocillin, mezlocillin/sulbactam, nacubactam, nafcillin, oxacillin, panipenem, penamecillin, penicillin/novobiocin, penicillin/sulbactam, pheneticillin, phenoxymethylpenicillin, piperacillin, piperacillin/sulbactam, piperacillin/tazobactam, piridicillin, pivampicillin, pivmecillinam, procaine benzylpenicillin, propicillin, razupenem, ritipenem, ritipenem acoxil, sarmoxicillin, sulbactam, sulbenicillin, sultamicillin, talampicillin, tazobactam, tebipenem, temocillin, ticarcillin, ticarcillin/clavulanic acid) carbapenems(biapenem, doripenem, ertapenem, imipenem, imipenem/EDTA, imipenem/relebactam, meropenem, meropenem/nacubactam, meropenem/vaborbactam, panipenem, razupenem, ritipenem, ritipenem acoxil, tebipenem) cephalosporins(cefacetrile, cefaclor, cefadroxil, cefalexin, cefaloridine, cefalotin, cefamandole, cefapirin, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol, cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/tazobactam, ceftriaxone, ceftriaxone/beta-lactamase inhibitor, cefuroxime, cefuroxime axetil, cephradine, latamoxef, loracarbef) cephalosporins_1st(cefacetrile, cefadroxil, cefalexin, cefaloridine, cefalotin, cefapirin, cefatrizine, cefazedone, cefazolin, cefroxadine, ceftezole, cephradine) cephalosporins_2nd(cefaclor, cefamandole, cefmetazole, cefonicid, ceforanide, cefotetan, cefotiam, cefoxitin, cefoxitin screening, cefprozil, cefuroxime, cefuroxime axetil, loracarbef) cephalosporins_3rd(cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefetamet, cefetamet pivoxil, cefixime, cefmenoxime, cefodizime, cefoperazone, cefoperazone/sulbactam, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotiam hexetil, cefovecin, cefpimizole, cefpiramide, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefsulodin, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftriaxone, ceftriaxone/beta-lactamase inhibitor, latamoxef) cephalosporins_4th(cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetecol, cefoselis, cefozopran, cefpirome, cefquinome) cephalosporins_5th(ceftaroline, ceftaroline/avibactam, ceftobiprole, ceftobiprole medocaril, ceftolozane/tazobactam) cephalosporins_except_caz(cefacetrile, cefaclor, cefadroxil, cefalexin, cefaloridine, cefalotin, cefamandole, cefapirin, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol, cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/tazobactam, ceftriaxone, ceftriaxone/beta-lactamase inhibitor, cefuroxime, cefuroxime axetil, cephradine, latamoxef, loracarbef) fluoroquinolones(besifloxacin, ciprofloxacin, clinafloxacin, danofloxacin, delafloxacin, difloxacin, enoxacin, enrofloxacin, finafloxacin, fleroxacin, garenoxacin, gatifloxacin, gemifloxacin, grepafloxacin, lascufloxacin, levofloxacin, levonadifloxacin, lomefloxacin, marbofloxacin, metioxate, miloxacin, moxifloxacin, nadifloxacin, nifuroquine, norfloxacin, ofloxacin, orbifloxacin, pazufloxacin, pefloxacin, pradofloxacin, premafloxacin, prulifloxacin, rufloxacin, sarafloxacin, sitafloxacin, sparfloxacin, temafloxacin, tilbroquinol, tioxacin, tosufloxacin, trovafloxacin) glycopeptides(avoparcin, dalbavancin, norvancomycin, oritavancin, ramoplanin, teicoplanin, teicoplanin-macromethod, telavancin, vancomycin, vancomycin-macromethod) glycopeptides_except_lipo(avoparcin, norvancomycin, ramoplanin, teicoplanin, teicoplanin-macromethod, vancomycin, vancomycin-macromethod) lincosamides(acetylmidecamycin, acetylspiramycin, clindamycin, clindamycin inducible screening, gamithromycin, kitasamycin, lincomycin, meleumycin, nafithromycin, pirlimycin, primycin, solithromycin, tildipirosin, tilmicosin, tulathromycin, tylosin, tylvalosin) lipoglycopeptides(dalbavancin, oritavancin, telavancin) macrolides(acetylmidecamycin, acetylspiramycin, azithromycin, clarithromycin, dirithromycin, erythromycin, flurithromycin, gamithromycin, josamycin, kitasamycin, meleumycin, midecamycin, miocamycin, nafithromycin, oleandomycin, pirlimycin, primycin, rokitamycin, roxithromycin, solithromycin, spiramycin, telithromycin, tildipirosin, tilmicosin, troleandomycin, tulathromycin, tylosin, tylvalosin) nitrofurans(furazidin, furazolidone, nifurtoinol, nitrofurantoin, nitrofurazone) oxazolidinones(cadazolid, cycloserine, linezolid, tedizolid, thiacetazone) penicillins(amoxicillin, amoxicillin/clavulanic acid, amoxicillin/sulbactam, ampicillin, ampicillin/sulbactam, apalcillin, aspoxicillin, avibactam, azidocillin, azlocillin, aztreonam, aztreonam/avibactam, aztreonam/nacubactam, bacampicillin, benzathine benzylpenicillin, benzathine phenoxymethylpenicillin, benzylpenicillin, carbenicillin, carindacillin, cefepime/nacubactam, ciclacillin, clometocillin, cloxacillin, dicloxacillin, epicillin, flucloxacillin, hetacillin, lenampicillin, mecillinam, metampicillin, meticillin, mezlocillin, mezlocillin/sulbactam, nacubactam, nafcillin, oxacillin, penamecillin, penicillin/novobiocin, penicillin/sulbactam, pheneticillin, phenoxymethylpenicillin, piperacillin, piperacillin/sulbactam, piperacillin/tazobactam, piridicillin, pivampicillin, pivmecillinam, procaine benzylpenicillin, propicillin, sarmoxicillin, sulbactam, sulbenicillin, sultamicillin, talampicillin, tazobactam, temocillin, ticarcillin, ticarcillin/clavulanic acid) polymyxins(colistin, polymyxin B, polymyxin B/polysorbate 80) quinolones(besifloxacin, cinoxacin, ciprofloxacin, ciprofloxacin/metronidazole, ciprofloxacin/ornidazole, ciprofloxacin/tinidazole, clinafloxacin, danofloxacin, delafloxacin, difloxacin, enoxacin, enrofloxacin, finafloxacin, fleroxacin, flumequine, garenoxacin, gatifloxacin, gemifloxacin, grepafloxacin, lascufloxacin, levofloxacin, levonadifloxacin, lomefloxacin, marbofloxacin, metioxate, miloxacin, moxifloxacin, nadifloxacin, nalidixic acid, nemonoxacin, nifuroquine, nitroxoline, norfloxacin, ofloxacin, orbifloxacin, oxolinic acid, pazufloxacin, pefloxacin, pipemidic acid, piromidic acid, pradofloxacin, premafloxacin, prulifloxacin, rosoxacin, rufloxacin, sarafloxacin, sitafloxacin, sparfloxacin, temafloxacin, tilbroquinol, tioxacin, tosufloxacin, trovafloxacin) rifamycins(rifabutin, rifampicin, rifampicin/ethambutol/isoniazid, rifampicin/isoniazid, rifampicin/pyrazinamide/ethambutol/isoniazid, rifampicin/pyrazinamide/isoniazid, rifamycin, rifapentine) streptogramins(pristinamycin quinupristin/dalfopristin) tetracyclines(cetocycline, chlortetracycline, clomocycline, demeclocycline, doxycycline, eravacycline, lymecycline, metacycline, minocycline, omadacycline, oxytetracycline, penimepicycline, rolitetracycline, sarecycline, tetracycline, tigecycline) tetracyclines_except_tgc(cetocycline, chlortetracycline, clomocycline, demeclocycline, doxycycline, eravacycline, lymecycline, metacycline, minocycline, omadacycline, oxytetracycline, penimepicycline, rolitetracycline, sarecycline, tetracycline) trimethoprims(brodimoprim, sulfadiazine, sulfadiazine/tetroxoprim, sulfadiazine/trimethoprim, sulfadimethoxine, sulfadimidine, sulfadimidine/trimethoprim, sulfafurazole, sulfaisodimidine, sulfalene, sulfamazone, sulfamerazine, sulfamerazine/trimethoprim, sulfamethizole, sulfamethoxazole, sulfamethoxypyridazine, sulfametomidine, sulfametoxydiazine, sulfametrole/trimethoprim, sulfamoxole, sulfamoxole/trimethoprim, sulfanilamide, sulfaperin, sulfaphenazole, sulfapyridine, sulfathiazole, sulfathiourea, trimethoprim, trimethoprim/sulfamethoxazole) ureidopenicillins(azlocillin, mezlocillin, piperacillin, piperacillin/tazobactam)","code":"x <- custom_eucast_rules(TZP == \"R\" ~ c(aminopenicillins, ureidopenicillins) == \"R\") x #> A set of custom EUCAST rules: #>  #>   1. If TZP is \"R\" then set to \"R\": #>      amoxicillin (AMX), ampicillin (AMP), azlocillin (AZL), mezlocillin (MEZ), piperacillin (PIP), piperacillin/tazobactam (TZP)"},{"path":"https://msberends.github.io/AMR/reference/custom_eucast_rules.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Define Custom EUCAST Rules — custom_eucast_rules","text":"","code":"x <- custom_eucast_rules(   AMC == \"R\" & genus == \"Klebsiella\" ~ aminopenicillins == \"R\",   AMC == \"I\" & genus == \"Klebsiella\" ~ aminopenicillins == \"I\" ) x #> A set of custom EUCAST rules: #>  #>   1. If AMC is \"R\" and genus is \"Klebsiella\" then set to  R : #>      amoxicillin (AMX), ampicillin (AMP) #>  #>   2. If AMC is \"I\" and genus is \"Klebsiella\" then set to  I : #>      amoxicillin (AMX), ampicillin (AMP)  # run the custom rule set (verbose = TRUE will return a logbook instead of the data set): eucast_rules(example_isolates,   rules = \"custom\",   custom_rules = x,   info = FALSE,   verbose = TRUE ) #> # A tibble: 8 × 9 #>     row col   mo_fullname     old   new   rule  rule_group rule_name rule_source #>   <int> <chr> <chr>           <ord> <chr> <chr> <chr>      <chr>     <chr>       #> 1    33 AMP   Klebsiella pne… R     I     \"rep… Custom EU… Custom E… Object 'x'… #> 2    33 AMX   Klebsiella pne… R     I     \"rep… Custom EU… Custom E… Object 'x'… #> 3    34 AMP   Klebsiella pne… R     I     \"rep… Custom EU… Custom E… Object 'x'… #> 4    34 AMX   Klebsiella pne… R     I     \"rep… Custom EU… Custom E… Object 'x'… #> 5   531 AMP   Klebsiella pne… R     I     \"rep… Custom EU… Custom E… Object 'x'… #> 6   531 AMX   Klebsiella pne… R     I     \"rep… Custom EU… Custom E… Object 'x'… #> 7  1485 AMP   Klebsiella oxy… R     I     \"rep… Custom EU… Custom E… Object 'x'… #> 8  1485 AMX   Klebsiella oxy… R     I     \"rep… Custom EU… Custom E… Object 'x'…  # combine rule sets x2 <- c(   x,   custom_eucast_rules(TZP == \"R\" ~ carbapenems == \"R\") ) x2 #> A set of custom EUCAST rules: #>  #>   1. If AMC is \"R\" and genus is \"Klebsiella\" then set to  R : #>      amoxicillin (AMX), ampicillin (AMP) #>  #>   2. If AMC is \"I\" and genus is \"Klebsiella\" then set to  I : #>      amoxicillin (AMX), ampicillin (AMP) #>  #>   3. If TZP is \"R\" then set to  R : #>      biapenem (BIA), doripenem (DOR), ertapenem (ETP), imipenem (IPM), #>      imipenem/EDTA (IPE), imipenem/relebactam (IMR), meropenem (MEM), #>      meropenem/nacubactam (MNC), meropenem/vaborbactam (MEV), panipenem (PAN), #>      razupenem (RZM), ritipenem (RIT), ritipenem acoxil (RIA), tebipenem (TBP)"},{"path":"https://msberends.github.io/AMR/reference/dosage.html","id":null,"dir":"Reference","previous_headings":"","what":"Data Set with Treatment Dosages as Defined by EUCAST — dosage","title":"Data Set with Treatment Dosages as Defined by EUCAST — dosage","text":"EUCAST breakpoints used package based dosages data set. can retrieved eucast_dosage().","code":""},{"path":"https://msberends.github.io/AMR/reference/dosage.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Data Set with Treatment Dosages as Defined by EUCAST — dosage","text":"","code":"dosage"},{"path":"https://msberends.github.io/AMR/reference/dosage.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data Set with Treatment Dosages as Defined by EUCAST — dosage","text":"tibble 503 observations 9 variables: ab Antibiotic ID used package (AMC), using official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes available name Official name antimicrobial drug used WHONET/EARS-Net type Type dosage, either \"high_dosage\", \"standard_dosage\", \"uncomplicated_uti\" dose Dose, \"2 g\" \"25 mg/kg\" dose_times Number times dose must administered administration Route administration, either \"im\", \"iv\", \"oral\" notes Additional dosage notes original_txt Original text PDF file EUCAST eucast_version Version number EUCAST Clinical Breakpoints guideline dosages apply, either 13, 12, 11","code":""},{"path":"https://msberends.github.io/AMR/reference/dosage.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Data Set with Treatment Dosages as Defined by EUCAST — dosage","text":"Like data sets package, data set publicly available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":"https://msberends.github.io/AMR/reference/dosage.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Data Set with Treatment Dosages as Defined by EUCAST — dosage","text":"","code":"dosage #> # A tibble: 503 × 9 #>    ab   name            type  dose  dose_times administration notes original_txt #>    <ab> <chr>           <chr> <chr>      <int> <chr>          <chr> <chr>        #>  1 AMK  Amikacin        stan… 25-3…          1 iv             \"\"    25-30 mg/kg… #>  2 AMX  Amoxicillin     high… 2 g            6 iv             \"\"    2 g x 6 iv   #>  3 AMX  Amoxicillin     stan… 1 g            3 iv             \"\"    1 g x 3-4 iv #>  4 AMX  Amoxicillin     high… 0.75…          3 oral           \"\"    0.75-1 g x … #>  5 AMX  Amoxicillin     stan… 0.5 g          3 oral           \"\"    0.5 g x 3 o… #>  6 AMX  Amoxicillin     unco… 0.5 g          3 oral           \"\"    0.5 g x 3 o… #>  7 AMC  Amoxicillin/cl… high… 2 g …          3 iv             \"\"    (2 g amoxic… #>  8 AMC  Amoxicillin/cl… stan… 1 g …          3 iv             \"\"    (1 g amoxic… #>  9 AMC  Amoxicillin/cl… high… 0.87…          3 oral           \"\"    (0.875 g am… #> 10 AMC  Amoxicillin/cl… stan… 0.5 …          3 oral           \"\"    (0.5 g amox… #> # ℹ 493 more rows #> # ℹ 1 more variable: eucast_version <dbl>"},{"path":"https://msberends.github.io/AMR/reference/eucast_rules.html","id":null,"dir":"Reference","previous_headings":"","what":"Apply EUCAST Rules — eucast_rules","title":"Apply EUCAST Rules — eucast_rules","text":"Apply rules clinical breakpoints intrinsic resistance defined European Committee Antimicrobial Susceptibility Testing (EUCAST, https://www.eucast.org), see Source. Use eucast_dosage() get data.frame advised dosages certain bug-drug combination, based dosage data set. improve interpretation antibiogram EUCAST rules applied, non-EUCAST rules can applied default, see Details.","code":""},{"path":"https://msberends.github.io/AMR/reference/eucast_rules.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Apply EUCAST Rules — eucast_rules","text":"","code":"eucast_rules(   x,   col_mo = NULL,   info = interactive(),   rules = getOption(\"AMR_eucastrules\", default = c(\"breakpoints\", \"expert\")),   verbose = FALSE,   version_breakpoints = 12,   version_expertrules = 3.3,   ampc_cephalosporin_resistance = NA,   only_sir_columns = FALSE,   custom_rules = NULL,   ... )  eucast_dosage(ab, administration = \"iv\", version_breakpoints = 12)"},{"path":"https://msberends.github.io/AMR/reference/eucast_rules.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Apply EUCAST Rules — eucast_rules","text":"EUCAST Expert Rules. Version 2.0, 2012. Leclercq et al. EUCAST expert rules antimicrobial susceptibility testing. Clin Microbiol Infect. 2013;19(2):141-60; doi:10.1111/j.1469-0691.2011.03703.x EUCAST Expert Rules, Intrinsic Resistance Exceptional Phenotypes Tables. Version 3.1, 2016. (link) EUCAST Intrinsic Resistance Unusual Phenotypes. Version 3.2, 2020. (link) EUCAST Intrinsic Resistance Unusual Phenotypes. Version 3.3, 2021. (link) EUCAST Breakpoint tables interpretation MICs zone diameters. Version 9.0, 2019. (link) EUCAST Breakpoint tables interpretation MICs zone diameters. Version 10.0, 2020. (link) EUCAST Breakpoint tables interpretation MICs zone diameters. Version 11.0, 2021. (link) EUCAST Breakpoint tables interpretation MICs zone diameters. Version 12.0, 2022. (link)","code":""},{"path":"https://msberends.github.io/AMR/reference/eucast_rules.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Apply EUCAST Rules — eucast_rules","text":"x data set antibiotic columns, amox, AMX AMC col_mo column name names codes microorganisms (see .mo()) - default first column class mo. Values coerced using .mo(). info logical indicate whether progress printed console - default print interactive sessions rules character vector specifies rules applied. Must one \"breakpoints\", \"expert\", \"\", \"custom\", \"\", defaults c(\"breakpoints\", \"expert\"). default value can set another value using package option AMR_eucastrules: options(AMR_eucastrules = \"\"). using \"custom\", sure fill argument custom_rules . Custom rules can created custom_eucast_rules(). verbose logical turn Verbose mode (default ). Verbose mode, function apply rules data, instead returns data set logbook form extensive info rows columns effected way. Using Verbose mode takes lot time. version_breakpoints version number use EUCAST Clinical Breakpoints guideline. Can \"12.0\", \"11.0\", \"10.0\". version_expertrules version number use EUCAST Expert Rules Intrinsic Resistance guideline. Can \"3.3\", \"3.2\", \"3.1\". ampc_cephalosporin_resistance character value applied cefotaxime, ceftriaxone ceftazidime AmpC de-repressed cephalosporin-resistant mutants - default NA. Currently works version_expertrules 3.2 higher; version 'EUCAST Expert Rules Enterobacterales' state results cefotaxime, ceftriaxone ceftazidime reported note, results suppressed (emptied) three drugs. value NA (default) argument remove results three drugs, e.g. value \"R\" make results drugs resistant. Use NULL FALSE alter results three drugs AmpC de-repressed cephalosporin-resistant mutants. Using TRUE equal using \"R\".  EUCAST Expert Rules v3.2, rule applies : Citrobacter braakii, Citrobacter freundii, Citrobacter gillenii, Citrobacter murliniae, Citrobacter rodenticum, Citrobacter sedlakii, Citrobacter werkmanii, Citrobacter youngae, Enterobacter, Hafnia alvei, Klebsiella aerogenes, Morganella morganii, Providencia, Serratia. only_sir_columns logical indicate whether antibiotic columns must detected transformed class sir (see .sir()) beforehand (default FALSE) custom_rules custom rules apply, created custom_eucast_rules() ... column name antibiotic, see section Antibiotics ab (vector ) text can coerced valid antibiotic drug code .ab() administration route administration, either \"im\", \"iv\", \"oral\"","code":""},{"path":"https://msberends.github.io/AMR/reference/eucast_rules.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Apply EUCAST Rules — eucast_rules","text":"input x, possibly edited values antibiotics. , verbose = TRUE, data.frame original new values affected bug-drug combinations.","code":""},{"path":"https://msberends.github.io/AMR/reference/eucast_rules.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Apply EUCAST Rules — eucast_rules","text":"Note: function translate MIC values SIR values. Use .sir() . Note: ampicillin (AMP, J01CA01) available amoxicillin (AMX, J01CA04) , latter used rules dependency ampicillin. drugs interchangeable comes expression antimicrobial resistance. file containing EUCAST rules located : https://github.com/msberends/AMR/blob/main/data-raw/eucast_rules.tsv.  Note: Old taxonomic names replaced current taxonomy applicable. example, Ochrobactrum anthropi renamed Brucella anthropi 2020; original EUCAST rules v3.1 v3.2 yet contain new taxonomic name. AMR package contains full microbial taxonomy updated January 8th, 2024, see microorganisms.","code":""},{"path":"https://msberends.github.io/AMR/reference/eucast_rules.html","id":"custom-rules","dir":"Reference","previous_headings":"","what":"Custom Rules","title":"Apply EUCAST Rules — eucast_rules","text":"Custom rules can created using custom_eucast_rules(), e.g.:","code":"x <- custom_eucast_rules(AMC == \"R\" & genus == \"Klebsiella\" ~ aminopenicillins == \"R\",                          AMC == \"I\" & genus == \"Klebsiella\" ~ aminopenicillins == \"I\")  eucast_rules(example_isolates, rules = \"custom\", custom_rules = x)"},{"path":"https://msberends.github.io/AMR/reference/eucast_rules.html","id":"-other-rules","dir":"Reference","previous_headings":"","what":"'Other' Rules","title":"Apply EUCAST Rules — eucast_rules","text":"processing, two non-EUCAST rules drug combinations can applied improve efficacy EUCAST rules, reliability data (analysis). rules : drug enzyme inhibitor set S drug without enzyme inhibitor S drug without enzyme inhibitor set R drug enzyme inhibitor R Important examples include amoxicillin amoxicillin/clavulanic acid, trimethoprim trimethoprim/sulfamethoxazole. Needless say, rules work, drugs must available data set. Since rules officially approved EUCAST, applied default. use rules, include \"\" rules argument, use eucast_rules(..., rules = \"\"). can also set package option AMR_eucastrules, .e. run options(AMR_eucastrules = \"\").","code":""},{"path":"https://msberends.github.io/AMR/reference/eucast_rules.html","id":"antibiotics","dir":"Reference","previous_headings":"","what":"Antibiotics","title":"Apply EUCAST Rules — eucast_rules","text":"define antibiotics column names, leave determine automatically guess_ab_col() input text (case-insensitive), use NULL skip column (e.g. TIC = NULL skip ticarcillin). Manually defined non-existing columns skipped warning. following antibiotics eligible functions eucast_rules() mdro(). shown format 'name (antimicrobial ID, ATC code)', sorted alphabetically: Amikacin (AMK, J01GB06), amoxicillin (AMX, J01CA04), amoxicillin/clavulanic acid (AMC, J01CR02), ampicillin (AMP, J01CA01), ampicillin/sulbactam (SAM, J01CR01), apramycin (APR, QA07AA92), arbekacin (ARB, J01GB12), aspoxicillin (APX, J01CA19), azidocillin (AZD, J01CE04), azithromycin (AZM, J01FA10), azlocillin (AZL, J01CA09), aztreonam (ATM, J01DF01), bacampicillin (BAM, J01CA06), bekanamycin (BEK, J01GB13), benzathine benzylpenicillin (BNB, J01CE08), benzathine phenoxymethylpenicillin (BNP, J01CE10), benzylpenicillin (PEN, J01CE01), besifloxacin (BES, S01AE08), biapenem (BIA, J01DH05), carbenicillin (CRB, J01CA03), carindacillin (CRN, J01CA05), cefacetrile (CAC, J01DB10), cefaclor (CEC, J01DC04), cefadroxil (CFR, J01DB05), cefalexin (LEX, J01DB01), cefaloridine (RID, J01DB02), cefalotin (CEP, J01DB03), cefamandole (MAN, J01DC03), cefapirin (HAP, J01DB08), cefatrizine (CTZ, J01DB07), cefazedone (CZD, J01DB06), cefazolin (CZO, J01DB04), cefcapene (CCP, J01DD17), cefdinir (CDR, J01DD15), cefditoren (DIT, J01DD16), cefepime (FEP, J01DE01), cefetamet (CAT, J01DD10), cefixime (CFM, J01DD08), cefmenoxime (CMX, J01DD05), cefmetazole (CMZ, J01DC09), cefodizime (DIZ, J01DD09), cefonicid (CID, J01DC06), cefoperazone (CFP, J01DD12), cefoperazone/sulbactam (CSL, J01DD62), ceforanide (CND, J01DC11), cefotaxime (CTX, J01DD01), cefotaxime/clavulanic acid (CTC, J01DD51), cefotetan (CTT, J01DC05), cefotiam (CTF, J01DC07), cefovecin (FOV, QJ01DD91), cefoxitin (FOX, J01DC01), cefozopran (ZOP, J01DE03), cefpiramide (CPM, J01DD11), cefpirome (CPO, J01DE02), cefpodoxime (CPD, J01DD13), cefprozil (CPR, J01DC10), cefquinome (CEQ, QG51AA07), cefroxadine (CRD, J01DB11), cefsulodin (CFS, J01DD03), ceftaroline (CPT, J01DI02), ceftazidime (CAZ, J01DD02), ceftazidime/clavulanic acid (CCV, J01DD52), cefteram (CEM, J01DD18), ceftezole (CTL, J01DB12), ceftibuten (CTB, J01DD14), ceftiofur (TIO, QJ01DD90), ceftizoxime (CZX, J01DD07), ceftobiprole medocaril (CFM1, J01DI01), ceftolozane/tazobactam (CZT, J01DI54), ceftriaxone (CRO, J01DD04), ceftriaxone/beta-lactamase inhibitor (CEB, J01DD63), cefuroxime (CXM, J01DC02), cephradine (CED, J01DB09), chloramphenicol (CHL, J01BA01), ciprofloxacin (CIP, J01MA02), clarithromycin (CLR, J01FA09), clindamycin (CLI, J01FF01), clometocillin (CLM, J01CE07), cloxacillin (CLO, J01CF02), colistin (COL, J01XB01), cycloserine (CYC, J04AB01), dalbavancin (DAL, J01XA04), danofloxacin (DAN, QJ01MA92), daptomycin (DAP, J01XX09), delafloxacin (DFX, J01MA23), dibekacin (DKB, J01GB09), dicloxacillin (DIC, J01CF01), difloxacin (DIF, QJ01MA94), dirithromycin (DIR, J01FA13), doripenem (DOR, J01DH04), doxycycline (DOX, J01AA02), enoxacin (ENX, J01MA04), enrofloxacin (ENR, QJ01MA90), epicillin (EPC, J01CA07), ertapenem (ETP, J01DH03), erythromycin (ERY, J01FA01), fleroxacin (FLE, J01MA08), flucloxacillin (FLC, J01CF05), flurithromycin (FLR1, J01FA14), fosfomycin (FOS, J01XX01), framycetin (FRM, D09AA01), fusidic acid (FUS, J01XC01), gamithromycin (GAM, QJ01FA95), garenoxacin (GRN, J01MA19), gatifloxacin (GAT, J01MA16), gemifloxacin (GEM, J01MA15), gentamicin (GEN, J01GB03), grepafloxacin (GRX, J01MA11), hetacillin (HET, J01CA18), imipenem (IPM, J01DH51), imipenem/relebactam (IMR, J01DH56), isepamicin (ISE, J01GB11), josamycin (JOS, J01FA07), kanamycin (KAN, J01GB04), kitasamycin (KIT, QJ01FA93), lascufloxacin (LSC, J01MA25), latamoxef (LTM, J01DD06), levofloxacin (LVX, J01MA12), levonadifloxacin (LND, J01MA24), lincomycin (LIN, J01FF02), linezolid (LNZ, J01XX08), lomefloxacin (LOM, J01MA07), loracarbef (LOR, J01DC08), marbofloxacin (MAR, QJ01MA93), mecillinam (MEC, J01CA11), meropenem (MEM, J01DH02), meropenem/vaborbactam (MEV, J01DH52), metampicillin (MTM, J01CA14), meticillin (MET, J01CF03), mezlocillin (MEZ, J01CA10), micronomicin (MCR, S01AA22), midecamycin (MID, J01FA03), minocycline (MNO, J01AA08), miocamycin (MCM, J01FA11), moxifloxacin (MFX, J01MA14), nadifloxacin (NAD, D10AF05), nafcillin (NAF, J01CF06), nalidixic acid (NAL, J01MB02), neomycin (NEO, J01GB05), netilmicin (NET, J01GB07), nitrofurantoin (NIT, J01XE01), norfloxacin (, J01MA06), novobiocin (NOV, QJ01XX95), ofloxacin (OFX, J01MA01), oleandomycin (OLE, J01FA05), orbifloxacin (ORB, QJ01MA95), oritavancin (ORI, J01XA05), oxacillin (OXA, J01CF04), panipenem (PAN, J01DH55), pazufloxacin (PAZ, J01MA18), pefloxacin (PEF, J01MA03), penamecillin (PNM, J01CE06), pheneticillin (PHE, J01CE05), phenoxymethylpenicillin (PHN, J01CE02), piperacillin (PIP, J01CA12), piperacillin/tazobactam (TZP, J01CR05), pirlimycin (PRL, QJ51FF90), pivampicillin (PVM, J01CA02), pivmecillinam (PME, J01CA08), plazomicin (PLZ, J01GB14), polymyxin B (PLB, J01XB02), pradofloxacin (PRA, QJ01MA97), pristinamycin (PRI, J01FG01), procaine benzylpenicillin (PRB, J01CE09), propicillin (PRP, J01CE03), prulifloxacin (PRU, J01MA17), quinupristin/dalfopristin (QDA, QJ01FG02), ribostamycin (RST, J01GB10), rifampicin (RIF, J04AB02), rokitamycin (ROK, J01FA12), roxithromycin (RXT, J01FA06), rufloxacin (RFL, J01MA10), sarafloxacin (SAR, QJ01MA98), sisomicin (SIS, J01GB08), sitafloxacin (SIT, J01MA21), solithromycin (SOL, J01FA16), sparfloxacin (SPX, J01MA09), spiramycin (SPI, J01FA02), streptoduocin (STR, J01GA02), streptomycin (STR1, J01GA01), sulbactam (SUL, J01CG01), sulbenicillin (SBC, J01CA16), sulfadiazine (SDI, J01EC02), sulfadiazine/trimethoprim (SLT1, J01EE02), sulfadimethoxine (SUD, J01ED01), sulfadimidine (SDM, J01EB03), sulfadimidine/trimethoprim (SLT2, J01EE05), sulfafurazole (SLF, J01EB05), sulfaisodimidine (SLF1, J01EB01), sulfalene (SLF2, J01ED02), sulfamazone (SZO, J01ED09), sulfamerazine (SLF3, J01ED07), sulfamerazine/trimethoprim (SLT3, J01EE07), sulfamethizole (SLF4, J01EB02), sulfamethoxazole (SMX, J01EC01), sulfamethoxypyridazine (SLF5, J01ED05), sulfametomidine (SLF6, J01ED03), sulfametoxydiazine (SLF7, J01ED04), sulfametrole/trimethoprim (SLT4, J01EE03), sulfamoxole (SLF8, J01EC03), sulfamoxole/trimethoprim (SLT5, J01EE04), sulfanilamide (SLF9, J01EB06), sulfaperin (SLF10, J01ED06), sulfaphenazole (SLF11, J01ED08), sulfapyridine (SLF12, J01EB04), sulfathiazole (SUT, J01EB07), sulfathiourea (SLF13, J01EB08), sultamicillin (SLT6, J01CR04), talampicillin (TAL, J01CA15), tazobactam (TAZ, J01CG02), tebipenem (TBP, J01DH06), tedizolid (TZD, J01XX11), teicoplanin (TEC, J01XA02), telavancin (TLV, J01XA03), telithromycin (TLT, J01FA15), temafloxacin (TMX, J01MA05), temocillin (TEM, J01CA17), tetracycline (TCY, J01AA07), ticarcillin (TIC, J01CA13), ticarcillin/clavulanic acid (TCC, J01CR03), tigecycline (TGC, J01AA12), tilbroquinol (TBQ, P01AA05), tildipirosin (TIP, QJ01FA96), tilmicosin (TIL, QJ01FA91), tobramycin (TOB, J01GB01), tosufloxacin (TFX, J01MA22), trimethoprim (TMP, J01EA01), trimethoprim/sulfamethoxazole (SXT, J01EE01), troleandomycin (TRL, J01FA08), trovafloxacin (TVA, J01MA13), tulathromycin (TUL, QJ01FA94), tylosin (TYL, QJ01FA90), tylvalosin (TYL1, QJ01FA92), vancomycin (VAN, J01XA01)","code":""},{"path":"https://msberends.github.io/AMR/reference/eucast_rules.html","id":"reference-data-publicly-available","dir":"Reference","previous_headings":"","what":"Reference Data Publicly Available","title":"Apply EUCAST Rules — eucast_rules","text":"data sets AMR package (microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) publicly freely available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. also provide tab-separated plain text files machine-readable suitable input software program, laboratory information systems. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":"https://msberends.github.io/AMR/reference/eucast_rules.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Apply EUCAST Rules — eucast_rules","text":"","code":"# \\donttest{ a <- data.frame(   mo = c(     \"Staphylococcus aureus\",     \"Enterococcus faecalis\",     \"Escherichia coli\",     \"Klebsiella pneumoniae\",     \"Pseudomonas aeruginosa\"   ),   VAN = \"-\", # Vancomycin   AMX = \"-\", # Amoxicillin   COL = \"-\", # Colistin   CAZ = \"-\", # Ceftazidime   CXM = \"-\", # Cefuroxime   PEN = \"S\", # Benzylpenicillin   FOX = \"S\", # Cefoxitin   stringsAsFactors = FALSE )  head(a) #>                       mo VAN AMX COL CAZ CXM PEN FOX #> 1  Staphylococcus aureus   -   -   -   -   -   S   S #> 2  Enterococcus faecalis   -   -   -   -   -   S   S #> 3       Escherichia coli   -   -   -   -   -   S   S #> 4  Klebsiella pneumoniae   -   -   -   -   -   S   S #> 5 Pseudomonas aeruginosa   -   -   -   -   -   S   S   # apply EUCAST rules: some results wil be changed b <- eucast_rules(a) #> Warning: in eucast_rules(): not all columns with antimicrobial results are of #> class 'sir'. Transform them on beforehand, with e.g.: #>   - a %>% as.sir(CXM:AMX) #>   - a %>% mutate_if(is_sir_eligible, as.sir) #>   - a %>% mutate(across(where(is_sir_eligible), as.sir))  head(b) #>                       mo VAN AMX COL CAZ CXM PEN FOX #> 1  Staphylococcus aureus   -   S   R   S   S   S   S #> 2  Enterococcus faecalis   -   -   R   R   R   S   R #> 3       Escherichia coli   R   -   -   -   -   R   S #> 4  Klebsiella pneumoniae   R   R   -   -   -   R   S #> 5 Pseudomonas aeruginosa   R   R   -   -   R   R   R   # do not apply EUCAST rules, but rather get a data.frame # containing all details about the transformations: c <- eucast_rules(a, verbose = TRUE) #> Warning: in eucast_rules(): not all columns with antimicrobial results are of #> class 'sir'. Transform them on beforehand, with e.g.: #>   - a %>% as.sir(CXM:AMX) #>   - a %>% mutate_if(is_sir_eligible, as.sir) #>   - a %>% mutate(across(where(is_sir_eligible), as.sir)) head(c) #>   row col           mo_fullname old new rule   rule_group #> 1   1 AMX Staphylococcus aureus   -   S       Breakpoints #> 2   1 CXM Staphylococcus aureus   -   S       Breakpoints #> 3   1 CAZ Staphylococcus aureus   R   S      Expert Rules #> 4   1 CAZ Staphylococcus aureus   -   R      Expert Rules #> 5   1 COL Staphylococcus aureus   -   R      Expert Rules #> 6   2 CAZ Enterococcus faecalis   -   R      Expert Rules #>                                                 rule_name #> 1                                          Staphylococcus #> 2                                          Staphylococcus #> 3                          Expert Rules on Staphylococcus #> 4 Table 4: Intrinsic resistance in gram-positive bacteria #> 5 Table 4: Intrinsic resistance in gram-positive bacteria #> 6 Table 4: Intrinsic resistance in gram-positive bacteria #>                                                                                 rule_source #> 1                                           'EUCAST Clinical Breakpoint Tables' v12.0, 2022 #> 2                                           'EUCAST Clinical Breakpoint Tables' v12.0, 2022 #> 3 'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3, 2021 #> 4 'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3, 2021 #> 5 'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3, 2021 #> 6 'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3, 2021 # }  # Dosage guidelines:  eucast_dosage(c(\"tobra\", \"genta\", \"cipro\"), \"iv\") #> ℹ Dosages for antimicrobial drugs, as meant for 'EUCAST Clinical Breakpoint #>   Tables' v12.0 (2022). This note will be shown once per session. #> # A tibble: 3 × 4 #>   ab   name          standard_dosage  high_dosage  #>   <ab> <chr>         <chr>            <chr>        #> 1 TOB  Tobramycin    6-7 mg/kg x 1 iv NA           #> 2 GEN  Gentamicin    6-7 mg/kg x 1 iv NA           #> 3 CIP  Ciprofloxacin 0.4 g x 2 iv     0.4 g x 3 iv  eucast_dosage(c(\"tobra\", \"genta\", \"cipro\"), \"iv\", version_breakpoints = 10) #> ℹ Dosages for antimicrobial drugs, as meant for 'EUCAST Clinical Breakpoint #>   Tables' v10.0 (2020). This note will be shown once per session. #> # A tibble: 3 × 4 #>   ab   name          standard_dosage  high_dosage  #>   <ab> <chr>         <chr>            <chr>        #> 1 TOB  Tobramycin    6-7 mg/kg x 1 iv NA           #> 2 GEN  Gentamicin    6-7 mg/kg x 1 iv NA           #> 3 CIP  Ciprofloxacin 0.4 g x 2 iv     0.4 g x 3 iv"},{"path":"https://msberends.github.io/AMR/reference/example_isolates.html","id":null,"dir":"Reference","previous_headings":"","what":"Data Set with 2 000 Example Isolates — example_isolates","title":"Data Set with 2 000 Example Isolates — example_isolates","text":"data set containing 2 000 microbial isolates full antibiograms. data set contains randomised fictitious data, reflects reality can used practise AMR data analysis. examples, please read tutorial website.","code":""},{"path":"https://msberends.github.io/AMR/reference/example_isolates.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Data Set with 2 000 Example Isolates — example_isolates","text":"","code":"example_isolates"},{"path":"https://msberends.github.io/AMR/reference/example_isolates.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data Set with 2 000 Example Isolates — example_isolates","text":"tibble 2 000 observations 46 variables: date Date receipt laboratory patient ID patient age Age patient gender Gender patient, either \"F\" \"M\" ward Ward type patient admitted, either \"Clinical\", \"ICU\", \"Outpatient\" mo ID microorganism created .mo(), see also microorganisms data set PEN:RIF 40 different antibiotics class sir (see .sir()); column names occur antibiotics data set can translated set_ab_names() ab_name()","code":""},{"path":"https://msberends.github.io/AMR/reference/example_isolates.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Data Set with 2 000 Example Isolates — example_isolates","text":"Like data sets package, data set publicly available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":"https://msberends.github.io/AMR/reference/example_isolates.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Data Set with 2 000 Example Isolates — example_isolates","text":"","code":"example_isolates #> # A tibble: 2,000 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-03 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  3 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  4 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  5 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  6 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  7 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  8 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  9 2002-01-16 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #> 10 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R     NA    S     NA    #> # ℹ 1,990 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, …"},{"path":"https://msberends.github.io/AMR/reference/example_isolates_unclean.html","id":null,"dir":"Reference","previous_headings":"","what":"Data Set with Unclean Data — example_isolates_unclean","title":"Data Set with Unclean Data — example_isolates_unclean","text":"data set containing 3 000 microbial isolates cleaned consequently ready AMR data analysis. data set can used practice.","code":""},{"path":"https://msberends.github.io/AMR/reference/example_isolates_unclean.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Data Set with Unclean Data — example_isolates_unclean","text":"","code":"example_isolates_unclean"},{"path":"https://msberends.github.io/AMR/reference/example_isolates_unclean.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data Set with Unclean Data — example_isolates_unclean","text":"tibble 3 000 observations 8 variables: patient_id ID patient date date receipt laboratory hospital ID hospital, C bacteria info microorganism can transformed .mo(), see also microorganisms AMX:GEN 4 different antibiotics transformed .sir()","code":""},{"path":"https://msberends.github.io/AMR/reference/example_isolates_unclean.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Data Set with Unclean Data — example_isolates_unclean","text":"Like data sets package, data set publicly available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":"https://msberends.github.io/AMR/reference/example_isolates_unclean.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Data Set with Unclean Data — example_isolates_unclean","text":"","code":"example_isolates_unclean #> # A tibble: 3,000 × 8 #>    patient_id hospital date       bacteria      AMX   AMC   CIP   GEN   #>    <chr>      <chr>    <date>     <chr>         <chr> <chr> <chr> <chr> #>  1 J3         A        2012-11-21 E. coli       R     I     S     S     #>  2 R7         A        2018-04-03 K. pneumoniae R     I     S     S     #>  3 P3         A        2014-09-19 E. coli       R     S     S     S     #>  4 P10        A        2015-12-10 E. coli       S     I     S     S     #>  5 B7         A        2015-03-02 E. coli       S     S     S     S     #>  6 W3         A        2018-03-31 S. aureus     R     S     R     S     #>  7 J8         A        2016-06-14 E. coli       R     S     S     S     #>  8 M3         A        2015-10-25 E. coli       R     S     S     S     #>  9 J3         A        2019-06-19 E. coli       S     S     S     S     #> 10 G6         A        2015-04-27 S. aureus     S     S     S     S     #> # ℹ 2,990 more rows"},{"path":"https://msberends.github.io/AMR/reference/export_ncbi_biosample.html","id":null,"dir":"Reference","previous_headings":"","what":"Export Data Set as NCBI BioSample Antibiogram — export_ncbi_biosample","title":"Export Data Set as NCBI BioSample Antibiogram — export_ncbi_biosample","text":"Export Data Set NCBI BioSample Antibiogram","code":""},{"path":"https://msberends.github.io/AMR/reference/export_ncbi_biosample.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Export Data Set as NCBI BioSample Antibiogram — export_ncbi_biosample","text":"","code":"export_ncbi_biosample(   x,   filename = paste0(\"biosample_\", format(Sys.time(), \"%Y-%m-%d-%H%M%S\"), \".xlsx\"),   type = \"pathogen MIC\",   columns = where(is.mic),   save_as_xlsx = TRUE )"},{"path":"https://msberends.github.io/AMR/reference/export_ncbi_biosample.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Export Data Set as NCBI BioSample Antibiogram — export_ncbi_biosample","text":"x data set filename character string specifying file name type character string specifying type data set, either \"pathogen MIC\" \"beta-lactamase MIC\", see https://www.ncbi.nlm.nih.gov/biosample/docs/","code":""},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":null,"dir":"Reference","previous_headings":"","what":"Determine First Isolates — first_isolate","title":"Determine First Isolates — first_isolate","text":"Determine first isolates microorganisms every patient per episode (needed) per specimen type. functions support four methods summarised Hindler et al. 2007 (doi:10.1086/511864 ). determine patient episodes necessarily based microorganisms, use is_new_episode() also supports grouping dplyr package.","code":""},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Determine First Isolates — first_isolate","text":"","code":"first_isolate(   x = NULL,   col_date = NULL,   col_patient_id = NULL,   col_mo = NULL,   col_testcode = NULL,   col_specimen = NULL,   col_icu = NULL,   col_keyantimicrobials = NULL,   episode_days = 365,   testcodes_exclude = NULL,   icu_exclude = FALSE,   specimen_group = NULL,   type = \"points\",   method = c(\"phenotype-based\", \"episode-based\", \"patient-based\", \"isolate-based\"),   ignore_I = TRUE,   points_threshold = 2,   info = interactive(),   include_unknown = FALSE,   include_untested_sir = TRUE,   ... )  filter_first_isolate(   x = NULL,   col_date = NULL,   col_patient_id = NULL,   col_mo = NULL,   episode_days = 365,   method = c(\"phenotype-based\", \"episode-based\", \"patient-based\", \"isolate-based\"),   ... )"},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Determine First Isolates — first_isolate","text":"Methodology function strictly based : M39 Analysis Presentation Cumulative Antimicrobial Susceptibility Test Data, 5th Edition, 2022, Clinical Laboratory Standards Institute (CLSI). https://clsi.org/standards/products/microbiology/documents/m39/. Hindler JF Stelling J (2007). Analysis Presentation Cumulative Antibiograms: New Consensus Guideline Clinical Laboratory Standards Institute. Clinical Infectious Diseases, 44(6), 867-873. doi:10.1086/511864","code":""},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Determine First Isolates — first_isolate","text":"x data.frame containing isolates. Can left blank automatic determination, see Examples. col_date column name result date (date received lab) - default first column date class col_patient_id column name unique IDs patients - default first column starts 'patient' 'patid' (case insensitive) col_mo column name names codes microorganisms (see .mo()) - default first column class mo. Values coerced using .mo(). col_testcode column name test codes. Use col_testcode = NULL exclude certain test codes (test codes screening). case testcodes_exclude ignored. col_specimen column name specimen type group col_icu column name logicals (TRUE/FALSE) whether ward department Intensive Care Unit (ICU). can also logical vector length rows x. col_keyantimicrobials (useful method = \"phenotype-based\") column name key antimicrobials determine first isolates, see key_antimicrobials(). default first column starts 'key' followed 'ab' 'antibiotics' 'antimicrobials' (case insensitive). Use col_keyantimicrobials = FALSE prevent . Can also output key_antimicrobials(). episode_days episode days genus/species combination determined 'first isolate' . default 365 days based guideline CLSI, see Source. testcodes_exclude character vector test codes excluded (case-insensitive) icu_exclude logical indicate whether ICU isolates excluded (rows value TRUE column set col_icu) specimen_group value column set col_specimen filter type type determine weighed isolates; can \"keyantimicrobials\" \"points\", see Details method method apply, either \"phenotype-based\", \"episode-based\", \"patient-based\" \"isolate-based\" (can abbreviated), see Details. default \"phenotype-based\" antimicrobial test results present data, \"episode-based\" otherwise. ignore_I logical indicate whether antibiotic interpretations \"\" ignored type = \"keyantimicrobials\", see Details points_threshold minimum number points require differences antibiogram lead inclusion isolate type = \"points\", see Details info logical indicate info printed - default TRUE interactive mode include_unknown logical indicate whether 'unknown' microorganisms included , .e. microbial code \"UNKNOWN\", defaults FALSE. WHONET users, means records organism code \"con\" (contamination) excluded default. Isolates microbial ID NA always excluded first isolate. include_untested_sir logical indicate whether also rows without antibiotic results still eligible becoming first isolate. Use include_untested_sir = FALSE always return FALSE rows. checks data set columns class sir consequently requires transforming columns antibiotic results using .sir() first. ... arguments passed first_isolate() using filter_first_isolate(), otherwise arguments passed key_antimicrobials() (universal, gram_negative, gram_positive)","code":""},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Determine First Isolates — first_isolate","text":"logical vector","code":""},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Determine First Isolates — first_isolate","text":"conduct epidemiological analyses antimicrobial resistance data, -called first isolates included prevent overestimation underestimation antimicrobial resistance. Different methods can used , see . functions context-aware. means x argument can left blank used inside data.frame call, see Examples. first_isolate() function wrapper around is_new_episode() function, efficient data sets containing microorganism codes names. isolates microbial ID NA excluded first isolate.","code":""},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":"different-methods","dir":"Reference","previous_headings":"","what":"Different methods","title":"Determine First Isolates — first_isolate","text":"According Hindler et al. (2007, doi:10.1086/511864 ), different methods (algorithms) select first isolates increasing reliability: isolate-based, patient-based, episode-based phenotype-based. methods select combination taxonomic genus species (subspecies). mentioned methods covered first_isolate() function:","code":""},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":"isolate-based","dir":"Reference","previous_headings":"","what":"Isolate-based","title":"Determine First Isolates — first_isolate","text":"method require selection, isolates included. , however, respect arguments set first_isolate() function. example, default setting include_unknown (FALSE) omit selection rows without microbial ID.","code":""},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":"patient-based","dir":"Reference","previous_headings":"","what":"Patient-based","title":"Determine First Isolates — first_isolate","text":"include every genus-species combination per patient , set episode_days Inf. Although often inappropriate, method makes sure duplicate isolates selected patient. large longitudinal data set, mean isolates excluded found years initial isolate.","code":""},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":"episode-based","dir":"Reference","previous_headings":"","what":"Episode-based","title":"Determine First Isolates — first_isolate","text":"include every genus-species combination per patient episode , set episode_days sensible number days. Depending type analysis, 14, 30, 60 365. Short episodes common analysing specific hospital ward data, long episodes common analysing regional national data. common method correct duplicate isolates. Patients categorised episodes based ID dates (e.g., date specimen receipt laboratory result). common method, take account antimicrobial test results. means e.g. methicillin-resistant Staphylococcus aureus (MRSA) isolate differentiated wildtype Staphylococcus aureus isolate.","code":""},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":"phenotype-based","dir":"Reference","previous_headings":"","what":"Phenotype-based","title":"Determine First Isolates — first_isolate","text":"reliable method, since also weighs antibiogram (antimicrobial test results) yielding -called 'first weighted isolates'. two different methods weigh antibiogram: Using type = \"points\" argument points_threshold (default) method weighs antimicrobial drugs available data set. difference S R (vice versa) counts 0.5 points, difference S R (vice versa) counts 1 point. sum points exceeds points_threshold, defaults 2, isolate selected first weighted isolate. antimicrobials internally selected using all_antimicrobials() function. output function need passed first_isolate() function. Using type = \"keyantimicrobials\" argument ignore_I method weighs specific antimicrobial drugs, called key antimicrobials. difference S R (vice versa) key antimicrobials select isolate first weighted isolate. ignore_I = FALSE, also differences S R (vice versa) lead . Key antimicrobials internally selected using key_antimicrobials() function, can also added manually variable data set col_keyantimicrobials argument. Another option pass output key_antimicrobials() function directly col_keyantimicrobials argument. default method phenotype-based (using type = \"points\") episode-based (using episode_days = 365). makes sure every genus-species combination selected per patient per year, taking account antimicrobial test results. antimicrobial test results available data set, episode-based method applied default.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Determine First Isolates — first_isolate","text":"","code":"# `example_isolates` is a data set available in the AMR package. # See ?example_isolates.  example_isolates[first_isolate(info = TRUE), ] #> ℹ Determining first isolates using an episode length of 365 days #> ℹ Using column 'date' as input for col_date. #> ℹ Using column 'patient' as input for col_patient_id. #> ℹ Basing inclusion on all antimicrobial results, using a points threshold #>   of 2 #> ℹ Excluding 16 isolates with a microbial ID 'UNKNOWN' (in column 'mo') #> => Found 1,373 'phenotype-based' first isolates (68.7% of total where a #>    microbial ID was available) #> # A tibble: 1,373 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  3 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  4 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R     NA    S     NA    #>  5 2002-01-17 495616     67 M      Clinical B_STPHY_EPDR R     NA    S     NA    #>  6 2002-01-19 738003     71 M      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  7 2002-01-21 462081     75 F      Clinical B_CTRBC_FRND R     NA    NA    R     #>  8 2002-01-22 F35553     50 M      ICU      B_PROTS_MRBL R     NA    NA    NA    #>  9 2002-02-03 481442     76 M      ICU      B_STPHY_CONS R     NA    S     NA    #> 10 2002-02-05 023456     50 M      Clinical B_STPHY_HMNS S     NA    S     NA    #> # ℹ 1,363 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, … # \\donttest{ # get all first Gram-negatives example_isolates[which(first_isolate(info = FALSE) & mo_is_gram_negative()), ] #> ℹ Using column 'mo' as input for mo_is_gram_negative() #> # A tibble: 434 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-19 738003     71 M      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  3 2002-01-21 462081     75 F      Clinical B_CTRBC_FRND R     NA    NA    R     #>  4 2002-01-22 F35553     50 M      ICU      B_PROTS_MRBL R     NA    NA    NA    #>  5 2002-02-05 067927     45 F      ICU      B_SERRT_MRCS R     NA    NA    R     #>  6 2002-02-27 066895     85 F      Clinical B_KLBSL_PNMN R     NA    NA    R     #>  7 2002-03-08 4FC193     69 M      Clinical B_ESCHR_COLI R     NA    NA    R     #>  8 2002-03-16 4FC193     69 M      Clinical B_PSDMN_AERG R     NA    NA    R     #>  9 2002-04-01 496896     46 F      ICU      B_ESCHR_COLI R     NA    NA    NA    #> 10 2002-04-23 EE2510     69 F      ICU      B_ESCHR_COLI R     NA    NA    NA    #> # ℹ 424 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, …  if (require(\"dplyr\")) {   # filter on first isolates using dplyr:   example_isolates %>%     filter(first_isolate(info = TRUE)) } #> ℹ Determining first isolates using an episode length of 365 days #> ℹ Basing inclusion on all antimicrobial results, using a points threshold #>   of 2 #> ℹ Excluding 16 isolates with a microbial ID 'UNKNOWN' (in column 'mo') #> => Found 1,373 'phenotype-based' first isolates (68.7% of total where a #>    microbial ID was available) #> # A tibble: 1,373 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  3 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  4 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R     NA    S     NA    #>  5 2002-01-17 495616     67 M      Clinical B_STPHY_EPDR R     NA    S     NA    #>  6 2002-01-19 738003     71 M      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  7 2002-01-21 462081     75 F      Clinical B_CTRBC_FRND R     NA    NA    R     #>  8 2002-01-22 F35553     50 M      ICU      B_PROTS_MRBL R     NA    NA    NA    #>  9 2002-02-03 481442     76 M      ICU      B_STPHY_CONS R     NA    S     NA    #> 10 2002-02-05 023456     50 M      Clinical B_STPHY_HMNS S     NA    S     NA    #> # ℹ 1,363 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, … if (require(\"dplyr\")) {   # short-hand version:   example_isolates %>%     filter_first_isolate(info = FALSE) } #> # A tibble: 1,373 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  3 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  4 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R     NA    S     NA    #>  5 2002-01-17 495616     67 M      Clinical B_STPHY_EPDR R     NA    S     NA    #>  6 2002-01-19 738003     71 M      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  7 2002-01-21 462081     75 F      Clinical B_CTRBC_FRND R     NA    NA    R     #>  8 2002-01-22 F35553     50 M      ICU      B_PROTS_MRBL R     NA    NA    NA    #>  9 2002-02-03 481442     76 M      ICU      B_STPHY_CONS R     NA    S     NA    #> 10 2002-02-05 023456     50 M      Clinical B_STPHY_HMNS S     NA    S     NA    #> # ℹ 1,363 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, … if (require(\"dplyr\")) {   # flag the first isolates per group:   example_isolates %>%     group_by(ward) %>%     mutate(first = first_isolate(info = TRUE)) %>%     select(ward, date, patient, mo, first) } #> ℹ Determining first isolates using an episode length of 365 days #> ℹ Basing inclusion on all antimicrobial results, using a points threshold #>   of 2 #>  #> Group: ward = \"Clinical\" #> ℹ Excluding 9 isolates with a microbial ID 'UNKNOWN' (in column 'mo') #> => Found 857 'phenotype-based' first isolates (69.4% of total where a #>    microbial ID was available) #>  #> Group: ward = \"ICU\" #> ℹ Excluding 6 isolates with a microbial ID 'UNKNOWN' (in column 'mo') #> => Found 447 'phenotype-based' first isolates (69.2% of total where a #>    microbial ID was available) #>  #> Group: ward = \"Outpatient\" #> ℹ Excluding 1 isolates with a microbial ID 'UNKNOWN' (in column 'mo') #> => Found 98 'phenotype-based' first isolates (81.7% of total where a #>    microbial ID was available) #> # A tibble: 2,000 × 5 #> # Groups:   ward [3] #>    ward     date       patient mo           first #>    <chr>    <date>     <chr>   <mo>         <lgl> #>  1 Clinical 2002-01-02 A77334  B_ESCHR_COLI TRUE  #>  2 Clinical 2002-01-03 A77334  B_ESCHR_COLI FALSE #>  3 ICU      2002-01-07 067927  B_STPHY_EPDR TRUE  #>  4 ICU      2002-01-07 067927  B_STPHY_EPDR FALSE #>  5 ICU      2002-01-13 067927  B_STPHY_EPDR FALSE #>  6 ICU      2002-01-13 067927  B_STPHY_EPDR FALSE #>  7 Clinical 2002-01-14 462729  B_STPHY_AURS TRUE  #>  8 Clinical 2002-01-14 462729  B_STPHY_AURS FALSE #>  9 ICU      2002-01-16 067927  B_STPHY_EPDR FALSE #> 10 ICU      2002-01-17 858515  B_STPHY_EPDR TRUE  #> # ℹ 1,990 more rows # }"},{"path":"https://msberends.github.io/AMR/reference/g.test.html","id":null,"dir":"Reference","previous_headings":"","what":"G-test for Count Data — g.test","title":"G-test for Count Data — g.test","text":"g.test() performs chi-squared contingency table tests goodness--fit tests, just like chisq.test() reliable (1). G-test can used see whether number observations category fits theoretical expectation (called G-test goodness--fit), see whether proportions one variable different different values variable (called G-test independence).","code":""},{"path":"https://msberends.github.io/AMR/reference/g.test.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"G-test for Count Data — g.test","text":"","code":"g.test(x, y = NULL, p = rep(1/length(x), length(x)), rescale.p = FALSE)"},{"path":"https://msberends.github.io/AMR/reference/g.test.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"G-test for Count Data — g.test","text":"code function identical chisq.test(), except : calculation statistic changed \\(2 * sum(x * log(x / E))\\) Yates' continuity correction removed apply G-test possibility simulate p values simulate.p.value removed","code":""},{"path":"https://msberends.github.io/AMR/reference/g.test.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"G-test for Count Data — g.test","text":"x numeric vector matrix. x y can also     factors. y numeric vector; ignored x matrix.      x factor, y factor length. p vector probabilities length x.     error given entry p negative. rescale.p logical scalar; TRUE p rescaled     (necessary) sum 1.  rescale.p FALSE,     p sum 1, error given.","code":""},{"path":"https://msberends.github.io/AMR/reference/g.test.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"G-test for Count Data — g.test","text":"list class \"htest\" containing following   components: statistic value chi-squared test statistic. parameter degrees freedom approximate     chi-squared distribution test statistic, NA     p-value computed Monte Carlo simulation. p.value p-value test. method character string indicating type test     performed, whether Monte Carlo simulation continuity     correction used. data.name character string giving name(s) data. observed observed counts. expected expected counts null hypothesis. residuals Pearson residuals,     (observed - expected) / sqrt(expected). stdres standardized residuals,     (observed - expected) / sqrt(V), V     residual cell variance (Agresti, 2007, section 2.4.5     case x matrix, n * p * (1 - p) otherwise).","code":""},{"path":"https://msberends.github.io/AMR/reference/g.test.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"G-test for Count Data — g.test","text":"x matrix one row column, x vector y given, goodness--fit test performed (x treated one-dimensional contingency table). entries x must non-negative integers. case, hypothesis tested whether population probabilities equal p, equal p given. x matrix least two rows columns, taken two-dimensional contingency table: entries x must non-negative integers.  Otherwise, x y must vectors factors length; cases missing values removed, objects coerced factors, contingency table computed .  Pearson's chi-squared test performed null hypothesis joint distribution cell counts 2-dimensional contingency table product row column marginals. p-value computed asymptotic chi-squared distribution test statistic. contingency table case simulation done random sampling set contingency tables given marginals, works marginals strictly positive. Note usual sampling situation assumed chi-squared test (G-test) rather Fisher's exact test. goodness--fit case simulation done random sampling discrete distribution specified p, sample size n = sum(x). simulation done R may slow.","code":""},{"path":"https://msberends.github.io/AMR/reference/g.test.html","id":"g-test-of-goodness-of-fit-likelihood-ratio-test-","dir":"Reference","previous_headings":"","what":"G-test Of Goodness-of-Fit (Likelihood Ratio Test)","title":"G-test for Count Data — g.test","text":"Use G-test goodness--fit one nominal variable two values (male female, red, pink white flowers). compare observed counts numbers observations category expected counts, calculate using kind theoretical expectation (1:1 sex ratio 1:2:1 ratio genetic cross). expected number observations category small, G-test may give inaccurate results, use exact test instead (fisher.test()). G-test goodness--fit alternative chi-square test goodness--fit (chisq.test()); tests advantages disadvantages, results two tests usually similar.","code":""},{"path":"https://msberends.github.io/AMR/reference/g.test.html","id":"g-test-of-independence","dir":"Reference","previous_headings":"","what":"G-test of Independence","title":"G-test for Count Data — g.test","text":"Use G-test independence two nominal variables, two possible values. want know whether proportions one variable different among values variable. also possible G-test independence two nominal variables. example, Jackson et al. (2013) also data children 3, analysis old vs. young, thigh vs. arm, reaction vs. reaction, analyzed together. Fisher's exact test (fisher.test()) exact test, G-test still approximation. 2x2 table, Fisher's Exact test may slower still run seconds, even sum observations multiple millions. G-test independence alternative chi-square test independence (chisq.test()), give approximately results.","code":""},{"path":"https://msberends.github.io/AMR/reference/g.test.html","id":"how-the-test-works","dir":"Reference","previous_headings":"","what":"How the Test Works","title":"G-test for Count Data — g.test","text":"Unlike exact test goodness--fit (fisher.test()), G-test directly calculate probability obtaining observed results something extreme. Instead, like almost statistical tests, G-test intermediate step; uses data calculate test statistic measures far observed data null expectation. use mathematical relationship, case chi-square distribution, estimate probability obtaining value test statistic. G-test uses log ratio two likelihoods test statistic, also called likelihood ratio test log-likelihood ratio test. formula calculate G-statistic : \\(G = 2 * sum(x * log(x / E))\\) E expected values. Since chi-square distributed, p value can calculated R :   df degrees freedom. two categories want find ones significantly different null expectation, can use method testing category vs. sum categories, Bonferroni correction. use G-tests category, course.","code":"p <- stats::pchisq(G, df, lower.tail = FALSE)"},{"path":"https://msberends.github.io/AMR/reference/g.test.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"G-test for Count Data — g.test","text":"McDonald, J.H. 2014. Handbook Biological Statistics (3rd ed.). Sparky House Publishing, Baltimore, Maryland. http://www.biostathandbook.com/gtestgof.html.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/g.test.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"G-test for Count Data — g.test","text":"","code":"# = EXAMPLE 1 = # Shivrain et al. (2006) crossed clearfield rice (which are resistant # to the herbicide imazethapyr) with red rice (which are susceptible to # imazethapyr). They then crossed the hybrid offspring and examined the # F2 generation, where they found 772 resistant plants, 1611 moderately # resistant plants, and 737 susceptible plants. If resistance is controlled # by a single gene with two co-dominant alleles, you would expect a 1:2:1 # ratio.  x <- c(772, 1611, 737) g.test(x, p = c(1, 2, 1) / 4) #>  #> \tG-test of goodness-of-fit (likelihood ratio test) #>  #> data:  x #> X-squared = 4.1471, p-value = 0.1257 #>   # There is no significant difference from a 1:2:1 ratio. # Meaning: resistance controlled by a single gene with two co-dominant # alleles, is plausible.   # = EXAMPLE 2 = # Red crossbills (Loxia curvirostra) have the tip of the upper bill either # right or left of the lower bill, which helps them extract seeds from pine # cones. Some have hypothesized that frequency-dependent selection would # keep the number of right and left-billed birds at a 1:1 ratio. Groth (1992) # observed 1752 right-billed and 1895 left-billed crossbills.  x <- c(1752, 1895) g.test(x) #>  #> \tG-test of goodness-of-fit (likelihood ratio test) #>  #> data:  x #> X-squared = 5.6085, p-value = 0.01787 #>   # There is a significant difference from a 1:1 ratio. # Meaning: there are significantly more left-billed birds."},{"path":"https://msberends.github.io/AMR/reference/get_episode.html","id":null,"dir":"Reference","previous_headings":"","what":"Determine Clinical or Epidemic Episodes — get_episode","title":"Determine Clinical or Epidemic Episodes — get_episode","text":"functions determine items vector can considered (start ) new episode. can used determine clinical episodes epidemiological analysis. get_episode() function returns index number episode per group, is_new_episode() function returns TRUE every new get_episode() index. absolute relative episode determination supported.","code":""},{"path":"https://msberends.github.io/AMR/reference/get_episode.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Determine Clinical or Epidemic Episodes — get_episode","text":"","code":"get_episode(x, episode_days = NULL, case_free_days = NULL, ...)  is_new_episode(x, episode_days = NULL, case_free_days = NULL, ...)"},{"path":"https://msberends.github.io/AMR/reference/get_episode.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Determine Clinical or Epidemic Episodes — get_episode","text":"x vector dates (class Date POSIXt), sorted internally determine episodes episode_days episode length days specify time period new episode begins, can also less day Inf, see Details case_free_days (inter-epidemic) interval length days new episode start, can also less day Inf, see Details ... ignored, place allow future extensions","code":""},{"path":"https://msberends.github.io/AMR/reference/get_episode.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Determine Clinical or Epidemic Episodes — get_episode","text":"get_episode(): integer vector is_new_episode(): logical vector","code":""},{"path":"https://msberends.github.io/AMR/reference/get_episode.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Determine Clinical or Epidemic Episodes — get_episode","text":"Episodes can determined two ways: absolute relative. Absolute method uses episode_days define episode length days, new episode start. common use case AMR data analysis microbial epidemiology: episodes S. aureus bacteraemia ICU patients example. episode length 30 days, new S. aureus isolates ICU episode 30 days considered different (new) episode. Thus, method counts since start previous episode. Relative method uses case_free_days quantify duration case-free days (inter-epidemic interval), new episode start. common use case infectious disease epidemiology: episodes norovirus outbreaks hospital example. case-free period 14 days, new norovirus cases time considered different (new) episode. Thus, methods counts since last case previous episode. table: ** marks start new episode, 8 January 2023 7 days since start previous episode (1 January 2023).  *** marks start new episode, 21 January 2023 7 days since last case previous episode (8 January 2023). Either episode_days case_free_days must provided function.","code":""},{"path":"https://msberends.github.io/AMR/reference/get_episode.html","id":"difference-between-get-episode-and-is-new-episode-","dir":"Reference","previous_headings":"","what":"Difference between get_episode() and is_new_episode()","title":"Determine Clinical or Epidemic Episodes — get_episode","text":"get_episode() function returns index number episode, cases/patients/isolates first episode number 1, cases/patients/isolates second episode number 2, etc. is_new_episode() function hand, returns TRUE every new get_episode() index. specify, setting episode_days = 365 (using method 1 explained ), two functions differ:","code":""},{"path":"https://msberends.github.io/AMR/reference/get_episode.html","id":"other","dir":"Reference","previous_headings":"","what":"Other","title":"Determine Clinical or Epidemic Episodes — get_episode","text":"first_isolate() function wrapper around is_new_episode() function, efficient data sets containing microorganism codes names allows different isolate selection methods. dplyr package required functions work, episode functions support variable grouping work conveniently inside dplyr verbs filter(), mutate() summarise().","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/get_episode.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Determine Clinical or Epidemic Episodes — get_episode","text":"","code":"# difference between absolute and relative determination of episodes: x <- data.frame(dates = as.Date(c(   \"2021-01-01\",   \"2021-01-02\",   \"2021-01-05\",   \"2021-01-08\",   \"2021-02-21\",   \"2021-02-22\",   \"2021-02-23\",   \"2021-02-24\",   \"2021-03-01\",   \"2021-03-01\" ))) x$absolute <- get_episode(x$dates, episode_days = 7) x$relative <- get_episode(x$dates, case_free_days = 7) x #>         dates absolute relative #> 1  2021-01-01        1        1 #> 2  2021-01-02        1        1 #> 3  2021-01-05        1        1 #> 4  2021-01-08        2        1 #> 5  2021-02-21        3        2 #> 6  2021-02-22        3        2 #> 7  2021-02-23        3        2 #> 8  2021-02-24        3        2 #> 9  2021-03-01        4        2 #> 10 2021-03-01        4        2   # `example_isolates` is a data set available in the AMR package. # See ?example_isolates df <- example_isolates[sample(seq_len(2000), size = 100), ]  get_episode(df$date, episode_days = 60) # indices #>   [1] 39 42 29 45 31 14 41 39 26 40 18 36 15 39 18 45 32 27 10  2 13 24 43 12  8 #>  [26]  5  3 12 31  9 16  4  1 26 32 27 21 45 42 17 16 21  8  4 30  1 17 25 34  5 #>  [51] 10  1 18 44 33  4  6 12 43  2 43 45 37 33 18 38 45 36 46  4 35 40 12  7 11 #>  [76] 23 10 35 20  4  5 29 27 41 12 30 45 18 47 22 28 39 19 27 16  4 21 40 33 39 is_new_episode(df$date, episode_days = 60) # TRUE/FALSE #>   [1]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE #>  [13]  TRUE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE #>  [25]  TRUE  TRUE  TRUE FALSE FALSE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE #>  [37]  TRUE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE  TRUE #>  [49]  TRUE FALSE FALSE FALSE FALSE  TRUE  TRUE FALSE  TRUE FALSE FALSE FALSE #>  [61] FALSE FALSE  TRUE FALSE FALSE  TRUE FALSE FALSE  TRUE FALSE  TRUE FALSE #>  [73] FALSE  TRUE  TRUE  TRUE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE #>  [85] FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE FALSE  TRUE FALSE FALSE FALSE #>  [97] FALSE FALSE FALSE FALSE  # filter on results from the third 60-day episode only, using base R df[which(get_episode(df$date, 60) == 3), ] #> # A tibble: 1 × 46 #>   date       patient   age gender ward  mo           PEN   OXA   FLC   AMX   #>   <date>     <chr>   <dbl> <chr>  <chr> <mo>         <sir> <sir> <sir> <sir> #> 1 2002-12-13 285137     78 F      ICU   B_ESCHR_COLI R     NA    NA    NA    #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, RIF <sir>  # the functions also work for less than a day, e.g. to include one per hour: get_episode(   c(     Sys.time(),     Sys.time() + 60 * 60   ),   episode_days = 1 / 24 ) #> [1] 1 2  # \\donttest{ if (require(\"dplyr\")) {   # is_new_episode() can also be used in dplyr verbs to determine patient   # episodes based on any (combination of) grouping variables:   df %>%     mutate(condition = sample(       x = c(\"A\", \"B\", \"C\"),       size = 100,       replace = TRUE     )) %>%     group_by(patient, condition) %>%     mutate(new_episode = is_new_episode(date, 365)) %>%     select(patient, date, condition, new_episode) %>%     arrange(patient, condition, date) } #> # A tibble: 100 × 4 #> # Groups:   patient, condition [97] #>    patient date       condition new_episode #>    <chr>   <date>     <chr>     <lgl>       #>  1 036063  2010-01-28 A         TRUE        #>  2 077922  2009-08-18 C         TRUE        #>  3 080086  2010-08-08 C         TRUE        #>  4 0DBF93  2015-10-12 B         TRUE        #>  5 105248  2005-06-16 A         TRUE        #>  6 114570  2003-04-08 B         TRUE        #>  7 119392  2010-11-01 C         TRUE        #>  8 161740  2005-06-21 A         TRUE        #>  9 174209  2011-10-03 C         TRUE        #> 10 210105  2009-06-13 C         TRUE        #> # ℹ 90 more rows  if (require(\"dplyr\")) {   df %>%     group_by(ward, patient) %>%     transmute(date,       patient,       new_index = get_episode(date, 60),       new_logical = is_new_episode(date, 60)     ) %>%     arrange(patient, ward, date) } #> # A tibble: 100 × 5 #> # Groups:   ward, patient [96] #>    ward       date       patient new_index new_logical #>    <chr>      <date>     <chr>       <int> <lgl>       #>  1 Clinical   2010-01-28 036063          1 TRUE        #>  2 Clinical   2009-08-18 077922          1 TRUE        #>  3 Clinical   2010-08-08 080086          1 TRUE        #>  4 Clinical   2015-10-12 0DBF93          1 TRUE        #>  5 Clinical   2005-06-16 105248          1 TRUE        #>  6 ICU        2003-04-08 114570          1 TRUE        #>  7 Clinical   2010-11-01 119392          1 TRUE        #>  8 Clinical   2005-06-21 161740          1 TRUE        #>  9 Outpatient 2011-10-03 174209          1 TRUE        #> 10 Clinical   2009-06-13 210105          1 TRUE        #> # ℹ 90 more rows  if (require(\"dplyr\")) {   df %>%     group_by(ward) %>%     summarise(       n_patients = n_distinct(patient),       n_episodes_365 = sum(is_new_episode(date, episode_days = 365)),       n_episodes_60 = sum(is_new_episode(date, episode_days = 60)),       n_episodes_30 = sum(is_new_episode(date, episode_days = 30))     ) } #> # A tibble: 3 × 5 #>   ward       n_patients n_episodes_365 n_episodes_60 n_episodes_30 #>   <chr>           <int>          <int>         <int>         <int> #> 1 Clinical           64             13            37            47 #> 2 ICU                23              9            17            20 #> 3 Outpatient          9              7             7             9  # grouping on patients and microorganisms leads to the same # results as first_isolate() when using 'episode-based': if (require(\"dplyr\")) {   x <- df %>%     filter_first_isolate(       include_unknown = TRUE,       method = \"episode-based\"     )    y <- df %>%     group_by(patient, mo) %>%     filter(is_new_episode(date, 365)) %>%     ungroup()    identical(x, y) } #> [1] TRUE  # but is_new_episode() has a lot more flexibility than first_isolate(), # since you can now group on anything that seems relevant: if (require(\"dplyr\")) {   df %>%     group_by(patient, mo, ward) %>%     mutate(flag_episode = is_new_episode(date, 365)) %>%     select(group_vars(.), flag_episode) } #> # A tibble: 100 × 4 #> # Groups:   patient, mo, ward [96] #>    patient mo           ward     flag_episode #>    <chr>   <mo>         <chr>    <lgl>        #>  1 A76045  B_ENTRC_FACM ICU      TRUE         #>  2 964129  B_SERRT_MRCS Clinical TRUE         #>  3 686445  B_STPHY_CONS Clinical TRUE         #>  4 D39422  B_KLBSL_PNMN Clinical TRUE         #>  5 298662  B_ESCHR_COLI Clinical TRUE         #>  6 5B78D5  B_STPHY_AURS Clinical TRUE         #>  7 E52625  B_STRPT_PNMN Clinical TRUE         #>  8 645121  B_SERRT_MRCS Clinical TRUE         #>  9 807228  B_STRPT_PNMN Clinical TRUE         #> 10 D41749  B_ESCHR_COLI ICU      TRUE         #> # ℹ 90 more rows # }"},{"path":"https://msberends.github.io/AMR/reference/ggplot_pca.html","id":null,"dir":"Reference","previous_headings":"","what":"PCA Biplot with ggplot2 — ggplot_pca","title":"PCA Biplot with ggplot2 — ggplot_pca","text":"Produces ggplot2 variant -called biplot PCA (principal component analysis), flexible appealing base R biplot() function.","code":""},{"path":"https://msberends.github.io/AMR/reference/ggplot_pca.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"PCA Biplot with ggplot2 — ggplot_pca","text":"","code":"ggplot_pca(   x,   choices = 1:2,   scale = 1,   pc.biplot = TRUE,   labels = NULL,   labels_textsize = 3,   labels_text_placement = 1.5,   groups = NULL,   ellipse = TRUE,   ellipse_prob = 0.68,   ellipse_size = 0.5,   ellipse_alpha = 0.5,   points_size = 2,   points_alpha = 0.25,   arrows = TRUE,   arrows_colour = \"darkblue\",   arrows_size = 0.5,   arrows_textsize = 3,   arrows_textangled = TRUE,   arrows_alpha = 0.75,   base_textsize = 10,   ... )"},{"path":"https://msberends.github.io/AMR/reference/ggplot_pca.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"PCA Biplot with ggplot2 — ggplot_pca","text":"ggplot_pca() function based ggbiplot() function ggbiplot package Vince Vu, found GitHub: https://github.com/vqv/ggbiplot (retrieved: 2 March 2020, latest commit: 7325e88; 12 February 2015). per GPL-2 licence demands documentation code changes, changes made based source code : Rewritten code remove dependency packages plyr, scales grid Parametrised options, like arrow ellipse settings Hardened input possibilities defining exact type user input every argument Added total amount explained variance caption plot Cleaned syntax based lintr package, fixed grammatical errors added integrity checks Updated documentation","code":""},{"path":"https://msberends.github.io/AMR/reference/ggplot_pca.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"PCA Biplot with ggplot2 — ggplot_pca","text":"x object returned pca(), prcomp() princomp() choices length 2 vector specifying components plot. default     biplot strict sense. scale variables scaled lambda ^ scale     observations scaled lambda ^ (1-scale)     lambda singular values computed     princomp. Normally 0 <= scale <= 1, warning     issued specified scale outside range. pc.biplot true, use Gabriel (1971) refers \"principal component     biplot\", lambda = 1 observations scaled sqrt(n)     variables scaled sqrt(n).  inner products     variables approximate covariances distances observations     approximate Mahalanobis distance. labels optional vector labels observations. set, labels placed respective points. using pca() function input x, determined automatically based attribute non_numeric_cols, see pca(). labels_textsize size text used labels labels_text_placement adjustment factor placement variable names (>=1 means away arrow head) groups optional vector groups labels, length labels. set, points labels coloured according groups. using pca() function input x, determined automatically based attribute non_numeric_cols, see pca(). ellipse logical indicate whether normal data ellipse drawn group (set groups) ellipse_prob statistical size ellipse normal probability ellipse_size size ellipse line ellipse_alpha alpha (transparency) ellipse line points_size size points points_alpha alpha (transparency) points arrows logical indicate whether arrows drawn arrows_colour colour arrow text arrows_size size (thickness) arrow lines arrows_textsize size text end arrows arrows_textangled logical whether text end arrows angled arrows_alpha alpha (transparency) arrows text base_textsize text size plot elements except labels arrows ... arguments passed functions","code":""},{"path":"https://msberends.github.io/AMR/reference/ggplot_pca.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"PCA Biplot with ggplot2 — ggplot_pca","text":"colours labels points can changed adding another scale layer colour, scale_colour_viridis_d() scale_colour_brewer().","code":""},{"path":"https://msberends.github.io/AMR/reference/ggplot_pca.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"PCA Biplot with ggplot2 — ggplot_pca","text":"","code":"# `example_isolates` is a data set available in the AMR package. # See ?example_isolates.  # \\donttest{ if (require(\"dplyr\")) {   # calculate the resistance per group first   resistance_data <- example_isolates %>%     group_by(       order = mo_order(mo), # group on anything, like order       genus = mo_genus(mo)     ) %>% #   and genus as we do here;     filter(n() >= 30) %>% # filter on only 30 results per group     summarise_if(is.sir, resistance) # then get resistance of all drugs    # now conduct PCA for certain antimicrobial drugs   pca_result <- resistance_data %>%     pca(AMC, CXM, CTX, CAZ, GEN, TOB, TMP, SXT)    summary(pca_result)    # old base R plotting method:   biplot(pca_result, main = \"Base R biplot\")    # new ggplot2 plotting method using this package:   if (require(\"ggplot2\")) {     ggplot_pca(pca_result) +       labs(title = \"ggplot2 biplot\")   }   if (require(\"ggplot2\")) {     # still extendible with any ggplot2 function     ggplot_pca(pca_result) +       scale_colour_viridis_d() +       labs(title = \"ggplot2 biplot\")   } } #> Warning: There were 73 warnings in `summarise()`. #> The first warning was: #> ℹ In argument: `PEN = (function (..., minimum = 30, as_percent = FALSE, #>   only_all_tested = FALSE) ...`. #> ℹ In group 5: `order = \"Lactobacillales\"` and `genus = \"Enterococcus\"`. #> Caused by warning: #> ! Introducing NA: only 14 results available for PEN in group: order = #> \"Lactobacillales\", genus = \"Enterococcus\" (minimum = 30). #> ℹ Run `dplyr::last_dplyr_warnings()` to see the 72 remaining warnings. #> ℹ Columns selected for PCA: \"AMC\", \"CAZ\", \"CTX\", \"CXM\", \"GEN\", \"SXT\", #>   \"TMP\", and \"TOB\". Total observations available: 7. #> Groups (n=4, named as 'order'): #> [1] \"Caryophanales\"    \"Enterobacterales\" \"Lactobacillales\"  \"Pseudomonadales\"  #>    # }"},{"path":"https://msberends.github.io/AMR/reference/ggplot_sir.html","id":null,"dir":"Reference","previous_headings":"","what":"AMR Plots with ggplot2 — ggplot_sir","title":"AMR Plots with ggplot2 — ggplot_sir","text":"Use functions create bar plots AMR data analysis. functions rely ggplot2 functions.","code":""},{"path":"https://msberends.github.io/AMR/reference/ggplot_sir.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"AMR Plots with ggplot2 — ggplot_sir","text":"","code":"ggplot_sir(   data,   position = NULL,   x = \"antibiotic\",   fill = \"interpretation\",   facet = NULL,   breaks = seq(0, 1, 0.1),   limits = NULL,   translate_ab = \"name\",   combine_SI = TRUE,   minimum = 30,   language = get_AMR_locale(),   nrow = NULL,   colours = c(S = \"#3CAEA3\", SI = \"#3CAEA3\", I = \"#F6D55C\", IR = \"#ED553B\", R =     \"#ED553B\"),   datalabels = TRUE,   datalabels.size = 2.5,   datalabels.colour = \"grey15\",   title = NULL,   subtitle = NULL,   caption = NULL,   x.title = \"Antimicrobial\",   y.title = \"Proportion\",   ... )  geom_sir(   position = NULL,   x = c(\"antibiotic\", \"interpretation\"),   fill = \"interpretation\",   translate_ab = \"name\",   minimum = 30,   language = get_AMR_locale(),   combine_SI = TRUE,   ... )  facet_sir(facet = c(\"interpretation\", \"antibiotic\"), nrow = NULL)  scale_y_percent(breaks = seq(0, 1, 0.1), limits = NULL)  scale_sir_colours(..., aesthetics = \"fill\")  theme_sir()  labels_sir_count(   position = NULL,   x = \"antibiotic\",   translate_ab = \"name\",   minimum = 30,   language = get_AMR_locale(),   combine_SI = TRUE,   datalabels.size = 3,   datalabels.colour = \"grey15\" )"},{"path":"https://msberends.github.io/AMR/reference/ggplot_sir.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"AMR Plots with ggplot2 — ggplot_sir","text":"data data.frame column(s) class sir (see .sir()) position position adjustment bars, either \"fill\", \"stack\" \"dodge\" x variable show x axis, either \"antibiotic\" (default) \"interpretation\" grouping variable fill variable categorise using plots legend, either \"antibiotic\" (default) \"interpretation\" grouping variable facet variable split plots , either \"interpretation\" (default) \"antibiotic\" grouping variable breaks numeric vector positions limits numeric vector length two providing limits scale, use NA refer existing minimum maximum translate_ab column name antibiotics data set translate antibiotic abbreviations , using ab_property() combine_SI logical indicate whether values S must merged one, output consists S+vs. R (susceptible vs. resistant) - default TRUE minimum minimum allowed number available (tested) isolates. isolate count lower minimum return NA warning. default number 30 isolates advised Clinical Laboratory Standards Institute (CLSI) best practice, see Source. language language returned text - default current system language (see get_AMR_locale()) can also set package option AMR_locale. Use language = NULL language = \"\" prevent translation. nrow (using facet) number rows colours named vactor colour used filling. default colours colour-blind friendly. datalabels show datalabels using labels_sir_count() datalabels.size size datalabels datalabels.colour colour datalabels title text show title plot subtitle text show subtitle plot caption text show caption plot x.title text show x axis description y.title text show y axis description ... arguments passed geom_sir() , case scale_sir_colours(), named values set colours. default colours colour-blind friendly, maintaining convention e.g. 'susceptible' green 'resistant' red. See Examples. aesthetics aesthetics apply colours - default \"fill\" can also (combination ) \"alpha\", \"colour\", \"fill\", \"linetype\", \"shape\" \"size\"","code":""},{"path":"https://msberends.github.io/AMR/reference/ggplot_sir.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"AMR Plots with ggplot2 — ggplot_sir","text":"default, names antibiotics shown plots using ab_name(). can set translate_ab argument. See count_df().","code":""},{"path":"https://msberends.github.io/AMR/reference/ggplot_sir.html","id":"the-functions","dir":"Reference","previous_headings":"","what":"The Functions","title":"AMR Plots with ggplot2 — ggplot_sir","text":"geom_sir() take variable data sir class (created .sir()) using sir_df() plot bars percentage S, , R. default behaviour bars stacked different antibiotics x axis. facet_sir() creates 2d plots (default based S//R) using ggplot2::facet_wrap(). scale_y_percent() transforms y axis 0 100% range using ggplot2::scale_y_continuous(). scale_sir_colours() sets colours bars (green S, yellow , red R). multilingual support. default colours colour-blind friendly, maintaining convention e.g. 'susceptible' green 'resistant' red. theme_sir() [ggplot2 theme][ggplot2::theme() minimal distraction. labels_sir_count() print datalabels bars percentage amount isolates using ggplot2::geom_text(). ggplot_sir() wrapper around functions uses data first input. makes possible use function pipe (%>%). See Examples.","code":""},{"path":"https://msberends.github.io/AMR/reference/ggplot_sir.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"AMR Plots with ggplot2 — ggplot_sir","text":"","code":"# \\donttest{ if (require(\"ggplot2\") && require(\"dplyr\")) {   # get antimicrobial results for drugs against a UTI:   ggplot(example_isolates %>% select(AMX, NIT, FOS, TMP, CIP)) +     geom_sir() }  if (require(\"ggplot2\") && require(\"dplyr\")) {   # prettify the plot using some additional functions:   df <- example_isolates %>% select(AMX, NIT, FOS, TMP, CIP)   ggplot(df) +     geom_sir() +     scale_y_percent() +     scale_sir_colours() +     labels_sir_count() +     theme_sir() }  if (require(\"ggplot2\") && require(\"dplyr\")) {   # or better yet, simplify this using the wrapper function - a single command:   example_isolates %>%     select(AMX, NIT, FOS, TMP, CIP) %>%     ggplot_sir() }  if (require(\"ggplot2\") && require(\"dplyr\")) {   # get only proportions and no counts:   example_isolates %>%     select(AMX, NIT, FOS, TMP, CIP) %>%     ggplot_sir(datalabels = FALSE) }  if (require(\"ggplot2\") && require(\"dplyr\")) {   # add other ggplot2 arguments as you like:   example_isolates %>%     select(AMX, NIT, FOS, TMP, CIP) %>%     ggplot_sir(       width = 0.5,       colour = \"black\",       size = 1,       linetype = 2,       alpha = 0.25     ) }  if (require(\"ggplot2\") && require(\"dplyr\")) {   # you can alter the colours with colour names:   example_isolates %>%     select(AMX) %>%     ggplot_sir(colours = c(SI = \"yellow\")) }  if (require(\"ggplot2\") && require(\"dplyr\")) {   # but you can also use the built-in colour-blind friendly colours for   # your plots, where \"S\" is green, \"I\" is yellow and \"R\" is red:   data.frame(     x = c(\"Value1\", \"Value2\", \"Value3\"),     y = c(1, 2, 3),     z = c(\"Value4\", \"Value5\", \"Value6\")   ) %>%     ggplot() +     geom_col(aes(x = x, y = y, fill = z)) +     scale_sir_colours(Value4 = \"S\", Value5 = \"I\", Value6 = \"R\") }  if (require(\"ggplot2\") && require(\"dplyr\")) {   # resistance of ciprofloxacine per age group   example_isolates %>%     mutate(first_isolate = first_isolate()) %>%     filter(       first_isolate == TRUE,       mo == as.mo(\"Escherichia coli\")     ) %>%     # age_groups() is also a function in this AMR package:     group_by(age_group = age_groups(age)) %>%     select(age_group, CIP) %>%     ggplot_sir(x = \"age_group\") } #> Warning: Removed 6 rows containing missing values or values outside the scale range #> (`geom_col()`). #> Warning: Removed 6 rows containing missing values or values outside the scale range #> (`geom_text()`).  if (require(\"ggplot2\") && require(\"dplyr\")) {   # a shorter version which also adjusts data label colours:   example_isolates %>%     select(AMX, NIT, FOS, TMP, CIP) %>%     ggplot_sir(colours = FALSE) }  if (require(\"ggplot2\") && require(\"dplyr\")) {   # it also supports groups (don't forget to use the group var on `x` or `facet`):   example_isolates %>%     filter(mo_is_gram_negative(), ward != \"Outpatient\") %>%     # select only UTI-specific drugs     select(ward, AMX, NIT, FOS, TMP, CIP) %>%     group_by(ward) %>%     ggplot_sir(       x = \"ward\",       facet = \"antibiotic\",       nrow = 1,       title = \"AMR of Anti-UTI Drugs Per Ward\",       x.title = \"Ward\",       datalabels = FALSE     ) } #> ℹ Using column 'mo' as input for mo_is_gram_negative()  # }"},{"path":"https://msberends.github.io/AMR/reference/guess_ab_col.html","id":null,"dir":"Reference","previous_headings":"","what":"Guess Antibiotic Column — guess_ab_col","title":"Guess Antibiotic Column — guess_ab_col","text":"tries find column name data set based information antibiotics data set. Also supports WHONET abbreviations.","code":""},{"path":"https://msberends.github.io/AMR/reference/guess_ab_col.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Guess Antibiotic Column — guess_ab_col","text":"","code":"guess_ab_col(   x = NULL,   search_string = NULL,   verbose = FALSE,   only_sir_columns = FALSE )"},{"path":"https://msberends.github.io/AMR/reference/guess_ab_col.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Guess Antibiotic Column — guess_ab_col","text":"x data.frame search_string text search x , checked .ab() value column x verbose logical indicate whether additional info printed only_sir_columns logical indicate whether antibiotic columns must detected transformed class sir (see .sir()) beforehand (default FALSE)","code":""},{"path":"https://msberends.github.io/AMR/reference/guess_ab_col.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Guess Antibiotic Column — guess_ab_col","text":"column name x, NULL result found.","code":""},{"path":"https://msberends.github.io/AMR/reference/guess_ab_col.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Guess Antibiotic Column — guess_ab_col","text":"can look antibiotic (trade) name abbreviation search x antibiotics data set column containing name code antibiotic.","code":""},{"path":"https://msberends.github.io/AMR/reference/guess_ab_col.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Guess Antibiotic Column — guess_ab_col","text":"","code":"df <- data.frame(   amox = \"S\",   tetr = \"R\" )  guess_ab_col(df, \"amoxicillin\") #> [1] \"amox\" guess_ab_col(df, \"J01AA07\") # ATC code of tetracycline #> [1] \"tetr\"  guess_ab_col(df, \"J01AA07\", verbose = TRUE) #> Auto-guessing columns suitable for analysis #> ... #>  OK. #> ℹ Using column 'amox' as input for AMX (amoxicillin). #> ℹ Using column 'tetr' as input for TCY (tetracycline). #> ℹ Using column 'tetr' as input for J01AA07 (tetracycline). #> [1] \"tetr\" # NOTE: Using column 'tetr' as input for J01AA07 (tetracycline).  # WHONET codes df <- data.frame(   AMP_ND10 = \"R\",   AMC_ED20 = \"S\" ) guess_ab_col(df, \"ampicillin\") #> [1] \"AMP_ND10\" guess_ab_col(df, \"J01CR02\") #> [1] \"AMC_ED20\" guess_ab_col(df, as.ab(\"augmentin\")) #> [1] \"AMC_ED20\""},{"path":"https://msberends.github.io/AMR/reference/intrinsic_resistant.html","id":null,"dir":"Reference","previous_headings":"","what":"Data Set with Bacterial Intrinsic Resistance — intrinsic_resistant","title":"Data Set with Bacterial Intrinsic Resistance — intrinsic_resistant","text":"Data set containing defined intrinsic resistance EUCAST bug-drug combinations.","code":""},{"path":"https://msberends.github.io/AMR/reference/intrinsic_resistant.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Data Set with Bacterial Intrinsic Resistance — intrinsic_resistant","text":"","code":"intrinsic_resistant"},{"path":"https://msberends.github.io/AMR/reference/intrinsic_resistant.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data Set with Bacterial Intrinsic Resistance — intrinsic_resistant","text":"tibble 134 634 observations 2 variables: mo Microorganism ID ab Antibiotic ID","code":""},{"path":"https://msberends.github.io/AMR/reference/intrinsic_resistant.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Data Set with Bacterial Intrinsic Resistance — intrinsic_resistant","text":"data set based 'EUCAST Expert Rules' 'EUCAST Intrinsic Resistance Unusual Phenotypes' v3.3 (2021).","code":""},{"path":"https://msberends.github.io/AMR/reference/intrinsic_resistant.html","id":"direct-download","dir":"Reference","previous_headings":"","what":"Direct download","title":"Data Set with Bacterial Intrinsic Resistance — intrinsic_resistant","text":"Like data sets package, data set publicly available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. Please visit website download links. actual files course available GitHub repository. allow machine reading EUCAST CLSI guidelines, almost impossible MS Excel PDF files distributed EUCAST CLSI.","code":""},{"path":"https://msberends.github.io/AMR/reference/intrinsic_resistant.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Data Set with Bacterial Intrinsic Resistance — intrinsic_resistant","text":"","code":"intrinsic_resistant #> # A tibble: 134,634 × 2 #>    mo      ab    #>    <mo>    <chr> #>  1 B_GRAMP ATM   #>  2 B_GRAMP COL   #>  3 B_GRAMP NAL   #>  4 B_GRAMP PLB   #>  5 B_GRAMP TEM   #>  6 B_ABTRP ATM   #>  7 B_ABTRP COL   #>  8 B_ABTRP NAL   #>  9 B_ABTRP PLB   #> 10 B_ABTRP TEM   #> # ℹ 134,624 more rows"},{"path":"https://msberends.github.io/AMR/reference/italicise_taxonomy.html","id":null,"dir":"Reference","previous_headings":"","what":"Italicise Taxonomic Families, Genera, Species, Subspecies — italicise_taxonomy","title":"Italicise Taxonomic Families, Genera, Species, Subspecies — italicise_taxonomy","text":"According binomial nomenclature, lowest four taxonomic levels (family, genus, species, subspecies) printed italics. function finds taxonomic names within strings makes italic.","code":""},{"path":"https://msberends.github.io/AMR/reference/italicise_taxonomy.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Italicise Taxonomic Families, Genera, Species, Subspecies — italicise_taxonomy","text":"","code":"italicise_taxonomy(string, type = c(\"markdown\", \"ansi\", \"html\"))  italicize_taxonomy(string, type = c(\"markdown\", \"ansi\", \"html\"))"},{"path":"https://msberends.github.io/AMR/reference/italicise_taxonomy.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Italicise Taxonomic Families, Genera, Species, Subspecies — italicise_taxonomy","text":"string character (vector) type type conversion taxonomic names, either \"markdown\", \"html\" \"ansi\", see Details","code":""},{"path":"https://msberends.github.io/AMR/reference/italicise_taxonomy.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Italicise Taxonomic Families, Genera, Species, Subspecies — italicise_taxonomy","text":"function finds taxonomic names makes italic based microorganisms data set. taxonomic names can italicised using markdown (default) adding * taxonomic names, <> <\/> using html. using 'ansi', ANSI colours added using \\033[3m \\033[23m taxonomic names. multiple ANSI colours available, conversion occur. function also supports abbreviation genus followed species, \"E. coli\" \"K. pneumoniae ozaenae\".","code":""},{"path":"https://msberends.github.io/AMR/reference/italicise_taxonomy.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Italicise Taxonomic Families, Genera, Species, Subspecies — italicise_taxonomy","text":"","code":"italicise_taxonomy(\"An overview of Staphylococcus aureus isolates\") #> [1] \"An overview of *Staphylococcus aureus* isolates\" italicise_taxonomy(\"An overview of S. aureus isolates\") #> [1] \"An overview of *S. aureus* isolates\"  cat(italicise_taxonomy(\"An overview of S. aureus isolates\", type = \"ansi\")) #> An overview of S. aureus isolates"},{"path":"https://msberends.github.io/AMR/reference/join.html","id":null,"dir":"Reference","previous_headings":"","what":"Join microorganisms to a Data Set — join","title":"Join microorganisms to a Data Set — join","text":"Join data set microorganisms easily existing data set character vector.","code":""},{"path":"https://msberends.github.io/AMR/reference/join.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Join microorganisms to a Data Set — join","text":"","code":"inner_join_microorganisms(x, by = NULL, suffix = c(\"2\", \"\"), ...)  left_join_microorganisms(x, by = NULL, suffix = c(\"2\", \"\"), ...)  right_join_microorganisms(x, by = NULL, suffix = c(\"2\", \"\"), ...)  full_join_microorganisms(x, by = NULL, suffix = c(\"2\", \"\"), ...)  semi_join_microorganisms(x, by = NULL, ...)  anti_join_microorganisms(x, by = NULL, ...)"},{"path":"https://msberends.github.io/AMR/reference/join.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Join microorganisms to a Data Set — join","text":"x existing data set join, character vector. case character vector, resulting data.frame contain column 'x' values. variable join - left empty search column class mo (created .mo()) \"mo\" column name exists x, otherwise column name x values exist microorganisms$mo (= \"bacteria_id\"), another column microorganisms (named, like = c(\"bacteria_id\" = \"fullname\")) suffix non-joined duplicate variables x y, suffixes added output disambiguate . character vector length 2. ... ignored, place allow future extensions","code":""},{"path":"https://msberends.github.io/AMR/reference/join.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Join microorganisms to a Data Set — join","text":"data.frame","code":""},{"path":"https://msberends.github.io/AMR/reference/join.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Join microorganisms to a Data Set — join","text":"Note: opposed join() functions dplyr, character vectors supported default existing columns get suffix \"2\" newly joined columns get suffix. dplyr package installed, join functions used. Otherwise, much slower merge() interaction() functions base R used.","code":""},{"path":"https://msberends.github.io/AMR/reference/join.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Join microorganisms to a Data Set — join","text":"","code":"left_join_microorganisms(as.mo(\"K. pneumoniae\")) #> # A tibble: 1 × 23 #>   mo           fullname   status kingdom phylum class order family genus species #>   <mo>         <chr>      <chr>  <chr>   <chr>  <chr> <chr> <chr>  <chr> <chr>   #> 1 B_KLBSL_PNMN Klebsiell… accep… Bacter… Pseud… Gamm… Ente… Enter… Kleb… pneumo… #> # ℹ 13 more variables: subspecies <chr>, rank <chr>, ref <chr>, #> #   oxygen_tolerance <chr>, source <chr>, lpsn <chr>, lpsn_parent <chr>, #> #   lpsn_renamed_to <chr>, gbif <chr>, gbif_parent <chr>, #> #   gbif_renamed_to <chr>, prevalence <dbl>, snomed <list> left_join_microorganisms(\"B_KLBSL_PNMN\") #> # A tibble: 1 × 23 #>   mo           fullname   status kingdom phylum class order family genus species #>   <mo>         <chr>      <chr>  <chr>   <chr>  <chr> <chr> <chr>  <chr> <chr>   #> 1 B_KLBSL_PNMN Klebsiell… accep… Bacter… Pseud… Gamm… Ente… Enter… Kleb… pneumo… #> # ℹ 13 more variables: subspecies <chr>, rank <chr>, ref <chr>, #> #   oxygen_tolerance <chr>, source <chr>, lpsn <chr>, lpsn_parent <chr>, #> #   lpsn_renamed_to <chr>, gbif <chr>, gbif_parent <chr>, #> #   gbif_renamed_to <chr>, prevalence <dbl>, snomed <list>  df <- data.frame(   date = seq(     from = as.Date(\"2018-01-01\"),     to = as.Date(\"2018-01-07\"),     by = 1   ),   bacteria = as.mo(c(     \"S. aureus\", \"MRSA\", \"MSSA\", \"STAAUR\",     \"E. coli\", \"E. coli\", \"E. coli\"   )),   stringsAsFactors = FALSE ) colnames(df) #> [1] \"date\"     \"bacteria\"  df_joined <- left_join_microorganisms(df, \"bacteria\") colnames(df_joined) #>  [1] \"date\"             \"bacteria\"         \"fullname\"         \"status\"           #>  [5] \"kingdom\"          \"phylum\"           \"class\"            \"order\"            #>  [9] \"family\"           \"genus\"            \"species\"          \"subspecies\"       #> [13] \"rank\"             \"ref\"              \"oxygen_tolerance\" \"source\"           #> [17] \"lpsn\"             \"lpsn_parent\"      \"lpsn_renamed_to\"  \"gbif\"             #> [21] \"gbif_parent\"      \"gbif_renamed_to\"  \"prevalence\"       \"snomed\"            # \\donttest{ if (require(\"dplyr\")) {   example_isolates %>%     left_join_microorganisms() %>%     colnames() } #> Joining, by = \"mo\" #>  [1] \"date\"             \"patient\"          \"age\"              \"gender\"           #>  [5] \"ward\"             \"mo\"               \"PEN\"              \"OXA\"              #>  [9] \"FLC\"              \"AMX\"              \"AMC\"              \"AMP\"              #> [13] \"TZP\"              \"CZO\"              \"FEP\"              \"CXM\"              #> [17] \"FOX\"              \"CTX\"              \"CAZ\"              \"CRO\"              #> [21] \"GEN\"              \"TOB\"              \"AMK\"              \"KAN\"              #> [25] \"TMP\"              \"SXT\"              \"NIT\"              \"FOS\"              #> [29] \"LNZ\"              \"CIP\"              \"MFX\"              \"VAN\"              #> [33] \"TEC\"              \"TCY\"              \"TGC\"              \"DOX\"              #> [37] \"ERY\"              \"CLI\"              \"AZM\"              \"IPM\"              #> [41] \"MEM\"              \"MTR\"              \"CHL\"              \"COL\"              #> [45] \"MUP\"              \"RIF\"              \"fullname\"         \"status\"           #> [49] \"kingdom\"          \"phylum\"           \"class\"            \"order\"            #> [53] \"family\"           \"genus\"            \"species\"          \"subspecies\"       #> [57] \"rank\"             \"ref\"              \"oxygen_tolerance\" \"source\"           #> [61] \"lpsn\"             \"lpsn_parent\"      \"lpsn_renamed_to\"  \"gbif\"             #> [65] \"gbif_parent\"      \"gbif_renamed_to\"  \"prevalence\"       \"snomed\"           # }"},{"path":"https://msberends.github.io/AMR/reference/key_antimicrobials.html","id":null,"dir":"Reference","previous_headings":"","what":"(Key) Antimicrobials for First Weighted Isolates — key_antimicrobials","title":"(Key) Antimicrobials for First Weighted Isolates — key_antimicrobials","text":"functions can used determine first weighted isolates considering phenotype isolate selection (see first_isolate()). Using phenotype-based method determine first isolates reliable methods disregard phenotypes.","code":""},{"path":"https://msberends.github.io/AMR/reference/key_antimicrobials.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"(Key) Antimicrobials for First Weighted Isolates — key_antimicrobials","text":"","code":"key_antimicrobials(   x = NULL,   col_mo = NULL,   universal = c(\"ampicillin\", \"amoxicillin/clavulanic acid\", \"cefuroxime\",     \"piperacillin/tazobactam\", \"ciprofloxacin\", \"trimethoprim/sulfamethoxazole\"),   gram_negative = c(\"gentamicin\", \"tobramycin\", \"colistin\", \"cefotaxime\", \"ceftazidime\",     \"meropenem\"),   gram_positive = c(\"vancomycin\", \"teicoplanin\", \"tetracycline\", \"erythromycin\",     \"oxacillin\", \"rifampin\"),   antifungal = c(\"anidulafungin\", \"caspofungin\", \"fluconazole\", \"miconazole\", \"nystatin\",     \"voriconazole\"),   only_sir_columns = FALSE,   ... )  all_antimicrobials(x = NULL, only_sir_columns = FALSE, ...)  antimicrobials_equal(   y,   z,   type = c(\"points\", \"keyantimicrobials\"),   ignore_I = TRUE,   points_threshold = 2,   ... )"},{"path":"https://msberends.github.io/AMR/reference/key_antimicrobials.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"(Key) Antimicrobials for First Weighted Isolates — key_antimicrobials","text":"x data.frame antibiotics columns, like AMX amox. Can left blank determine automatically col_mo column name names codes microorganisms (see .mo()) - default first column class mo. Values coerced using .mo(). universal names broad-spectrum antimicrobial drugs, case-insensitive. Set NULL ignore. See Details default antimicrobial drugs gram_negative names antibiotic drugs Gram-positives, case-insensitive. Set NULL ignore. See Details default antibiotic drugs gram_positive names antibiotic drugs Gram-negatives, case-insensitive. Set NULL ignore. See Details default antibiotic drugs antifungal names antifungal drugs fungi, case-insensitive. Set NULL ignore. See Details default antifungal drugs only_sir_columns logical indicate whether columns must included transformed class sir (see .sir()) beforehand (default FALSE) ... ignored, place allow future extensions y, z character vectors compare type type determine weighed isolates; can \"keyantimicrobials\" \"points\", see Details ignore_I logical indicate whether antibiotic interpretations \"\" ignored type = \"keyantimicrobials\", see Details points_threshold minimum number points require differences antibiogram lead inclusion isolate type = \"points\", see Details","code":""},{"path":"https://msberends.github.io/AMR/reference/key_antimicrobials.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"(Key) Antimicrobials for First Weighted Isolates — key_antimicrobials","text":"key_antimicrobials() all_antimicrobials() functions context-aware. means x argument can left blank used inside data.frame call, see Examples. function key_antimicrobials() returns character vector 12 antimicrobial results every isolate. function all_antimicrobials() returns character vector antimicrobial drug results every isolate. vectors can compared using antimicrobials_equal(), check two isolates generally antibiogram. Missing invalid values replaced dot (\".\") key_antimicrobials() ignored antimicrobials_equal(). Please see first_isolate() function important functions enable 'phenotype-based' method determination first isolates. default antimicrobial drugs used rows (set universal) : Ampicillin Amoxicillin/clavulanic acid Cefuroxime Ciprofloxacin Piperacillin/tazobactam Trimethoprim/sulfamethoxazole default antimicrobial drugs used Gram-negative bacteria (set gram_negative) : Cefotaxime Ceftazidime Colistin Gentamicin Meropenem Tobramycin default antimicrobial drugs used Gram-positive bacteria (set gram_positive) : Erythromycin Oxacillin Rifampin Teicoplanin Tetracycline Vancomycin default antimicrobial drugs used fungi (set antifungal) : Anidulafungin Caspofungin Fluconazole Miconazole Nystatin Voriconazole","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/key_antimicrobials.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"(Key) Antimicrobials for First Weighted Isolates — key_antimicrobials","text":"","code":"# `example_isolates` is a data set available in the AMR package. # See ?example_isolates.  # output of the `key_antimicrobials()` function could be like this: strainA <- \"SSSRR.S.R..S\" strainB <- \"SSSIRSSSRSSS\"  # those strings can be compared with: antimicrobials_equal(strainA, strainB, type = \"keyantimicrobials\") #> [1] TRUE # TRUE, because I is ignored (as well as missing values)  antimicrobials_equal(strainA, strainB, type = \"keyantimicrobials\", ignore_I = FALSE) #> [1] FALSE # FALSE, because I is not ignored and so the 4th [character] differs  # \\donttest{ if (require(\"dplyr\")) {   # set key antibiotics to a new variable   my_patients <- example_isolates %>%     mutate(keyab = key_antimicrobials(antifungal = NULL)) %>% # no need to define `x`     mutate(       # now calculate first isolates       first_regular = first_isolate(col_keyantimicrobials = FALSE),       # and first WEIGHTED isolates       first_weighted = first_isolate(col_keyantimicrobials = \"keyab\")     )    # Check the difference in this data set, 'weighted' results in more isolates:   sum(my_patients$first_regular, na.rm = TRUE)   sum(my_patients$first_weighted, na.rm = TRUE) } #> [1] 1376 # }"},{"path":"https://msberends.github.io/AMR/reference/kurtosis.html","id":null,"dir":"Reference","previous_headings":"","what":"Kurtosis of the Sample — kurtosis","title":"Kurtosis of the Sample — kurtosis","text":"Kurtosis measure \"tailedness\" probability distribution real-valued random variable. normal distribution kurtosis 3 excess kurtosis 0.","code":""},{"path":"https://msberends.github.io/AMR/reference/kurtosis.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Kurtosis of the Sample — kurtosis","text":"","code":"kurtosis(x, na.rm = FALSE, excess = FALSE)  # S3 method for default kurtosis(x, na.rm = FALSE, excess = FALSE)  # S3 method for matrix kurtosis(x, na.rm = FALSE, excess = FALSE)  # S3 method for data.frame kurtosis(x, na.rm = FALSE, excess = FALSE)"},{"path":"https://msberends.github.io/AMR/reference/kurtosis.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Kurtosis of the Sample — kurtosis","text":"x vector values, matrix data.frame na.rm logical indicate whether NA values stripped computation proceeds excess logical indicate whether excess kurtosis returned, defined kurtosis minus 3.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/kurtosis.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Kurtosis of the Sample — kurtosis","text":"","code":"kurtosis(rnorm(10000)) #> [1] 3.021297 kurtosis(rnorm(10000), excess = TRUE) #> [1] 0.08143396"},{"path":"https://msberends.github.io/AMR/reference/like.html","id":null,"dir":"Reference","previous_headings":"","what":"Vectorised Pattern Matching with Keyboard Shortcut — like","title":"Vectorised Pattern Matching with Keyboard Shortcut — like","text":"Convenient wrapper around grepl() match pattern: x %like% pattern. always returns logical vector always case-insensitive (use x %like_case% pattern case-sensitive matching). Also, pattern can long x compare items index vectors, can length iterate cases.","code":""},{"path":"https://msberends.github.io/AMR/reference/like.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Vectorised Pattern Matching with Keyboard Shortcut — like","text":"","code":"like(x, pattern, ignore.case = TRUE)  x %like% pattern  x %unlike% pattern  x %like_case% pattern  x %unlike_case% pattern"},{"path":"https://msberends.github.io/AMR/reference/like.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Vectorised Pattern Matching with Keyboard Shortcut — like","text":"Idea like function data.table package, although altered explained Details.","code":""},{"path":"https://msberends.github.io/AMR/reference/like.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Vectorised Pattern Matching with Keyboard Shortcut — like","text":"x character vector matches sought, object can coerced .character() character vector. pattern character vector containing regular expressions (character string fixed = TRUE) matched given character vector. Coerced .character() character string possible. ignore.case FALSE, pattern matching case sensitive TRUE, case ignored matching.","code":""},{"path":"https://msberends.github.io/AMR/reference/like.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Vectorised Pattern Matching with Keyboard Shortcut — like","text":"logical vector","code":""},{"path":"https://msberends.github.io/AMR/reference/like.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Vectorised Pattern Matching with Keyboard Shortcut — like","text":"like() %like%/%unlike% functions: case-insensitive (use %like_case%/%unlike_case% case-sensitive matching) Support multiple patterns Check pattern valid regular expression sets fixed = TRUE , greatly improve speed (vectorised pattern) Always use compatibility Perl unless fixed = TRUE, greatly improve speed Using RStudio? %like%/%unlike% functions can also directly inserted code Addins menu can keyboard shortcut like Shift+Ctrl+L Shift+Cmd+L (see menu Tools > Modify Keyboard Shortcuts...). keep pressing shortcut, inserted text iterated %like% -> %unlike% -> %like_case% -> %unlike_case%.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/like.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Vectorised Pattern Matching with Keyboard Shortcut — like","text":"","code":"# data.table has a more limited version of %like%, so unload it: try(detach(\"package:data.table\", unload = TRUE), silent = TRUE)  a <- \"This is a test\" b <- \"TEST\" a %like% b #> [1] TRUE b %like% a #> [1] FALSE  # also supports multiple patterns a <- c(\"Test case\", \"Something different\", \"Yet another thing\") b <- c(\"case\", \"diff\", \"yet\") a %like% b #> [1] TRUE TRUE TRUE a %unlike% b #> [1] FALSE FALSE FALSE  a[1] %like% b #> [1]  TRUE FALSE FALSE a %like% b[1] #> [1]  TRUE FALSE FALSE  # \\donttest{ # get isolates whose name start with 'Entero' (case-insensitive) example_isolates[which(mo_name() %like% \"^entero\"), ] #> ℹ Using column 'mo' as input for mo_name() #> # A tibble: 106 × 46 #>    date       patient   age gender ward    mo            PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>   <mo>          <sir> <sir> <sir> <sir> #>  1 2002-02-21 4FC193     69 M      Clinic… B_ENTRC_FACM  NA    NA    NA    NA    #>  2 2002-04-08 130252     78 M      ICU     B_ENTRC_FCLS  NA    NA    NA    NA    #>  3 2002-06-23 798871     82 M      Clinic… B_ENTRC_FCLS  NA    NA    NA    NA    #>  4 2002-06-23 798871     82 M      Clinic… B_ENTRC_FCLS  NA    NA    NA    NA    #>  5 2003-04-20 6BC362     62 M      ICU     B_ENTRC       NA    NA    NA    NA    #>  6 2003-04-21 6BC362     62 M      ICU     B_ENTRC       NA    NA    NA    NA    #>  7 2003-08-13 F35553     52 M      ICU     B_ENTRBC_CLOC R     NA    NA    R     #>  8 2003-08-13 F35553     52 M      ICU     B_ENTRC_FCLS  NA    NA    NA    NA    #>  9 2003-09-05 F35553     52 M      ICU     B_ENTRC       NA    NA    NA    NA    #> 10 2003-09-05 F35553     52 M      ICU     B_ENTRBC_CLOC R     NA    NA    R     #> # ℹ 96 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, …  if (require(\"dplyr\")) {   example_isolates %>%     filter(mo_name() %like% \"^ent\") } #> ℹ Using column 'mo' as input for mo_name() #> # A tibble: 106 × 46 #>    date       patient   age gender ward    mo            PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>   <mo>          <sir> <sir> <sir> <sir> #>  1 2002-02-21 4FC193     69 M      Clinic… B_ENTRC_FACM  NA    NA    NA    NA    #>  2 2002-04-08 130252     78 M      ICU     B_ENTRC_FCLS  NA    NA    NA    NA    #>  3 2002-06-23 798871     82 M      Clinic… B_ENTRC_FCLS  NA    NA    NA    NA    #>  4 2002-06-23 798871     82 M      Clinic… B_ENTRC_FCLS  NA    NA    NA    NA    #>  5 2003-04-20 6BC362     62 M      ICU     B_ENTRC       NA    NA    NA    NA    #>  6 2003-04-21 6BC362     62 M      ICU     B_ENTRC       NA    NA    NA    NA    #>  7 2003-08-13 F35553     52 M      ICU     B_ENTRBC_CLOC R     NA    NA    R     #>  8 2003-08-13 F35553     52 M      ICU     B_ENTRC_FCLS  NA    NA    NA    NA    #>  9 2003-09-05 F35553     52 M      ICU     B_ENTRC       NA    NA    NA    NA    #> 10 2003-09-05 F35553     52 M      ICU     B_ENTRBC_CLOC R     NA    NA    R     #> # ℹ 96 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, … # }"},{"path":"https://msberends.github.io/AMR/reference/mdro.html","id":null,"dir":"Reference","previous_headings":"","what":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","title":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","text":"Determine isolates multidrug-resistant organisms (MDRO) according international, national custom guidelines.","code":""},{"path":"https://msberends.github.io/AMR/reference/mdro.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","text":"","code":"mdro(   x = NULL,   guideline = \"CMI2012\",   col_mo = NULL,   info = interactive(),   pct_required_classes = 0.5,   combine_SI = TRUE,   verbose = FALSE,   only_sir_columns = FALSE,   ... )  custom_mdro_guideline(..., as_factor = TRUE)  brmo(x = NULL, only_sir_columns = FALSE, ...)  mrgn(x = NULL, only_sir_columns = FALSE, ...)  mdr_tb(x = NULL, only_sir_columns = FALSE, ...)  mdr_cmi2012(x = NULL, only_sir_columns = FALSE, ...)  eucast_exceptional_phenotypes(x = NULL, only_sir_columns = FALSE, ...)"},{"path":"https://msberends.github.io/AMR/reference/mdro.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","text":"See supported guidelines list publications used function.","code":""},{"path":"https://msberends.github.io/AMR/reference/mdro.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","text":"x data.frame antibiotics columns, like AMX amox. Can left blank automatic determination. guideline specific guideline follow, see sections Supported international / national guidelines Using Custom Guidelines . left empty, publication Magiorakos et al. (see ) followed. col_mo column name names codes microorganisms (see .mo()) - default first column class mo. Values coerced using .mo(). info logical indicate whether progress printed console - default print interactive sessions pct_required_classes minimal required percentage antimicrobial classes must available per isolate, rounded . example, default guideline, 17 antimicrobial classes must available S. aureus. Setting pct_required_classes argument 0.5 (default) means every S. aureus isolate least 8 different classes must available. lower number available classes return NA isolate. combine_SI logical indicate whether values S must merged one, resistance considered isolates R, . default behaviour mdro() function, follows redefinition EUCAST interpretation (increased exposure) 2019, see section 'Interpretation S, R' . using combine_SI = FALSE, resistance considered isolates R . verbose logical turn Verbose mode (default ). Verbose mode, function return MDRO results, instead returns data set logbook form extensive info isolates MDRO-positive, . only_sir_columns logical indicate whether antibiotic columns must detected transformed class sir (see .sir()) beforehand (default FALSE) ... case custom_mdro_guideline(): set rules, see section Using Custom Guidelines . Otherwise: column name antibiotic, see section Antibiotics . as_factor logical indicate whether returned value ordered factor (TRUE, default), otherwise character vector","code":""},{"path":"https://msberends.github.io/AMR/reference/mdro.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","text":"CMI 2012 paper - function mdr_cmi2012() mdro(): Ordered factor levels Negative < Multi-drug-resistant (MDR) < Extensively drug-resistant (XDR) < Pandrug-resistant (PDR) TB guideline - function mdr_tb() mdro(..., guideline = \"TB\"): Ordered factor levels Negative < Mono-resistant < Poly-resistant < Multi-drug-resistant < Extensively drug-resistant German guideline - function mrgn() mdro(..., guideline = \"MRGN\"): Ordered factor levels Negative < 3MRGN < 4MRGN Everything else, except custom guidelines: Ordered factor levels Negative < Positive, unconfirmed < Positive. value \"Positive, unconfirmed\" means , according guideline, entirely sure isolate multi-drug resistant confirmed additional (e.g. molecular) tests","code":""},{"path":"https://msberends.github.io/AMR/reference/mdro.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","text":"functions context-aware. means x argument can left blank used inside data.frame call, see Examples. pct_required_classes argument, values 1 divided 100. support fractions (0.75 3/4) percentages (75). Note: Every test involves Enterobacteriaceae family, internally performed using newly named order Enterobacterales, since Enterobacteriaceae family taxonomically reclassified Adeolu et al. 2016. , Enterobacteriaceae family Enterobacteriales () order. species old Enterobacteriaceae family still new Enterobacterales (without ) order, divided multiple families. way tests performed now mdro() function makes sure results 2016 2016 identical.","code":""},{"path":"https://msberends.github.io/AMR/reference/mdro.html","id":"supported-international-national-guidelines","dir":"Reference","previous_headings":"","what":"Supported International / National Guidelines","title":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","text":"Currently supported guidelines (case-insensitive): guideline = \"CMI2012\" (default) Magiorakos AP, Srinivasan et al. \"Multidrug-resistant, extensively drug-resistant pandrug-resistant bacteria: international expert proposal interim standard definitions acquired resistance.\" Clinical Microbiology Infection (2012) (doi:10.1111/j.1469-0691.2011.03570.x ) guideline = \"EUCAST3.3\" (simply guideline = \"EUCAST\") European international guideline - EUCAST Expert Rules Version 3.3 \"Intrinsic Resistance Unusual Phenotypes\" (link) guideline = \"EUCAST3.2\" European international guideline - EUCAST Expert Rules Version 3.2 \"Intrinsic Resistance Unusual Phenotypes\" (link) guideline = \"EUCAST3.1\" European international guideline - EUCAST Expert Rules Version 3.1 \"Intrinsic Resistance Exceptional Phenotypes Tables\" (link) guideline = \"TB\" international guideline multi-drug resistant tuberculosis - World Health Organization \"Companion handbook guidelines programmatic management drug-resistant tuberculosis\" (link) guideline = \"MRGN\" German national guideline - Mueller et al. (2015) Antimicrobial Resistance Infection Control 4:7; doi:10.1186/s13756-015-0047-6 guideline = \"BRMO\" Dutch national guideline - Rijksinstituut voor Volksgezondheid en Milieu \"WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen) (ZKH)\" (link) Please suggest (country-specific) guidelines letting us know: https://github.com/msberends/AMR/issues/new.","code":""},{"path":"https://msberends.github.io/AMR/reference/mdro.html","id":"using-custom-guidelines","dir":"Reference","previous_headings":"","what":"Using Custom Guidelines","title":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","text":"Custom guidelines can set custom_mdro_guideline() function. great importance custom rules determine MDROs hospital, e.g., rules dependent ward, state contact isolation variables data. familiar case_when() function dplyr package, recognise input method set rules. Rules must set using R considers 'formula notation'. rule written tilde (~) consequence rule written tilde:   row/isolate matches first rule, value first ~ (case 'Elderly Type ') set MDRO value. Otherwise, second rule tried . number rules unlimited. can print rules set console overview. Colours help reading console supports colours.   outcome function can used guideline argument mdro() function:   Rules can also combined custom rules using c():   rules set (custom object case) exported shared file location using saveRDS() collaborate multiple users. custom rules set imported using readRDS().","code":"custom <- custom_mdro_guideline(CIP == \"R\" & age > 60 ~ \"Elderly Type A\",                                 ERY == \"R\" & age > 60 ~ \"Elderly Type B\") custom #> A set of custom MDRO rules: #>   1. CIP is \"R\" and age is higher than 60 -> Elderly Type A #>   2. ERY is \"R\" and age is higher than 60 -> Elderly Type B #>   3. Otherwise -> Negative #> #> Unmatched rows will return NA. x <- mdro(example_isolates,           guideline = custom) table(x) #>       Negative Elderly Type A Elderly Type B #>           1070            198            732 x <- mdro(example_isolates,           guideline = c(custom,                         custom_mdro_guideline(ERY == \"R\" & age > 50 ~ \"Elderly Type C\"))) table(x) #>       Negative Elderly Type A Elderly Type B Elderly Type C #>            961            198            732            109"},{"path":"https://msberends.github.io/AMR/reference/mdro.html","id":"antibiotics","dir":"Reference","previous_headings":"","what":"Antibiotics","title":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","text":"define antibiotics column names, leave determine automatically guess_ab_col() input text (case-insensitive), use NULL skip column (e.g. TIC = NULL skip ticarcillin). Manually defined non-existing columns skipped warning. following antibiotics eligible functions eucast_rules() mdro(). shown format 'name (antimicrobial ID, ATC code)', sorted alphabetically: Amikacin (AMK, J01GB06), amoxicillin (AMX, J01CA04), amoxicillin/clavulanic acid (AMC, J01CR02), ampicillin (AMP, J01CA01), ampicillin/sulbactam (SAM, J01CR01), apramycin (APR, QA07AA92), arbekacin (ARB, J01GB12), aspoxicillin (APX, J01CA19), azidocillin (AZD, J01CE04), azithromycin (AZM, J01FA10), azlocillin (AZL, J01CA09), aztreonam (ATM, J01DF01), bacampicillin (BAM, J01CA06), bekanamycin (BEK, J01GB13), benzathine benzylpenicillin (BNB, J01CE08), benzathine phenoxymethylpenicillin (BNP, J01CE10), benzylpenicillin (PEN, J01CE01), besifloxacin (BES, S01AE08), biapenem (BIA, J01DH05), carbenicillin (CRB, J01CA03), carindacillin (CRN, J01CA05), cefacetrile (CAC, J01DB10), cefaclor (CEC, J01DC04), cefadroxil (CFR, J01DB05), cefalexin (LEX, J01DB01), cefaloridine (RID, J01DB02), cefalotin (CEP, J01DB03), cefamandole (MAN, J01DC03), cefapirin (HAP, J01DB08), cefatrizine (CTZ, J01DB07), cefazedone (CZD, J01DB06), cefazolin (CZO, J01DB04), cefcapene (CCP, J01DD17), cefdinir (CDR, J01DD15), cefditoren (DIT, J01DD16), cefepime (FEP, J01DE01), cefetamet (CAT, J01DD10), cefixime (CFM, J01DD08), cefmenoxime (CMX, J01DD05), cefmetazole (CMZ, J01DC09), cefodizime (DIZ, J01DD09), cefonicid (CID, J01DC06), cefoperazone (CFP, J01DD12), cefoperazone/sulbactam (CSL, J01DD62), ceforanide (CND, J01DC11), cefotaxime (CTX, J01DD01), cefotaxime/clavulanic acid (CTC, J01DD51), cefotetan (CTT, J01DC05), cefotiam (CTF, J01DC07), cefovecin (FOV, QJ01DD91), cefoxitin (FOX, J01DC01), cefozopran (ZOP, J01DE03), cefpiramide (CPM, J01DD11), cefpirome (CPO, J01DE02), cefpodoxime (CPD, J01DD13), cefprozil (CPR, J01DC10), cefquinome (CEQ, QG51AA07), cefroxadine (CRD, J01DB11), cefsulodin (CFS, J01DD03), ceftaroline (CPT, J01DI02), ceftazidime (CAZ, J01DD02), ceftazidime/clavulanic acid (CCV, J01DD52), cefteram (CEM, J01DD18), ceftezole (CTL, J01DB12), ceftibuten (CTB, J01DD14), ceftiofur (TIO, QJ01DD90), ceftizoxime (CZX, J01DD07), ceftobiprole medocaril (CFM1, J01DI01), ceftolozane/tazobactam (CZT, J01DI54), ceftriaxone (CRO, J01DD04), ceftriaxone/beta-lactamase inhibitor (CEB, J01DD63), cefuroxime (CXM, J01DC02), cephradine (CED, J01DB09), chloramphenicol (CHL, J01BA01), ciprofloxacin (CIP, J01MA02), clarithromycin (CLR, J01FA09), clindamycin (CLI, J01FF01), clometocillin (CLM, J01CE07), cloxacillin (CLO, J01CF02), colistin (COL, J01XB01), cycloserine (CYC, J04AB01), dalbavancin (DAL, J01XA04), danofloxacin (DAN, QJ01MA92), daptomycin (DAP, J01XX09), delafloxacin (DFX, J01MA23), dibekacin (DKB, J01GB09), dicloxacillin (DIC, J01CF01), difloxacin (DIF, QJ01MA94), dirithromycin (DIR, J01FA13), doripenem (DOR, J01DH04), doxycycline (DOX, J01AA02), enoxacin (ENX, J01MA04), enrofloxacin (ENR, QJ01MA90), epicillin (EPC, J01CA07), ertapenem (ETP, J01DH03), erythromycin (ERY, J01FA01), fleroxacin (FLE, J01MA08), flucloxacillin (FLC, J01CF05), flurithromycin (FLR1, J01FA14), fosfomycin (FOS, J01XX01), framycetin (FRM, D09AA01), fusidic acid (FUS, J01XC01), gamithromycin (GAM, QJ01FA95), garenoxacin (GRN, J01MA19), gatifloxacin (GAT, J01MA16), gemifloxacin (GEM, J01MA15), gentamicin (GEN, J01GB03), grepafloxacin (GRX, J01MA11), hetacillin (HET, J01CA18), imipenem (IPM, J01DH51), imipenem/relebactam (IMR, J01DH56), isepamicin (ISE, J01GB11), josamycin (JOS, J01FA07), kanamycin (KAN, J01GB04), kitasamycin (KIT, QJ01FA93), lascufloxacin (LSC, J01MA25), latamoxef (LTM, J01DD06), levofloxacin (LVX, J01MA12), levonadifloxacin (LND, J01MA24), lincomycin (LIN, J01FF02), linezolid (LNZ, J01XX08), lomefloxacin (LOM, J01MA07), loracarbef (LOR, J01DC08), marbofloxacin (MAR, QJ01MA93), mecillinam (MEC, J01CA11), meropenem (MEM, J01DH02), meropenem/vaborbactam (MEV, J01DH52), metampicillin (MTM, J01CA14), meticillin (MET, J01CF03), mezlocillin (MEZ, J01CA10), micronomicin (MCR, S01AA22), midecamycin (MID, J01FA03), minocycline (MNO, J01AA08), miocamycin (MCM, J01FA11), moxifloxacin (MFX, J01MA14), nadifloxacin (NAD, D10AF05), nafcillin (NAF, J01CF06), nalidixic acid (NAL, J01MB02), neomycin (NEO, J01GB05), netilmicin (NET, J01GB07), nitrofurantoin (NIT, J01XE01), norfloxacin (, J01MA06), novobiocin (NOV, QJ01XX95), ofloxacin (OFX, J01MA01), oleandomycin (OLE, J01FA05), orbifloxacin (ORB, QJ01MA95), oritavancin (ORI, J01XA05), oxacillin (OXA, J01CF04), panipenem (PAN, J01DH55), pazufloxacin (PAZ, J01MA18), pefloxacin (PEF, J01MA03), penamecillin (PNM, J01CE06), pheneticillin (PHE, J01CE05), phenoxymethylpenicillin (PHN, J01CE02), piperacillin (PIP, J01CA12), piperacillin/tazobactam (TZP, J01CR05), pirlimycin (PRL, QJ51FF90), pivampicillin (PVM, J01CA02), pivmecillinam (PME, J01CA08), plazomicin (PLZ, J01GB14), polymyxin B (PLB, J01XB02), pradofloxacin (PRA, QJ01MA97), pristinamycin (PRI, J01FG01), procaine benzylpenicillin (PRB, J01CE09), propicillin (PRP, J01CE03), prulifloxacin (PRU, J01MA17), quinupristin/dalfopristin (QDA, QJ01FG02), ribostamycin (RST, J01GB10), rifampicin (RIF, J04AB02), rokitamycin (ROK, J01FA12), roxithromycin (RXT, J01FA06), rufloxacin (RFL, J01MA10), sarafloxacin (SAR, QJ01MA98), sisomicin (SIS, J01GB08), sitafloxacin (SIT, J01MA21), solithromycin (SOL, J01FA16), sparfloxacin (SPX, J01MA09), spiramycin (SPI, J01FA02), streptoduocin (STR, J01GA02), streptomycin (STR1, J01GA01), sulbactam (SUL, J01CG01), sulbenicillin (SBC, J01CA16), sulfadiazine (SDI, J01EC02), sulfadiazine/trimethoprim (SLT1, J01EE02), sulfadimethoxine (SUD, J01ED01), sulfadimidine (SDM, J01EB03), sulfadimidine/trimethoprim (SLT2, J01EE05), sulfafurazole (SLF, J01EB05), sulfaisodimidine (SLF1, J01EB01), sulfalene (SLF2, J01ED02), sulfamazone (SZO, J01ED09), sulfamerazine (SLF3, J01ED07), sulfamerazine/trimethoprim (SLT3, J01EE07), sulfamethizole (SLF4, J01EB02), sulfamethoxazole (SMX, J01EC01), sulfamethoxypyridazine (SLF5, J01ED05), sulfametomidine (SLF6, J01ED03), sulfametoxydiazine (SLF7, J01ED04), sulfametrole/trimethoprim (SLT4, J01EE03), sulfamoxole (SLF8, J01EC03), sulfamoxole/trimethoprim (SLT5, J01EE04), sulfanilamide (SLF9, J01EB06), sulfaperin (SLF10, J01ED06), sulfaphenazole (SLF11, J01ED08), sulfapyridine (SLF12, J01EB04), sulfathiazole (SUT, J01EB07), sulfathiourea (SLF13, J01EB08), sultamicillin (SLT6, J01CR04), talampicillin (TAL, J01CA15), tazobactam (TAZ, J01CG02), tebipenem (TBP, J01DH06), tedizolid (TZD, J01XX11), teicoplanin (TEC, J01XA02), telavancin (TLV, J01XA03), telithromycin (TLT, J01FA15), temafloxacin (TMX, J01MA05), temocillin (TEM, J01CA17), tetracycline (TCY, J01AA07), ticarcillin (TIC, J01CA13), ticarcillin/clavulanic acid (TCC, J01CR03), tigecycline (TGC, J01AA12), tilbroquinol (TBQ, P01AA05), tildipirosin (TIP, QJ01FA96), tilmicosin (TIL, QJ01FA91), tobramycin (TOB, J01GB01), tosufloxacin (TFX, J01MA22), trimethoprim (TMP, J01EA01), trimethoprim/sulfamethoxazole (SXT, J01EE01), troleandomycin (TRL, J01FA08), trovafloxacin (TVA, J01MA13), tulathromycin (TUL, QJ01FA94), tylosin (TYL, QJ01FA90), tylvalosin (TYL1, QJ01FA92), vancomycin (VAN, J01XA01)","code":""},{"path":"https://msberends.github.io/AMR/reference/mdro.html","id":"interpretation-of-sir","dir":"Reference","previous_headings":"","what":"Interpretation of SIR","title":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","text":"2019, European Committee Antimicrobial Susceptibility Testing (EUCAST) decided change definitions susceptibility testing categories S, , R shown (https://www.eucast.org/newsiandr): S - Susceptible, standard dosing regimen microorganism categorised \"Susceptible, standard dosing regimen\", high likelihood therapeutic success using standard dosing regimen agent. - Susceptible, increased exposure  microorganism categorised \"Susceptible, Increased exposure\" high likelihood therapeutic success exposure agent increased adjusting dosing regimen concentration site infection. R = Resistant microorganism categorised \"Resistant\" high likelihood therapeutic failure even increased exposure. Exposure function mode administration, dose, dosing interval, infusion time, well distribution excretion antimicrobial agent influence infecting organism site infection. AMR package honours insight. Use susceptibility() (equal proportion_SI()) determine antimicrobial susceptibility count_susceptible() (equal count_SI()) count susceptible isolates.","code":""},{"path":"https://msberends.github.io/AMR/reference/mdro.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","text":"","code":"out <- mdro(example_isolates, guideline = \"EUCAST\") str(out) #>  Ord.factor w/ 3 levels \"Negative\"<\"Positive, unconfirmed\"<..: 1 1 1 1 1 1 1 1 1 1 ... table(out) #> out #>              Negative Positive, unconfirmed              Positive  #>                  1978                     0                     6   out <- mdro(example_isolates,   guideline = custom_mdro_guideline(     AMX == \"R\" ~ \"Custom MDRO 1\",     VAN == \"R\" ~ \"Custom MDRO 2\"   ) ) table(out) #> out #>      Negative Custom MDRO 1 Custom MDRO 2  #>           870           804           326   # \\donttest{ if (require(\"dplyr\")) {   example_isolates %>%     mdro() %>%     table()    # no need to define `x` when used inside dplyr verbs:   example_isolates %>%     mutate(MDRO = mdro()) %>%     pull(MDRO) %>%     table() } #> Warning: in mdro(): NA introduced for isolates where the available percentage of #> antimicrobial classes was below 50% (set with pct_required_classes) #> Warning: There was 1 warning in `mutate()`. #> ℹ In argument: `MDRO = mdro()`. #> Caused by warning: #> ! in mdro(): NA introduced for isolates where the available percentage of #> antimicrobial classes was below 50% (set with pct_required_classes) #> . #>                         Negative       Multi-drug-resistant (MDR)  #>                             1601                              128  #> Extensively drug-resistant (XDR)          Pandrug-resistant (PDR)  #>                                0                                0  # }"},{"path":"https://msberends.github.io/AMR/reference/mean_amr_distance.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the Mean AMR Distance — mean_amr_distance","title":"Calculate the Mean AMR Distance — mean_amr_distance","text":"Calculates normalised mean antimicrobial resistance multiple observations, help identify similar isolates without comparing antibiograms hand.","code":""},{"path":"https://msberends.github.io/AMR/reference/mean_amr_distance.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate the Mean AMR Distance — mean_amr_distance","text":"","code":"mean_amr_distance(x, ...)  # S3 method for sir mean_amr_distance(x, ..., combine_SI = TRUE)  # S3 method for data.frame mean_amr_distance(x, ..., combine_SI = TRUE)  amr_distance_from_row(amr_distance, row)"},{"path":"https://msberends.github.io/AMR/reference/mean_amr_distance.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate the Mean AMR Distance — mean_amr_distance","text":"x vector class sir, mic disk, data.frame containing columns classes ... variables select (supports tidyselect language column1:column4 (.mic), can thus also antibiotic selectors combine_SI logical indicate whether values S must merged one, input consists S+vs. R (susceptible vs. resistant) - default TRUE amr_distance outcome mean_amr_distance() row index, row number","code":""},{"path":"https://msberends.github.io/AMR/reference/mean_amr_distance.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate the Mean AMR Distance — mean_amr_distance","text":"mean AMR distance effectively Z-score; normalised numeric value compare AMR test results can help identify similar isolates, without comparing antibiograms hand. MIC values (see .mic()) transformed log2() first; distance thus calculated (log2(x) - mean(log2(x))) / sd(log2(x)). SIR values (see .sir()) transformed using \"S\" = 1, \"\" = 2, \"R\" = 3. combine_SI TRUE (default), \"\" considered 1. data sets, mean AMR distance calculated per column, mean per row returned, see Examples. Use amr_distance_from_row() subtract distances distance one row, see Examples.","code":""},{"path":"https://msberends.github.io/AMR/reference/mean_amr_distance.html","id":"interpretation","dir":"Reference","previous_headings":"","what":"Interpretation","title":"Calculate the Mean AMR Distance — mean_amr_distance","text":"Isolates distances less 0.01 difference considered similar. Differences lower 0.025 considered suspicious.","code":""},{"path":"https://msberends.github.io/AMR/reference/mean_amr_distance.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate the Mean AMR Distance — mean_amr_distance","text":"","code":"sir <- random_sir(10) sir #> Class 'sir' #>  [1] R R S I I S I I R I mean_amr_distance(sir) #>  [1]  1.449138  1.449138 -0.621059 -0.621059 -0.621059 -0.621059 -0.621059 #>  [8] -0.621059  1.449138 -0.621059  mic <- random_mic(10) mic #> Class 'mic' #>  [1] 0.002 0.5   0.125 128   0.25  0.5   256   0.125 0.125 64    mean_amr_distance(mic) #>  [1] -1.6429088 -0.1673475 -0.5378223  1.3145519 -0.3525849 -0.1673475 #>  [7]  1.4997893 -0.5378223 -0.5378223  1.1293145 # equal to the Z-score of their log2: (log2(mic) - mean(log2(mic))) / sd(log2(mic)) #>  [1] -1.6429088 -0.1673475 -0.5378223  1.3145519 -0.3525849 -0.1673475 #>  [7]  1.4997893 -0.5378223 -0.5378223  1.1293145  disk <- random_disk(10) disk #> Class 'disk' #>  [1] 40 45 43 14 42 40 37 15 42 11 mean_amr_distance(disk) #>  [1]  0.5182957  0.8832927  0.7372939 -1.3796886  0.6642945  0.5182957 #>  [7]  0.2992975 -1.3066892  0.6642945 -1.5986868  y <- data.frame(   id = LETTERS[1:10],   amox = random_sir(10, ab = \"amox\", mo = \"Escherichia coli\"),   cipr = random_disk(10, ab = \"cipr\", mo = \"Escherichia coli\"),   gent = random_mic(10, ab = \"gent\", mo = \"Escherichia coli\"),   tobr = random_mic(10, ab = \"tobr\", mo = \"Escherichia coli\") ) y #>    id amox cipr  gent  tobr #> 1   A    R   17 <=0.5   >=8 #> 2   B    I   26 <=0.5     4 #> 3   C    R   18     4   >=8 #> 4   D    R   22 <=0.5 <=0.5 #> 5   E    I   30 <=0.5     1 #> 6   F    S   18     4     2 #> 7   G    I   26     8     2 #> 8   H    S   29     8     1 #> 9   I    I   22    16     1 #> 10  J    S   31     1     4 mean_amr_distance(y) #> ℹ Calculating mean AMR distance based on columns \"amox\", \"cipr\", \"gent\", #>   and \"tobr\" #>  [1]  0.12957466 -0.14083442  0.55230568 -0.36152662 -0.31478853 -0.33012168 #>  [7]  0.17672648  0.13748045 -0.07163669  0.22282068 y$amr_distance <- mean_amr_distance(y, where(is.mic)) #> Error in .subset(x, j): invalid subscript type 'list' y[order(y$amr_distance), ] #> Error in order(y$amr_distance): argument 1 is not a vector  if (require(\"dplyr\")) {   y %>%     mutate(       amr_distance = mean_amr_distance(y),       check_id_C = amr_distance_from_row(amr_distance, id == \"C\")     ) %>%     arrange(check_id_C) } #> ℹ Calculating mean AMR distance based on columns \"amox\", \"cipr\", \"gent\", #>   and \"tobr\" #>    id amox cipr  gent  tobr amr_distance check_id_C #> 1   C    R   18     4   >=8   0.55230568  0.0000000 #> 2   J    S   31     1     4   0.22282068  0.3294850 #> 3   G    I   26     8     2   0.17672648  0.3755792 #> 4   H    S   29     8     1   0.13748045  0.4148252 #> 5   A    R   17 <=0.5   >=8   0.12957466  0.4227310 #> 6   I    I   22    16     1  -0.07163669  0.6239424 #> 7   B    I   26 <=0.5     4  -0.14083442  0.6931401 #> 8   E    I   30 <=0.5     1  -0.31478853  0.8670942 #> 9   F    S   18     4     2  -0.33012168  0.8824274 #> 10  D    R   22 <=0.5 <=0.5  -0.36152662  0.9138323 if (require(\"dplyr\")) {   # support for groups   example_isolates %>%     filter(mo_genus() == \"Enterococcus\" & mo_species() != \"\") %>%     select(mo, TCY, carbapenems()) %>%     group_by(mo) %>%     mutate(dist = mean_amr_distance(.)) %>%     arrange(mo, dist) } #> ℹ Using column 'mo' as input for mo_genus() #> ℹ Using column 'mo' as input for mo_species() #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> ℹ Calculating mean AMR distance based on columns \"TCY\", \"IPM\", and \"MEM\" #> # A tibble: 63 × 5 #> # Groups:   mo [4] #>    mo           TCY   IPM   MEM     dist #>    <mo>         <sir> <sir> <sir>  <dbl> #>  1 B_ENTRC_AVIM S     S     NA     0     #>  2 B_ENTRC_AVIM S     S     NA     0     #>  3 B_ENTRC_CSSL NA    S     NA    NA     #>  4 B_ENTRC_FACM S     S     NA    -2.66  #>  5 B_ENTRC_FACM S     R     R     -0.423 #>  6 B_ENTRC_FACM S     R     R     -0.423 #>  7 B_ENTRC_FACM NA    R     R      0.224 #>  8 B_ENTRC_FACM NA    R     R      0.224 #>  9 B_ENTRC_FACM NA    R     R      0.224 #> 10 B_ENTRC_FACM NA    R     R      0.224 #> # ℹ 53 more rows"},{"path":"https://msberends.github.io/AMR/reference/microorganisms.codes.html","id":null,"dir":"Reference","previous_headings":"","what":"Data Set with 4 971 Common Microorganism Codes — microorganisms.codes","title":"Data Set with 4 971 Common Microorganism Codes — microorganisms.codes","text":"data set containing commonly used codes microorganisms, laboratory systems WHONET. Define set_mo_source(). searched using .mo() consequently mo_* functions.","code":""},{"path":"https://msberends.github.io/AMR/reference/microorganisms.codes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Data Set with 4 971 Common Microorganism Codes — microorganisms.codes","text":"","code":"microorganisms.codes"},{"path":"https://msberends.github.io/AMR/reference/microorganisms.codes.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data Set with 4 971 Common Microorganism Codes — microorganisms.codes","text":"tibble 4 971 observations 2 variables: code Commonly used code microorganism. unique identifier. mo ID microorganism microorganisms data set","code":""},{"path":"https://msberends.github.io/AMR/reference/microorganisms.codes.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Data Set with 4 971 Common Microorganism Codes — microorganisms.codes","text":"Like data sets package, data set publicly available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/microorganisms.codes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Data Set with 4 971 Common Microorganism Codes — microorganisms.codes","text":"","code":"microorganisms.codes #> # A tibble: 4,971 × 2 #>    code  mo                #>    <chr> <mo>              #>  1 1011  B_GRAMP           #>  2 1012  B_GRAMP           #>  3 1013  B_GRAMN           #>  4 1014  B_GRAMN           #>  5 1015  F_YEAST           #>  6 103   B_ESCHR_COLI      #>  7 104   B_SLMNL_ENTR_ENTR #>  8 1100  B_STRPT           #>  9 1101  B_STRPT_VIRI      #> 10 1102  B_STRPT_HAEM      #> # ℹ 4,961 more rows  # 'ECO' or 'eco' is the WHONET code for E. coli: microorganisms.codes[microorganisms.codes$code == \"ECO\", ] #> # A tibble: 1 × 2 #>   code  mo           #>   <chr> <mo>         #> 1 ECO   B_ESCHR_COLI  # and therefore, 'eco' will be understood as E. coli in this package: mo_info(\"eco\") #> $mo #> [1] \"B_ESCHR_COLI\" #>  #> $kingdom #> [1] \"Bacteria\" #>  #> $phylum #> [1] \"Pseudomonadota\" #>  #> $class #> [1] \"Gammaproteobacteria\" #>  #> $order #> [1] \"Enterobacterales\" #>  #> $family #> [1] \"Enterobacteriaceae\" #>  #> $genus #> [1] \"Escherichia\" #>  #> $species #> [1] \"coli\" #>  #> $subspecies #> [1] \"\" #>  #> $status #> [1] \"accepted\" #>  #> $synonyms #> NULL #>  #> $gramstain #> [1] \"Gram-negative\" #>  #> $oxygen_tolerance #> [1] \"facultative anaerobe\" #>  #> $url #> [1] \"https://lpsn.dsmz.de/species/escherichia-coli\" #>  #> $ref #> [1] \"Castellani et al., 1919\" #>  #> $snomed #>  [1] \"1095001000112106\" \"715307006\"        \"737528008\"        \"416989002\"        #>  [5] \"116397003\"        \"414097009\"        \"414098004\"        \"414099007\"        #>  [9] \"414100004\"        \"116395006\"        \"735270003\"        \"116396007\"        #> [13] \"83285000\"         \"116394005\"        \"112283007\"        \"710886005\"        #> [17] \"710887001\"        \"710888006\"        \"710889003\"        \"414132004\"        #> [21] \"721892009\"        \"416812001\"        \"416740004\"        \"417216001\"        #> [25] \"457541006\"        \"710253004\"        \"416530004\"        \"417189006\"        #> [29] \"409800005\"        \"713925008\"        \"444771000124108\"  \"838549008\"        #>  #> $lpsn #> [1] \"776057\" #>  #> $gbif #> [1] \"11286021\" #>  #> $group_members #> character(0) #>   # works for all AMR functions: mo_is_intrinsic_resistant(\"eco\", ab = \"vancomycin\") #> [1] TRUE"},{"path":"https://msberends.github.io/AMR/reference/microorganisms.groups.html","id":null,"dir":"Reference","previous_headings":"","what":"Data Set with 521 Microorganisms In Species Groups — microorganisms.groups","title":"Data Set with 521 Microorganisms In Species Groups — microorganisms.groups","text":"data set containing species groups microbiological complexes, used clinical breakpoints table.","code":""},{"path":"https://msberends.github.io/AMR/reference/microorganisms.groups.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Data Set with 521 Microorganisms In Species Groups — microorganisms.groups","text":"","code":"microorganisms.groups"},{"path":"https://msberends.github.io/AMR/reference/microorganisms.groups.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data Set with 521 Microorganisms In Species Groups — microorganisms.groups","text":"tibble 521 observations 4 variables: mo_group ID species group / microbiological complex mo ID microorganism belonging species group / microbiological complex mo_group_name Name species group / microbiological complex, retrieved mo_name() mo_name Name microorganism belonging species group / microbiological complex, retrieved mo_name()","code":""},{"path":"https://msberends.github.io/AMR/reference/microorganisms.groups.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Data Set with 521 Microorganisms In Species Groups — microorganisms.groups","text":"Like data sets package, data set publicly available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/microorganisms.groups.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Data Set with 521 Microorganisms In Species Groups — microorganisms.groups","text":"","code":"microorganisms.groups #> # A tibble: 521 × 4 #>    mo_group       mo           mo_group_name                   mo_name           #>    <mo>           <mo>         <chr>                           <chr>             #>  1 B_ACNTB_BMNN-C B_ACNTB_BMNN Acinetobacter baumannii complex Acinetobacter ba… #>  2 B_ACNTB_BMNN-C B_ACNTB_CLCC Acinetobacter baumannii complex Acinetobacter ca… #>  3 B_ACNTB_BMNN-C B_ACNTB_DJKS Acinetobacter baumannii complex Acinetobacter di… #>  4 B_ACNTB_BMNN-C B_ACNTB_NSCM Acinetobacter baumannii complex Acinetobacter no… #>  5 B_ACNTB_BMNN-C B_ACNTB_PITT Acinetobacter baumannii complex Acinetobacter pi… #>  6 B_ACNTB_BMNN-C B_ACNTB_SFRT Acinetobacter baumannii complex Acinetobacter se… #>  7 B_BCTRD_FRGL-C B_BCTRD_FRGL Bacteroides fragilis complex    Bacteroides frag… #>  8 B_BCTRD_FRGL-C B_BCTRD_OVTS Bacteroides fragilis complex    Bacteroides ovat… #>  9 B_BCTRD_FRGL-C B_BCTRD_THTT Bacteroides fragilis complex    Bacteroides thet… #> 10 B_BCTRD_FRGL-C B_BCTRD_VLGT Bacteroides fragilis complex    Bacteroides vulg… #> # ℹ 511 more rows  # these are all species in the Bacteroides fragilis group, as per WHONET: microorganisms.groups[microorganisms.groups$mo_group == \"B_BCTRD_FRGL-C\", ] #> # A tibble: 5 × 4 #>   mo_group       mo           mo_group_name                mo_name               #>   <mo>           <mo>         <chr>                        <chr>                 #> 1 B_BCTRD_FRGL-C B_BCTRD_FRGL Bacteroides fragilis complex Bacteroides fragilis  #> 2 B_BCTRD_FRGL-C B_BCTRD_OVTS Bacteroides fragilis complex Bacteroides ovatus    #> 3 B_BCTRD_FRGL-C B_BCTRD_THTT Bacteroides fragilis complex Bacteroides thetaiot… #> 4 B_BCTRD_FRGL-C B_BCTRD_VLGT Bacteroides fragilis complex Bacteroides vulgatus  #> 5 B_BCTRD_FRGL-C B_PRBCT_DSTS Bacteroides fragilis complex Parabacteroides dist…"},{"path":"https://msberends.github.io/AMR/reference/microorganisms.html","id":null,"dir":"Reference","previous_headings":"","what":"Data Set with 52 171 Microorganisms — microorganisms","title":"Data Set with 52 171 Microorganisms — microorganisms","text":"data set containing full microbial taxonomy (last updated: January 8th, 2024) five kingdoms List Prokaryotic names Standing Nomenclature (LPSN) Global Biodiversity Information Facility (GBIF). data set backbone AMR package. MO codes can looked using .mo().","code":""},{"path":"https://msberends.github.io/AMR/reference/microorganisms.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Data Set with 52 171 Microorganisms — microorganisms","text":"","code":"microorganisms"},{"path":"https://msberends.github.io/AMR/reference/microorganisms.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data Set with 52 171 Microorganisms — microorganisms","text":"tibble 52 171 observations 23 variables: mo ID microorganism used package. unique identifier. fullname Full name, like \"Escherichia coli\". taxonomic ranks genus, species subspecies, 'pasted' text genus, species, subspecies. taxonomic ranks higher genus, name taxon. unique identifier. status  Status taxon, either \"accepted\" \"synonym\" kingdom, phylum, class, order, family, genus, species, subspecies Taxonomic rank microorganism rank Text taxonomic rank microorganism, \"species\" \"genus\" ref Author(s) year related scientific publication. contains first surname year latest authors, e.g. \"Wallis et al. 2006 emend. Smith Jones 2018\" becomes \"Smith et al., 2018\". field directly retrieved source specified column source. Moreover, accents removed comply CRAN allows ASCII characters. lpsn Identifier ('Record number') List Prokaryotic names Standing Nomenclature (LPSN). first/highest LPSN identifier keep one identifier per row. example, Acetobacter ascendens LPSN Record number 7864 11011. first available microorganisms data set. oxygen_tolerance  Oxygen tolerance, either \"aerobe\", \"anaerobe\", \"anaerobe/microaerophile\", \"facultative anaerobe\", \"likely facultative anaerobe\", \"microaerophile\". data retrieved BacDive (see Source). Items contain \"likely\" missing BacDive extrapolated species within genus guess oxygen tolerance. Currently 73.4% ~37 000 bacteria data set contain oxygen tolerance. lpsn_parent LPSN identifier parent taxon lpsn_renamed_to LPSN identifier currently valid taxon gbif Identifier ('taxonID') Global Biodiversity Information Facility (GBIF) gbif_parent GBIF identifier parent taxon gbif_renamed_to GBIF identifier currently valid taxon source Either \"GBIF\", \"LPSN\", \"manually added\" (see Source) prevalence Prevalence microorganism based Bartlett et al. (2022, doi:10.1099/mic.0.001269 ), see mo_matching_score() full explanation snomed Systematized Nomenclature Medicine (SNOMED) code microorganism, version July 1st, 2021 (see Source). Use mo_snomed() retrieve quickly, see mo_property().","code":""},{"path":"https://msberends.github.io/AMR/reference/microorganisms.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data Set with 52 171 Microorganisms — microorganisms","text":"Parte, AC et al. (2020). List Prokaryotic names Standing Nomenclature (LPSN) moves DSMZ. International Journal Systematic Evolutionary Microbiology, 70, 5607-5612; doi:10.1099/ijsem.0.004332 . Accessed https://lpsn.dsmz.de December 11th, 2022. GBIF Secretariat (2023). GBIF Backbone Taxonomy. Checklist dataset doi:10.15468/39omei . Accessed https://www.gbif.org January 8th, 2024. Reimer, LC et al. (2022). BacDive 2022: knowledge base standardized bacterial archaeal data. Nucleic Acids Res., 50(D1):D741-D74; doi:10.1093/nar/gkab961 . Accessed https://bacdive.dsmz.de May 12th, 2023. Public Health Information Network Vocabulary Access Distribution System (PHIN VADS). US Edition SNOMED CT 1 September 2020. Value Set Name 'Microorganism', OID 2.16.840.1.114222.4.11.1009 (v12). URL: https://phinvads.cdc.gov Grimont et al. (2007). Antigenic Formulae Salmonella Serovars, 9th Edition. Collaborating Centre Reference Research Salmonella (WHOCC-SALM). Bartlett et al. (2022). comprehensive list bacterial pathogens infecting humans Microbiology 168:001269; doi:10.1099/mic.0.001269","code":""},{"path":"https://msberends.github.io/AMR/reference/microorganisms.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Data Set with 52 171 Microorganisms — microorganisms","text":"Please note entries based List Prokaryotic names Standing Nomenclature (LPSN) Global Biodiversity Information Facility (GBIF) (see ). Since sources incorporate entries based (recent) publications International Journal Systematic Evolutionary Microbiology (IJSEM), can happen year publication sometimes later one might expect. example, Staphylococcus pettenkoferi described first time Diagnostic Microbiology Infectious Disease 2002 (doi:10.1016/s0732-8893(02)00399-1 ), 2007 publication IJSEM followed (doi:10.1099/ijs.0.64381-0 ). Consequently, AMR package returns 2007 mo_year(\"S. pettenkoferi\").","code":""},{"path":"https://msberends.github.io/AMR/reference/microorganisms.html","id":"included-taxa","dir":"Reference","previous_headings":"","what":"Included Taxa","title":"Data Set with 52 171 Microorganisms — microorganisms","text":"Included taxonomic data : ~37 000 (sub)species kingdoms Archaea Bacteria ~7 900 (sub)species kingdom Fungi. kingdom Fungi large taxon almost 300,000 different (sub)species, microbial (rather macroscopic, like mushrooms). , fungi fit scope package. relevant fungi covered (species Aspergillus, Candida, Cryptococcus, Histoplasma, Pneumocystis, Saccharomyces Trichophyton). ~5 100 (sub)species kingdom Protozoa ~1 400 (sub)species 43 relevant genera kingdom Animalia (Strongyloides Taenia) ~9 800 previously accepted names included (sub)species (taxonomically renamed) complete taxonomic tree included (sub)species: kingdom subspecies identifier parent taxons year first author related scientific publication","code":""},{"path":"https://msberends.github.io/AMR/reference/microorganisms.html","id":"manual-additions","dir":"Reference","previous_headings":"","what":"Manual additions","title":"Data Set with 52 171 Microorganisms — microorganisms","text":"convenience, entries added manually: ~1 500 entries Salmonella, city-like serovars groups H 36 species groups (beta-haemolytic Streptococcus groups K, coagulase-negative Staphylococcus (CoNS), Mycobacterium tuberculosis complex, etc.), group compositions stored microorganisms.groups data set 1 entry Blastocystis (B.  hominis), although officially exist (Noel et al. 2005, PMID 15634993) 1 entry Moraxella (M. catarrhalis), formally named Branhamella catarrhalis (Catlin, 1970) though change never accepted within field clinical microbiology 8 'undefined' entries (unknown, unknown Gram-negatives, unknown Gram-positives, unknown yeast, unknown fungus, unknown anaerobic Gram-pos/Gram-neg bacteria) syntax used transform original data cleansed R format, can found : https://github.com/msberends/AMR/blob/main/data-raw/reproduction_of_microorganisms.R.","code":""},{"path":"https://msberends.github.io/AMR/reference/microorganisms.html","id":"direct-download","dir":"Reference","previous_headings":"","what":"Direct download","title":"Data Set with 52 171 Microorganisms — microorganisms","text":"Like data sets package, data set publicly available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":"https://msberends.github.io/AMR/reference/microorganisms.html","id":"about-the-records-from-lpsn-see-source-","dir":"Reference","previous_headings":"","what":"About the Records from LPSN (see Source)","title":"Data Set with 52 171 Microorganisms — microorganisms","text":"LPSN main source bacteriological taxonomy AMR package. List Prokaryotic names Standing Nomenclature (LPSN) provides comprehensive information nomenclature prokaryotes. LPSN free use service founded Jean P. Euzeby 1997 later maintained Aidan C. Parte.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/microorganisms.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Data Set with 52 171 Microorganisms — microorganisms","text":"","code":"microorganisms #> # A tibble: 52,171 × 23 #>    mo               fullname      status kingdom phylum class order family genus #>    <mo>             <chr>         <chr>  <chr>   <chr>  <chr> <chr> <chr>  <chr> #>  1 B_GRAMN          (unknown Gra… accep… Bacter… (unkn… (unk… (unk… \"(unk… \"(un… #>  2 B_GRAMP          (unknown Gra… accep… Bacter… (unkn… (unk… (unk… \"(unk… \"(un… #>  3 B_ANAER-NEG      (unknown ana… accep… Bacter… (unkn… (unk… (unk… \"(unk… \"(un… #>  4 B_ANAER-POS      (unknown ana… accep… Bacter… (unkn… (unk… (unk… \"(unk… \"(un… #>  5 B_ANAER          (unknown ana… accep… Bacter… (unkn… (unk… (unk… \"(unk… \"(un… #>  6 F_FUNGUS         (unknown fun… accep… Fungi   (unkn… (unk… (unk… \"(unk… \"(un… #>  7   UNKNOWN        (unknown nam… accep… (unkno… (unkn… (unk… (unk… \"(unk… \"(un… #>  8 F_YEAST          (unknown yea… accep… Fungi   (unkn… (unk… (unk… \"(unk… \"(un… #>  9 B_[FAM]_ABDTBCTR Abditibacter… accep… Bacter… Abdit… Abdi… Abdi… \"Abdi… \"\"    #> 10 B_[ORD]_ABDTBCTR Abditibacter… accep… Bacter… Abdit… Abdi… Abdi… \"\"     \"\"    #> # ℹ 52,161 more rows #> # ℹ 14 more variables: species <chr>, subspecies <chr>, rank <chr>, ref <chr>, #> #   oxygen_tolerance <chr>, source <chr>, lpsn <chr>, lpsn_parent <chr>, #> #   lpsn_renamed_to <chr>, gbif <chr>, gbif_parent <chr>, #> #   gbif_renamed_to <chr>, prevalence <dbl>, snomed <list>"},{"path":"https://msberends.github.io/AMR/reference/mo_matching_score.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the Matching Score for Microorganisms — mo_matching_score","title":"Calculate the Matching Score for Microorganisms — mo_matching_score","text":"algorithm used .mo() mo_* functions determine probable match taxonomic records based user input.","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_matching_score.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate the Matching Score for Microorganisms — mo_matching_score","text":"","code":"mo_matching_score(x, n)"},{"path":"https://msberends.github.io/AMR/reference/mo_matching_score.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate the Matching Score for Microorganisms — mo_matching_score","text":"x user input value(s) n full taxonomic name, exists microorganisms$fullname","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_matching_score.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculate the Matching Score for Microorganisms — mo_matching_score","text":"algorithm originally described : Berends MS et al. (2022). AMR: R Package Working Antimicrobial Resistance Data. Journal Statistical Software, 104(3), 1-31; doi:10.18637/jss.v104.i03 . Later, work Bartlett et al. bacterial pathogens infecting humans (2022, doi:10.1099/mic.0.001269 ) incorporated.","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_matching_score.html","id":"matching-score-for-microorganisms","dir":"Reference","previous_headings":"","what":"Matching Score for Microorganisms","title":"Calculate the Matching Score for Microorganisms — mo_matching_score","text":"ambiguous user input .mo() mo_* functions, returned results chosen based matching score using mo_matching_score(). matching score \\(m\\), calculated :  : \\(x\\) user input; \\(n\\) taxonomic name (genus, species, subspecies); \\(l_n\\) length \\(n\\); \\(lev\\) Levenshtein distance function (counting insertion 1, deletion substitution 2) needed change \\(x\\) \\(n\\); \\(p_n\\) human pathogenic prevalence group \\(n\\), described ; \\(k_n\\) taxonomic kingdom \\(n\\), set Bacteria = 1, Fungi = 1.25, Protozoa = 1.5, Archaea = 2, others = 3. grouping human pathogenic prevalence \\(p\\) based recent work Bartlett et al. (2022, doi:10.1099/mic.0.001269 ) extensively studied medical-scientific literature categorise bacterial species groups: Established, taxonomic species infected least three persons three references. records prevalence = 1.0 microorganisms data set; Putative, taxonomic species fewer three known cases. records prevalence = 1.25 microorganisms data set. Furthermore, genus present established list also prevalence = 1.0 microorganisms data set; genus present putative list prevalence = 1.25 microorganisms data set; species subspecies genus present two aforementioned groups, prevalence = 1.5 microorganisms data set; non-bacterial genus, species subspecies genus present following list, prevalence = 1.25 microorganisms data set: Absidia, Acanthamoeba, Acremonium, Aedes, Alternaria, Amoeba, Ancylostoma, Angiostrongylus, Anisakis, Anopheles, Apophysomyces, Arthroderma, Aspergillus, Aureobasidium, Basidiobolus, Beauveria, Blastocystis, Blastomyces, Candida, Capillaria, Chaetomium, Chrysonilia, Chrysosporium, Cladophialophora, Cladosporium, Conidiobolus, Contracaecum, Cordylobia, Cryptococcus, Curvularia, Demodex, Dermatobia, Dientamoeba, Diphyllobothrium, Dirofilaria, Echinostoma, Entamoeba, Enterobius, Exophiala, Exserohilum, Fasciola, Fonsecaea, Fusarium, Geotrichum, Giardia, Haloarcula, Halobacterium, Halococcus, Hendersonula, Heterophyes, Histomonas, Histoplasma, Hymenolepis, Hypomyces, Hysterothylacium, Kloeckera, Kodamaea, Leishmania, Lichtheimia, Lodderomyces, Malassezia, Malbranchea, Metagonimus, Meyerozyma, Microsporidium, Microsporum, Millerozyma, Mortierella, Mucor, Mycocentrospora, Necator, Nectria, Ochroconis, Oesophagostomum, Oidiodendron, Opisthorchis, Paecilomyces, Pediculus, Penicillium, Phlebotomus, Phoma, Pichia, Piedraia, Pithomyces, Pityrosporum, Pneumocystis, Pseudallescheria, Pseudoterranova, Pulex, Rhizomucor, Rhizopus, Rhodotorula, Saccharomyces, Saprochaete, Sarcoptes, Scedosporium, Scolecobasidium, Scopulariopsis, Scytalidium, Spirometra, Sporobolomyces, Sporotrichum, Stachybotrys, Strongyloides, Syngamus, Taenia, Talaromyces, Toxocara, Trichinella, Trichobilharzia, Trichoderma, Trichomonas, Trichophyton, Trichosporon, Trichostrongylus, Trichuris, Tritirachium, Trombicula, Trypanosoma, Tunga, Verticillium, Wuchereria; records prevalence = 2.0 microorganisms data set. calculating matching score, characters \\(x\\) \\(n\\) ignored -Z, -z, 0-9, spaces parentheses. matches sorted descending matching score user input values, top match returned. lead effect e.g., \"E. coli\" return microbial ID Escherichia coli (\\(m = 0.688\\), highly prevalent microorganism found humans) Entamoeba coli (\\(m = 0.381\\), less prevalent microorganism humans), although latter alphabetically come first.","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_matching_score.html","id":"reference-data-publicly-available","dir":"Reference","previous_headings":"","what":"Reference Data Publicly Available","title":"Calculate the Matching Score for Microorganisms — mo_matching_score","text":"data sets AMR package (microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) publicly freely available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. also provide tab-separated plain text files machine-readable suitable input software program, laboratory information systems. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_matching_score.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate the Matching Score for Microorganisms — mo_matching_score","text":"Dr. Matthijs Berends, 2018","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_matching_score.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate the Matching Score for Microorganisms — mo_matching_score","text":"","code":"mo_reset_session() #> ℹ Reset 17 previously matched input values.  as.mo(\"E. coli\") #> Class 'mo' #> [1] B_ESCHR_COLI mo_uncertainties() #> Matching scores are based on the resemblance between the input and the full #> taxonomic name, and the pathogenicity in humans. See ?mo_matching_score. #>  #> -------------------------------------------------------------------------------- #> \"E. coli\" -> Escherichia coli (B_ESCHR_COLI, 0.688) #> Also matched: Enterobacter cowanii (0.600), Eubacterium combesii #>               (0.600), Eggerthia catenaformis (0.591), Eubacterium callanderi #>               (0.591), Enterocloster citroniae (0.587), Eubacterium cylindroides #>               (0.583), Enterococcus casseliflavus (0.577), Enterobacter cloacae #>               cloacae (0.571), Enterobacter cloacae complex (0.571), and Ehrlichia #>               canis (0.567) #>  #> Only the first 10 other matches of each record are shown. Run #> print(mo_uncertainties(), n = ...) to view more entries, or save #> mo_uncertainties() to an object.  mo_matching_score(   x = \"E. coli\",   n = c(\"Escherichia coli\", \"Entamoeba coli\") ) #> [1] 0.6875000 0.3809524"},{"path":"https://msberends.github.io/AMR/reference/mo_property.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Properties of a Microorganism — mo_property","title":"Get Properties of a Microorganism — mo_property","text":"Use functions return specific property microorganism based latest accepted taxonomy. input values evaluated internally .mo(), makes possible use microbial abbreviations, codes names input. See Examples.","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_property.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Properties of a Microorganism — mo_property","text":"","code":"mo_name(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_fullname(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_shortname(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_subspecies(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_species(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_genus(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_family(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_order(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_class(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_phylum(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_kingdom(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_domain(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_type(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_status(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_pathogenicity(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_gramstain(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_is_gram_negative(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_is_gram_positive(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_is_yeast(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_is_intrinsic_resistant(   x,   ab,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_oxygen_tolerance(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_is_anaerobic(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_snomed(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_ref(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_authors(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_year(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_lpsn(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_gbif(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_rank(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_taxonomy(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_synonyms(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_current(x, language = get_AMR_locale(), ...)  mo_group_members(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_info(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_url(   x,   open = FALSE,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_property(   x,   property = \"fullname\",   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )"},{"path":"https://msberends.github.io/AMR/reference/mo_property.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Properties of a Microorganism — mo_property","text":"x character (vector) can coerced valid microorganism code .mo(). Can left blank auto-guessing column containing microorganism codes used data set, see Examples. language language translate text like \"growth\", defaults system language (see get_AMR_locale()) keep_synonyms logical indicate old, previously valid taxonomic names must preserved corrected currently accepted names. default FALSE, return note old taxonomic names processed. default can set package option AMR_keep_synonyms, .e. options(AMR_keep_synonyms = TRUE) options(AMR_keep_synonyms = FALSE). ... arguments passed .mo(), 'minimum_matching_score', 'ignore_pattern', 'remove_from_input' ab (vector ) text can coerced valid antibiotic drug code .ab() open browse URL using browseURL() property one column names microorganisms data set: \"mo\", \"fullname\", \"status\", \"kingdom\", \"phylum\", \"class\", \"order\", \"family\", \"genus\", \"species\", \"subspecies\", \"rank\", \"ref\", \"oxygen_tolerance\", \"source\", \"lpsn\", \"lpsn_parent\", \"lpsn_renamed_to\", \"gbif\", \"gbif_parent\", \"gbif_renamed_to\", \"prevalence\", \"snomed\", must \"shortname\"","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_property.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Properties of a Microorganism — mo_property","text":"integer case mo_year() ordered factor case mo_pathogenicity() list case mo_taxonomy(), mo_synonyms(), mo_snomed() mo_info() named character case mo_url() character cases","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_property.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get Properties of a Microorganism — mo_property","text":"functions , default, keep old taxonomic properties, synonyms automatically replaced current taxonomy. Take example Enterobacter aerogenes, initially named 1960 renamed Klebsiella aerogenes 2017: mo_genus(\"Enterobacter aerogenes\") return \"Klebsiella\" (note renaming) mo_genus(\"Enterobacter aerogenes\", keep_synonyms = TRUE) return \"Enterobacter\" (-per-session warning name outdated) mo_ref(\"Enterobacter aerogenes\") return \"Tindall et al., 2017\" (note) mo_ref(\"Enterobacter aerogenes\", keep_synonyms = TRUE) return \"Hormaeche et al., 1960\" (warning) short name (mo_shortname()) returns first character genus full species, \"E. coli\", species subspecies. Exceptions abbreviations staphylococci (\"CoNS\", Coagulase-Negative Staphylococci) beta-haemolytic streptococci (\"GBS\", Group B Streptococci). Please bear mind e.g. E. coli mean Escherichia coli (kingdom Bacteria) well Entamoeba coli (kingdom Protozoa). Returning full name done using .mo() internally, giving priority bacteria human pathogens, .e. \"E. coli\" considered Escherichia coli. result, mo_fullname(mo_shortname(\"Entamoeba coli\")) returns \"Escherichia coli\". Since top-level taxonomy sometimes referred 'kingdom' sometimes 'domain', functions mo_kingdom() mo_domain() return exact results. Determination human pathogenicity (mo_pathogenicity()) strongly based Bartlett et al. (2022, doi:10.1099/mic.0.001269 ). function returns factor levels Pathogenic, Potentially pathogenic, Non-pathogenic, Unknown. Determination Gram stain (mo_gramstain()) based taxonomic kingdom phylum. Originally, Cavalier-Smith defined -called subkingdoms Negibacteria Posibacteria (2002, PMID 11837318), considered phyla Posibacteria: Actinobacteria, Chloroflexi, Firmicutes, Tenericutes. phyla later renamed Actinomycetota, Chloroflexota, Bacillota, Mycoplasmatota (2021, PMID 34694987). Bacteria phyla considered Gram-positive AMR package, except members class Negativicutes (within phylum Bacillota) Gram-negative. bacteria considered Gram-negative. Species outside kingdom Bacteria return value NA. Functions mo_is_gram_negative() mo_is_gram_positive() always return TRUE FALSE (NA input NA MO code UNKNOWN), thus always return FALSE species outside taxonomic kingdom Bacteria. Determination yeasts (mo_is_yeast()) based taxonomic kingdom class. Budding yeasts fungi phylum Ascomycota, class Saccharomycetes (also called Hemiascomycetes). True yeasts aggregated underlying order Saccharomycetales. Thus, microorganisms member taxonomic class Saccharomycetes, function return TRUE. returns FALSE otherwise (NA input NA MO code UNKNOWN). Determination intrinsic resistance (mo_is_intrinsic_resistant()) based intrinsic_resistant data set, based 'EUCAST Expert Rules' 'EUCAST Intrinsic Resistance Unusual Phenotypes' v3.3 (2021). mo_is_intrinsic_resistant() function can vectorised argument x (input microorganisms) ab (input antibiotics). Determination bacterial oxygen tolerance (mo_oxygen_tolerance()) based BacDive, see Source. function mo_is_anaerobic() returns TRUE oxygen tolerance \"anaerobe\", indicting obligate anaerobic species genus. always returns FALSE species outside taxonomic kingdom Bacteria. function mo_url() return direct URL online database entry, also shows scientific reference concerned species. SNOMED codes (mo_snomed()) version July 1st, 2021. See Source microorganisms data set info. Old taxonomic names (-called 'synonyms') can retrieved mo_synonyms() (scientific reference name), current taxonomic name can retrieved mo_current(). functions return full names. output translated possible.","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_property.html","id":"matching-score-for-microorganisms","dir":"Reference","previous_headings":"","what":"Matching Score for Microorganisms","title":"Get Properties of a Microorganism — mo_property","text":"function uses .mo() internally, uses advanced algorithm translate arbitrary user input valid taxonomy using -called matching score. can read public algorithm MO matching score page.","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_property.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get Properties of a Microorganism — mo_property","text":"Berends MS et al. (2022). AMR: R Package Working Antimicrobial Resistance Data. Journal Statistical Software, 104(3), 1-31; doi:10.18637/jss.v104.i03 Becker K et al. (2014). Coagulase-Negative Staphylococci. Clin Microbiol Rev. 27(4): 870-926; doi:10.1128/CMR.00109-13 Becker K et al. (2019). Implications identifying recently defined members S. aureus complex, S. argenteus S. schweitzeri: position paper members ESCMID Study Group staphylococci Staphylococcal Diseases (ESGS). Clin Microbiol Infect; doi:10.1016/j.cmi.2019.02.028 Becker K et al. (2020). Emergence coagulase-negative staphylococci. Expert Rev Anti Infect Ther. 18(4):349-366; doi:10.1080/14787210.2020.1730813 Lancefield RC (1933). serological differentiation human groups hemolytic streptococci. J Exp Med. 57(4): 571-95; doi:10.1084/jem.57.4.571 Berends MS et al. (2022). Trends Occurrence Phenotypic Resistance Coagulase-Negative Staphylococci (CoNS) Found Human Blood Northern Netherlands 2013 2019/ Micro.rganisms 10(9), 1801; doi:10.3390/microorganisms10091801 Parte, AC et al. (2020). List Prokaryotic names Standing Nomenclature (LPSN) moves DSMZ. International Journal Systematic Evolutionary Microbiology, 70, 5607-5612; doi:10.1099/ijsem.0.004332 . Accessed https://lpsn.dsmz.de December 11th, 2022. GBIF Secretariat (2023). GBIF Backbone Taxonomy. Checklist dataset doi:10.15468/39omei . Accessed https://www.gbif.org January 8th, 2024. Reimer, LC et al. (2022). BacDive 2022: knowledge base standardized bacterial archaeal data. Nucleic Acids Res., 50(D1):D741-D74; doi:10.1093/nar/gkab961 . Accessed https://bacdive.dsmz.de May 12th, 2023. Public Health Information Network Vocabulary Access Distribution System (PHIN VADS). US Edition SNOMED CT 1 September 2020. Value Set Name 'Microorganism', OID 2.16.840.1.114222.4.11.1009 (v12). URL: https://phinvads.cdc.gov Bartlett et al. (2022). comprehensive list bacterial pathogens infecting humans Microbiology 168:001269; doi:10.1099/mic.0.001269","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_property.html","id":"reference-data-publicly-available","dir":"Reference","previous_headings":"","what":"Reference Data Publicly Available","title":"Get Properties of a Microorganism — mo_property","text":"data sets AMR package (microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) publicly freely available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. also provide tab-separated plain text files machine-readable suitable input software program, laboratory information systems. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/mo_property.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Properties of a Microorganism — mo_property","text":"","code":"# taxonomic tree -----------------------------------------------------------  mo_kingdom(\"Klebsiella pneumoniae\") #> [1] \"Bacteria\" mo_phylum(\"Klebsiella pneumoniae\") #> [1] \"Pseudomonadota\" mo_class(\"Klebsiella pneumoniae\") #> [1] \"Gammaproteobacteria\" mo_order(\"Klebsiella pneumoniae\") #> [1] \"Enterobacterales\" mo_family(\"Klebsiella pneumoniae\") #> [1] \"Enterobacteriaceae\" mo_genus(\"Klebsiella pneumoniae\") #> [1] \"Klebsiella\" mo_species(\"Klebsiella pneumoniae\") #> [1] \"pneumoniae\" mo_subspecies(\"Klebsiella pneumoniae\") #> [1] \"\"   # full names and short names -----------------------------------------------  mo_name(\"Klebsiella pneumoniae\") #> [1] \"Klebsiella pneumoniae\" mo_fullname(\"Klebsiella pneumoniae\") #> [1] \"Klebsiella pneumoniae\" mo_shortname(\"Klebsiella pneumoniae\") #> [1] \"K. pneumoniae\"   # other properties ---------------------------------------------------------  mo_pathogenicity(\"Klebsiella pneumoniae\") #> [1] Pathogenic #> Levels: Pathogenic < Potentially pathogenic < Non-pathogenic < Unknown mo_gramstain(\"Klebsiella pneumoniae\") #> [1] \"Gram-negative\" mo_snomed(\"Klebsiella pneumoniae\") #> [[1]] #> [1] \"1098101000112102\" \"446870005\"        \"1098201000112108\" \"409801009\"        #> [5] \"56415008\"         \"714315002\"        \"713926009\"        #>  mo_type(\"Klebsiella pneumoniae\") #> [1] \"Bacteria\" mo_rank(\"Klebsiella pneumoniae\") #> [1] \"species\" mo_url(\"Klebsiella pneumoniae\") #>                                Klebsiella pneumoniae  #> \"https://lpsn.dsmz.de/species/klebsiella-pneumoniae\"  mo_is_yeast(c(\"Candida\", \"Trichophyton\", \"Klebsiella\")) #> [1]  TRUE FALSE FALSE  mo_group_members(\"Streptococcus group A\") #> [1] \"Streptococcus pyogenes\" mo_group_members(c(\"Streptococcus group C\",                    \"Streptococcus group G\",                    \"Streptococcus group L\")) #> $`Streptococcus Group C` #> [1] \"Streptococcus dysgalactiae\"              #> [2] \"Streptococcus dysgalactiae dysgalactiae\" #> [3] \"Streptococcus dysgalactiae equisimilis\"  #> [4] \"Streptococcus equi\"                      #> [5] \"Streptococcus equi equi\"                 #> [6] \"Streptococcus equi ruminatorum\"          #> [7] \"Streptococcus equi zooepidemicus\"        #>  #> $`Streptococcus Group G` #> [1] \"Streptococcus canis\"                     #> [2] \"Streptococcus dysgalactiae\"              #> [3] \"Streptococcus dysgalactiae dysgalactiae\" #> [4] \"Streptococcus dysgalactiae equisimilis\"  #>  #> $`Streptococcus Group L` #> [1] \"Streptococcus dysgalactiae\"              #> [2] \"Streptococcus dysgalactiae dysgalactiae\" #> [3] \"Streptococcus dysgalactiae equisimilis\"  #>    # scientific reference -----------------------------------------------------  mo_ref(\"Klebsiella aerogenes\") #> [1] \"Tindall et al., 2017\" mo_authors(\"Klebsiella aerogenes\") #> [1] \"Tindall et al.\" mo_year(\"Klebsiella aerogenes\") #> [1] 2017 mo_lpsn(\"Klebsiella aerogenes\") #> [1] \"777146\" mo_gbif(\"Klebsiella aerogenes\") #> [1] \"9281703\" mo_synonyms(\"Klebsiella aerogenes\") #>   Hormaeche et al., 1960     Bascomb et al., 1971  #> \"Enterobacter aerogenes\"     \"Klebsiella mobilis\"    # abbreviations known in the field -----------------------------------------  mo_genus(\"MRSA\") #> [1] \"Staphylococcus\" mo_species(\"MRSA\") #> [1] \"aureus\" mo_shortname(\"VISA\") #> [1] \"S. aureus\" mo_gramstain(\"VISA\") #> [1] \"Gram-positive\"  mo_genus(\"EHEC\") #> [1] \"Escherichia\" mo_species(\"EIEC\") #> [1] \"coli\" mo_name(\"UPEC\") #> [1] \"Escherichia coli\"   # known subspecies ---------------------------------------------------------  mo_fullname(\"K. pneu rh\") #> [1] \"Klebsiella pneumoniae rhinoscleromatis\" mo_shortname(\"K. pneu rh\") #> [1] \"K. pneumoniae\"  # \\donttest{ # Becker classification, see ?as.mo ----------------------------------------  mo_fullname(\"Staph epidermidis\") #> [1] \"Staphylococcus epidermidis\" mo_fullname(\"Staph epidermidis\", Becker = TRUE) #> [1] \"Coagulase-negative Staphylococcus (CoNS)\" mo_shortname(\"Staph epidermidis\") #> [1] \"S. epidermidis\" mo_shortname(\"Staph epidermidis\", Becker = TRUE) #> [1] \"CoNS\"   # Lancefield classification, see ?as.mo ------------------------------------  mo_fullname(\"Strep agalactiae\") #> [1] \"Streptococcus agalactiae\" mo_fullname(\"Strep agalactiae\", Lancefield = TRUE) #> [1] \"Streptococcus Group B\" mo_shortname(\"Strep agalactiae\") #> [1] \"S. agalactiae\" mo_shortname(\"Strep agalactiae\", Lancefield = TRUE) #> [1] \"GBS\"   # language support  --------------------------------------------------------  mo_gramstain(\"Klebsiella pneumoniae\", language = \"de\") # German #> [1] \"Gramnegativ\" mo_gramstain(\"Klebsiella pneumoniae\", language = \"nl\") # Dutch #> [1] \"Gram-negatief\" mo_gramstain(\"Klebsiella pneumoniae\", language = \"es\") # Spanish #> [1] \"Gram negativo\" mo_gramstain(\"Klebsiella pneumoniae\", language = \"el\") # Greek #> [1] \"Αρνητικό κατά Gram\" mo_gramstain(\"Klebsiella pneumoniae\", language = \"uk\") # Ukrainian #> [1] \"Грамнегативні\"  # mo_type is equal to mo_kingdom, but mo_kingdom will remain untranslated mo_kingdom(\"Klebsiella pneumoniae\") #> [1] \"Bacteria\" mo_type(\"Klebsiella pneumoniae\") #> [1] \"Bacteria\" mo_kingdom(\"Klebsiella pneumoniae\", language = \"zh\") # Chinese, no effect #> [1] \"Bacteria\" mo_type(\"Klebsiella pneumoniae\", language = \"zh\") # Chinese, translated #> [1] \"细菌\"  mo_fullname(\"S. pyogenes\", Lancefield = TRUE, language = \"de\") #> [1] \"Streptococcus Gruppe A\" mo_fullname(\"S. pyogenes\", Lancefield = TRUE, language = \"uk\") #> [1] \"Streptococcus Група A\"   # other --------------------------------------------------------------------  # gram stains and intrinsic resistance can be used as a filter in dplyr verbs if (require(\"dplyr\")) {   example_isolates %>%     filter(mo_is_gram_positive()) %>%     count(mo_genus(), sort = TRUE) } #> ℹ Using column 'mo' as input for mo_is_gram_positive() #> ℹ Using column 'mo' as input for mo_genus() #> # A tibble: 18 × 2 #>    `mo_genus()`        n #>    <chr>           <int> #>  1 Staphylococcus    840 #>  2 Streptococcus     275 #>  3 Enterococcus       83 #>  4 Corynebacterium    17 #>  5 Micrococcus         6 #>  6 Gemella             3 #>  7 Aerococcus          2 #>  8 Cutibacterium       1 #>  9 Dermabacter         1 #> 10 Fusibacter          1 #> 11 Globicatella        1 #> 12 Granulicatella      1 #> 13 Lactobacillus       1 #> 14 Leuconostoc         1 #> 15 Listeria            1 #> 16 Paenibacillus       1 #> 17 Rothia              1 #> 18 Schaalia            1 if (require(\"dplyr\")) {   example_isolates %>%     filter(mo_is_intrinsic_resistant(ab = \"vanco\")) %>%     count(mo_genus(), sort = TRUE) } #> ℹ Using column 'mo' as input for mo_is_intrinsic_resistant() #> ℹ Using column 'mo' as input for mo_genus() #> # A tibble: 20 × 2 #>    `mo_genus()`         n #>    <chr>            <int> #>  1 Escherichia        467 #>  2 Klebsiella          77 #>  3 Proteus             39 #>  4 Pseudomonas         30 #>  5 Serratia            25 #>  6 Enterobacter        23 #>  7 Citrobacter         11 #>  8 Haemophilus          8 #>  9 Acinetobacter        6 #> 10 Morganella           6 #> 11 Pantoea              4 #> 12 Salmonella           3 #> 13 Neisseria            2 #> 14 Stenotrophomonas     2 #> 15 Campylobacter        1 #> 16 Enterococcus         1 #> 17 Hafnia               1 #> 18 Lactobacillus        1 #> 19 Leuconostoc          1 #> 20 Pseudescherichia     1  # get a list with the complete taxonomy (from kingdom to subspecies) mo_taxonomy(\"Klebsiella pneumoniae\") #> $kingdom #> [1] \"Bacteria\" #>  #> $phylum #> [1] \"Pseudomonadota\" #>  #> $class #> [1] \"Gammaproteobacteria\" #>  #> $order #> [1] \"Enterobacterales\" #>  #> $family #> [1] \"Enterobacteriaceae\" #>  #> $genus #> [1] \"Klebsiella\" #>  #> $species #> [1] \"pneumoniae\" #>  #> $subspecies #> [1] \"\" #>   # get a list with the taxonomy, the authors, Gram-stain, # SNOMED codes, and URL to the online database mo_info(\"Klebsiella pneumoniae\") #> $mo #> [1] \"B_KLBSL_PNMN\" #>  #> $kingdom #> [1] \"Bacteria\" #>  #> $phylum #> [1] \"Pseudomonadota\" #>  #> $class #> [1] \"Gammaproteobacteria\" #>  #> $order #> [1] \"Enterobacterales\" #>  #> $family #> [1] \"Enterobacteriaceae\" #>  #> $genus #> [1] \"Klebsiella\" #>  #> $species #> [1] \"pneumoniae\" #>  #> $subspecies #> [1] \"\" #>  #> $status #> [1] \"accepted\" #>  #> $synonyms #> NULL #>  #> $gramstain #> [1] \"Gram-negative\" #>  #> $oxygen_tolerance #> [1] \"aerobe\" #>  #> $url #> [1] \"https://lpsn.dsmz.de/species/klebsiella-pneumoniae\" #>  #> $ref #> [1] \"Trevisan, 1887\" #>  #> $snomed #> [1] \"1098101000112102\" \"446870005\"        \"1098201000112108\" \"409801009\"        #> [5] \"56415008\"         \"714315002\"        \"713926009\"        #>  #> $lpsn #> [1] \"777151\" #>  #> $gbif #> [1] \"3221874\" #>  #> $group_members #> character(0) #>  # }"},{"path":"https://msberends.github.io/AMR/reference/mo_source.html","id":null,"dir":"Reference","previous_headings":"","what":"User-Defined Reference Data Set for Microorganisms — mo_source","title":"User-Defined Reference Data Set for Microorganisms — mo_source","text":"functions can used predefine reference used .mo() consequently mo_* functions (mo_genus() mo_gramstain()). fastest way organisation (analysis) specific codes picked translated package, since bother setting .","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_source.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"User-Defined Reference Data Set for Microorganisms — mo_source","text":"","code":"set_mo_source(   path,   destination = getOption(\"AMR_mo_source\", \"~/mo_source.rds\") )  get_mo_source(destination = getOption(\"AMR_mo_source\", \"~/mo_source.rds\"))"},{"path":"https://msberends.github.io/AMR/reference/mo_source.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"User-Defined Reference Data Set for Microorganisms — mo_source","text":"path location reference file, can text file (comma-, tab- pipe-separated) Excel file (see Details). Can also \"\", NULL FALSE delete reference file. destination destination compressed data file - default user's home directory.","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_source.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"User-Defined Reference Data Set for Microorganisms — mo_source","text":"reference file can text file separated commas (CSV) tabs pipes, Excel file (either 'xls' 'xlsx' format) R object file (extension '.rds'). use Excel file, need readxl package installed. set_mo_source() check file validity: must data.frame, must column named \"mo\" contains values microorganisms$mo microorganisms$fullname must reference column defined values. tests pass, set_mo_source() read file R ask export \"~/mo_source.rds\". CRAN policy disallows packages write file system, although 'exceptions may allowed interactive sessions package obtains confirmation user'. reason, function works interactive sessions user can specifically confirm allow file created. destination file can set destination argument defaults user's home directory. can also set package option AMR_mo_source, e.g. options(AMR_mo_source = \"/location/file.rds\"). created compressed data file \"mo_source.rds\" used default MO determination (function .mo() consequently mo_* functions like mo_genus() mo_gramstain()). location timestamp original file saved attribute compressed data file. function get_mo_source() return data set reading \"mo_source.rds\" readRDS(). original file changed (checking location timestamp original file), call set_mo_source() update data file automatically used interactive session. Reading Excel file (.xlsx) one row size 8-9 kB. compressed file created set_mo_source() size 0.1 kB can read get_mo_source() couple microseconds (millionths second).","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_source.html","id":"how-to-setup","dir":"Reference","previous_headings":"","what":"How to Setup","title":"User-Defined Reference Data Set for Microorganisms — mo_source","text":"Imagine data sheet Excel file. first column contains organisation specific codes, second column contains valid taxonomic names:   save \"home//ourcodes.xlsx\". Now set source:   now created file \"~/mo_source.rds\" contents Excel file. first column foreign values 'mo' column kept creating RDS file. now can use functions:   edit Excel file , say, adding row 4 like :   ...new usage MO function package update data file:   delete reference data file, just use \"\", NULL FALSE input set_mo_source():   original file (previous case Excel file) moved deleted, mo_source.rds file removed upon next use .mo() mo_* function.","code":"|         A          |            B          | --|--------------------|-----------------------| 1 | Organisation XYZ   | mo                    | 2 | lab_mo_ecoli       | Escherichia coli      | 3 | lab_mo_kpneumoniae | Klebsiella pneumoniae | 4 |                    |                       | set_mo_source(\"home/me/ourcodes.xlsx\") #> NOTE: Created mo_source file '/Users/me/mo_source.rds' (0.3 kB) from #>       '/Users/me/Documents/ourcodes.xlsx' (9 kB), columns #>       \"Organisation XYZ\" and \"mo\" as.mo(\"lab_mo_ecoli\") #> Class 'mo' #> [1] B_ESCHR_COLI  mo_genus(\"lab_mo_kpneumoniae\") #> [1] \"Klebsiella\"  # other input values still work too as.mo(c(\"Escherichia coli\", \"E. coli\", \"lab_mo_ecoli\")) #> NOTE: Translation to one microorganism was guessed with uncertainty. #>       Use mo_uncertainties() to review it. #> Class 'mo' #> [1] B_ESCHR_COLI B_ESCHR_COLI B_ESCHR_COLI |         A          |            B          | --|--------------------|-----------------------| 1 | Organisation XYZ   | mo                    | 2 | lab_mo_ecoli       | Escherichia coli      | 3 | lab_mo_kpneumoniae | Klebsiella pneumoniae | 4 | lab_Staph_aureus   | Staphylococcus aureus | 5 |                    |                       | as.mo(\"lab_mo_ecoli\") #> NOTE: Updated mo_source file '/Users/me/mo_source.rds' (0.3 kB) from #>       '/Users/me/Documents/ourcodes.xlsx' (9 kB), columns #>        \"Organisation XYZ\" and \"mo\" #> Class 'mo' #> [1] B_ESCHR_COLI  mo_genus(\"lab_Staph_aureus\") #> [1] \"Staphylococcus\" set_mo_source(NULL) #> Removed mo_source file '/Users/me/mo_source.rds'"},{"path":"https://msberends.github.io/AMR/reference/pca.html","id":null,"dir":"Reference","previous_headings":"","what":"Principal Component Analysis (for AMR) — pca","title":"Principal Component Analysis (for AMR) — pca","text":"Performs principal component analysis (PCA) based data set automatic determination afterwards plotting groups labels, automatic filtering suitable (.e. non-empty numeric) variables.","code":""},{"path":"https://msberends.github.io/AMR/reference/pca.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Principal Component Analysis (for AMR) — pca","text":"","code":"pca(   x,   ...,   retx = TRUE,   center = TRUE,   scale. = TRUE,   tol = NULL,   rank. = NULL )"},{"path":"https://msberends.github.io/AMR/reference/pca.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Principal Component Analysis (for AMR) — pca","text":"x data.frame containing numeric columns ... columns x selected PCA, can unquoted since supports quasiquotation. retx logical value indicating whether rotated variables     returned. center logical value indicating whether variables     shifted zero centered. Alternately, vector     length equal number columns x can supplied.     value passed scale. scale. logical value indicating whether variables     scaled unit variance analysis takes     place.  default FALSE consistency S,     general scaling advisable.  Alternatively, vector length     equal number columns x can supplied.      value passed scale. tol value indicating magnitude components     omitted. (Components omitted     standard deviations less equal tol times     standard deviation first component.)  default null     setting, components omitted (unless rank. specified     less min(dim(x)).).  settings tol     tol = 0 tol = sqrt(.Machine$double.eps),     omit essentially constant components. rank. optionally, number specifying maximal rank, .e.,     maximal number principal components used.  Can set     alternative addition tol, useful notably     desired rank considerably smaller dimensions matrix.","code":""},{"path":"https://msberends.github.io/AMR/reference/pca.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Principal Component Analysis (for AMR) — pca","text":"object classes pca prcomp","code":""},{"path":"https://msberends.github.io/AMR/reference/pca.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Principal Component Analysis (for AMR) — pca","text":"pca() function takes data.frame input performs actual PCA R function prcomp(). result pca() function prcomp object, additional attribute non_numeric_cols vector column names columns contain numeric values. probably groups labels, used ggplot_pca().","code":""},{"path":"https://msberends.github.io/AMR/reference/pca.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Principal Component Analysis (for AMR) — pca","text":"","code":"# `example_isolates` is a data set available in the AMR package. # See ?example_isolates.  # \\donttest{ if (require(\"dplyr\")) {   # calculate the resistance per group first   resistance_data <- example_isolates %>%     group_by(       order = mo_order(mo), # group on anything, like order       genus = mo_genus(mo)     ) %>% #   and genus as we do here;     filter(n() >= 30) %>% # filter on only 30 results per group     summarise_if(is.sir, resistance) # then get resistance of all drugs    # now conduct PCA for certain antimicrobial drugs   pca_result <- resistance_data %>%     pca(AMC, CXM, CTX, CAZ, GEN, TOB, TMP, SXT)    pca_result   summary(pca_result)    # old base R plotting method:   biplot(pca_result)   # new ggplot2 plotting method using this package:   if (require(\"ggplot2\")) {     ggplot_pca(pca_result)      ggplot_pca(pca_result) +       scale_colour_viridis_d() +       labs(title = \"Title here\")   } } #> Warning: There were 73 warnings in `summarise()`. #> The first warning was: #> ℹ In argument: `PEN = (function (..., minimum = 30, as_percent = FALSE, #>   only_all_tested = FALSE) ...`. #> ℹ In group 5: `order = \"Lactobacillales\"` and `genus = \"Enterococcus\"`. #> Caused by warning: #> ! Introducing NA: only 14 results available for PEN in group: order = #> \"Lactobacillales\", genus = \"Enterococcus\" (minimum = 30). #> ℹ Run `dplyr::last_dplyr_warnings()` to see the 72 remaining warnings. #> ℹ Columns selected for PCA: \"AMC\", \"CAZ\", \"CTX\", \"CXM\", \"GEN\", \"SXT\", #>   \"TMP\", and \"TOB\". Total observations available: 7. #> Groups (n=4, named as 'order'): #> [1] \"Caryophanales\"    \"Enterobacterales\" \"Lactobacillales\"  \"Pseudomonadales\"  #>    # }"},{"path":"https://msberends.github.io/AMR/reference/plot.html","id":null,"dir":"Reference","previous_headings":"","what":"Plotting for Classes sir, mic and disk — plot","title":"Plotting for Classes sir, mic and disk — plot","text":"Functions plot classes sir, mic disk, support base R ggplot2. Especially scale_*_mic() functions relevant wrappers plot MIC values ggplot2. allows custom MIC ranges plot intermediate log2 levels missing MIC values.","code":""},{"path":"https://msberends.github.io/AMR/reference/plot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plotting for Classes sir, mic and disk — plot","text":"","code":"scale_x_mic(keep_operators = \"edges\", mic_range = NULL, drop = FALSE, ...)  scale_y_mic(keep_operators = \"edges\", mic_range = NULL, drop = FALSE, ...)  scale_colour_mic(keep_operators = \"edges\", mic_range = NULL, drop = FALSE, ...)  scale_fill_mic(keep_operators = \"edges\", mic_range = NULL, drop = FALSE, ...)  # S3 method for mic plot(   x,   mo = NULL,   ab = NULL,   guideline = \"EUCAST\",   main = deparse(substitute(x)),   ylab = translate_AMR(\"Frequency\", language = language),   xlab = translate_AMR(\"Minimum Inhibitory Concentration (mg/L)\", language = language),   colours_SIR = c(\"#3CAEA3\", \"#F6D55C\", \"#ED553B\"),   language = get_AMR_locale(),   expand = TRUE,   include_PKPD = getOption(\"AMR_include_PKPD\", TRUE),   breakpoint_type = getOption(\"AMR_breakpoint_type\", \"human\"),   ... )  # S3 method for mic autoplot(   object,   mo = NULL,   ab = NULL,   guideline = \"EUCAST\",   title = deparse(substitute(object)),   ylab = translate_AMR(\"Frequency\", language = language),   xlab = translate_AMR(\"Minimum Inhibitory Concentration (mg/L)\", language = language),   colours_SIR = c(\"#3CAEA3\", \"#F6D55C\", \"#ED553B\"),   language = get_AMR_locale(),   expand = TRUE,   include_PKPD = getOption(\"AMR_include_PKPD\", TRUE),   breakpoint_type = getOption(\"AMR_breakpoint_type\", \"human\"),   ... )  # S3 method for mic fortify(object, ...)  # S3 method for disk plot(   x,   main = deparse(substitute(x)),   ylab = translate_AMR(\"Frequency\", language = language),   xlab = translate_AMR(\"Disk diffusion diameter (mm)\", language = language),   mo = NULL,   ab = NULL,   guideline = \"EUCAST\",   colours_SIR = c(\"#3CAEA3\", \"#F6D55C\", \"#ED553B\"),   language = get_AMR_locale(),   expand = TRUE,   include_PKPD = getOption(\"AMR_include_PKPD\", TRUE),   breakpoint_type = getOption(\"AMR_breakpoint_type\", \"human\"),   ... )  # S3 method for disk autoplot(   object,   mo = NULL,   ab = NULL,   title = deparse(substitute(object)),   ylab = translate_AMR(\"Frequency\", language = language),   xlab = translate_AMR(\"Disk diffusion diameter (mm)\", language = language),   guideline = \"EUCAST\",   colours_SIR = c(\"#3CAEA3\", \"#F6D55C\", \"#ED553B\"),   language = get_AMR_locale(),   expand = TRUE,   include_PKPD = getOption(\"AMR_include_PKPD\", TRUE),   breakpoint_type = getOption(\"AMR_breakpoint_type\", \"human\"),   ... )  # S3 method for disk fortify(object, ...)  # S3 method for sir plot(   x,   ylab = translate_AMR(\"Percentage\", language = language),   xlab = translate_AMR(\"Antimicrobial Interpretation\", language = language),   main = deparse(substitute(x)),   language = get_AMR_locale(),   ... )  # S3 method for sir autoplot(   object,   title = deparse(substitute(object)),   xlab = translate_AMR(\"Antimicrobial Interpretation\", language = language),   ylab = translate_AMR(\"Frequency\", language = language),   colours_SIR = c(\"#3CAEA3\", \"#F6D55C\", \"#ED553B\"),   language = get_AMR_locale(),   ... )  # S3 method for sir fortify(object, ...)"},{"path":"https://msberends.github.io/AMR/reference/plot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plotting for Classes sir, mic and disk — plot","text":"keep_operators character specifying handle operators (> <=) input. Accepts one three values: \"\" (TRUE) keep operators, \"none\" (FALSE) remove operators, \"edges\" keep operators ends range. mic_range manual range limit MIC values, e.g., mic_range = c(0.001, 32). Use NA set limit one side, e.g., mic_range = c(NA, 32). drop logical remove intermediate MIC values, defaults FALSE ... arguments passed methods x, object values created .mic(), .disk() .sir() (random_* variants, random_mic()) mo (vector ) text can coerced valid microorganism code .mo() ab (vector ) text can coerced valid antimicrobial drug code .ab() guideline interpretation guideline use - default latest included EUCAST guideline, see Details main, title title plot xlab, ylab axis title colours_SIR colours use filling bars, must vector three values (order S, R). default colours colour-blind friendly. language language used translate 'Susceptible', 'Increased exposure'/'Intermediate' 'Resistant' - default system language (see get_AMR_locale()) can overwritten setting package option AMR_locale, e.g. options(AMR_locale = \"de\"), see translate. Use language = NULL language = \"\" prevent translation. expand logical indicate whether range x axis expanded lowest highest value. MIC values, intermediate values factors 2 starting highest MIC value. disk diameters, whole diameter range filled. include_PKPD logical indicate PK/PD clinical breakpoints must applied last resort - default TRUE. Can also set package option AMR_include_PKPD. breakpoint_type type breakpoints use, either \"ECOFF\", \"animal\", \"human\". ECOFF stands Epidemiological Cut-values. default \"human\", can also set package option AMR_breakpoint_type. host set values veterinary species, automatically set \"animal\".","code":""},{"path":"https://msberends.github.io/AMR/reference/plot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plotting for Classes sir, mic and disk — plot","text":"autoplot() functions return ggplot model extendible ggplot2 function. fortify() functions return data.frame extension usage ggplot2::ggplot() function.","code":""},{"path":"https://msberends.github.io/AMR/reference/plot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plotting for Classes sir, mic and disk — plot","text":"interpretation \"\" named \"Increased exposure\" EUCAST guidelines since 2019, named \"Intermediate\" cases. interpreting MIC values well disk diffusion diameters, supported guidelines used input guideline argument : \"EUCAST 2024\", \"EUCAST 2023\", \"EUCAST 2022\", \"EUCAST 2021\", \"EUCAST 2020\", \"EUCAST 2019\", \"EUCAST 2018\", \"EUCAST 2017\", \"EUCAST 2016\", \"EUCAST 2015\", \"EUCAST 2014\", \"EUCAST 2013\", \"EUCAST 2012\", \"EUCAST 2011\", \"CLSI 2024\", \"CLSI 2023\", \"CLSI 2022\", \"CLSI 2021\", \"CLSI 2020\", \"CLSI 2019\", \"CLSI 2018\", \"CLSI 2017\", \"CLSI 2016\", \"CLSI 2015\", \"CLSI 2014\", \"CLSI 2013\", \"CLSI 2012\", \"CLSI 2011\". Simply using \"CLSI\" \"EUCAST\" input automatically select latest version guideline.","code":""},{"path":"https://msberends.github.io/AMR/reference/plot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plotting for Classes sir, mic and disk — plot","text":"","code":"some_mic_values <- random_mic(size = 100) some_disk_values <- random_disk(size = 100, mo = \"Escherichia coli\", ab = \"cipro\") some_sir_values <- random_sir(50, prob_SIR = c(0.55, 0.05, 0.30))  plot(some_mic_values)  plot(some_disk_values)  plot(some_sir_values)   # when providing the microorganism and antibiotic, colours will show interpretations: plot(some_mic_values, mo = \"S. aureus\", ab = \"ampicillin\")  plot(some_disk_values, mo = \"Escherichia coli\", ab = \"cipro\")  plot(some_disk_values, mo = \"Escherichia coli\", ab = \"cipro\", language = \"nl\")    # Plotting using scale_x_mic() # \\donttest{ if (require(\"ggplot2\")) {   mic_plot <- ggplot(data.frame(mics = as.mic(c(0.125, \"<=4\", 4, 8, 32, \">=32\")),                                 counts = c(1, 1, 2, 2, 3, 3)),                      aes(mics, counts)) +     geom_col()   mic_plot +     labs(title = \"without scale_x_mic()\") }  if (require(\"ggplot2\")) {   mic_plot +     scale_x_mic() +     labs(title = \"with scale_x_mic()\") }  if (require(\"ggplot2\")) {   mic_plot +     scale_x_mic(keep_operators = \"all\") +     labs(title = \"with scale_x_mic() keeping all operators\") }  if (require(\"ggplot2\")) {   mic_plot +     scale_x_mic(mic_range = c(1, 128)) +     labs(title = \"with scale_x_mic() using a manual range\") }   if (require(\"ggplot2\")) {   autoplot(some_mic_values) }  if (require(\"ggplot2\")) {   autoplot(some_disk_values, mo = \"Escherichia coli\", ab = \"cipro\") }  if (require(\"ggplot2\")) {   autoplot(some_sir_values) }  # }"},{"path":"https://msberends.github.io/AMR/reference/proportion.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate Antimicrobial Resistance — proportion","title":"Calculate Antimicrobial Resistance — proportion","text":"functions can used calculate (co-)resistance susceptibility microbial isolates (.e. percentage S, SI, , IR R). functions support quasiquotation pipes, can used summarise() dplyr package also support grouped variables, see Examples. resistance() used calculate resistance, susceptibility() used calculate susceptibility.","code":""},{"path":"https://msberends.github.io/AMR/reference/proportion.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate Antimicrobial Resistance — proportion","text":"","code":"resistance(..., minimum = 30, as_percent = FALSE, only_all_tested = FALSE)  susceptibility(..., minimum = 30, as_percent = FALSE, only_all_tested = FALSE)  sir_confidence_interval(   ...,   ab_result = \"R\",   minimum = 30,   as_percent = FALSE,   only_all_tested = FALSE,   confidence_level = 0.95,   side = \"both\",   collapse = FALSE )  proportion_R(..., minimum = 30, as_percent = FALSE, only_all_tested = FALSE)  proportion_IR(..., minimum = 30, as_percent = FALSE, only_all_tested = FALSE)  proportion_I(..., minimum = 30, as_percent = FALSE, only_all_tested = FALSE)  proportion_SI(..., minimum = 30, as_percent = FALSE, only_all_tested = FALSE)  proportion_S(..., minimum = 30, as_percent = FALSE, only_all_tested = FALSE)  proportion_df(   data,   translate_ab = \"name\",   language = get_AMR_locale(),   minimum = 30,   as_percent = FALSE,   combine_SI = TRUE,   confidence_level = 0.95 )  sir_df(   data,   translate_ab = \"name\",   language = get_AMR_locale(),   minimum = 30,   as_percent = FALSE,   combine_SI = TRUE,   confidence_level = 0.95 )"},{"path":"https://msberends.github.io/AMR/reference/proportion.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Calculate Antimicrobial Resistance — proportion","text":"M39 Analysis Presentation Cumulative Antimicrobial Susceptibility Test Data, 5th Edition, 2022, Clinical Laboratory Standards Institute (CLSI). https://clsi.org/standards/products/microbiology/documents/m39/.","code":""},{"path":"https://msberends.github.io/AMR/reference/proportion.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate Antimicrobial Resistance — proportion","text":"... one vectors (columns) antibiotic interpretations. transformed internally .sir() needed. Use multiple columns calculate (lack ) co-resistance: probability one two drugs resistant susceptible result. See Examples. minimum minimum allowed number available (tested) isolates. isolate count lower minimum return NA warning. default number 30 isolates advised Clinical Laboratory Standards Institute (CLSI) best practice, see Source. as_percent logical indicate whether output must returned hundred fold % sign (character). value 0.123456 returned \"12.3%\". only_all_tested (combination therapies, .e. using one variable ...): logical indicate isolates must tested antibiotics, see section Combination Therapy ab_result antibiotic results test , must one values \"S\", \"\", \"R\" confidence_level confidence level returned confidence interval. calculation, number S SI isolates, R isolates compared total number available isolates R, S, using binom.test(), .e., Clopper-Pearson method. side side confidence interval return. default \"\" length 2 vector, can also (abbreviated ) \"min\"/\"left\"/\"lower\"/\"less\" \"max\"/\"right\"/\"higher\"/\"greater\". collapse logical indicate whether output values 'collapsed', .e. merged together one value, character value use collapsing data data.frame containing columns class sir (see .sir()) translate_ab column name antibiotics data set translate antibiotic abbreviations , using ab_property() language language returned text - default current system language (see get_AMR_locale()) can also set package option AMR_locale. Use language = NULL language = \"\" prevent translation. combine_SI logical indicate whether values S must merged one, output consists S+vs. R (susceptible vs. resistant) - default TRUE","code":""},{"path":"https://msberends.github.io/AMR/reference/proportion.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate Antimicrobial Resistance — proportion","text":"double , as_percent = TRUE, character.","code":""},{"path":"https://msberends.github.io/AMR/reference/proportion.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate Antimicrobial Resistance — proportion","text":"Remember filter data let contain first isolates! needed exclude duplicates reduce selection bias. Use first_isolate() determine data set one four available algorithms. function resistance() equal function proportion_R(). function susceptibility() equal function proportion_SI(). Since AMR v3.0, proportion_SI() proportion_I() include dose-dependent susceptibility ('SDD'). Use sir_confidence_interval() calculate confidence interval, relies binom.test(), .e., Clopper-Pearson method. function returns vector length 2 default antimicrobial resistance. Change side argument \"left\"/\"min\" \"right\"/\"max\" return single value, change ab_result argument e.g. c(\"S\", \"\") test antimicrobial susceptibility, see Examples. functions meant count isolates, calculate proportion resistance/susceptibility. Use count_*() functions count isolates. function susceptibility() essentially equal count_susceptible()/count_all(). Low counts can influence outcome - proportion_*() functions may camouflage , since return proportion (albeit dependent minimum argument). function proportion_df() takes variable data sir class (created .sir()) calculates proportions S, , R. also supports grouped variables. function sir_df() works exactly like proportion_df(), adds number isolates.","code":""},{"path":"https://msberends.github.io/AMR/reference/proportion.html","id":"combination-therapy","dir":"Reference","previous_headings":"","what":"Combination Therapy","title":"Calculate Antimicrobial Resistance — proportion","text":"using one variable ... (= combination therapy), use only_all_tested count isolates tested antibiotics/variables test . See example two antibiotics, Drug Drug B, susceptibility() works calculate %SI:   Please note , combination therapies, only_all_tested = TRUE applies :   , combination therapies, only_all_tested = FALSE applies :   Using only_all_tested impact using one antibiotic input.","code":"--------------------------------------------------------------------                     only_all_tested = FALSE  only_all_tested = TRUE                     -----------------------  -----------------------  Drug A    Drug B   include as  include as   include as  include as                     numerator   denominator  numerator   denominator --------  --------  ----------  -----------  ----------  -----------  S or I    S or I       X            X            X            X    R       S or I       X            X            X            X   <NA>     S or I       X            X            -            -  S or I      R          X            X            X            X    R         R          -            X            -            X   <NA>       R          -            -            -            -  S or I     <NA>        X            X            -            -    R        <NA>        -            -            -            -   <NA>      <NA>        -            -            -            - -------------------------------------------------------------------- count_S()    +   count_I()    +   count_R()    = count_all()   proportion_S() + proportion_I() + proportion_R() = 1 count_S()    +   count_I()    +   count_R()    >= count_all()   proportion_S() + proportion_I() + proportion_R() >= 1"},{"path":"https://msberends.github.io/AMR/reference/proportion.html","id":"interpretation-of-sir","dir":"Reference","previous_headings":"","what":"Interpretation of SIR","title":"Calculate Antimicrobial Resistance — proportion","text":"2019, European Committee Antimicrobial Susceptibility Testing (EUCAST) decided change definitions susceptibility testing categories S, , R shown (https://www.eucast.org/newsiandr): S - Susceptible, standard dosing regimen microorganism categorised \"Susceptible, standard dosing regimen\", high likelihood therapeutic success using standard dosing regimen agent. - Susceptible, increased exposure  microorganism categorised \"Susceptible, Increased exposure\" high likelihood therapeutic success exposure agent increased adjusting dosing regimen concentration site infection. R = Resistant microorganism categorised \"Resistant\" high likelihood therapeutic failure even increased exposure. Exposure function mode administration, dose, dosing interval, infusion time, well distribution excretion antimicrobial agent influence infecting organism site infection. AMR package honours insight. Use susceptibility() (equal proportion_SI()) determine antimicrobial susceptibility count_susceptible() (equal count_SI()) count susceptible isolates.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/proportion.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate Antimicrobial Resistance — proportion","text":"","code":"# example_isolates is a data set available in the AMR package. # run ?example_isolates for more info. example_isolates #> # A tibble: 2,000 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-03 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  3 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  4 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  5 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  6 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  7 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  8 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  9 2002-01-16 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #> 10 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R     NA    S     NA    #> # ℹ 1,990 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, …   # base R ------------------------------------------------------------ # determines %R resistance(example_isolates$AMX) #> [1] 0.5955556 sir_confidence_interval(example_isolates$AMX) #> [1] 0.5688204 0.6218738 sir_confidence_interval(example_isolates$AMX,   confidence_level = 0.975 ) #> [1] 0.5650148 0.6255670 sir_confidence_interval(example_isolates$AMX,   confidence_level = 0.975,   collapse = \", \" ) #> [1] \"0.565, 0.626\"  # determines %S+I: susceptibility(example_isolates$AMX) #> [1] 0.4044444 sir_confidence_interval(example_isolates$AMX,   ab_result = c(\"S\", \"I\") ) #> [1] 0.3781262 0.4311796  # be more specific proportion_S(example_isolates$AMX) #> [1] 0.4022222 proportion_SI(example_isolates$AMX) #> Note that proportion_SI() will also include dose-dependent #> susceptibility, 'SDD'. This note will be shown once for this session. #> [1] 0.4044444 proportion_I(example_isolates$AMX) #> Note that proportion_I() will also include dose-dependent susceptibility, #> 'SDD'. This note will be shown once for this session. #> [1] 0.002222222 proportion_IR(example_isolates$AMX) #> Note that proportion_IR() will also include dose-dependent #> susceptibility, 'SDD'. This note will be shown once for this session. #> [1] 0.5977778 proportion_R(example_isolates$AMX) #> [1] 0.5955556  # dplyr ------------------------------------------------------------- # \\donttest{ if (require(\"dplyr\")) {   example_isolates %>%     group_by(ward) %>%     summarise(       r = resistance(CIP),       n = n_sir(CIP)     ) # n_sir works like n_distinct in dplyr, see ?n_sir } #> # A tibble: 3 × 3 #>   ward           r     n #>   <chr>      <dbl> <int> #> 1 Clinical   0.147   869 #> 2 ICU        0.190   447 #> 3 Outpatient 0.161    93 if (require(\"dplyr\")) {   example_isolates %>%     group_by(ward) %>%     summarise(       cipro_R = resistance(CIP),       ci_min = sir_confidence_interval(CIP, side = \"min\"),       ci_max = sir_confidence_interval(CIP, side = \"max\"),     ) } #> # A tibble: 3 × 4 #>   ward       cipro_R ci_min ci_max #>   <chr>        <dbl>  <dbl>  <dbl> #> 1 Clinical     0.147 0.124   0.173 #> 2 ICU          0.190 0.155   0.230 #> 3 Outpatient   0.161 0.0932  0.252 if (require(\"dplyr\")) {   # scoped dplyr verbs with antibiotic selectors   # (you could also use across() of course)   example_isolates %>%     group_by(ward) %>%     summarise_at(       c(aminoglycosides(), carbapenems()),       resistance     ) } #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> Warning: There was 1 warning in `summarise()`. #> ℹ In argument: `KAN = (function (..., minimum = 30, as_percent = FALSE, #>   only_all_tested = FALSE) ...`. #> ℹ In group 3: `ward = \"Outpatient\"`. #> Caused by warning: #> ! Introducing NA: only 23 results available for KAN in group: ward = #> \"Outpatient\" (minimum = 30). #> # A tibble: 3 × 7 #>   ward         GEN   TOB   AMK   KAN    IPM    MEM #>   <chr>      <dbl> <dbl> <dbl> <dbl>  <dbl>  <dbl> #> 1 Clinical   0.229 0.315 0.626     1 0.0498 0.0458 #> 2 ICU        0.290 0.400 0.662     1 0.0862 0.0894 #> 3 Outpatient 0.2   0.368 0.605    NA 0.0541 0.0541 if (require(\"dplyr\")) {   example_isolates %>%     group_by(ward) %>%     summarise(       R = resistance(CIP, as_percent = TRUE),       SI = susceptibility(CIP, as_percent = TRUE),       n1 = count_all(CIP), # the actual total; sum of all three       n2 = n_sir(CIP), # same - analogous to n_distinct       total = n()     ) # NOT the number of tested isolates!    # Calculate co-resistance between amoxicillin/clav acid and gentamicin,   # so we can see that combination therapy does a lot more than mono therapy:   example_isolates %>% susceptibility(AMC) # %SI = 76.3%   example_isolates %>% count_all(AMC) #   n = 1879    example_isolates %>% susceptibility(GEN) # %SI = 75.4%   example_isolates %>% count_all(GEN) #   n = 1855    example_isolates %>% susceptibility(AMC, GEN) # %SI = 94.1%   example_isolates %>% count_all(AMC, GEN) #   n = 1939     # See Details on how `only_all_tested` works. Example:   example_isolates %>%     summarise(       numerator = count_susceptible(AMC, GEN),       denominator = count_all(AMC, GEN),       proportion = susceptibility(AMC, GEN)     )    example_isolates %>%     summarise(       numerator = count_susceptible(AMC, GEN, only_all_tested = TRUE),       denominator = count_all(AMC, GEN, only_all_tested = TRUE),       proportion = susceptibility(AMC, GEN, only_all_tested = TRUE)     )     example_isolates %>%     group_by(ward) %>%     summarise(       cipro_p = susceptibility(CIP, as_percent = TRUE),       cipro_n = count_all(CIP),       genta_p = susceptibility(GEN, as_percent = TRUE),       genta_n = count_all(GEN),       combination_p = susceptibility(CIP, GEN, as_percent = TRUE),       combination_n = count_all(CIP, GEN)     )    # Get proportions S/I/R immediately of all sir columns   example_isolates %>%     select(AMX, CIP) %>%     proportion_df(translate = FALSE)    # It also supports grouping variables   # (use sir_df to also include the count)   example_isolates %>%     select(ward, AMX, CIP) %>%     group_by(ward) %>%     sir_df(translate = FALSE) } #> # A tibble: 12 × 7 #>    ward       antibiotic interpretation value ci_min ci_max isolates #>  * <chr>      <chr>      <ord>          <dbl>  <dbl>  <dbl>    <int> #>  1 Clinical   AMX        SI             0.423 0.389   0.457      357 #>  2 Clinical   AMX        R              0.577 0.543   0.611      487 #>  3 Clinical   CIP        SI             0.853 0.827   0.876      741 #>  4 Clinical   CIP        R              0.147 0.124   0.173      128 #>  5 ICU        AMX        SI             0.369 0.323   0.417      158 #>  6 ICU        AMX        R              0.631 0.583   0.677      270 #>  7 ICU        CIP        SI             0.810 0.770   0.845      362 #>  8 ICU        CIP        R              0.190 0.155   0.230       85 #>  9 Outpatient AMX        SI             0.397 0.288   0.515       31 #> 10 Outpatient AMX        R              0.603 0.485   0.712       47 #> 11 Outpatient CIP        SI             0.839 0.748   0.907       78 #> 12 Outpatient CIP        R              0.161 0.0932  0.252       15 # }"},{"path":"https://msberends.github.io/AMR/reference/random.html","id":null,"dir":"Reference","previous_headings":"","what":"Random MIC Values/Disk Zones/SIR Generation — random","title":"Random MIC Values/Disk Zones/SIR Generation — random","text":"functions can used generating random MIC values disk diffusion diameters, AMR data analysis practice. providing microorganism antimicrobial drug, generated results reflect reality much possible.","code":""},{"path":"https://msberends.github.io/AMR/reference/random.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Random MIC Values/Disk Zones/SIR Generation — random","text":"","code":"random_mic(size = NULL, mo = NULL, ab = NULL, ...)  random_disk(size = NULL, mo = NULL, ab = NULL, ...)  random_sir(size = NULL, prob_SIR = c(0.33, 0.33, 0.33), ...)"},{"path":"https://msberends.github.io/AMR/reference/random.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Random MIC Values/Disk Zones/SIR Generation — random","text":"size desired size returned vector. used data.frame call dplyr verb, get current (group) size left blank. mo character can coerced valid microorganism code .mo() ab character can coerced valid antimicrobial drug code .ab() ... ignored, place allow future extensions prob_SIR vector length 3: probabilities \"S\" (1st value), \"\" (2nd value) \"R\" (3rd value)","code":""},{"path":"https://msberends.github.io/AMR/reference/random.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Random MIC Values/Disk Zones/SIR Generation — random","text":"class mic random_mic() (see .mic()) class disk random_disk() (see .disk())","code":""},{"path":"https://msberends.github.io/AMR/reference/random.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Random MIC Values/Disk Zones/SIR Generation — random","text":"base R function sample() used generating values. Generated values based EUCAST 2024 guideline implemented clinical_breakpoints data set. create specific generated values per bug drug, set mo /ab argument.","code":""},{"path":"https://msberends.github.io/AMR/reference/random.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Random MIC Values/Disk Zones/SIR Generation — random","text":"","code":"random_mic(25) #> Class 'mic' #>  [1] 16     64     256    0.002  1      0.001  64     0.25   1      16     #> [11] 0.5    8      8      0.0625 1      0.5    0.025  256    256    1      #> [21] 0.01   1      64     32     4      random_disk(25) #> Class 'disk' #>  [1] 49 47 14 33 49 43 41 41 43 31 20 43 42 11 18 42  8 42 16 25 42  8 15 30 29 random_sir(25) #> Class 'sir' #>  [1] I S S I S I I S R S S I I S S I I S I R S S R I S  # \\donttest{ # make the random generation more realistic by setting a bug and/or drug: random_mic(25, \"Klebsiella pneumoniae\") # range 0.0625-64 #> Class 'mic' #>  [1] 64     0.025  2      0.25   32     64     0.002  32     0.01   0.001  #> [11] 0.25   0.125  0.0625 64     128    0.002  128    128    1      0.002  #> [21] 1      0.005  0.001  4      0.001  random_mic(25, \"Klebsiella pneumoniae\", \"meropenem\") # range 0.0625-16 #> Class 'mic' #>  [1] 1    2    1    >=16 8    1    >=16 >=16 2    1    2    1    1    8    4    #> [16] 1    1    4    2    >=16 >=16 2    4    2    1    random_mic(25, \"Streptococcus pneumoniae\", \"meropenem\") # range 0.0625-4 #> Class 'mic' #>  [1] 2     0.25  >=8   >=8   0.5   1     1     0.125 0.25  1     2     1     #> [13] 0.25  >=8   0.25  2     1     1     >=8   0.125 0.5   >=8   0.125 0.25  #> [25] 0.25   random_disk(25, \"Klebsiella pneumoniae\") # range 8-50 #> Class 'disk' #>  [1] 45 49 24 46 23 18 15 17 17 28 40 20 21 43 39  9 33 17  8 20 30 21 44 48 41 random_disk(25, \"Klebsiella pneumoniae\", \"ampicillin\") # range 11-17 #> Class 'disk' #>  [1] 13 15 11 14 16 16 11 15 11 17 14 15 17 17 16 16 16 12 14 12 15 13 13 13 16 random_disk(25, \"Streptococcus pneumoniae\", \"ampicillin\") # range 12-27 #> Class 'disk' #>  [1] 22 23 19 19 23 15 23 18 21 24 22 25 19 19 16 17 17 16 27 21 27 25 15 21 27 # }"},{"path":"https://msberends.github.io/AMR/reference/resistance_predict.html","id":null,"dir":"Reference","previous_headings":"","what":"Predict Antimicrobial Resistance — resistance_predict","title":"Predict Antimicrobial Resistance — resistance_predict","text":"Create prediction model predict antimicrobial resistance next years statistical solid ground. Standard errors (SE) returned columns se_min se_max. See Examples real live example.","code":""},{"path":"https://msberends.github.io/AMR/reference/resistance_predict.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Predict Antimicrobial Resistance — resistance_predict","text":"","code":"resistance_predict(   x,   col_ab,   col_date = NULL,   year_min = NULL,   year_max = NULL,   year_every = 1,   minimum = 30,   model = NULL,   I_as_S = TRUE,   preserve_measurements = TRUE,   info = interactive(),   ... )  sir_predict(   x,   col_ab,   col_date = NULL,   year_min = NULL,   year_max = NULL,   year_every = 1,   minimum = 30,   model = NULL,   I_as_S = TRUE,   preserve_measurements = TRUE,   info = interactive(),   ... )  # S3 method for resistance_predict plot(x, main = paste(\"Resistance Prediction of\", x_name), ...)  ggplot_sir_predict(   x,   main = paste(\"Resistance Prediction of\", x_name),   ribbon = TRUE,   ... )  # S3 method for resistance_predict autoplot(   object,   main = paste(\"Resistance Prediction of\", x_name),   ribbon = TRUE,   ... )"},{"path":"https://msberends.github.io/AMR/reference/resistance_predict.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Predict Antimicrobial Resistance — resistance_predict","text":"x data.frame containing isolates. Can left blank automatic determination, see Examples. col_ab column name x containing antimicrobial interpretations (\"R\", \"\" \"S\") col_date column name date, used calculate years column consist years already - default first column date class year_min lowest year use prediction model, dafaults lowest year col_date year_max highest year use prediction model - default 10 years today year_every unit sequence lowest year found data year_max minimum minimal amount available isolates per year include. Years containing less observations estimated model. model statistical model choice. generalised linear regression model binomial distribution (.e. using glm(..., family = binomial), assuming period zero resistance followed period increasing resistance leading slowly resistance. See Details valid options. I_as_S logical indicate whether values \"\" treated \"S\" (otherwise treated \"R\"). default, TRUE, follows redefinition EUCAST interpretation (increased exposure) 2019, see section Interpretation S, R . preserve_measurements logical indicate whether predictions years actually available data overwritten original data. standard errors years NA. info logical indicate whether textual analysis printed name summary() statistical model. ... arguments passed functions main title plot ribbon logical indicate whether ribbon shown (default) error bars object model data plotted","code":""},{"path":"https://msberends.github.io/AMR/reference/resistance_predict.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Predict Antimicrobial Resistance — resistance_predict","text":"data.frame extra class resistance_predict columns: year value, estimated preserve_measurements = FALSE, combination observed estimated otherwise se_min, lower bound standard error minimum 0 (standard error never go 0%) se_max upper bound standard error maximum 1 (standard error never go 100%) observations, total number available observations year, .e. \\(S + + R\\) observed, original observed resistant percentages estimated, estimated resistant percentages, calculated model Furthermore, model available attribute: attributes(x)$model, see Examples.","code":""},{"path":"https://msberends.github.io/AMR/reference/resistance_predict.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Predict Antimicrobial Resistance — resistance_predict","text":"Valid options statistical model (argument model) : \"binomial\" \"binom\" \"logit\": generalised linear regression model binomial distribution \"loglin\" \"poisson\": generalised log-linear regression model poisson distribution \"lin\" \"linear\": linear regression model","code":""},{"path":"https://msberends.github.io/AMR/reference/resistance_predict.html","id":"interpretation-of-sir","dir":"Reference","previous_headings":"","what":"Interpretation of SIR","title":"Predict Antimicrobial Resistance — resistance_predict","text":"2019, European Committee Antimicrobial Susceptibility Testing (EUCAST) decided change definitions susceptibility testing categories S, , R shown (https://www.eucast.org/newsiandr): S - Susceptible, standard dosing regimen microorganism categorised \"Susceptible, standard dosing regimen\", high likelihood therapeutic success using standard dosing regimen agent. - Susceptible, increased exposure  microorganism categorised \"Susceptible, Increased exposure\" high likelihood therapeutic success exposure agent increased adjusting dosing regimen concentration site infection. R = Resistant microorganism categorised \"Resistant\" high likelihood therapeutic failure even increased exposure. Exposure function mode administration, dose, dosing interval, infusion time, well distribution excretion antimicrobial agent influence infecting organism site infection. AMR package honours insight. Use susceptibility() (equal proportion_SI()) determine antimicrobial susceptibility count_susceptible() (equal count_SI()) count susceptible isolates.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/resistance_predict.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Predict Antimicrobial Resistance — resistance_predict","text":"","code":"x <- resistance_predict(example_isolates,   col_ab = \"AMX\",   year_min = 2010,   model = \"binomial\" ) plot(x)  # \\donttest{ if (require(\"ggplot2\")) {   ggplot_sir_predict(x) }   # using dplyr: if (require(\"dplyr\")) {   x <- example_isolates %>%     filter_first_isolate() %>%     filter(mo_genus(mo) == \"Staphylococcus\") %>%     resistance_predict(\"PEN\", model = \"binomial\")   print(plot(x))    # get the model from the object   mymodel <- attributes(x)$model   summary(mymodel) }  #> NULL #>  #> Call: #> glm(formula = df_matrix ~ year, family = binomial) #>  #> Coefficients: #>             Estimate Std. Error z value Pr(>|z|) #> (Intercept) 27.05312   72.24652   0.374    0.708 #> year        -0.01286    0.03601  -0.357    0.721 #>  #> (Dispersion parameter for binomial family taken to be 1) #>  #>     Null deviance: 5.7883  on 11  degrees of freedom #> Residual deviance: 5.6608  on 10  degrees of freedom #> AIC: 50.745 #>  #> Number of Fisher Scoring iterations: 4 #>   # create nice plots with ggplot2 yourself if (require(\"dplyr\") && require(\"ggplot2\")) {   data <- example_isolates %>%     filter(mo == as.mo(\"E. coli\")) %>%     resistance_predict(       col_ab = \"AMX\",       col_date = \"date\",       model = \"binomial\",       info = FALSE,       minimum = 15     )   head(data)   autoplot(data) }  # }"},{"path":"https://msberends.github.io/AMR/reference/skewness.html","id":null,"dir":"Reference","previous_headings":"","what":"Skewness of the Sample — skewness","title":"Skewness of the Sample — skewness","text":"Skewness measure asymmetry probability distribution real-valued random variable mean. negative ('left-skewed'): left tail longer; mass distribution concentrated right histogram. positive ('right-skewed'): right tail longer; mass distribution concentrated left histogram. normal distribution skewness 0.","code":""},{"path":"https://msberends.github.io/AMR/reference/skewness.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Skewness of the Sample — skewness","text":"","code":"skewness(x, na.rm = FALSE)  # S3 method for default skewness(x, na.rm = FALSE)  # S3 method for matrix skewness(x, na.rm = FALSE)  # S3 method for data.frame skewness(x, na.rm = FALSE)"},{"path":"https://msberends.github.io/AMR/reference/skewness.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Skewness of the Sample — skewness","text":"x vector values, matrix data.frame na.rm logical value indicating whether NA values stripped computation proceeds","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/skewness.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Skewness of the Sample — skewness","text":"","code":"skewness(runif(1000)) #> [1] -0.03310027"},{"path":"https://msberends.github.io/AMR/reference/translate.html","id":null,"dir":"Reference","previous_headings":"","what":"Translate Strings from the AMR Package — translate","title":"Translate Strings from the AMR Package — translate","text":"language-dependent output AMR functions, mo_name(), mo_gramstain(), mo_type() ab_name().","code":""},{"path":"https://msberends.github.io/AMR/reference/translate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Translate Strings from the AMR Package — translate","text":"","code":"get_AMR_locale()  set_AMR_locale(language)  reset_AMR_locale()  translate_AMR(x, language = get_AMR_locale())"},{"path":"https://msberends.github.io/AMR/reference/translate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Translate Strings from the AMR Package — translate","text":"language language choose. Use one supported language names ISO-639-1 codes: English (en), Chinese (zh), Czech (cs), Danish (da), Dutch (nl), Finnish (fi), French (fr), German (de), Greek (el), Italian (), Japanese (ja), Norwegian (), Polish (pl), Portuguese (pt), Romanian (ro), Russian (ru), Spanish (es), Swedish (sv), Turkish (tr), Ukrainian (uk). x text translate","code":""},{"path":"https://msberends.github.io/AMR/reference/translate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Translate Strings from the AMR Package — translate","text":"currently 20 supported languages English (en), Chinese (zh), Czech (cs), Danish (da), Dutch (nl), Finnish (fi), French (fr), German (de), Greek (el), Italian (), Japanese (ja), Norwegian (), Polish (pl), Portuguese (pt), Romanian (ro), Russian (ru), Spanish (es), Swedish (sv), Turkish (tr), Ukrainian (uk). languages translations available antimicrobial drugs colloquial microorganism names. permanently silence -per-session language note non-English operating system, can set package option AMR_locale .Rprofile file like :   save file. Please read adding updating language Wiki.","code":"# Open .Rprofile file utils::file.edit(\"~/.Rprofile\")  # Then add e.g. Italian support to that file using: options(AMR_locale = \"Italian\")"},{"path":"https://msberends.github.io/AMR/reference/translate.html","id":"changing-the-default-language","dir":"Reference","previous_headings":"","what":"Changing the Default Language","title":"Translate Strings from the AMR Package — translate","text":"system language used default (returned Sys.getenv(\"LANG\") , LANG set, Sys.getlocale(\"LC_COLLATE\")), language supported. language used can overwritten two ways checked order: Setting package option AMR_locale, either using e.g. set_AMR_locale(\"German\") running e.g. options(AMR_locale = \"German\"). Note setting R option works session. Save command options(AMR_locale = \"(language)\") .Rprofile file apply every session. Run utils::file.edit(\"~/.Rprofile\") edit .Rprofile file. Setting system variable LANGUAGE LANG, e.g. adding LANGUAGE=\"de_DE.utf8\" .Renviron file home directory. Thus, package option AMR_locale set, system variables LANGUAGE LANG ignored.","code":""},{"path":"https://msberends.github.io/AMR/reference/translate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Translate Strings from the AMR Package — translate","text":"","code":"# Current settings (based on system language) ab_name(\"Ciprofloxacin\") #> [1] \"Ciprofloxacin\" mo_name(\"Coagulase-negative Staphylococcus (CoNS)\") #> [1] \"Coagulase-negative Staphylococcus (CoNS)\"  # setting another language set_AMR_locale(\"Dutch\") #> ℹ Using Dutch (Nederlands) for the AMR package for this session. ab_name(\"Ciprofloxacin\") #> [1] \"Ciprofloxacine\" mo_name(\"Coagulase-negative Staphylococcus (CoNS)\") #> [1] \"Coagulase-negatieve Staphylococcus (CNS)\"  # setting yet another language set_AMR_locale(\"German\") #> ℹ Using German (Deutsch) for the AMR package for this session. ab_name(\"Ciprofloxacin\") #> [1] \"Ciprofloxacin\" mo_name(\"Coagulase-negative Staphylococcus (CoNS)\") #> [1] \"Koagulase-negative Staphylococcus (KNS)\"  # set_AMR_locale() understands endonyms, English exonyms, and ISO-639-1: set_AMR_locale(\"Deutsch\") #> ℹ Using German (Deutsch) for the AMR package for this session. set_AMR_locale(\"German\") #> ℹ Using German (Deutsch) for the AMR package for this session. set_AMR_locale(\"de\") #> ℹ Using German (Deutsch) for the AMR package for this session. ab_name(\"amox/clav\") #> ℹ More than one result was found for item 1: amoxicillin and clavulansäure #> [1] \"Amoxicillin/Clavulansäure\"  # reset to system default reset_AMR_locale() #> ℹ Using the English language (English) for the AMR package for this #>   session. ab_name(\"amox/clav\") #> [1] \"Amoxicillin/clavulanic acid\""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"amr-2119061","dir":"Changelog","previous_headings":"","what":"AMR 2.1.1.9061","title":"AMR 2.1.1.9061","text":"(beta version eventually become v3.0. ’re happy reach new major milestone soon, new One Health support! Install beta using instructions .)","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"a-new-milestone-amr-v30-with-one-health-support--human--veterinary--environmental-2-1-1-9061","dir":"Changelog","previous_headings":"","what":"A New Milestone: AMR v3.0 with One Health Support (= Human + Veterinary + Environmental)","title":"AMR 2.1.1.9061","text":"package now supports tools AMR data analysis clinical settings, also veterinary environmental microbiology. made possible collaboration University Prince Edward Island, Canada. celebrate great improvement package, also updated package logo reflect change.","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"breaking-2-1-1-9061","dir":"Changelog","previous_headings":"","what":"Breaking","title":"AMR 2.1.1.9061","text":"Removed functions references used deprecated rsi class, replaced sir equivalents year ago","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"new-2-1-1-9061","dir":"Changelog","previous_headings":"","what":"New","title":"AMR 2.1.1.9061","text":"Function .sir() now extensive support animal breakpoints CLSI. Use breakpoint_type = \"animal\" set host argument variable contains animal species names. clinical_breakpoints data set contains breakpoints, can downloaded download page. antibiotics data set contains veterinary antibiotics, pradofloxacin enrofloxacin. WHOCC codes veterinary use added well. ab_atc() now supports ATC codes veterinary antibiotics (start “Q”) ab_url() now supports retrieving WHOCC url ATCvet pages EUCAST 2024 CLSI 2024 now supported, adding 4,000 new clinical breakpoints clinical_breakpoints data set usage .sir(). EUCAST 2024 now new default guideline MIC disks diffusion interpretations. .sir() now brings additional factor levels: “NI” non-interpretable “SDD” susceptible dose-dependent. Currently, clinical_breakpoints data set contains 24 breakpoints can return value “SDD” instead “”. function group scale_*_mic(), namely: scale_x_mic(), scale_y_mic(), scale_colour_mic() scale_fill_mic(). advanced ggplot2 extensions allow easy plotting MIC values. allow manual range definition plotting missing intermediate log2 levels. Function rescale_mic(), allows rescale MIC values manually set range. powerhouse behind scale_*_mic() functions, can used users directly e.g. compare equality MIC distributions rescaling range first. Function mo_group_members() retrieve member microorganisms microorganism group. example, mo_group_members(\"Strep group C\") returns vector microorganisms group.","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"changed-2-1-1-9061","dir":"Changelog","previous_headings":"","what":"Changed","title":"AMR 2.1.1.9061","text":"now possible use column names argument ab, mo, uti: .sir(..., ab = \"column1\", mo = \"column2\", uti = \"column3\"). greatly improves flexibility users. Users can now set criteria (using regular expressions) considered S, , R, SDD, NI. get quantitative values, .double() sir object return 1 S, 2 SDD/, 3 R (NI become NA). functions using sir classes (e.g., summary()) updated reflect change contain NI SDD. Added “clindamycin inducible screening” CLI1. Since clindamycin lincosamide, antibiotic selector lincosamides() now contains argument only_treatable = TRUE (similar antibiotic selectors contain non-treatable drugs) Added Amorolfine (AMO, D01AE16), now also part antifungals() selector Added selectors nitrofurans() rifamycins() using antibiotic selectors aminoglycosides() exclude non-treatable drugs like gentamicin-high, function now always returns warning can included using only_treatable = FALSE Added valid levels: 4096, 6 powers 0.0625, 5 powers 192 (192, 384, 576, 768, 960) Added new argument keep_operators .mic(). can \"\" (default), \"none\", \"edges\". argument also available new rescale_mic() scale_*_mic() functions. Comparisons MIC values now strict. example, >32 higher (never equal ) 32. Thus, .mic(\">32\") == .mic(32) now returns FALSE, .mic(\">32\") > .mic(32) now returns TRUE. Sorting MIC values (using sort()) fixed manner; <0.001 now gets sorted 0.001, >0.001 gets sorted 0.001. Updated italicise_taxonomy() support HTML output custom_eucast_rules() now supports multiple antibiotics antibiotic groups affected single rule mo_info() now contains extra element group_members, contents new mo_group_members() function Greatly improved vctrs integration, Tidyverse package working background many Tidyverse functions. users, means functions dplyr’s bind_rows(), rowwise() c_across() now supported e.g. columns class mic. Despite , AMR package still zero-dependent package, including dplyr vctrs. Updated ATC codes WHOCC Updated antibiotic DDDs WHOCC Fix using manual value mo_transform antibiogram() Fix mapping ‘high level’ antibiotics .ab() (amphotericin B-high, gentamicin-high, kanamycin-high, streptomycin-high, tobramycin-high) Improved overall algorithm .ab() better performance accuracy Improved overall algorithm .mo() better performance accuracy. Specifically, weight given genus species combinations cases subspecies miswritten, result correct genus species. Intermediate log2 levels used MIC plotting now common values instead following strict dilution range","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"other-2-1-1-9061","dir":"Changelog","previous_headings":"","what":"Other","title":"AMR 2.1.1.9061","text":"Added Jordan Stull, Matthew Saab, Javier Sanchez contributors, thank valuable input","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"amr-211","dir":"Changelog","previous_headings":"","what":"AMR 2.1.1","title":"AMR 2.1.1","text":"CRAN release: 2023-10-21 included many isolates patients altering antibiograms within bacterial species See info issue #122 Added 1,366 LOINC codes antibiotics data set updated latest version (LOINC v2.76) MICs can now used complex number calculations allow scientific number format input (e.g., .mic(\"1.28e-2\")) Fix rounding MICs latest R beta (‘R-devel’) Removed unneeded note used language option AMR_locale set Fixed non-ASCII characters documentation, according CRAN maintainers","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"amr-210","dir":"Changelog","previous_headings":"","what":"AMR 2.1.0","title":"AMR 2.1.0","text":"CRAN release: 2023-07-16","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"new-2-1-0","dir":"Changelog","previous_headings":"","what":"New","title":"AMR 2.1.0","text":"Clinical breakpoints intrinsic resistance EUCAST 2023 CLSI 2023 added clinical_breakpoints data set usage .sir(). EUCAST 2023 (v13.0) now new default guideline MIC disks diffusion interpretations EUCAST dosage guideline v13.0 added dosage data set clinical_breakpoints data set now also contains epidemiological cut-(ECOFF) values CLSI animal breakpoints. two new breakpoint types can used MIC/disk interpretation using .sir(..., breakpoint_type = \"ECOFF\") oras.sir(..., breakpoint_type = \"animal\"), important new addition veterinary microbiology. Added support 30 species groups / complexes. gathered new data set microorganisms.groups used clinical breakpoint interpretation. example, CLSI 2023 contains breakpoints RGM group (Rapidly Growing Mycobacterium, containing 80 species) now supported package. Added mo_oxygen_tolerance() retrieve values Added mo_is_anaerobic() determine genera/species obligate anaerobic bacteria Added LPSN GBIF identifiers, oxygen tolerance mo_info() Added SAS Transport files (file extension .xpt) download page use SAS software Added microbial codes Gram-negative/positive anaerobic bacteria","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"changed-2-1-0","dir":"Changelog","previous_headings":"","what":"Changed","title":"AMR 2.1.0","text":"Updated algorithm .mo() giving weight fungi Fixed clinical breakpoints errors introduced source import rules mo_rank() now returns NA ‘unknown’ microorganisms (B_ANAER, B_ANAER-NEG, B_ANAER-POS, B_GRAMN, B_GRAMP, F_FUNGUS, F_YEAST, UNKNOWN) printing microorganism antibiotic codes tibble, mouse-hover now shows full name code Now settable arguments breakpoint type PK/PD, like .sir() now contain name guideline table subtitle plot Fixed formatting sir_interpretation_history() Fixed WHONET codes microorganisms consequently couple entries clinical_breakpoints Fixed bug .mo() led coercion NA values using custom microorganism codes Fixed usage icu_exclude first_isolates() Now allows searching species names Fix using keep_synonyms argument using MO codes input Fix using minimum_matching_score argument Updated code table microorganisms.codes Fixed endless loop using reference_df .mo() Fixed bug indicating UTIs .sir() Greatly improved speed .sir()","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"amr-200","dir":"Changelog","previous_headings":"","what":"AMR 2.0.0","title":"AMR 2.0.0","text":"CRAN release: 2023-03-12 new major release AMR package, great new additions also breaking changes current users. listed . TL;DR functions arguments ‘rsi’ replaced ‘sir’, interpretation MIC values (now .sir() instead .rsi()) - old functions still work now Many new interesting functions, antibiogram() (generating traditional/combined/syndromic/WISCA antibiograms), sir_confidence_interval() mean_amr_distance(), add_custom_microorganisms() add custom microorganisms package Clinical breakpoints added EUCAST 2022 CLSI 2022 Microbiological taxonomy (microorganisms data set) updated 2022 now based LPSN GBIF Much increased algorithms translate user input valid taxonomy, e.g. using recent scientific work per-species human pathogenicity 20 new antibiotics added updated DDDs ATC codes Extended support antiviral agents (antivirals data set), many new functions Now available 20 languages Many small bug fixes","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/news/index.html","id":"sir-vs-rsi-2-0-0","dir":"Changelog","previous_headings":"New","what":"SIR vs. RSI","title":"AMR 2.0.0","text":"milestone version, replaced mentions RSI SIR, comply actually commonly used field clinical microbiology comes tri-form regarding AMR. existing functions .rsi(), rsi_df() ggplot_rsi() still work, replacements .sir(), sir_df(), ggplot_sir() now current functions AMR data analysis. warning thrown session remind users . data set rsi_translation now called clinical_breakpoints better reflect content. ‘RSI functions’ removed future version, late 2023 / early 2024.","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"new-antibiogram-function-2-0-0","dir":"Changelog","previous_headings":"New","what":"New antibiogram function","title":"AMR 2.0.0","text":"new antibiogram() function, users can now generate traditional, combined, syndromic, even weighted-incidence syndromic combination antibiograms (WISCA). , follow logic previously described work Klinker et al. (2021, DOI 10.1177/20499361211011373) Barbieri et al. (2021, DOI 10.1186/s13756-021-00939-2). help page antibiogram() extensively elaborates use cases, antibiogram() also supports printing R Markdown Quarto, support 20 languages. Furthermore, different plotting methods implemented allow graphical visualisations well.","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"interpretation-of-mic-and-disk-diffusion-values-2-0-0","dir":"Changelog","previous_headings":"New","what":"Interpretation of MIC and disk diffusion values","title":"AMR 2.0.0","text":"clinical breakpoints intrinsic resistance EUCAST 2022 CLSI 2022 added .sir(). EUCAST 2022 (v12.0) now new default guideline MIC disks diffusion interpretations, eucast_rules() apply EUCAST Expert Rules. default guideline (EUCAST) can now changed new AMR_guideline option, : options(AMR_guideline = \"CLSI 2020\"). new arguments include_PKPD (default: TRUE) include_screening (default: FALSE), users can now specify whether breakpoints screening PK/PD table included interpreting MICs disks diffusion values. options can set globally, can read new manual. Interpretation guidelines older 10 years removed, oldest now included guidelines EUCAST CLSI 2013.","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"supported-languages-2-0-0","dir":"Changelog","previous_headings":"New","what":"Supported languages","title":"AMR 2.0.0","text":"added support following ten languages: Chinese (simplified), Czech, Finnish, Greek, Japanese, Norwegian (bokmål), Polish, Romanian, Turkish Ukrainian. antibiotic names now available languages, AMR package automatically determine supported language based user’s system language. grateful valuable input colleagues countries. AMR package now available 20 languages total, according download stats used almost countries world!","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"outbreak-management-2-0-0","dir":"Changelog","previous_headings":"New","what":"Outbreak management","title":"AMR 2.0.0","text":"analysis outbreak management, updated get_episode() is_new_episode() functions: now contain argument case_free_days. argument can used quantify duration case-free days (inter-epidemic interval), new episode start. common requirement outbreak management, e.g. determining number norovirus outbreaks hospital. case-free period 14 28 days, new norovirus cases time considered different (new) episode.","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"microbiological-taxonomy-2-0-0","dir":"Changelog","previous_headings":"New","what":"Microbiological taxonomy","title":"AMR 2.0.0","text":"microorganisms data set longer relies Catalogue Life, List Prokaryotic names Standing Nomenclature (LPSN) supplemented ‘backbone taxonomy’ Global Biodiversity Information Facility (GBIF). structure data set changed include separate LPSN GBIF identifiers. Almost previous MO codes retained. contains 1,400 taxonomic names 2022. previously relied experience categorise species pathogenic groups, happy encounter recent work Bartlett et al. (2022, DOI 10.1099/mic.0.001269) extensively studied medical-scientific literature categorise bacterial species groups. See mo_matching_score() work incorporated prevalence column microorganisms data set. Using results, .mo() mo_*() functions now much better capable converting user input valid taxonomic records. new function add_custom_microorganisms() allows users add custom microorganisms AMR package. also made following changes regarding included taxonomy microorganisms functions: Updated full microbiological taxonomy according latest daily LPSN data set (December 2022) latest yearly GBIF taxonomy backbone (November 2022) Added function mo_current() get currently valid taxonomic name microorganism Support 1,516 city-like serovars Salmonella, Salmonella Goldcoast. Formally, serovars belonging S. enterica species, reported name genus city. reason, serovars subspecies column microorganisms data set “enterica” species column, full name contain species name (enterica). new argument keep_synonyms allows correct updated taxonomy, favour now deleted argument allow_uncertain increased tremendously speed returns generally consequent results Sequential coercion now extremely fast results stored package environment, although coercion unknown values must run per session. Previous results can reset/removed new mo_reset_session() function. Support microorganism codes ASIan Antimicrobial Resistance Surveillance Network (ASIARS-Net) MO matching score algorithm (mo_matching_score()) now counts deletions substitutions 2 instead 1, impacts outcome .mo() mo_*() function CRAN allows packages around 5 MB maximum, packages exempted package one Chromista relevant comes antimicrobial resistance, thus lacking primary scope package Chromista almost never clinically relevant, thus lacking secondary scope package microorganisms.old data set removed, previously accepted names now included microorganisms data set. new column status contains \"accepted\" currently accepted names \"synonym\" taxonomic synonyms; currently invalid names. previously accepted names now microorganisms ID - available - LPSN, GBIF SNOMED CT identifier.","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"antibiotic-agents-and-selectors-2-0-0","dir":"Changelog","previous_headings":"New","what":"Antibiotic agents and selectors","title":"AMR 2.0.0","text":"new function add_custom_antimicrobials() allows users add custom antimicrobial codes names AMR package. antibiotics data set greatly updated: following 20 antibiotics added (also includes new J01RA ATC group): azithromycin/fluconazole/secnidazole (AFC), cefepime/amikacin (CFA), cefixime/ornidazole (CEO), ceftriaxone/beta-lactamase inhibitor (CEB), ciprofloxacin/metronidazole (CIM), ciprofloxacin/ornidazole (CIO), ciprofloxacin/tinidazole (CIT), furazidin (FUR), isoniazid/sulfamethoxazole/trimethoprim/pyridoxine (IST), lascufloxacin (LSC), levofloxacin/ornidazole (LEO), nemonoxacin (NEM), norfloxacin/metronidazole (NME), norfloxacin/tinidazole (NTI), ofloxacin/ornidazole (OOR), oteseconazole (OTE), rifampicin/ethambutol/isoniazid (REI), sarecycline (SRC), tetracycline/oleandomycin (TOL), thioacetazone (TAT) Added missing ATC codes Updated DDDs PubChem Compound IDs Updated antibiotic name spelling, now used WHOCC (cephalexin -> cefalexin, phenethicillin -> pheneticillin) Antibiotic code “CEI” ceftolozane/tazobactam replaced “CZT” comply EARS-Net WHONET 2022. old code still work cases using .ab() ab_*() functions. Support antimicrobial interpretation anaerobic bacteria, adding ‘placeholder’ code B_ANAER microorganisms data set adding breakpoints anaerobics clinical_breakpoints data set, used .sir() interpretion MIC disk diffusion values Also, added support using antibiotic selectors scoped dplyr verbs (without using vars()), : ... %>% summarise_at(aminoglycosides(), resistance), please see resistance() examples.","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"antiviral-agents-2-0-0","dir":"Changelog","previous_headings":"New","what":"Antiviral agents","title":"AMR 2.0.0","text":"now added extensive support antiviral agents! first time, AMR package extensive support antiviral drugs work names, codes data way. antivirals data set extended 18 new drugs (also new J05AJ ATC group) now also contains antiviral identifiers LOINC codes new data type av (antivirals) added, functionally similar ab antibiotics Functions .av(), av_name(), av_atc(), av_synonyms(), av_from_text() added siblings ab_*() equivalents","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"other-new-functions-2-0-0","dir":"Changelog","previous_headings":"New","what":"Other new functions","title":"AMR 2.0.0","text":"Function sir_confidence_interval() add confidence intervals AMR calculation. now also included sir_df() proportion_df(). Function mean_amr_distance() calculate mean AMR distance. mean AMR distance normalised numeric value compare AMR test results can help identify similar isolates, without comparing antibiograms hand. Function sir_interpretation_history() view history previous runs .sir() (previously .rsi()). returns ‘logbook’ selected guideline, reference table specific interpretation row data set .sir() run.","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"changes-2-0-0","dir":"Changelog","previous_headings":"","what":"Changes","title":"AMR 2.0.0","text":"Fix working NA values Fix unsorted dates length 2 Now returns class integer instead numeric since always whole numbers Argument combine_IR removed package (affecting functions count_df(), proportion_df(), sir_df() plotting functions), since replaced combine_SI three years ago Using units ab_ddd(..., units = \"...\") deprecated time now supported anymore. Use ab_ddd_units() instead. Support data.frame-enhancing R packages, specifically: data.table::data.table, janitor::tabyl, tibble::tibble, tsibble::tsibble. AMR package functions data set output (sir_df() bug_drug_combinations()), now return data type input. data sets package now tibble, instead base R data.frames. Older R versions still supported, even support tibbles. data sets now also continually exported Apache Feather Apache Parquet formats. can find info article website. Fixed certain EUCAST breakpoints MIC values Allow NA values (e.g. .sir(.disk(NA), ...)) Fix bug-drug combinations multiple breakpoints different body sites Interpretation MIC disk zones now informative availability breakpoints robust Removed .integer() method MIC values, since MIC integer values running table() MIC values consequently failed able retrieve level position (’s normally .integer() factors work) Fixed determination Gram stains (mo_gramstain()), since taxonomic phyla Actinobacteria, Chloroflexi, Firmicutes, Tenericutes renamed respectively Actinomycetota, Chloroflexota, Bacillota, Mycoplasmatota 2021 droplevels() MIC now return common factor default lose mic class. Use droplevels(..., .mic = TRUE) keep mic class. Small fix using ab_from_text() Fixes reading text files using set_mo_source(), now also allows source file contain valid taxonomic names instead valid microorganism ID package Fixed bug mdro() using similar column names Magiorakos guideline Using random_*() function (random_mic()) now possible directly calling package without loading first: AMR::random_mic(10) Extended support vctrs package, used internally tidyverse. allows change values class mic, disk, sir, mo ab tibbles, use antibiotic selectors selecting/filtering, e.g. df[carbapenems() == \"R\", ] Fix using info = FALSE mdro() interpretation guidelines using .sir() amoxicillin, rules ampicillin used amoxicillin rules available Fix using ab_atc() non-existing ATC codes Black white message texts now reversed colour using RStudio dark theme mo_snomed() now returns class character, numeric anymore (make long SNOMED codes readable) Fix using .ab() NA values Updated support WHONET 2022 microorganism codes Antimicrobial interpretation ‘SDD’ (susceptible dose-dependent, coined CLSI) interpreted ‘’ comply EUCAST’s ‘’ .sir() Fix mo_shortname() case higher taxonomic ranks (order, class, phylum) Cleaning columns .sir(), .mic(), .disk() now show column name warning invalid results Fix using g.test() zeroes 2x2 table mo_synonyns() now contains scientific reference names","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"other-2-0-0","dir":"Changelog","previous_headings":"","what":"Other","title":"AMR 2.0.0","text":"Added Peter Dutey-Magni, Dmytro Mykhailenko, Anton Mymrikov, Andrew Norgan, Jonas Salm, Anita Williams contributors, thank valuable input New website make use new Bootstrap 5 pkgdown 2.0. website now contains results examples automatically regenerated every change repository, using GitHub Actions R Rmd files project now styled using styler package Set scalar conditional expressions (&& ||) possible comply upcoming R 4.3 enormous lot code cleaning, fixing small bugs along way changelog contains changes AMR v2.0 (January 2023) later. prior versions, please see archive.","code":""}]
+[{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"How to conduct AMR data analysis","text":"Conducting AMR data analysis unfortunately requires -depth knowledge different scientific fields, makes hard right. least, requires: Good questions (always start !) reliable data thorough understanding (clinical) epidemiology, understand clinical epidemiological relevance possible bias results thorough understanding (clinical) microbiology/infectious diseases, understand microorganisms causal infections implications pharmaceutical treatment, well understanding intrinsic acquired microbial resistance Experience data analysis microbiological tests results, understand determination limitations MIC values interpretations SIR values Availability biological taxonomy microorganisms probably normalisation factors pharmaceuticals, defined daily doses (DDD) Available (inter-)national guidelines, profound methods apply course, instantly provide knowledge experience. AMR package, aimed providing (1) tools simplify antimicrobial resistance data cleaning, transformation analysis, (2) methods easily incorporate international guidelines (3) scientifically reliable reference data, including requirements mentioned . AMR package enables standardised reproducible AMR data analysis, application evidence-based rules, determination first isolates, translation various codes microorganisms antimicrobial agents, determination (multi-drug) resistant microorganisms, calculation antimicrobial resistance, prevalence future trends.","code":""},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"preparation","dir":"Articles","previous_headings":"","what":"Preparation","title":"How to conduct AMR data analysis","text":"tutorial, create fake demonstration data work . can skip Cleaning data already data ready. start analysis, try make structure data generally look like :","code":""},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"needed-r-packages","dir":"Articles","previous_headings":"Preparation","what":"Needed R packages","title":"How to conduct AMR data analysis","text":"many uses R, need additional packages AMR data analysis. package works closely together tidyverse packages dplyr ggplot2 RStudio. tidyverse tremendously improves way conduct data science - allows natural way writing syntaxes creating beautiful plots R. also use cleaner package, can used cleaning data creating frequency tables. AMR package contains data set example_isolates_unclean, might look data users extracted laboratory systems: AMR data analysis, like microorganism column contain valid, --date taxonomy, antibiotic columns cleaned SIR values well.","code":"library(dplyr) library(ggplot2) library(AMR)  # (if not yet installed, install with:) # install.packages(c(\"dplyr\", \"ggplot2\", \"AMR\")) example_isolates_unclean #> # A tibble: 3,000 × 8 #>    patient_id hospital date       bacteria      AMX   AMC   CIP   GEN   #>    <chr>      <chr>    <date>     <chr>         <chr> <chr> <chr> <chr> #>  1 J3         A        2012-11-21 E. coli       R     I     S     S     #>  2 R7         A        2018-04-03 K. pneumoniae R     I     S     S     #>  3 P3         A        2014-09-19 E. coli       R     S     S     S     #>  4 P10        A        2015-12-10 E. coli       S     I     S     S     #>  5 B7         A        2015-03-02 E. coli       S     S     S     S     #>  6 W3         A        2018-03-31 S. aureus     R     S     R     S     #>  7 J8         A        2016-06-14 E. coli       R     S     S     S     #>  8 M3         A        2015-10-25 E. coli       R     S     S     S     #>  9 J3         A        2019-06-19 E. coli       S     S     S     S     #> 10 G6         A        2015-04-27 S. aureus     S     S     S     S     #> # ℹ 2,990 more rows  # we will use 'our_data' as the data set name for this tutorial our_data <- example_isolates_unclean"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"taxonomy-of-microorganisms","dir":"Articles","previous_headings":"Preparation","what":"Taxonomy of microorganisms","title":"How to conduct AMR data analysis","text":".mo(), users can transform arbitrary microorganism names codes current taxonomy. AMR package contains --date taxonomic data. specific, currently included data retrieved 24 Jun 2024. codes AMR packages come .mo() short, still human readable. importantly, .mo() supports kinds input: first character codes denote taxonomic kingdom, Bacteria (B), Fungi (F), Protozoa (P). AMR package also contain functions directly retrieve taxonomic properties, name, genus, species, family, order, even Gram-stain. start mo_ use .mo() internally, still arbitrary user input can used: Now can thus clean data: Apparently, uncertainty translation taxonomic codes. Let’s check : ’s good.","code":"as.mo(\"Klebsiella pneumoniae\") #> Class 'mo' #> [1] B_KLBSL_PNMN as.mo(\"K. pneumoniae\") #> Class 'mo' #> [1] B_KLBSL_PNMN as.mo(\"KLEPNE\") #> Class 'mo' #> [1] B_KLBSL_PNMN as.mo(\"KLPN\") #> Class 'mo' #> [1] B_KLBSL_PNMN mo_family(\"K. pneumoniae\") #> [1] \"Enterobacteriaceae\" mo_genus(\"K. pneumoniae\") #> [1] \"Klebsiella\" mo_species(\"K. pneumoniae\") #> [1] \"pneumoniae\"  mo_gramstain(\"Klebsiella pneumoniae\") #> [1] \"Gram-negative\"  mo_ref(\"K. pneumoniae\") #> [1] \"Trevisan, 1887\"  mo_snomed(\"K. pneumoniae\") #> [[1]] #> [1] \"1098101000112102\" \"446870005\"        \"1098201000112108\" \"409801009\"        #> [5] \"56415008\"         \"714315002\"        \"713926009\" our_data$bacteria <- as.mo(our_data$bacteria, info = TRUE) #> ℹ Microorganism translation was uncertain for four microorganisms. Run #>   mo_uncertainties() to review these uncertainties, or use #>   add_custom_microorganisms() to add custom entries. mo_uncertainties() #> Matching scores are based on the resemblance between the input and the full #> taxonomic name, and the pathogenicity in humans. See ?mo_matching_score. #>  #> -------------------------------------------------------------------------------- #> \"E. coli\" -> Escherichia coli (B_ESCHR_COLI, 0.688) #> Also matched: Escherichia coli coli (0.643), Escherichia coli #>               expressing (0.611), Enterobacter cowanii (0.600), Eubacterium combesii #>               (0.600), Eggerthia catenaformis (0.591), Eubacterium callanderi #>               (0.591), Enterocloster citroniae (0.587), Eubacterium cylindroides #>               (0.583), Enterococcus casseliflavus (0.577), and Enterobacter cloacae #>               cloacae (0.571) #> -------------------------------------------------------------------------------- #> \"K. pneumoniae\" -> Klebsiella pneumoniae (B_KLBSL_PNMN, 0.786) #> Also matched: Klebsiella pneumoniae ozaenae (0.707), Klebsiella #>               pneumoniae pneumoniae (0.688), Klebsiella pneumoniae rhinoscleromatis #>               (0.658), Klebsiella pasteurii (0.500), Klebsiella planticola (0.500), #>               Kingella potus (0.400), Kluyveromyces pseudotropicale (0.386), #>               Kluyveromyces pseudotropicalis (0.363), Kosakonia pseudosacchari #>               (0.361), and Kluyveromyces pseudotropicalis pseudotropicalis (0.361) #> -------------------------------------------------------------------------------- #> \"S. aureus\" -> Staphylococcus aureus (B_STPHY_AURS, 0.690) #> Also matched: Staphylococcus aureus aureus (0.643), Staphylococcus #>               argenteus (0.625), Staphylococcus aureus anaerobius (0.625), Salmonella #>               Aurelianis (0.595), Salmonella Aarhus (0.588), Salmonella Amounderness #>               (0.587), Selenomonas artemidis (0.571), Salmonella choleraesuis #>               arizonae (0.562), Streptococcus anginosus anginosus (0.561), and #>               Salmonella Abaetetuba (0.548) #> -------------------------------------------------------------------------------- #> \"S. pneumoniae\" -> Streptococcus pneumoniae (B_STRPT_PNMN, 0.750) #> Also matched: Streptococcus pseudopneumoniae (0.700), Serratia #>               proteamaculans quinovora (0.545), Streptococcus pseudoporcinus (0.536), #>               Staphylococcus pseudintermedius (0.532), Serratia proteamaculans #>               proteamaculans (0.526), Salmonella Portanigra (0.524), Sphingomonas #>               paucimobilis (0.520), Streptococcus pluranimalium (0.519), #>               Streptococcus constellatus pharyngis (0.514), and Salmonella Pakistan #>               (0.500) #>  #> Only the first 10 other matches of each record are shown. Run #> print(mo_uncertainties(), n = ...) to view more entries, or save #> mo_uncertainties() to an object."},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"antibiotic-results","dir":"Articles","previous_headings":"Preparation","what":"Antibiotic results","title":"How to conduct AMR data analysis","text":"column antibiotic test results must also cleaned. AMR package comes three new data types work test results: mic minimal inhibitory concentrations (MIC), disk disk diffusion diameters, sir SIR data interpreted already. package can also determine SIR values based MIC disk diffusion values, read .sir() page. now, just clean SIR columns data using dplyr: basically cleaning, time start data inclusion.","code":"# method 1, be explicit about the columns: our_data <- our_data %>%   mutate_at(vars(AMX:GEN), as.sir)  # method 2, let the AMR package determine the eligible columns our_data <- our_data %>%   mutate_if(is_sir_eligible, as.sir)  # result: our_data #> # A tibble: 3,000 × 8 #>    patient_id hospital date       bacteria     AMX   AMC   CIP   GEN   #>    <chr>      <chr>    <date>     <mo>         <sir> <sir> <sir> <sir> #>  1 J3         A        2012-11-21 B_ESCHR_COLI R     I     S     S     #>  2 R7         A        2018-04-03 B_KLBSL_PNMN R     I     S     S     #>  3 P3         A        2014-09-19 B_ESCHR_COLI R     S     S     S     #>  4 P10        A        2015-12-10 B_ESCHR_COLI S     I     S     S     #>  5 B7         A        2015-03-02 B_ESCHR_COLI S     S     S     S     #>  6 W3         A        2018-03-31 B_STPHY_AURS R     S     R     S     #>  7 J8         A        2016-06-14 B_ESCHR_COLI R     S     S     S     #>  8 M3         A        2015-10-25 B_ESCHR_COLI R     S     S     S     #>  9 J3         A        2019-06-19 B_ESCHR_COLI S     S     S     S     #> 10 G6         A        2015-04-27 B_STPHY_AURS S     S     S     S     #> # ℹ 2,990 more rows"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"first-isolates","dir":"Articles","previous_headings":"Preparation","what":"First isolates","title":"How to conduct AMR data analysis","text":"need know isolates can actually use analysis without repetition bias. conduct analysis antimicrobial resistance, must include first isolate every patient per episode (Hindler et al., Clin Infect Dis. 2007). , easily get overestimate underestimate resistance antibiotic. Imagine patient admitted MRSA found 5 different blood cultures following weeks (yes, countries like Netherlands blood drawing policies). resistance percentage oxacillin isolates overestimated, included MRSA . clearly selection bias. Clinical Laboratory Standards Institute (CLSI) appoints follows: (…) preparing cumulative antibiogram guide clinical decisions empirical antimicrobial therapy initial infections, first isolate given species per patient, per analysis period (eg, one year) included, irrespective body site, antimicrobial susceptibility profile, phenotypical characteristics (eg, biotype). first isolate easily identified, cumulative antimicrobial susceptibility test data prepared using first isolate generally comparable cumulative antimicrobial susceptibility test data calculated methods, providing duplicate isolates excluded. M39-A4 Analysis Presentation Cumulative Antimicrobial Susceptibility Test Data, 4th Edition. CLSI, 2014. Chapter 6.4 AMR package includes methodology first_isolate() function able apply four different methods defined Hindler et al. 2007: phenotype-based, episode-based, patient-based, isolate-based. right method depends goals analysis, default phenotype-based method case method properly correct duplicate isolates. Read methods first_isolate() page. outcome function can easily added data: 90% suitable resistance analysis! can now filter filter() function, also dplyr package: future use, two syntaxes can shortened: end 2 712 isolates analysis. Now data looks like: Time analysis.","code":"our_data <- our_data %>%   mutate(first = first_isolate(info = TRUE)) #> ℹ Determining first isolates using an episode length of 365 days #> ℹ Using column 'bacteria' as input for col_mo. #> ℹ Using column 'date' as input for col_date. #> ℹ Using column 'patient_id' as input for col_patient_id. #> ℹ Basing inclusion on all antimicrobial results, using a points threshold #>   of 2 #> => Found 2,712 'phenotype-based' first isolates (90.4% of total where a #>    microbial ID was available) our_data_1st <- our_data %>%   filter(first == TRUE) our_data_1st <- our_data %>%   filter_first_isolate() our_data_1st #> # A tibble: 2,712 × 9 #>    patient_id hospital date       bacteria     AMX   AMC   CIP   GEN   first #>    <chr>      <chr>    <date>     <mo>         <sir> <sir> <sir> <sir> <lgl> #>  1 J3         A        2012-11-21 B_ESCHR_COLI R     I     S     S     TRUE  #>  2 R7         A        2018-04-03 B_KLBSL_PNMN R     I     S     S     TRUE  #>  3 P10        A        2015-12-10 B_ESCHR_COLI S     I     S     S     TRUE  #>  4 B7         A        2015-03-02 B_ESCHR_COLI S     S     S     S     TRUE  #>  5 W3         A        2018-03-31 B_STPHY_AURS R     S     R     S     TRUE  #>  6 M3         A        2015-10-25 B_ESCHR_COLI R     S     S     S     TRUE  #>  7 J3         A        2019-06-19 B_ESCHR_COLI S     S     S     S     TRUE  #>  8 G6         A        2015-04-27 B_STPHY_AURS S     S     S     S     TRUE  #>  9 P4         A        2011-06-21 B_ESCHR_COLI S     S     S     S     TRUE  #> 10 Z1         A        2014-09-05 B_ESCHR_COLI S     S     S     S     TRUE  #> # ℹ 2,702 more rows"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"analysing-the-data","dir":"Articles","previous_headings":"","what":"Analysing the data","title":"How to conduct AMR data analysis","text":"base R summary() function gives good first impression, comes support new mo sir classes now data set:","code":"summary(our_data_1st) #>   patient_id          hospital              date            #>  Length:2712        Length:2712        Min.   :2011-01-01   #>  Class :character   Class :character   1st Qu.:2013-05-03   #>  Mode  :character   Mode  :character   Median :2015-06-16   #>                                        Mean   :2015-06-21   #>                                        3rd Qu.:2017-08-24   #>                                        Max.   :2019-12-27   #>    bacteria               AMX                    AMC                 #>  Class :mo             Class:sir              Class:sir              #>  <NA>  :0              %S   :41.0% (n=1112)   %S   :52.0% (n=1409)   #>  Unique:4              %SDD : 0.0% (n=0)      %SDD : 0.0% (n=0)      #>  #1    :B_ESCHR_COLI   %I   :16.1% (n=437)    %I   :12.0% (n=325)    #>  #2    :B_STPHY_AURS   %R   :42.9% (n=1163)   %R   :36.1% (n=978)    #>  #3    :B_STRPT_PNMN   %NI  : 0.0% (n=0)      %NI  : 0.0% (n=0)      #>     CIP                    GEN                  first         #>  Class:sir              Class:sir              Mode:logical   #>  %S   :51.5% (n=1396)   %S   :59.6% (n=1616)   TRUE:2712      #>  %SDD : 0.0% (n=0)      %SDD : 0.0% (n=0)                     #>  %I   : 6.6% (n=178)    %I   : 3.1% (n=85)                    #>  %R   :42.0% (n=1138)   %R   :37.3% (n=1011)                  #>  %NI  : 0.0% (n=0)      %NI  : 0.0% (n=0)  glimpse(our_data_1st) #> Rows: 2,712 #> Columns: 9 #> $ patient_id <chr> \"J3\", \"R7\", \"P10\", \"B7\", \"W3\", \"M3\", \"J3\", \"G6\", \"P4\", \"Z1\"… #> $ hospital   <chr> \"A\", \"A\", \"A\", \"A\", \"A\", \"A\", \"A\", \"A\", \"A\", \"A\", \"A\", \"A\",… #> $ date       <date> 2012-11-21, 2018-04-03, 2015-12-10, 2015-03-02, 2018-03-31… #> $ bacteria   <mo> \"B_ESCHR_COLI\", \"B_KLBSL_PNMN\", \"B_ESCHR_COLI\", \"B_ESCHR_COL… #> $ AMX        <sir> R, R, S, S, R, R, S, S, S, S, R, S, S, S, R, R, R, R, S, R,… #> $ AMC        <sir> I, I, I, S, S, S, S, S, S, S, S, S, I, S, S, S, S, R, S, S,… #> $ CIP        <sir> S, S, S, S, R, S, S, S, S, S, S, S, S, S, S, S, S, S, S, S,… #> $ GEN        <sir> S, S, S, S, S, S, S, S, S, S, R, S, S, S, S, S, S, S, S, S,… #> $ first      <lgl> TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,…  # number of unique values per column: sapply(our_data_1st, n_distinct) #> patient_id   hospital       date   bacteria        AMX        AMC        CIP  #>        260          3       1852          4          3          3          3  #>        GEN      first  #>          3          1"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"availability-of-species","dir":"Articles","previous_headings":"Analysing the data","what":"Availability of species","title":"How to conduct AMR data analysis","text":"just get idea species distributed, create frequency table count() based name microorganisms:","code":"our_data %>%   count(mo_name(bacteria), sort = TRUE) #> # A tibble: 4 × 2 #>   `mo_name(bacteria)`          n #>   <chr>                    <int> #> 1 Escherichia coli          1518 #> 2 Staphylococcus aureus      730 #> 3 Streptococcus pneumoniae   426 #> 4 Klebsiella pneumoniae      326  our_data_1st %>%   count(mo_name(bacteria), sort = TRUE) #> # A tibble: 4 × 2 #>   `mo_name(bacteria)`          n #>   <chr>                    <int> #> 1 Escherichia coli          1319 #> 2 Staphylococcus aureus      676 #> 3 Streptococcus pneumoniae   400 #> 4 Klebsiella pneumoniae      317"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"select-and-filter-with-antibiotic-selectors","dir":"Articles","previous_headings":"Analysing the data","what":"Select and filter with antibiotic selectors","title":"How to conduct AMR data analysis","text":"Using -called antibiotic class selectors, can select filter columns based antibiotic class antibiotic results :","code":"our_data_1st %>%   select(date, aminoglycosides()) #> ℹ For aminoglycosides() using column 'GEN' (gentamicin) #> # A tibble: 2,712 × 2 #>    date       GEN   #>    <date>     <sir> #>  1 2012-11-21 S     #>  2 2018-04-03 S     #>  3 2015-12-10 S     #>  4 2015-03-02 S     #>  5 2018-03-31 S     #>  6 2015-10-25 S     #>  7 2019-06-19 S     #>  8 2015-04-27 S     #>  9 2011-06-21 S     #> 10 2014-09-05 S     #> # ℹ 2,702 more rows  our_data_1st %>%   select(bacteria, betalactams()) #> ℹ For betalactams() using columns 'AMX' (amoxicillin) and 'AMC' #>   (amoxicillin/clavulanic acid) #> # A tibble: 2,712 × 3 #>    bacteria     AMX   AMC   #>    <mo>         <sir> <sir> #>  1 B_ESCHR_COLI R     I     #>  2 B_KLBSL_PNMN R     I     #>  3 B_ESCHR_COLI S     I     #>  4 B_ESCHR_COLI S     S     #>  5 B_STPHY_AURS R     S     #>  6 B_ESCHR_COLI R     S     #>  7 B_ESCHR_COLI S     S     #>  8 B_STPHY_AURS S     S     #>  9 B_ESCHR_COLI S     S     #> 10 B_ESCHR_COLI S     S     #> # ℹ 2,702 more rows  our_data_1st %>%   select(bacteria, where(is.sir)) #> # A tibble: 2,712 × 5 #>    bacteria     AMX   AMC   CIP   GEN   #>    <mo>         <sir> <sir> <sir> <sir> #>  1 B_ESCHR_COLI R     I     S     S     #>  2 B_KLBSL_PNMN R     I     S     S     #>  3 B_ESCHR_COLI S     I     S     S     #>  4 B_ESCHR_COLI S     S     S     S     #>  5 B_STPHY_AURS R     S     R     S     #>  6 B_ESCHR_COLI R     S     S     S     #>  7 B_ESCHR_COLI S     S     S     S     #>  8 B_STPHY_AURS S     S     S     S     #>  9 B_ESCHR_COLI S     S     S     S     #> 10 B_ESCHR_COLI S     S     S     S     #> # ℹ 2,702 more rows  # filtering using AB selectors is also possible: our_data_1st %>%   filter(any(aminoglycosides() == \"R\")) #> ℹ For aminoglycosides() using column 'GEN' (gentamicin) #> # A tibble: 1,011 × 9 #>    patient_id hospital date       bacteria     AMX   AMC   CIP   GEN   first #>    <chr>      <chr>    <date>     <mo>         <sir> <sir> <sir> <sir> <lgl> #>  1 J5         A        2017-12-25 B_STRPT_PNMN R     S     S     R     TRUE  #>  2 X1         A        2017-07-04 B_STPHY_AURS R     S     S     R     TRUE  #>  3 B3         A        2016-07-24 B_ESCHR_COLI S     S     S     R     TRUE  #>  4 V7         A        2012-04-03 B_ESCHR_COLI S     S     S     R     TRUE  #>  5 C9         A        2017-03-23 B_ESCHR_COLI S     S     S     R     TRUE  #>  6 R1         A        2018-06-10 B_STPHY_AURS S     S     S     R     TRUE  #>  7 S2         A        2013-07-19 B_STRPT_PNMN S     S     S     R     TRUE  #>  8 P5         A        2019-03-09 B_STPHY_AURS S     S     S     R     TRUE  #>  9 Q8         A        2019-08-10 B_STPHY_AURS S     S     S     R     TRUE  #> 10 K5         A        2013-03-15 B_STRPT_PNMN S     S     S     R     TRUE  #> # ℹ 1,001 more rows  our_data_1st %>%   filter(all(betalactams() == \"R\")) #> ℹ For betalactams() using columns 'AMX' (amoxicillin) and 'AMC' #>   (amoxicillin/clavulanic acid) #> # A tibble: 483 × 9 #>    patient_id hospital date       bacteria     AMX   AMC   CIP   GEN   first #>    <chr>      <chr>    <date>     <mo>         <sir> <sir> <sir> <sir> <lgl> #>  1 M7         A        2013-07-22 B_STRPT_PNMN R     R     S     S     TRUE  #>  2 R10        A        2013-12-20 B_STPHY_AURS R     R     S     S     TRUE  #>  3 R7         A        2015-10-25 B_STPHY_AURS R     R     S     S     TRUE  #>  4 R8         A        2019-10-25 B_STPHY_AURS R     R     S     S     TRUE  #>  5 B6         A        2016-11-20 B_ESCHR_COLI R     R     R     R     TRUE  #>  6 I7         A        2015-08-19 B_ESCHR_COLI R     R     S     S     TRUE  #>  7 N3         A        2014-12-29 B_STRPT_PNMN R     R     R     S     TRUE  #>  8 Q2         A        2019-09-22 B_ESCHR_COLI R     R     S     S     TRUE  #>  9 X7         A        2011-03-20 B_ESCHR_COLI R     R     S     R     TRUE  #> 10 V1         A        2018-08-07 B_STPHY_AURS R     R     S     S     TRUE  #> # ℹ 473 more rows  # even works in base R (since R 3.0): our_data_1st[all(betalactams() == \"R\"), ] #> ℹ For betalactams() using columns 'AMX' (amoxicillin) and 'AMC' #>   (amoxicillin/clavulanic acid) #> # A tibble: 483 × 9 #>    patient_id hospital date       bacteria     AMX   AMC   CIP   GEN   first #>    <chr>      <chr>    <date>     <mo>         <sir> <sir> <sir> <sir> <lgl> #>  1 M7         A        2013-07-22 B_STRPT_PNMN R     R     S     S     TRUE  #>  2 R10        A        2013-12-20 B_STPHY_AURS R     R     S     S     TRUE  #>  3 R7         A        2015-10-25 B_STPHY_AURS R     R     S     S     TRUE  #>  4 R8         A        2019-10-25 B_STPHY_AURS R     R     S     S     TRUE  #>  5 B6         A        2016-11-20 B_ESCHR_COLI R     R     R     R     TRUE  #>  6 I7         A        2015-08-19 B_ESCHR_COLI R     R     S     S     TRUE  #>  7 N3         A        2014-12-29 B_STRPT_PNMN R     R     R     S     TRUE  #>  8 Q2         A        2019-09-22 B_ESCHR_COLI R     R     S     S     TRUE  #>  9 X7         A        2011-03-20 B_ESCHR_COLI R     R     S     R     TRUE  #> 10 V1         A        2018-08-07 B_STPHY_AURS R     R     S     S     TRUE  #> # ℹ 473 more rows"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"generate-antibiograms","dir":"Articles","previous_headings":"Analysing the data","what":"Generate antibiograms","title":"How to conduct AMR data analysis","text":"Since AMR v2.0 (March 2023), easy create different types antibiograms, support 20 different languages. four antibiogram types, proposed Klinker et al. (2021, DOI 10.1177/20499361211011373), supported new antibiogram() function: Traditional Antibiogram (TA) e.g, susceptibility Pseudomonas aeruginosa piperacillin/tazobactam (TZP) Combination Antibiogram (CA) e.g, sdditional susceptibility Pseudomonas aeruginosa TZP + tobramycin versus TZP alone Syndromic Antibiogram (SA) e.g, susceptibility Pseudomonas aeruginosa TZP among respiratory specimens (obtained among ICU patients ) Weighted-Incidence Syndromic Combination Antibiogram (WISCA) e.g, susceptibility Pseudomonas aeruginosa TZP among respiratory specimens (obtained among ICU patients ) male patients age >=65 years heart failure section, show use antibiogram() function create antibiogram types. starters, included example_isolates data set looks like:","code":"example_isolates #> # A tibble: 2,000 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-03 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  3 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  4 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  5 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  6 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  7 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  8 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  9 2002-01-16 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #> 10 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R     NA    S     NA    #> # ℹ 1,990 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, …"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"traditional-antibiogram","dir":"Articles","previous_headings":"Analysing the data > Generate antibiograms","what":"Traditional Antibiogram","title":"How to conduct AMR data analysis","text":"create traditional antibiogram, simply state antibiotics used. antibiotics argument antibiogram() function supports (combination) previously mentioned antibiotic class selectors: Notice antibiogram() function automatically prints right format using Quarto R Markdown (page), even applies italics taxonomic names (using italicise_taxonomy() internally). also uses language OS either English, Chinese, Czech, Danish, Dutch, Finnish, French, German, Greek, Italian, Japanese, Norwegian, Polish, Portuguese, Romanian, Russian, Spanish, Swedish, Turkish, Ukrainian. next example, force language Spanish using language argument:","code":"antibiogram(example_isolates,             antibiotics = c(aminoglycosides(), carbapenems())) #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) antibiogram(example_isolates,             mo_transform = \"gramstain\",             antibiotics = aminoglycosides(),             ab_transform = \"name\",             language = \"es\") #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin)"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"combined-antibiogram","dir":"Articles","previous_headings":"Analysing the data > Generate antibiograms","what":"Combined Antibiogram","title":"How to conduct AMR data analysis","text":"create combined antibiogram, use antibiotic codes names plus + character like :","code":"antibiogram(example_isolates,             antibiotics = c(\"TZP\", \"TZP+TOB\", \"TZP+GEN\"))"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"syndromic-antibiogram","dir":"Articles","previous_headings":"Analysing the data > Generate antibiograms","what":"Syndromic Antibiogram","title":"How to conduct AMR data analysis","text":"create syndromic antibiogram, syndromic_group argument must used. can column data, e.g. ifelse() calculations based certain columns:","code":"antibiogram(example_isolates,             antibiotics = c(aminoglycosides(), carbapenems()),             syndromic_group = \"ward\") #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem)"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"weighted-incidence-syndromic-combination-antibiogram-wisca","dir":"Articles","previous_headings":"Analysing the data > Generate antibiograms","what":"Weighted-Incidence Syndromic Combination Antibiogram (WISCA)","title":"How to conduct AMR data analysis","text":"create WISCA, must state combination therapy antibiotics argument (similar Combination Antibiogram), define syndromic group syndromic_group argument (similar Syndromic Antibiogram) cases predefined based clinical demographic characteristics (e.g., endocarditis 75+ females). next example simplification without clinical characteristics, just gives idea WISCA can created:","code":"wisca <- antibiogram(example_isolates,                      antibiotics = c(\"AMC\", \"AMC+CIP\", \"TZP\", \"TZP+TOB\"),                      mo_transform = \"gramstain\",                      minimum = 10, # this should be >= 30, but now just as example                      syndromic_group = ifelse(example_isolates$age >= 65 &                                                 example_isolates$gender == \"M\",                                               \"WISCA Group 1\", \"WISCA Group 2\")) wisca"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"plotting-antibiograms","dir":"Articles","previous_headings":"Analysing the data > Generate antibiograms","what":"Plotting antibiograms","title":"How to conduct AMR data analysis","text":"Antibiograms can plotted using autoplot() ggplot2 packages, since AMR package provides extension function:  calculate antimicrobial resistance sensible way, also correcting results, use resistance() susceptibility() functions.","code":"autoplot(wisca)"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"resistance-percentages","dir":"Articles","previous_headings":"Analysing the data","what":"Resistance percentages","title":"How to conduct AMR data analysis","text":"functions resistance() susceptibility() can used calculate antimicrobial resistance susceptibility. specific analyses, functions proportion_S(), proportion_SI(), proportion_I(), proportion_IR() proportion_R() can used determine proportion specific antimicrobial outcome. functions contain minimum argument, denoting minimum required number test results returning value. functions otherwise return NA. default minimum = 30, following CLSI M39-A4 guideline applying microbial epidemiology. per EUCAST guideline 2019, calculate resistance proportion R (proportion_R(), equal resistance()) susceptibility proportion S (proportion_SI(), equal susceptibility()). functions can used : can used conjunction group_by() summarise(), dplyr package: Author: Dr. Matthijs Berends, 26th Feb 2023","code":"our_data_1st %>% resistance(AMX) #> [1] 0.4288348 our_data_1st %>%   group_by(hospital) %>%   summarise(amoxicillin = resistance(AMX)) #> # A tibble: 3 × 2 #>   hospital amoxicillin #>   <chr>          <dbl> #> 1 A              0.342 #> 2 B              0.564 #> 3 C              0.372"},{"path":"https://msberends.github.io/AMR/articles/EUCAST.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"How to apply EUCAST rules","text":"EUCAST rules? European Committee Antimicrobial Susceptibility Testing (EUCAST) states website: EUCAST expert rules tabulated collection expert knowledge intrinsic resistances, exceptional resistance phenotypes interpretive rules may applied antimicrobial susceptibility testing order reduce errors make appropriate recommendations reporting particular resistances. Europe, lot medical microbiological laboratories already apply rules (Brown et al., 2015). package features latest insights intrinsic resistance unusual phenotypes (v3.1, 2016). Moreover, eucast_rules() function use purpose can also apply additional rules, like forcing ampicillin = R isolates amoxicillin/clavulanic acid = R.","code":""},{"path":"https://msberends.github.io/AMR/articles/EUCAST.html","id":"examples","dir":"Articles","previous_headings":"","what":"Examples","title":"How to apply EUCAST rules","text":"rules can used discard impossible bug-drug combinations data. example, Klebsiella produces beta-lactamase prevents ampicillin (amoxicillin) working . words, practically every strain Klebsiella resistant ampicillin. Sometimes, laboratory data can still contain strains ampicillin susceptible ampicillin. antibiogram available identification available, antibiogram re-interpreted based identification (namely, Klebsiella). EUCAST expert rules solve , can applied using eucast_rules(): convenient function mo_is_intrinsic_resistant() uses guideline, allows check one specific microorganisms antibiotics: EUCAST rules can used correction, can also used filling known resistance susceptibility based results antimicrobials drugs. process called interpretive reading, basically form imputation, part eucast_rules() function well:","code":"oops <- data.frame(   mo = c(     \"Klebsiella\",     \"Escherichia\"   ),   ampicillin = \"S\" ) oops #>            mo ampicillin #> 1  Klebsiella          S #> 2 Escherichia          S  eucast_rules(oops, info = FALSE) #>            mo ampicillin #> 1  Klebsiella          R #> 2 Escherichia          S mo_is_intrinsic_resistant(   c(\"Klebsiella\", \"Escherichia\"),   \"ampicillin\" ) #> [1]  TRUE FALSE  mo_is_intrinsic_resistant(   \"Klebsiella\",   c(\"ampicillin\", \"kanamycin\") ) #> [1]  TRUE FALSE data <- data.frame(   mo = c(     \"Staphylococcus aureus\",     \"Enterococcus faecalis\",     \"Escherichia coli\",     \"Klebsiella pneumoniae\",     \"Pseudomonas aeruginosa\"   ),   VAN = \"-\", # Vancomycin   AMX = \"-\", # Amoxicillin   COL = \"-\", # Colistin   CAZ = \"-\", # Ceftazidime   CXM = \"-\", # Cefuroxime   PEN = \"S\", # Benzylenicillin   FOX = \"S\", # Cefoxitin   stringsAsFactors = FALSE ) data eucast_rules(data)"},{"path":"https://msberends.github.io/AMR/articles/MDR.html","id":"type-of-input","dir":"Articles","previous_headings":"","what":"Type of input","title":"How to determine multi-drug resistance (MDR)","text":"mdro() function takes data set input, regular data.frame. tries automatically determine right columns info isolates, name species columns results antimicrobial agents. See help page info set right settings data command ?mdro. WHONET data (data), settings automatically set correctly.","code":""},{"path":"https://msberends.github.io/AMR/articles/MDR.html","id":"guidelines","dir":"Articles","previous_headings":"","what":"Guidelines","title":"How to determine multi-drug resistance (MDR)","text":"mdro() function support multiple guidelines. can select guideline guideline parameter. Currently supported guidelines (case-insensitive): guideline = \"CMI2012\" (default) Magiorakos AP, Srinivasan et al. “Multidrug-resistant, extensively drug-resistant pandrug-resistant bacteria: international expert proposal interim standard definitions acquired resistance.” Clinical Microbiology Infection (2012) (link) guideline = \"EUCAST3.2\" (simply guideline = \"EUCAST\") European international guideline - EUCAST Expert Rules Version 3.2 “Intrinsic Resistance Unusual Phenotypes” (link) guideline = \"EUCAST3.1\" European international guideline - EUCAST Expert Rules Version 3.1 “Intrinsic Resistance Exceptional Phenotypes Tables” (link) guideline = \"TB\" international guideline multi-drug resistant tuberculosis - World Health Organization “Companion handbook guidelines programmatic management drug-resistant tuberculosis” (link) guideline = \"MRGN\" German national guideline - Mueller et al. (2015) Antimicrobial Resistance Infection Control 4:7. DOI: 10.1186/s13756-015-0047-6 guideline = \"BRMO\" Dutch national guideline - Rijksinstituut voor Volksgezondheid en Milieu “WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen) (ZKH)” (link) Please suggest (country-specific) guidelines letting us know: https://github.com/msberends/AMR/issues/new.","code":""},{"path":"https://msberends.github.io/AMR/articles/MDR.html","id":"custom-guidelines","dir":"Articles","previous_headings":"Guidelines","what":"Custom Guidelines","title":"How to determine multi-drug resistance (MDR)","text":"can also use custom guideline. Custom guidelines can set custom_mdro_guideline() function. great importance custom rules determine MDROs hospital, e.g., rules dependent ward, state contact isolation variables data. familiar case_when() dplyr package, recognise input method set rules. Rules must set using R considers ‘formula notation’: row/isolate matches first rule, value first ~ (case ‘Elderly Type ’) set MDRO value. Otherwise, second rule tried . maximum number rules unlimited. can print rules set console overview. Colours help reading console supports colours. outcome function can used guideline argument mdro() function: rules set (custom object case) exported shared file location using saveRDS() collaborate multiple users. custom rules set imported using readRDS().","code":"custom <- custom_mdro_guideline(   CIP == \"R\" & age > 60 ~ \"Elderly Type A\",   ERY == \"R\" & age > 60 ~ \"Elderly Type B\" ) custom #> A set of custom MDRO rules: #>   1. If CIP is \"R\" and age is higher than 60 then: Elderly Type A #>   2. If ERY is \"R\" and age is higher than 60 then: Elderly Type B #>   3. Otherwise: Negative #>  #> Unmatched rows will return NA. #> Results will be of class 'factor', with ordered levels: Negative < Elderly Type A < Elderly Type B x <- mdro(example_isolates, guideline = custom) table(x) #> x #>       Negative Elderly Type A Elderly Type B  #>           1070            198            732"},{"path":"https://msberends.github.io/AMR/articles/MDR.html","id":"examples","dir":"Articles","previous_headings":"","what":"Examples","title":"How to determine multi-drug resistance (MDR)","text":"mdro() function always returns ordered factor predefined guidelines. example, output default guideline Magiorakos et al. returns factor levels ‘Negative’, ‘MDR’, ‘XDR’ ‘PDR’ order. next example uses example_isolates data set. data set included package contains full antibiograms 2,000 microbial isolates. reflects reality can used practise AMR data analysis. test MDR/XDR/PDR guideline data set, get: Frequency table Class: factor > ordered (numeric) Length: 2,000 Levels: 4: Negative < Multi-drug-resistant (MDR) < Extensively drug-resistant … Available: 1,729 (86.45%, NA: 271 = 13.55%) Unique: 2 another example, create data set determine multi-drug resistant TB: column names automatically verified valid drug names codes, worked exactly way: data set now looks like : can now add interpretation MDR-TB data set. can use: shortcut mdr_tb(): Create frequency table results: Frequency table Class: factor > ordered (numeric) Length: 5,000 Levels: 5: Negative < Mono-resistant < Poly-resistant < Multi-drug-resistant <… Available: 5,000 (100%, NA: 0 = 0%) Unique: 5","code":"library(dplyr) # to support pipes: %>% library(cleaner) # to create frequency tables example_isolates %>%   mdro() %>%   freq() # show frequency table of the result #> Warning: in mdro(): NA introduced for isolates where the available percentage of #> antimicrobial classes was below 50% (set with pct_required_classes) # random_sir() is a helper function to generate # a random vector with values S, I and R my_TB_data <- data.frame(   rifampicin = random_sir(5000),   isoniazid = random_sir(5000),   gatifloxacin = random_sir(5000),   ethambutol = random_sir(5000),   pyrazinamide = random_sir(5000),   moxifloxacin = random_sir(5000),   kanamycin = random_sir(5000) ) my_TB_data <- data.frame(   RIF = random_sir(5000),   INH = random_sir(5000),   GAT = random_sir(5000),   ETH = random_sir(5000),   PZA = random_sir(5000),   MFX = random_sir(5000),   KAN = random_sir(5000) ) head(my_TB_data) #>   rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin #> 1          I         R            S          S            S            S #> 2          S         S            I          R            R            S #> 3          R         I            I          I            R            I #> 4          I         S            S          S            S            S #> 5          I         I            I          S            I            S #> 6          R         S            R          S            I            I #>   kanamycin #> 1         R #> 2         I #> 3         S #> 4         I #> 5         I #> 6         I mdro(my_TB_data, guideline = \"TB\") my_TB_data$mdr <- mdr_tb(my_TB_data) #> ℹ No column found as input for col_mo, assuming all rows contain #>   Mycobacterium tuberculosis. freq(my_TB_data$mdr)"},{"path":[]},{"path":"https://msberends.github.io/AMR/articles/PCA.html","id":"transforming","dir":"Articles","previous_headings":"","what":"Transforming","title":"How to conduct principal component analysis (PCA) for AMR","text":"PCA, need transform AMR data first. example_isolates data set package looks like: Now transform data set resistance percentages per taxonomic order genus:","code":"library(AMR) library(dplyr) glimpse(example_isolates) #> Rows: 2,000 #> Columns: 46 #> $ date    <date> 2002-01-02, 2002-01-03, 2002-01-07, 2002-01-07, 2002-01-13, 2… #> $ patient <chr> \"A77334\", \"A77334\", \"067927\", \"067927\", \"067927\", \"067927\", \"4… #> $ age     <dbl> 65, 65, 45, 45, 45, 45, 78, 78, 45, 79, 67, 67, 71, 71, 75, 50… #> $ gender  <chr> \"F\", \"F\", \"F\", \"F\", \"F\", \"F\", \"M\", \"M\", \"F\", \"F\", \"M\", \"M\", \"M… #> $ ward    <chr> \"Clinical\", \"Clinical\", \"ICU\", \"ICU\", \"ICU\", \"ICU\", \"Clinical\"… #> $ mo      <mo> \"B_ESCHR_COLI\", \"B_ESCHR_COLI\", \"B_STPHY_EPDR\", \"B_STPHY_EPDR\",… #> $ PEN     <sir> R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, S,… #> $ OXA     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ FLC     <sir> NA, NA, R, R, R, R, S, S, R, S, S, S, NA, NA, NA, NA, NA, R, R… #> $ AMX     <sir> NA, NA, NA, NA, NA, NA, R, R, NA, NA, NA, NA, NA, NA, R, NA, N… #> $ AMC     <sir> I, I, NA, NA, NA, NA, S, S, NA, NA, S, S, I, I, R, I, I, NA, N… #> $ AMP     <sir> NA, NA, NA, NA, NA, NA, R, R, NA, NA, NA, NA, NA, NA, R, NA, N… #> $ TZP     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ CZO     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, NA,… #> $ FEP     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ CXM     <sir> I, I, R, R, R, R, S, S, R, S, S, S, S, S, NA, S, S, R, R, S, S… #> $ FOX     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, NA,… #> $ CTX     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, S, S, NA, S, S… #> $ CAZ     <sir> NA, NA, R, R, R, R, R, R, R, R, R, R, NA, NA, NA, S, S, R, R, … #> $ CRO     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, S, S, NA, S, S… #> $ GEN     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ TOB     <sir> NA, NA, NA, NA, NA, NA, S, S, NA, NA, NA, NA, S, S, NA, NA, NA… #> $ AMK     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ KAN     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ TMP     <sir> R, R, S, S, R, R, R, R, S, S, NA, NA, S, S, S, S, S, R, R, R, … #> $ SXT     <sir> R, R, S, S, NA, NA, NA, NA, S, S, NA, NA, S, S, S, S, S, NA, N… #> $ NIT     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R,… #> $ FOS     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ LNZ     <sir> R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R, R, R, N… #> $ CIP     <sir> NA, NA, NA, NA, NA, NA, NA, NA, S, S, NA, NA, NA, NA, NA, S, S… #> $ MFX     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ VAN     <sir> R, R, S, S, S, S, S, S, S, S, NA, NA, R, R, R, R, R, S, S, S, … #> $ TEC     <sir> R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R, R, R, N… #> $ TCY     <sir> R, R, S, S, S, S, S, S, S, I, S, S, NA, NA, I, R, R, S, I, R, … #> $ TGC     <sir> NA, NA, S, S, S, S, S, S, S, NA, S, S, NA, NA, NA, R, R, S, NA… #> $ DOX     <sir> NA, NA, S, S, S, S, S, S, S, NA, S, S, NA, NA, NA, R, R, S, NA… #> $ ERY     <sir> R, R, R, R, R, R, S, S, R, S, S, S, R, R, R, R, R, R, R, R, S,… #> $ CLI     <sir> R, R, NA, NA, NA, R, NA, NA, NA, NA, NA, NA, R, R, R, R, R, NA… #> $ AZM     <sir> R, R, R, R, R, R, S, S, R, S, S, S, R, R, R, R, R, R, R, R, S,… #> $ IPM     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, S, S, NA, S, S… #> $ MEM     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ MTR     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ CHL     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ COL     <sir> NA, NA, R, R, R, R, R, R, R, R, R, R, NA, NA, NA, R, R, R, R, … #> $ MUP     <sir> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA… #> $ RIF     <sir> R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R, R, R, N… resistance_data <- example_isolates %>%   group_by(     order = mo_order(mo), # group on anything, like order     genus = mo_genus(mo)   ) %>% #  and genus as we do here   summarise_if(is.sir, resistance) %>% # then get resistance of all drugs   select(     order, genus, AMC, CXM, CTX,     CAZ, GEN, TOB, TMP, SXT   ) # and select only relevant columns  head(resistance_data) #> # A tibble: 6 × 10 #> # Groups:   order [5] #>   order             genus          AMC   CXM   CTX   CAZ   GEN   TOB   TMP   SXT #>   <chr>             <chr>        <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 (unknown order)   (unknown ge…    NA    NA    NA    NA    NA    NA    NA    NA #> 2 Actinomycetales   Schaalia        NA    NA    NA    NA    NA    NA    NA    NA #> 3 Bacteroidales     Bacteroides     NA    NA    NA    NA    NA    NA    NA    NA #> 4 Campylobacterales Campylobact…    NA    NA    NA    NA    NA    NA    NA    NA #> 5 Caryophanales     Gemella         NA    NA    NA    NA    NA    NA    NA    NA #> 6 Caryophanales     Listeria        NA    NA    NA    NA    NA    NA    NA    NA"},{"path":"https://msberends.github.io/AMR/articles/PCA.html","id":"perform-principal-component-analysis","dir":"Articles","previous_headings":"","what":"Perform principal component analysis","title":"How to conduct principal component analysis (PCA) for AMR","text":"new pca() function automatically filter rows contain numeric values selected variables, now need : result can reviewed good old summary() function: Good news. first two components explain total 93.3% variance (see PC1 PC2 values Proportion Variance. can create -called biplot base R biplot() function, see antimicrobial resistance per drug explain difference per microorganism.","code":"pca_result <- pca(resistance_data) #> ℹ Columns selected for PCA: \"AMC\", \"CAZ\", \"CTX\", \"CXM\", \"GEN\", \"SXT\", #>   \"TMP\", and \"TOB\". Total observations available: 7. summary(pca_result) #> Groups (n=4, named as 'order'): #> [1] \"Caryophanales\"    \"Enterobacterales\" \"Lactobacillales\"  \"Pseudomonadales\" #> Importance of components: #>                           PC1    PC2    PC3     PC4     PC5     PC6       PC7 #> Standard deviation     2.1539 1.6807 0.6138 0.33879 0.20808 0.03140 1.232e-16 #> Proportion of Variance 0.5799 0.3531 0.0471 0.01435 0.00541 0.00012 0.000e+00 #> Cumulative Proportion  0.5799 0.9330 0.9801 0.99446 0.99988 1.00000 1.000e+00 #> Groups (n=4, named as 'order'): #> [1] \"Caryophanales\"    \"Enterobacterales\" \"Lactobacillales\"  \"Pseudomonadales\""},{"path":"https://msberends.github.io/AMR/articles/PCA.html","id":"plotting-the-results","dir":"Articles","previous_headings":"","what":"Plotting the results","title":"How to conduct principal component analysis (PCA) for AMR","text":"can’t see explanation points. Perhaps works better new ggplot_pca() function, automatically adds right labels even groups:  can also print ellipse per group, edit appearance:","code":"biplot(pca_result) ggplot_pca(pca_result) ggplot_pca(pca_result, ellipse = TRUE) +   ggplot2::labs(title = \"An AMR/PCA biplot!\")"},{"path":"https://msberends.github.io/AMR/articles/WHONET.html","id":"import-of-data","dir":"Articles","previous_headings":"","what":"Import of data","title":"How to work with WHONET data","text":"tutorial assumes already imported WHONET data e.g. readxl package. RStudio, can done using menu button ‘Import Dataset’ tab ‘Environment’. Choose option ‘Excel’ select exported file. Make sure date fields imported correctly. example syntax look like : package comes example data set WHONET. use analysis.","code":"library(readxl) data <- read_excel(path = \"path/to/your/file.xlsx\")"},{"path":"https://msberends.github.io/AMR/articles/WHONET.html","id":"preparation","dir":"Articles","previous_headings":"","what":"Preparation","title":"How to work with WHONET data","text":"First, load relevant packages yet . use tidyverse analyses. . don’t know yet, suggest read website: https://www.tidyverse.org/. transform variables simplify automate analysis: Microorganisms transformed microorganism codes (called mo) using Catalogue Life reference data set, contains ~70,000 microorganisms taxonomic kingdoms Bacteria, Fungi Protozoa. tranformation .mo(). function also recognises almost WHONET abbreviations microorganisms. Antimicrobial results interpretations clean valid. words, contain values \"S\", \"\" \"R\". exactly .sir() function . errors warnings, values transformed succesfully. also created package dedicated data cleaning checking, called cleaner package. freq() function can used create frequency tables. let’s check data, couple frequency tables: Frequency table Class: character Length: 500 Available: 500 (100%, NA: 0 = 0%) Unique: 38 Shortest: 11 Longest: 40 (omitted 28 entries, n = 57 [11.4%]) Frequency table Class: factor > ordered > sir (numeric) Length: 500 Levels: 5: S < SDD < < R < NI Available: 481 (96.2%, NA: 19 = 3.8%) Unique: 3 Drug: Amoxicillin/clavulanic acid (AMC, J01CR02) Drug group: Beta-lactams/penicillins %SI: 78.59%","code":"library(dplyr) # part of tidyverse library(ggplot2) # part of tidyverse library(AMR) # this package library(cleaner) # to create frequency tables # transform variables data <- WHONET %>%   # get microbial ID based on given organism   mutate(mo = as.mo(Organism)) %>%   # transform everything from \"AMP_ND10\" to \"CIP_EE\" to the new `sir` class   mutate_at(vars(AMP_ND10:CIP_EE), as.sir) # our newly created `mo` variable, put in the mo_name() function data %>% freq(mo_name(mo), nmax = 10) # our transformed antibiotic columns # amoxicillin/clavulanic acid (J01CR02) as an example data %>% freq(AMC_ND2)"},{"path":"https://msberends.github.io/AMR/articles/WHONET.html","id":"a-first-glimpse-at-results","dir":"Articles","previous_headings":"","what":"A first glimpse at results","title":"How to work with WHONET data","text":"easy ggplot already give lot information, using included ggplot_sir() function:","code":"data %>%   group_by(Country) %>%   select(Country, AMP_ND2, AMC_ED20, CAZ_ED10, CIP_ED5) %>%   ggplot_sir(translate_ab = \"ab\", facet = \"Country\", datalabels = FALSE)"},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"microorganisms-full-microbial-taxonomy","dir":"Articles","previous_headings":"","what":"microorganisms: Full Microbial Taxonomy","title":"Data sets for download / own use","text":"data set 70 547 rows 26 columns, containing following column names:mo, fullname, status, kingdom, phylum, class, order, family, genus, species, subspecies, rank, ref, oxygen_tolerance, source, lpsn, lpsn_parent, lpsn_renamed_to, mycobank, mycobank_parent, mycobank_renamed_to, gbif, gbif_parent, gbif_renamed_to, prevalence, snomed. data set R available microorganisms, load AMR package. last updated 16 July 2024 12:51:57 UTC. Find info structure data set . Direct download links: Download original R Data Structure (RDS) file (1.6 MB) Download tab-separated text file (15.9 MB) Download Microsoft Excel workbook (7.8 MB) Download Apache Feather file (19 MB) Download Apache Parquet file (0 kB) Download SAS transport (XPT) file (69.5 MB) Download IBM SPSS Statistics data file (24.5 MB) Download Stata DTA file (69.5 MB) NOTE: exported files SAS, SPSS Stata contain first 50 SNOMED codes per record, file size otherwise exceed 100 MB; file size limit GitHub. file structures compression techniques inefficient. Advice? Use R instead. ’s free much better many ways. tab-separated text file Microsoft Excel workbook contain SNOMED codes comma separated values.","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"source","dir":"Articles","previous_headings":"microorganisms: Full Microbial Taxonomy","what":"Source","title":"Data sets for download / own use","text":"data set contains full microbial taxonomy six kingdoms List Prokaryotic names Standing Nomenclature (LPSN) Global Biodiversity Information Facility (GBIF): Parte, AC et al. (2020). List Prokaryotic names Standing Nomenclature (LPSN) moves DSMZ. International Journal Systematic Evolutionary Microbiology, 70, 5607-5612; . Accessed https://lpsn.dsmz.de June 24th, 2024. GBIF Secretariat (2023). GBIF Backbone Taxonomy. Checklist dataset . Accessed https://www.gbif.org June 24th, 2024. Public Health Information Network Vocabulary Access Distribution System (PHIN VADS). US Edition SNOMED CT 1 September 2020. Value Set Name ‘Microorganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: https://phinvads.cdc.gov","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"example-content","dir":"Articles","previous_headings":"microorganisms: Full Microbial Taxonomy","what":"Example content","title":"Data sets for download / own use","text":"Included (sub)species per taxonomic kingdom: Example rows filtering genus Escherichia:","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"antibiotics-antibiotic-antifungal-drugs","dir":"Articles","previous_headings":"","what":"antibiotics: Antibiotic (+Antifungal) Drugs","title":"Data sets for download / own use","text":"data set 485 rows 14 columns, containing following column names:ab, cid, name, group, atc, atc_group1, atc_group2, abbreviations, synonyms, oral_ddd, oral_units, iv_ddd, iv_units, loinc. data set R available antibiotics, load AMR package. last updated 14 June 2024 20:39:01 UTC. Find info structure data set . Direct download links: Download original R Data Structure (RDS) file (44 kB) Download tab-separated text file (0.1 MB) Download Microsoft Excel workbook (73 kB) Download Apache Feather file (0.2 MB) Download Apache Parquet file (0 kB) Download SAS transport (XPT) file (1.5 MB) Download IBM SPSS Statistics data file (0.4 MB) Download Stata DTA file (0.5 MB) tab-separated text file Microsoft Excel workbook, SAS, SPSS Stata files contain ATC codes, common abbreviations, trade names LOINC codes comma separated values.","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"source-1","dir":"Articles","previous_headings":"antibiotics: Antibiotic (+Antifungal) Drugs","what":"Source","title":"Data sets for download / own use","text":"data set contains EARS-Net ATC codes gathered WHONET, compound IDs PubChem. also contains brand names (synonyms) found PubChem Defined Daily Doses (DDDs) oral parenteral administration. ATC/DDD index Collaborating Centre Drug Statistics Methodology (note: may used commercial purposes, freely available CC website personal use) PubChem US National Library Medicine WHONET software 2019 LOINC (Logical Observation Identifiers Names Codes)","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"antivirals-antiviral-drugs","dir":"Articles","previous_headings":"","what":"antivirals: Antiviral Drugs","title":"Data sets for download / own use","text":"data set 120 rows 11 columns, containing following column names:av, name, atc, cid, atc_group, synonyms, oral_ddd, oral_units, iv_ddd, iv_units, loinc. data set R available antivirals, load AMR package. last updated 20 October 2023 12:51:48 UTC. Find info structure data set . Direct download links: Download original R Data Structure (RDS) file (6 kB) Download tab-separated text file (17 kB) Download Microsoft Excel workbook (16 kB) Download Apache Feather file (16 kB) Download Apache Parquet file (13 kB) Download SAS transport (XPT) file (73 kB) Download IBM SPSS Statistics data file (32 kB) Download Stata DTA file (78 kB) tab-separated text file Microsoft Excel workbook, SAS, SPSS Stata files contain trade names LOINC codes comma separated values.","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"source-2","dir":"Articles","previous_headings":"antivirals: Antiviral Drugs","what":"Source","title":"Data sets for download / own use","text":"data set contains ATC codes gathered compound IDs PubChem. also contains brand names (synonyms) found PubChem Defined Daily Doses (DDDs) oral parenteral administration. ATC/DDD index Collaborating Centre Drug Statistics Methodology (note: may used commercial purposes, freely available CC website personal use) PubChem US National Library Medicine LOINC (Logical Observation Identifiers Names Codes)","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"clinical_breakpoints-interpretation-from-mic-values-disk-diameters-to-sir","dir":"Articles","previous_headings":"","what":"clinical_breakpoints: Interpretation from MIC values & disk diameters to SIR","title":"Data sets for download / own use","text":"data set 34 063 rows 14 columns, containing following column names:guideline, type, host, method, site, mo, rank_index, ab, ref_tbl, disk_dose, breakpoint_S, breakpoint_R, uti, is_SDD. data set R available clinical_breakpoints, load AMR package. last updated 16 July 2024 12:51:57 UTC. Find info structure data set . Direct download links: Download original R Data Structure (RDS) file (70 kB) Download tab-separated text file (3.1 MB) Download Microsoft Excel workbook (2 MB) Download Apache Feather file (4.9 MB) Download Apache Parquet file (0 kB) Download SAS transport (XPT) file (9.6 MB) Download IBM SPSS Statistics data file (5.6 MB) Download Stata DTA file (9.3 MB)","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"source-3","dir":"Articles","previous_headings":"clinical_breakpoints: Interpretation from MIC values & disk diameters to SIR","what":"Source","title":"Data sets for download / own use","text":"data set contains interpretation rules MIC values disk diffusion diameters. Included guidelines CLSI (2011-2024) EUCAST (2011-2024). Clinical breakpoints package validated imported WHONET, free desktop Windows application developed supported Collaborating Centre Surveillance Antimicrobial Resistance. can read website. developers WHONET AMR package contact sharing work. highly appreciate development WHONET software. CEO CLSI chairman EUCAST endorsed work public use AMR package (consequently use breakpoints) June 2023, future development distributing clinical breakpoints discussed meeting CLSI, EUCAST, , developers WHONET AMR package. NOTE: AMR package (WHONET software well) contains internal methods apply guidelines, rather complex. example, breakpoints must applied certain species groups (case package available microorganisms.groups data set). important considered using breakpoints use.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"intrinsic_resistant-intrinsic-bacterial-resistance","dir":"Articles","previous_headings":"","what":"intrinsic_resistant: Intrinsic Bacterial Resistance","title":"Data sets for download / own use","text":"data set 340 804 rows 2 columns, containing following column names:mo ab. data set R available intrinsic_resistant, load AMR package. last updated 16 July 2024 12:51:57 UTC. Find info structure data set . Direct download links: Download original R Data Structure (RDS) file (0.1 MB) Download tab-separated text file (12.4 MB) Download Microsoft Excel workbook (3.4 MB) Download Apache Feather file (13.1 MB) Download Apache Parquet file (0 kB) Download SAS transport (XPT) file (28.3 MB) Download IBM SPSS Statistics data file (18.4 MB) Download Stata DTA file (28.3 MB)","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"source-4","dir":"Articles","previous_headings":"intrinsic_resistant: Intrinsic Bacterial Resistance","what":"Source","title":"Data sets for download / own use","text":"data set contains defined intrinsic resistance EUCAST bug-drug combinations, based ‘EUCAST Expert Rules’ ‘EUCAST Intrinsic Resistance Unusual Phenotypes’ v3.3 (2021).","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"example-content-4","dir":"Articles","previous_headings":"intrinsic_resistant: Intrinsic Bacterial Resistance","what":"Example content","title":"Data sets for download / own use","text":"Example rows filtering Enterobacter cloacae:","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"dosage-dosage-guidelines-from-eucast","dir":"Articles","previous_headings":"","what":"dosage: Dosage Guidelines from EUCAST","title":"Data sets for download / own use","text":"data set 503 rows 9 columns, containing following column names:ab, name, type, dose, dose_times, administration, notes, original_txt, eucast_version. data set R available dosage, load AMR package. last updated 22 June 2023 13:10:59 UTC. Find info structure data set . Direct download links: Download original R Data Structure (RDS) file (3 kB) Download tab-separated text file (43 kB) Download Microsoft Excel workbook (25 kB) Download Apache Feather file (21 kB) Download Apache Parquet file (9 kB) Download SAS transport (XPT) file (0.1 MB) Download IBM SPSS Statistics data file (64 kB) Download Stata DTA file (0.1 MB)","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"source-5","dir":"Articles","previous_headings":"dosage: Dosage Guidelines from EUCAST","what":"Source","title":"Data sets for download / own use","text":"EUCAST breakpoints used package based dosages data set. Currently included dosages data set meant :  (), ‘EUCAST Clinical Breakpoint Tables’ v11.0 (2021), ‘EUCAST Clinical Breakpoint Tables’ v12.0 (2022).","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"example_isolates-example-data-for-practice","dir":"Articles","previous_headings":"","what":"example_isolates: Example Data for Practice","title":"Data sets for download / own use","text":"data set 2 000 rows 46 columns, containing following column names:date, patient, age, gender, ward, mo, PEN, OXA, FLC, AMX, AMC, AMP, TZP, CZO, FEP, CXM, FOX, CTX, CAZ, CRO, GEN, TOB, AMK, KAN, TMP, SXT, NIT, FOS, LNZ, CIP, MFX, VAN, TEC, TCY, TGC, DOX, ERY, CLI, AZM, IPM, MEM, MTR, CHL, COL, MUP, RIF. data set R available example_isolates, load AMR package. last updated 15 June 2024 13:33:49 UTC. Find info structure data set .","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"source-6","dir":"Articles","previous_headings":"example_isolates: Example Data for Practice","what":"Source","title":"Data sets for download / own use","text":"data set contains randomised fictitious data, reflects reality can used practise AMR data analysis.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"example_isolates_unclean-example-data-for-practice","dir":"Articles","previous_headings":"","what":"example_isolates_unclean: Example Data for Practice","title":"Data sets for download / own use","text":"data set 3 000 rows 8 columns, containing following column names:patient_id, hospital, date, bacteria, AMX, AMC, CIP, GEN. data set R available example_isolates_unclean, load AMR package. last updated 27 August 2022 18:49:37 UTC. Find info structure data set .","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"source-7","dir":"Articles","previous_headings":"example_isolates_unclean: Example Data for Practice","what":"Source","title":"Data sets for download / own use","text":"data set contains randomised fictitious data, reflects reality can used practise AMR data analysis.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"microorganisms-groups-species-groups-and-microbiological-complexes","dir":"Articles","previous_headings":"","what":"microorganisms.groups: Species Groups and Microbiological Complexes","title":"Data sets for download / own use","text":"data set 521 rows 4 columns, containing following column names:mo_group, mo, mo_group_name, mo_name. data set R available microorganisms.groups, load AMR package. last updated 14 July 2023 08:49:06 UTC. Find info structure data set . Direct download links: Download original R Data Structure (RDS) file (6 kB) Download tab-separated text file (49 kB) Download Microsoft Excel workbook (20 kB) Download Apache Feather file (19 kB) Download Apache Parquet file (13 kB) Download SAS transport (XPT) file (0 kB) Download IBM SPSS Statistics data file (64 kB) Download Stata DTA file (81 kB)","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"source-8","dir":"Articles","previous_headings":"microorganisms.groups: Species Groups and Microbiological Complexes","what":"Source","title":"Data sets for download / own use","text":"data set contains species groups microbiological complexes, used clinical_breakpoints data set.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"microorganisms-codes-common-laboratory-codes","dir":"Articles","previous_headings":"","what":"microorganisms.codes: Common Laboratory Codes","title":"Data sets for download / own use","text":"data set 4 971 rows 2 columns, containing following column names:code mo. data set R available microorganisms.codes, load AMR package. last updated 16 July 2024 12:51:57 UTC. Find info structure data set . Direct download links: Download original R Data Structure (RDS) file (22 kB) Download tab-separated text file (0.1 MB) Download Microsoft Excel workbook (82 kB) Download Apache Feather file (0.1 MB) Download Apache Parquet file (0 kB) Download SAS transport (XPT) file (0 kB) Download IBM SPSS Statistics data file (0.1 MB) Download Stata DTA file (0.1 MB)","code":""},{"path":"https://msberends.github.io/AMR/articles/datasets.html","id":"source-9","dir":"Articles","previous_headings":"microorganisms.codes: Common Laboratory Codes","what":"Source","title":"Data sets for download / own use","text":"data set contains commonly used codes microorganisms, laboratory systems WHONET.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/articles/resistance_predict.html","id":"needed-r-packages","dir":"Articles","previous_headings":"","what":"Needed R packages","title":"How to predict antimicrobial resistance","text":"many uses R, need additional packages AMR data analysis. package works closely together tidyverse packages dplyr ggplot2. tidyverse tremendously improves way conduct data science - allows natural way writing syntaxes creating beautiful plots R. AMR package depends packages even extends use functions.","code":"library(dplyr) library(ggplot2) library(AMR)  # (if not yet installed, install with:) # install.packages(c(\"tidyverse\", \"AMR\"))"},{"path":"https://msberends.github.io/AMR/articles/resistance_predict.html","id":"prediction-analysis","dir":"Articles","previous_headings":"","what":"Prediction analysis","title":"How to predict antimicrobial resistance","text":"package contains function resistance_predict(), takes input functions AMR data analysis. Based date column, calculates cases per year uses regression model predict antimicrobial resistance. basically easy : function look date column col_date set. running commands, summary regression model printed unless using resistance_predict(..., info = FALSE). text printed summary - actual result (output) function data.frame containing year: number observations, actual observed resistance, estimated resistance standard error estimation: function plot available base R, can extended packages depend output based type input. extended function cope resistance predictions:  fastest way plot result. automatically adds right axes, error bars, titles, number available observations type model. also support ggplot2 package custom function ggplot_sir_predict() create appealing plots:","code":"# resistance prediction of piperacillin/tazobactam (TZP): resistance_predict(tbl = example_isolates, col_date = \"date\", col_ab = \"TZP\", model = \"binomial\")  # or: example_isolates %>%   resistance_predict(     col_ab = \"TZP\",     model = \"binomial\"   )  # to bind it to object 'predict_TZP' for example: predict_TZP <- example_isolates %>%   resistance_predict(     col_ab = \"TZP\",     model = \"binomial\"   ) predict_TZP #> # A tibble: 33 × 7 #>     year  value se_min se_max observations observed estimated #>  * <dbl>  <dbl>  <dbl>  <dbl>        <int>    <dbl>     <dbl> #>  1  2002 0.2        NA     NA           15   0.2       0.0562 #>  2  2003 0.0625     NA     NA           32   0.0625    0.0616 #>  3  2004 0.0854     NA     NA           82   0.0854    0.0676 #>  4  2005 0.05       NA     NA           60   0.05      0.0741 #>  5  2006 0.0508     NA     NA           59   0.0508    0.0812 #>  6  2007 0.121      NA     NA           66   0.121     0.0889 #>  7  2008 0.0417     NA     NA           72   0.0417    0.0972 #>  8  2009 0.0164     NA     NA           61   0.0164    0.106  #>  9  2010 0.0566     NA     NA           53   0.0566    0.116  #> 10  2011 0.183      NA     NA           93   0.183     0.127  #> # ℹ 23 more rows plot(predict_TZP) ggplot_sir_predict(predict_TZP) # choose for error bars instead of a ribbon ggplot_sir_predict(predict_TZP, ribbon = FALSE)"},{"path":"https://msberends.github.io/AMR/articles/resistance_predict.html","id":"choosing-the-right-model","dir":"Articles","previous_headings":"Prediction analysis","what":"Choosing the right model","title":"How to predict antimicrobial resistance","text":"Resistance easily predicted; look vancomycin resistance Gram-positive bacteria, spread (.e. standard error) enormous:  Vancomycin resistance 100% ten years, might remain low. can define model model parameter. model chosen generalised linear regression model using binomial distribution, assuming period zero resistance followed period increasing resistance leading slowly resistance. Valid values : vancomycin resistance Gram-positive bacteria, linear model might appropriate:  model also available object, attribute:","code":"example_isolates %>%   filter(mo_gramstain(mo, language = NULL) == \"Gram-positive\") %>%   resistance_predict(col_ab = \"VAN\", year_min = 2010, info = FALSE, model = \"binomial\") %>%   ggplot_sir_predict() example_isolates %>%   filter(mo_gramstain(mo, language = NULL) == \"Gram-positive\") %>%   resistance_predict(col_ab = \"VAN\", year_min = 2010, info = FALSE, model = \"linear\") %>%   ggplot_sir_predict() model <- attributes(predict_TZP)$model  summary(model)$family #>  #> Family: binomial  #> Link function: logit  summary(model)$coefficients #>                  Estimate  Std. Error   z value     Pr(>|z|) #> (Intercept) -200.67944891 46.17315349 -4.346237 1.384932e-05 #> year           0.09883005  0.02295317  4.305725 1.664395e-05"},{"path":"https://msberends.github.io/AMR/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Matthijs S. Berends. Author, maintainer. Dennis Souverein. Author, contributor. Erwin E. . Hassing. Author, contributor. Casper J. Albers. Thesis advisor. Peter Dutey-Magni. Contributor. Judith M. Fonville. Contributor. Alex W. Friedrich. Thesis advisor. Corinna Glasner. Thesis advisor. Eric H. L. C. M. Hazenberg. Contributor. Gwen Knight. Contributor. Annick Lenglet. Contributor. Christian F. Luz. Contributor. Bart C. Meijer. Contributor. Dmytro Mykhailenko. Contributor. Anton Mymrikov. Contributor. Andrew P. Norgan. Contributor. Sofia Ny. Contributor. Matthew Saab. Contributor. Jonas Salm. Contributor. Javier Sanchez. Contributor. Rogier P. Schade. Contributor. Bhanu N. M. Sinha. Thesis advisor. Jason Stull. Contributor. Anthony Underwood. Contributor. Anita Williams. Contributor.","code":""},{"path":"https://msberends.github.io/AMR/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C (2022). “AMR: R Package Working Antimicrobial Resistance Data.” Journal Statistical Software, 104(3), 1–31. doi:10.18637/jss.v104.i03.","code":"@Article{,   title = {{AMR}: An {R} Package for Working with Antimicrobial Resistance Data},   author = {Matthijs S. Berends and Christian F. Luz and Alexander W. Friedrich and Bhanu N. M. Sinha and Casper J. Albers and Corinna Glasner},   journal = {Journal of Statistical Software},   year = {2022},   volume = {104},   number = {3},   pages = {1--31},   doi = {10.18637/jss.v104.i03}, }"},{"path":"https://msberends.github.io/AMR/index.html","id":"the-amr-package-for-r-","dir":"","previous_headings":"","what":"Antimicrobial Resistance Data Analysis","title":"Antimicrobial Resistance Data Analysis","text":"Provides --one solution antimicrobial resistance (AMR) data analysis One Health approach Used 175 countries, available 20 languages Generates antibiograms - traditional, combined, syndromic, even WISCA Provides full microbiological taxonomy extensive info antimicrobial drugs Applies recent CLSI EUCAST clinical veterinary breakpoints MICs disk zones Corrects duplicate isolates, calculates predicts AMR per antibiotic class Integrates WHONET, ATC, EARS-Net, PubChem, LOINC, SNOMED CT, NCBI 100% free costs dependencies, highly suitable places limited resources https://msberends.github.io/AMR https://doi.org/10.18637/jss.v104.i03","code":""},{"path":"https://msberends.github.io/AMR/index.html","id":"introduction","dir":"","previous_headings":"","what":"Introduction","title":"Antimicrobial Resistance Data Analysis","text":"AMR package free open-source R package zero dependencies simplify analysis prediction Antimicrobial Resistance (AMR) work microbial antimicrobial data properties, using evidence-based methods. aim provide standard clean reproducible AMR data analysis, can therefore empower epidemiological analyses continuously enable surveillance treatment evaluation setting. Many different researchers around globe continually helping us make successful durable project! work published Journal Statistical Software (Volume 104(3); DOI 10.18637/jss.v104.i03) formed basis two PhD theses (DOI 10.33612/diss.177417131 DOI 10.33612/diss.192486375). installing package, R knows ~52,000 distinct microbial species (updated December 2022) ~600 antibiotic, antimycotic antiviral drugs name code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC SNOMED CT), knows valid SIR MIC values. integral clinical breakpoint guidelines CLSI EUCAST included, even epidemiological cut-(ECOFF) values. supports can read data format, including WHONET data. package works Windows, macOS Linux versions R since R-3.0 (April 2013). designed work setting, including limited resources. created routine data analysis academic research Faculty Medical Sciences University Groningen, collaboration non-profit organisations Certe Medical Diagnostics Advice Foundation University Medical Center Groningen.","code":""},{"path":"https://msberends.github.io/AMR/index.html","id":"used-in-over-175-countries-available-in-20-languages","dir":"","previous_headings":"Introduction","what":"Used in over 175 countries, available in 20 languages","title":"Antimicrobial Resistance Data Analysis","text":"Since first public release early 2018, R package used almost countries world. Click map enlarge see country names. help contributors corners world, AMR package available  English,  Czech,  Chinese,  Danish,  Dutch,  Finnish,  French,  German,  Greek,  Italian,  Japanese,  Norwegian,  Polish,  Portuguese,  Romanian,  Russian,  Spanish,  Swedish,  Turkish,  Ukrainian. Antimicrobial drug (group) names colloquial microorganism names provided languages.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/index.html","id":"filtering-and-selecting-data","dir":"","previous_headings":"Practical examples","what":"Filtering and selecting data","title":"Antimicrobial Resistance Data Analysis","text":"One powerful functions package, aside calculating plotting AMR, selecting filtering based antibiotic columns. can done using -called antibiotic class selectors work base R, dplyr data.table: defined row filter Gram-negative bacteria intrinsic resistance cefotaxime (mo_is_gram_negative() mo_is_intrinsic_resistant()) column selection two antibiotic groups (aminoglycosides() carbapenems()), reference data microorganisms antibiotics AMR package make sure get meant: base R equivalent : base R code work version R since April 2013 (R-3.0). Moreover, code works identically data.table package, starting :","code":"# AMR works great with dplyr, but it's not required or neccesary library(AMR) library(dplyr)  example_isolates %>%   mutate(bacteria = mo_fullname()) %>%   # filtering functions for microorganisms:   filter(mo_is_gram_negative(),          mo_is_intrinsic_resistant(ab = \"cefotax\")) %>%   # antibiotic selectors:   select(bacteria,          aminoglycosides(),          carbapenems()) library(AMR) example_isolates$bacteria <- mo_fullname(example_isolates$mo) example_isolates[which(mo_is_gram_negative() &                          mo_is_intrinsic_resistant(ab = \"cefotax\")),                  c(\"bacteria\", aminoglycosides(), carbapenems())] example_isolates <- data.table::as.data.table(example_isolates)"},{"path":"https://msberends.github.io/AMR/index.html","id":"generating-antibiograms","dir":"","previous_headings":"Practical examples","what":"Generating antibiograms","title":"Antimicrobial Resistance Data Analysis","text":"AMR package supports generating traditional, combined, syndromic, even weighted-incidence syndromic combination antibiograms (WISCA). used inside R Markdown Quarto, table printed right output format automatically (markdown, LaTeX, HTML, etc.). combination antibiograms, clear combined antibiotics yield higher empiric coverage: Like many functions package, antibiogram() comes support 20 languages often detected automatically based system language:","code":"antibiogram(example_isolates,             antibiotics = c(aminoglycosides(), carbapenems())) antibiogram(example_isolates,             antibiotics = c(\"TZP\", \"TZP+TOB\", \"TZP+GEN\"),             mo_transform = \"gramstain\") antibiogram(example_isolates,             antibiotics = c(\"cipro\", \"tobra\", \"genta\"), # any arbitrary name or code will work             mo_transform = \"gramstain\",             ab_transform = \"name\",             language = \"uk\") # Ukrainian"},{"path":"https://msberends.github.io/AMR/index.html","id":"calculating-resistance-per-group","dir":"","previous_headings":"Practical examples","what":"Calculating resistance per group","title":"Antimicrobial Resistance Data Analysis","text":"manual approach, can use resistance susceptibility() function: use antibiotic class selectors select series antibiotic columns:","code":"example_isolates %>%   # group by ward:   group_by(ward) %>%   # calculate AMR using resistance() for gentamicin and tobramycin   # and get their 95% confidence intervals using sir_confidence_interval():   summarise(across(c(GEN, TOB),                    list(total_R = resistance,                         conf_int = function(x) sir_confidence_interval(x, collapse = \"-\")))) library(AMR) library(dplyr)  out <- example_isolates %>%   # group by ward:   group_by(ward) %>%   # calculate AMR using resistance(), over all aminoglycosides and polymyxins:   summarise(across(c(aminoglycosides(), polymyxins()),             resistance)) out # transform the antibiotic columns to names: out %>% set_ab_names() # transform the antibiotic column to ATC codes: out %>% set_ab_names(property = \"atc\")"},{"path":"https://msberends.github.io/AMR/index.html","id":"what-else-can-you-do-with-this-package","dir":"","previous_headings":"","what":"What else can you do with this package?","title":"Antimicrobial Resistance Data Analysis","text":"package intended comprehensive toolbox integrated AMR data analysis. package can used : Reference taxonomy microorganisms, since package contains microbial (sub)species List Prokaryotic names Standing Nomenclature (LPSN) Global Biodiversity Information Facility (GBIF) (manual) Interpreting raw MIC disk diffusion values, based CLSI EUCAST guideline (manual) Retrieving antimicrobial drug names, doses forms administration clinical health care records (manual) Determining first isolates used AMR data analysis (manual) Calculating antimicrobial resistance (tutorial) Determining multi-drug resistance (MDR) / multi-drug resistant organisms (MDRO) (tutorial) Calculating (empirical) susceptibility mono therapy combination therapies (tutorial) Predicting future antimicrobial resistance using regression models (tutorial) Getting properties microorganism (like Gram stain, species, genus family) (manual) Getting properties antibiotic (like name, code EARS-Net/ATC/LOINC/PubChem, defined daily dose trade name) (manual) Plotting antimicrobial resistance (tutorial) Applying EUCAST expert rules (manual) Getting SNOMED codes microorganism, getting properties microorganism based SNOMED code (manual) Getting LOINC codes antibiotic, getting properties antibiotic based LOINC code (manual) Machine reading EUCAST CLSI guidelines 2011-2021 translate MIC values disk diffusion diameters SIR (link) Principal component analysis AMR (tutorial)","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/index.html","id":"latest-official-version","dir":"","previous_headings":"Get this package","what":"Latest official version","title":"Antimicrobial Resistance Data Analysis","text":"package available official R network (CRAN). Install package R CRAN using command: downloaded installed automatically. RStudio, click menu Tools > Install Packages… type “AMR” press Install. Note: functions website may available latest release. use functions data sets mentioned website, install latest development version.","code":"install.packages(\"AMR\")"},{"path":"https://msberends.github.io/AMR/index.html","id":"latest-development-version","dir":"","previous_headings":"Get this package","what":"Latest development version","title":"Antimicrobial Resistance Data Analysis","text":"Please read Developer Guideline . latest unpublished development version can installed GitHub two ways: Manually, using: Automatically, using rOpenSci R-universe platform, adding R-universe address list repositories (‘repos’): , can install update AMR package like official release (e.g., using install.packages(\"AMR\") RStudio via Tools > Check Package Updates…).","code":"install.packages(\"remotes\") # if you haven't already remotes::install_github(\"msberends/AMR\") options(repos = c(getOption(\"repos\"),                   msberends = \"https://msberends.r-universe.dev\"))"},{"path":"https://msberends.github.io/AMR/index.html","id":"get-started","dir":"","previous_headings":"","what":"Get started","title":"Antimicrobial Resistance Data Analysis","text":"find conduct AMR data analysis, please continue reading get started click link ‘’ menu.","code":""},{"path":"https://msberends.github.io/AMR/index.html","id":"partners","dir":"","previous_headings":"","what":"Partners","title":"Antimicrobial Resistance Data Analysis","text":"development package part , related , made possible following non-profit organisations initiatives:","code":""},{"path":"https://msberends.github.io/AMR/index.html","id":"copyright","dir":"","previous_headings":"","what":"Copyright","title":"Antimicrobial Resistance Data Analysis","text":"R package free, open-source software licensed GNU General Public License v2.0 (GPL-2). nutshell, means package: May used commercial purposes May used private purposes May used patent purposes May modified, although: Modifications must released license distributing package Changes made code must documented May distributed, although: Source code must made available package distributed copy license copyright notice must included package. Comes LIMITATION liability Comes warranty","code":""},{"path":"https://msberends.github.io/AMR/reference/AMR-options.html","id":null,"dir":"Reference","previous_headings":"","what":"Options for the AMR package — AMR-options","title":"Options for the AMR package — AMR-options","text":"overview package-specific options() can set AMR package.","code":""},{"path":"https://msberends.github.io/AMR/reference/AMR-options.html","id":"options","dir":"Reference","previous_headings":"","what":"Options","title":"Options for the AMR package — AMR-options","text":"AMR_breakpoint_type  character use .sir(), indicate breakpoint type use. must either \"ECOFF\", \"animal\", \"human\". AMR_cleaning_regex  regular expression (case-insensitive) use .mo() mo_* functions, clean user input. default outcome mo_cleaning_regex(), removes texts brackets texts \"species\" \"serovar\". AMR_custom_ab  file location RDS file, use custom antimicrobial drugs package. explained add_custom_antimicrobials(). AMR_custom_mo  file location RDS file, use custom microorganisms package. explained add_custom_microorganisms(). AMR_eucastrules  character set default types rules eucast_rules() function, must one : \"breakpoints\", \"expert\", \"\", \"custom\", \"\", defaults c(\"breakpoints\", \"expert\"). AMR_guideline  character set default guideline interpreting MIC values disk diffusion diameters .sir(). Can guideline name (e.g., \"CLSI\") name year (e.g. \"CLSI 2019\"). default latest implemented EUCAST guideline, currently \"EUCAST 2024\". Supported guideline currently EUCAST (2011-2024) CLSI (2011-2024). AMR_ignore_pattern  regular expression ignore (.e., make NA) match given .mo() mo_* functions. AMR_include_PKPD  logical use .sir(), indicate PK/PD clinical breakpoints must applied last resort - default TRUE. AMR_include_screening  logical use .sir(), indicate clinical breakpoints screening allowed - default FALSE. AMR_keep_synonyms  logical use .mo() mo_* functions, indicate old, previously valid taxonomic names must preserved corrected currently accepted names. default FALSE. AMR_locale  character set language AMR package, can one supported language names ISO-639-1 codes: English (en), Chinese (zh), Czech (cs), Danish (da), Dutch (nl), Finnish (fi), French (fr), German (de), Greek (el), Italian (), Japanese (ja), Norwegian (), Polish (pl), Portuguese (pt), Romanian (ro), Russian (ru), Spanish (es), Swedish (sv), Turkish (tr), Ukrainian (uk). default current system language (supported, English otherwise). AMR_mo_source  file location manual code list used .mo() mo_* functions. explained set_mo_source().","code":""},{"path":"https://msberends.github.io/AMR/reference/AMR-options.html","id":"saving-settings-between-sessions","dir":"Reference","previous_headings":"","what":"Saving Settings Between Sessions","title":"Options for the AMR package — AMR-options","text":"Settings R saved globally thus lost R exited. can save options .Rprofile file, user-specific file. can edit using:   file, can set options ...   ...add Portuguese language support antibiotics, allow PK/PD rules interpreting MIC values .sir().","code":"utils::file.edit(\"~/.Rprofile\") options(AMR_locale = \"pt\")  options(AMR_include_PKPD = TRUE)"},{"path":"https://msberends.github.io/AMR/reference/AMR-options.html","id":"share-options-within-team","dir":"Reference","previous_headings":"","what":"Share Options Within Team","title":"Options for the AMR package — AMR-options","text":"global approach, e.g. within (data) team, save options file remote file location, shared network drive, user read file automatically start-. work way: Save plain text file e.g. \"X:/team_folder/R_options.R\" fill preferred settings. user, open .Rprofile file using utils::file.edit(\"~/.Rprofile\") put :   Reload R/RStudio check settings getOption(), e.g. getOption(\"AMR_locale\") set value. Now team settings configured one place, can maintained .","code":"source(\"X:/team_folder/R_options.R\")"},{"path":"https://msberends.github.io/AMR/reference/AMR.html","id":null,"dir":"Reference","previous_headings":"","what":"The AMR Package — AMR","title":"The AMR Package — AMR","text":"Welcome AMR package. AMR package free open-source R package zero dependencies simplify analysis prediction Antimicrobial Resistance (AMR) work microbial antimicrobial data properties, using evidence-based methods. aim provide standard clean reproducible AMR data analysis, can therefore empower epidemiological analyses continuously enable surveillance treatment evaluation setting. Many different researchers around globe continually helping us make successful durable project! work published Journal Statistical Software (Volume 104(3); doi:10.18637/jss.v104.i03 ) formed basis two PhD theses (doi:10.33612/diss.177417131  doi:10.33612/diss.192486375 ). installing package, R knows ~71 000 microorganisms (updated June 2024) ~600 antibiotic, antimycotic antiviral drugs name code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC SNOMED CT), knows valid SIR MIC values. integral clinical breakpoint guidelines CLSI EUCAST included, even epidemiological cut-(ECOFF) values. supports can read data format, including WHONET data. package works Windows, macOS Linux versions R since R-3.0 (April 2013). designed work setting, including limited resources. created routine data analysis academic research Faculty Medical Sciences public University Groningen, collaboration non-profit organisations Certe Medical Diagnostics Advice Foundation University Medical Center Groningen. AMR package available English, Chinese, Czech, Danish, Dutch, Finnish, French, German, Greek, Italian, Japanese, Norwegian, Polish, Portuguese, Romanian, Russian, Spanish, Swedish, Turkish, Ukrainian. Antimicrobial drug (group) names colloquial microorganism names provided languages.","code":""},{"path":"https://msberends.github.io/AMR/reference/AMR.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"The AMR Package — AMR","text":"cite AMR publications use: Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C (2022). \"AMR: R Package Working Antimicrobial Resistance Data.\" Journal Statistical Software, 104(3), 1-31. doi:10.18637/jss.v104.i03 BibTeX entry LaTeX users :","code":"@Article{,   title = {{AMR}: An {R} Package for Working with Antimicrobial Resistance Data},   author = {Matthijs S. Berends and Christian F. Luz and Alexander W. Friedrich and Bhanu N. M. Sinha and Casper J. Albers and Corinna Glasner},   journal = {Journal of Statistical Software},   year = {2022},   volume = {104},   number = {3},   pages = {1--31},   doi = {10.18637/jss.v104.i03}, }"},{"path":"https://msberends.github.io/AMR/reference/AMR.html","id":"reference-data-publicly-available","dir":"Reference","previous_headings":"","what":"Reference Data Publicly Available","title":"The AMR Package — AMR","text":"data sets AMR package (microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) publicly freely available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. also provide tab-separated plain text files machine-readable suitable input software program, laboratory information systems. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/AMR.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"The AMR Package — AMR","text":"Maintainer: Matthijs S. Berends m.s.berends@umcg.nl (ORCID) Authors: Dennis Souverein (ORCID) [contributor] Erwin E. . Hassing [contributor] contributors: Casper J. Albers (ORCID) [thesis advisor] Peter Dutey-Magni (ORCID) [contributor] Judith M. Fonville [contributor] Alex W. Friedrich (ORCID) [thesis advisor] Corinna Glasner (ORCID) [thesis advisor] Eric H. L. C. M. Hazenberg [contributor] Gwen Knight (ORCID) [contributor] Annick Lenglet (ORCID) [contributor] Christian F. Luz (ORCID) [contributor] Bart C. Meijer [contributor] Dmytro Mykhailenko [contributor] Anton Mymrikov [contributor] Andrew P. Norgan (ORCID) [contributor] Sofia Ny (ORCID) [contributor] Matthew Saab [contributor] Jonas Salm [contributor] Javier Sanchez (ORCID) [contributor] Rogier P. Schade [contributor] Bhanu N. M. Sinha (ORCID) [thesis advisor] Jason Stull (ORCID) [contributor] Anthony Underwood (ORCID) [contributor] Anita Williams (ORCID) [contributor]","code":""},{"path":"https://msberends.github.io/AMR/reference/WHOCC.html","id":null,"dir":"Reference","previous_headings":"","what":"WHOCC: WHO Collaborating Centre for Drug Statistics Methodology — WHOCC","title":"WHOCC: WHO Collaborating Centre for Drug Statistics Methodology — WHOCC","text":"antimicrobial drugs official names, ATC codes, ATC groups defined daily dose (DDD) included package, using Collaborating Centre Drug Statistics Methodology.","code":""},{"path":"https://msberends.github.io/AMR/reference/WHOCC.html","id":"whocc","dir":"Reference","previous_headings":"","what":"WHOCC","title":"WHOCC: WHO Collaborating Centre for Drug Statistics Methodology — WHOCC","text":"package contains ~550 antibiotic, antimycotic antiviral drugs Anatomical Therapeutic Chemical (ATC) codes, ATC groups Defined Daily Dose (DDD) World Health Organization Collaborating Centre Drug Statistics Methodology (WHOCC, https://atcddd.fhi.) Pharmaceuticals Community Register European Commission (https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm). become gold standard international drug utilisation monitoring research. WHOCC located Oslo Norwegian Institute Public Health funded Norwegian government. European Commission executive European Union promotes general interest. NOTE: WHOCC copyright allow use commercial purposes, unlike info package. See https://atcddd.fhi./copyright_disclaimer/.","code":""},{"path":"https://msberends.github.io/AMR/reference/WHOCC.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"WHOCC: WHO Collaborating Centre for Drug Statistics Methodology — WHOCC","text":"","code":"as.ab(\"meropenem\") #> Class 'ab' #> [1] MEM ab_name(\"J01DH02\") #> [1] \"Meropenem\"  ab_tradenames(\"flucloxacillin\") #>  [1] \"culpen\"               \"floxacillin\"          \"floxacillin sodium\"   #>  [4] \"floxapen\"             \"floxapen sodium salt\" \"fluclox\"              #>  [7] \"flucloxacilina\"       \"flucloxacillin\"       \"flucloxacilline\"      #> [10] \"flucloxacillinum\"     \"fluorochloroxacillin\" \"staphylex\""},{"path":"https://msberends.github.io/AMR/reference/WHONET.html","id":null,"dir":"Reference","previous_headings":"","what":"Data Set with 500 Isolates - WHONET Example — WHONET","title":"Data Set with 500 Isolates - WHONET Example — WHONET","text":"example data set exact structure export file WHONET. files can used package, example data set shows. antibiotic results example_isolates data set. patient names created using online surname generators place practice purposes.","code":""},{"path":"https://msberends.github.io/AMR/reference/WHONET.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Data Set with 500 Isolates - WHONET Example — WHONET","text":"","code":"WHONET"},{"path":"https://msberends.github.io/AMR/reference/WHONET.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data Set with 500 Isolates - WHONET Example — WHONET","text":"tibble 500 observations 53 variables: Identification number ID sample Specimen number ID specimen Organism Name microorganism. analysis, transform valid microbial class, using .mo(). Country Country origin Laboratory Name laboratory Last name Fictitious last name patient First name Fictitious initial patient Sex Fictitious gender patient Age Fictitious age patient Age category Age group, can also looked using age_groups() Date admissionDate hospital admission Specimen dateDate specimen received laboratory Specimen type Specimen type group Specimen type (Numeric) Translation \"Specimen type\" Reason Reason request Differential Diagnosis Isolate number ID isolate Organism type Type microorganism, can also looked using mo_type() Serotype Serotype microorganism Beta-lactamase Microorganism produces beta-lactamase? ESBL Microorganism produces extended spectrum beta-lactamase? Carbapenemase Microorganism produces carbapenemase? MRSA screening test Microorganism possible MRSA? Inducible clindamycin resistance Clindamycin can induced? Comment comments Date data entryDate data entered WHONET AMP_ND10:CIP_EE 28 different antibiotics. can lookup abbreviations antibiotics data set, use e.g. ab_name(\"AMP\") get official name immediately. analysis, transform valid antibiotic class, using .sir().","code":""},{"path":"https://msberends.github.io/AMR/reference/WHONET.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Data Set with 500 Isolates - WHONET Example — WHONET","text":"Like data sets package, data set publicly available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":"https://msberends.github.io/AMR/reference/WHONET.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Data Set with 500 Isolates - WHONET Example — WHONET","text":"","code":"WHONET #> # A tibble: 500 × 53 #>    `Identification number` `Specimen number` Organism Country         Laboratory #>    <chr>                               <int> <chr>    <chr>           <chr>      #>  1 fe41d7bafa                           1748 SPN      Belgium         National … #>  2 91f175ec37                           1767 eco      The Netherlands National … #>  3 cc4015056e                           1343 eco      The Netherlands National … #>  4 e864b692f5                           1894 MAP      Denmark         National … #>  5 3d051fe345                           1739 PVU      Belgium         National … #>  6 c80762a08d                           1846 103      The Netherlands National … #>  7 8022d3727c                           1628 103      Denmark         National … #>  8 f3dc5f553d                           1493 eco      The Netherlands National … #>  9 15add38f6c                           1847 eco      France          National … #> 10 fd41248def                           1458 eco      Germany         National … #> # ℹ 490 more rows #> # ℹ 48 more variables: `Last name` <chr>, `First name` <chr>, Sex <chr>, #> #   Age <dbl>, `Age category` <chr>, `Date of admission` <date>, #> #   `Specimen date` <date>, `Specimen type` <chr>, #> #   `Specimen type (Numeric)` <dbl>, Reason <chr>, `Isolate number` <int>, #> #   `Organism type` <chr>, Serotype <chr>, `Beta-lactamase` <lgl>, ESBL <lgl>, #> #   Carbapenemase <lgl>, `MRSA screening test` <lgl>, …"},{"path":"https://msberends.github.io/AMR/reference/ab_from_text.html","id":null,"dir":"Reference","previous_headings":"","what":"Retrieve Antimicrobial Drug Names and Doses from Clinical Text — ab_from_text","title":"Retrieve Antimicrobial Drug Names and Doses from Clinical Text — ab_from_text","text":"Use function e.g. clinical texts health care records. returns list antimicrobial drugs, doses forms administration found texts.","code":""},{"path":"https://msberends.github.io/AMR/reference/ab_from_text.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Retrieve Antimicrobial Drug Names and Doses from Clinical Text — ab_from_text","text":"","code":"ab_from_text(   text,   type = c(\"drug\", \"dose\", \"administration\"),   collapse = NULL,   translate_ab = FALSE,   thorough_search = NULL,   info = interactive(),   ... )"},{"path":"https://msberends.github.io/AMR/reference/ab_from_text.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Retrieve Antimicrobial Drug Names and Doses from Clinical Text — ab_from_text","text":"text text analyse type type property search , either \"drug\", \"dose\" \"administration\", see Examples collapse character pass paste(, collapse = ...) return one character per element text, see Examples translate_ab type = \"drug\": column name antibiotics data set translate antibiotic abbreviations , using ab_property(). default FALSE. Using TRUE equal using \"name\". thorough_search logical indicate whether input must extensively searched misspelling faulty input values. Setting TRUE take considerably time using FALSE. default, turn TRUE input elements contain maximum three words. info logical indicate whether progress bar printed - default TRUE interactive mode ... arguments passed .ab()","code":""},{"path":"https://msberends.github.io/AMR/reference/ab_from_text.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Retrieve Antimicrobial Drug Names and Doses from Clinical Text — ab_from_text","text":"list,  character collapse NULL","code":""},{"path":"https://msberends.github.io/AMR/reference/ab_from_text.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Retrieve Antimicrobial Drug Names and Doses from Clinical Text — ab_from_text","text":"function also internally used .ab(), although searches first drug name throw note drug names returned. Note: .ab() function may use long regular expression match brand names antimicrobial drugs. may fail systems.","code":""},{"path":"https://msberends.github.io/AMR/reference/ab_from_text.html","id":"argument-type","dir":"Reference","previous_headings":"","what":"Argument type","title":"Retrieve Antimicrobial Drug Names and Doses from Clinical Text — ab_from_text","text":"default, function search antimicrobial drug names. text elements searched official names, ATC codes brand names. uses .ab() internally, correct misspelling. type = \"dose\" (similar, like \"dosing\", \"doses\"), text elements searched numeric values higher 100 resemble years. output numeric. supports unit (g, mg, IE, etc.) multiple values one clinical text, see Examples. type = \"administration\" (abbreviations, like \"admin\", \"adm\"), text elements searched form drug administration. supports following forms (including common abbreviations): buccal, implant, inhalation, instillation, intravenous, nasal, oral, parenteral, rectal, sublingual, transdermal vaginal. Abbreviations oral ('po', 'per os') become \"oral\", values intravenous ('iv', 'intraven') become \"iv\". supports multiple values one clinical text, see Examples.","code":""},{"path":"https://msberends.github.io/AMR/reference/ab_from_text.html","id":"argument-collapse","dir":"Reference","previous_headings":"","what":"Argument collapse","title":"Retrieve Antimicrobial Drug Names and Doses from Clinical Text — ab_from_text","text":"Without using collapse, function return list. can convenient use e.g. inside mutate()):df %>% mutate(abx = ab_from_text(clinical_text)) returned AB codes can transformed official names, groups, etc. ab_* functions ab_name() ab_group(), using translate_ab argument. using collapse, function return character:df %>% mutate(abx = ab_from_text(clinical_text, collapse = \"|\"))","code":""},{"path":"https://msberends.github.io/AMR/reference/ab_from_text.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Retrieve Antimicrobial Drug Names and Doses from Clinical Text — ab_from_text","text":"","code":"# mind the bad spelling of amoxicillin in this line, # straight from a true health care record: ab_from_text(\"28/03/2020 regular amoxicilliin 500mg po tid\") #> [[1]] #> Class 'ab' #> [1] AMX #>   ab_from_text(\"500 mg amoxi po and 400mg cipro iv\") #> [[1]] #> Class 'ab' #> [1] AMX CIP #>  ab_from_text(\"500 mg amoxi po and 400mg cipro iv\", type = \"dose\") #> [[1]] #> [1] 500 400 #>  ab_from_text(\"500 mg amoxi po and 400mg cipro iv\", type = \"admin\") #> [[1]] #> [1] \"oral\" \"iv\"   #>   ab_from_text(\"500 mg amoxi po and 400mg cipro iv\", collapse = \", \") #> [1] \"AMX, CIP\" # \\donttest{ # if you want to know which antibiotic groups were administered, do e.g.: abx <- ab_from_text(\"500 mg amoxi po and 400mg cipro iv\") ab_group(abx[[1]]) #> [1] \"Beta-lactams/penicillins\" \"Quinolones\"                if (require(\"dplyr\")) {   tibble(clinical_text = c(     \"given 400mg cipro and 500 mg amox\",     \"started on doxy iv today\"   )) %>%     mutate(       abx_codes = ab_from_text(clinical_text),       abx_doses = ab_from_text(clinical_text, type = \"doses\"),       abx_admin = ab_from_text(clinical_text, type = \"admin\"),       abx_coll = ab_from_text(clinical_text, collapse = \"|\"),       abx_coll_names = ab_from_text(clinical_text,         collapse = \"|\",         translate_ab = \"name\"       ),       abx_coll_doses = ab_from_text(clinical_text,         type = \"doses\",         collapse = \"|\"       ),       abx_coll_admin = ab_from_text(clinical_text,         type = \"admin\",         collapse = \"|\"       )     ) } #> Loading required package: dplyr #>  #> Attaching package: ‘dplyr’ #> The following objects are masked from ‘package:stats’: #>  #>     filter, lag #> The following objects are masked from ‘package:base’: #>  #>     intersect, setdiff, setequal, union #> # A tibble: 2 × 8 #>   clinical_text            abx_codes abx_doses abx_admin abx_coll abx_coll_names #>   <chr>                    <list>    <list>    <list>    <chr>    <chr>          #> 1 given 400mg cipro and 5… <ab [2]>  <dbl [2]> <chr [1]> CIP|AMX  Ciprofloxacin… #> 2 started on doxy iv today <ab [1]>  <dbl [1]> <chr [1]> DOX      Doxycycline    #> # ℹ 2 more variables: abx_coll_doses <chr>, abx_coll_admin <chr> # }"},{"path":"https://msberends.github.io/AMR/reference/ab_property.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Properties of an Antibiotic — ab_property","title":"Get Properties of an Antibiotic — ab_property","text":"Use functions return specific property antibiotic antibiotics data set. input values evaluated internally .ab().","code":""},{"path":"https://msberends.github.io/AMR/reference/ab_property.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Properties of an Antibiotic — ab_property","text":"","code":"ab_name(x, language = get_AMR_locale(), tolower = FALSE, ...)  ab_cid(x, ...)  ab_synonyms(x, ...)  ab_tradenames(x, ...)  ab_group(x, language = get_AMR_locale(), ...)  ab_atc(x, only_first = FALSE, ...)  ab_atc_group1(x, language = get_AMR_locale(), ...)  ab_atc_group2(x, language = get_AMR_locale(), ...)  ab_loinc(x, ...)  ab_ddd(x, administration = \"oral\", ...)  ab_ddd_units(x, administration = \"oral\", ...)  ab_info(x, language = get_AMR_locale(), ...)  ab_url(x, open = FALSE, ...)  ab_property(x, property = \"name\", language = get_AMR_locale(), ...)  set_ab_names(   data,   ...,   property = \"name\",   language = get_AMR_locale(),   snake_case = NULL )"},{"path":"https://msberends.github.io/AMR/reference/ab_property.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Properties of an Antibiotic — ab_property","text":"x (vector ) text can coerced valid antibiotic drug code .ab() language language returned text - default current system language (see get_AMR_locale()) can also set package option AMR_locale. Use language = NULL language = \"\" prevent translation. tolower logical indicate whether first character every output transformed lower case character. lead e.g. \"polymyxin B\" \"polymyxin b\". ... case set_ab_names() data data.frame: columns select (supports tidy selection column1:column4), otherwise arguments passed .ab() only_first logical indicate whether first ATC code must returned, giving preference J0-codes (.e., antimicrobial drug group) administration way administration, either \"oral\" \"iv\" open browse URL using utils::browseURL() property one column names one antibiotics data set: vector_or(colnames(antibiotics), sort = FALSE). data data.frame columns need renamed, character vector column names snake_case logical indicate whether names -called snake case: lower case spaces/slashes replaced underscore (_)","code":""},{"path":"https://msberends.github.io/AMR/reference/ab_property.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Properties of an Antibiotic — ab_property","text":"integer case ab_cid() named list case ab_info() multiple ab_atc()/ab_synonyms()/ab_tradenames() double case ab_ddd() data.frame case set_ab_names() character cases","code":""},{"path":"https://msberends.github.io/AMR/reference/ab_property.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get Properties of an Antibiotic — ab_property","text":"output translated possible. function ab_url() return direct URL official website. warning returned required ATC code available. function set_ab_names() special column renaming function data.frames. renames columns names resemble antimicrobial drugs. always makes sure new column names unique. property = \"atc\" set, preference given ATC codes J-group.","code":""},{"path":"https://msberends.github.io/AMR/reference/ab_property.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get Properties of an Antibiotic — ab_property","text":"World Health Organization () Collaborating Centre Drug Statistics Methodology: https://atcddd.fhi./atc_ddd_index/ European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm","code":""},{"path":"https://msberends.github.io/AMR/reference/ab_property.html","id":"reference-data-publicly-available","dir":"Reference","previous_headings":"","what":"Reference Data Publicly Available","title":"Get Properties of an Antibiotic — ab_property","text":"data sets AMR package (microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) publicly freely available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. also provide tab-separated plain text files machine-readable suitable input software program, laboratory information systems. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/ab_property.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Properties of an Antibiotic — ab_property","text":"","code":"# all properties: ab_name(\"AMX\") #> [1] \"Amoxicillin\" ab_atc(\"AMX\") #> [1] \"J01CA04\" ab_cid(\"AMX\") #> [1] 33613 ab_synonyms(\"AMX\") #>  [1] \"actimoxi\"            \"amoclen\"             \"amolin\"              #>  [4] \"amopen\"              \"amopenixin\"          \"amoxibiotic\"         #>  [7] \"amoxicaps\"           \"amoxicilina\"         \"amoxicillin\"         #> [10] \"amoxicillin hydrate\" \"amoxicilline\"        \"amoxicillinum\"       #> [13] \"amoxiden\"            \"amoxil\"              \"amoxivet\"            #> [16] \"amoxy\"               \"amoxycillin\"         \"amoxyke\"             #> [19] \"anemolin\"            \"aspenil\"             \"atoksilin\"           #> [22] \"biomox\"              \"bristamox\"           \"cemoxin\"             #> [25] \"clamoxyl\"            \"damoxy\"              \"delacillin\"          #> [28] \"demoksil\"            \"dispermox\"           \"efpenix\"             #> [31] \"flemoxin\"            \"hiconcil\"            \"histocillin\"         #> [34] \"hydroxyampicillin\"   \"ibiamox\"             \"imacillin\"           #> [37] \"lamoxy\"              \"largopen\"            \"metafarma capsules\"  #> [40] \"metifarma capsules\"  \"moksilin\"            \"moxacin\"             #> [43] \"moxatag\"             \"ospamox\"             \"pamoxicillin\"        #> [46] \"piramox\"             \"promoxil\"            \"remoxil\"             #> [49] \"robamox\"             \"sawamox pm\"          \"tolodina\"            #> [52] \"topramoxin\"          \"unicillin\"           \"utimox\"              #> [55] \"vetramox\"            ab_tradenames(\"AMX\") #>  [1] \"actimoxi\"            \"amoclen\"             \"amolin\"              #>  [4] \"amopen\"              \"amopenixin\"          \"amoxibiotic\"         #>  [7] \"amoxicaps\"           \"amoxicilina\"         \"amoxicillin\"         #> [10] \"amoxicillin hydrate\" \"amoxicilline\"        \"amoxicillinum\"       #> [13] \"amoxiden\"            \"amoxil\"              \"amoxivet\"            #> [16] \"amoxy\"               \"amoxycillin\"         \"amoxyke\"             #> [19] \"anemolin\"            \"aspenil\"             \"atoksilin\"           #> [22] \"biomox\"              \"bristamox\"           \"cemoxin\"             #> [25] \"clamoxyl\"            \"damoxy\"              \"delacillin\"          #> [28] \"demoksil\"            \"dispermox\"           \"efpenix\"             #> [31] \"flemoxin\"            \"hiconcil\"            \"histocillin\"         #> [34] \"hydroxyampicillin\"   \"ibiamox\"             \"imacillin\"           #> [37] \"lamoxy\"              \"largopen\"            \"metafarma capsules\"  #> [40] \"metifarma capsules\"  \"moksilin\"            \"moxacin\"             #> [43] \"moxatag\"             \"ospamox\"             \"pamoxicillin\"        #> [46] \"piramox\"             \"promoxil\"            \"remoxil\"             #> [49] \"robamox\"             \"sawamox pm\"          \"tolodina\"            #> [52] \"topramoxin\"          \"unicillin\"           \"utimox\"              #> [55] \"vetramox\"            ab_group(\"AMX\") #> [1] \"Beta-lactams/penicillins\" ab_atc_group1(\"AMX\") #> [1] \"Beta-lactam antibacterials, penicillins\" ab_atc_group2(\"AMX\") #> [1] \"Penicillins with extended spectrum\" ab_url(\"AMX\") #>                                                             Amoxicillin  #> \"https://atcddd.fhi.no/atc_ddd_index//?code=J01CA04&showdescription=no\"   # smart lowercase transformation ab_name(x = c(\"AMC\", \"PLB\")) #> [1] \"Amoxicillin/clavulanic acid\" \"Polymyxin B\"                 ab_name(x = c(\"AMC\", \"PLB\"), tolower = TRUE) #> [1] \"amoxicillin/clavulanic acid\" \"polymyxin B\"                  # defined daily doses (DDD) ab_ddd(\"AMX\", \"oral\") #> [1] 1.5 ab_ddd_units(\"AMX\", \"oral\") #> [1] \"g\" ab_ddd(\"AMX\", \"iv\") #> [1] 3 ab_ddd_units(\"AMX\", \"iv\") #> [1] \"g\"  ab_info(\"AMX\") # all properties as a list #> $ab #> [1] \"AMX\" #>  #> $cid #> [1] 33613 #>  #> $name #> [1] \"Amoxicillin\" #>  #> $group #> [1] \"Beta-lactams/penicillins\" #>  #> $atc #> [1] \"J01CA04\" #>  #> $atc_group1 #> [1] \"Beta-lactam antibacterials, penicillins\" #>  #> $atc_group2 #> [1] \"Penicillins with extended spectrum\" #>  #> $tradenames #>  [1] \"actimoxi\"            \"amoclen\"             \"amolin\"              #>  [4] \"amopen\"              \"amopenixin\"          \"amoxibiotic\"         #>  [7] \"amoxicaps\"           \"amoxicilina\"         \"amoxicillin\"         #> [10] \"amoxicillin hydrate\" \"amoxicilline\"        \"amoxicillinum\"       #> [13] \"amoxiden\"            \"amoxil\"              \"amoxivet\"            #> [16] \"amoxy\"               \"amoxycillin\"         \"amoxyke\"             #> [19] \"anemolin\"            \"aspenil\"             \"atoksilin\"           #> [22] \"biomox\"              \"bristamox\"           \"cemoxin\"             #> [25] \"clamoxyl\"            \"damoxy\"              \"delacillin\"          #> [28] \"demoksil\"            \"dispermox\"           \"efpenix\"             #> [31] \"flemoxin\"            \"hiconcil\"            \"histocillin\"         #> [34] \"hydroxyampicillin\"   \"ibiamox\"             \"imacillin\"           #> [37] \"lamoxy\"              \"largopen\"            \"metafarma capsules\"  #> [40] \"metifarma capsules\"  \"moksilin\"            \"moxacin\"             #> [43] \"moxatag\"             \"ospamox\"             \"pamoxicillin\"        #> [46] \"piramox\"             \"promoxil\"            \"remoxil\"             #> [49] \"robamox\"             \"sawamox pm\"          \"tolodina\"            #> [52] \"topramoxin\"          \"unicillin\"           \"utimox\"              #> [55] \"vetramox\"            #>  #> $loinc #>  [1] \"101498-4\" \"15-8\"     \"16-6\"     \"16365-9\"  \"17-4\"     \"18-2\"     #>  [7] \"18861-5\"  \"18862-3\"  \"19-0\"     \"20-8\"     \"21-6\"     \"22-4\"     #> [13] \"25274-2\"  \"25310-4\"  \"3344-9\"   \"55614-2\"  \"55615-9\"  \"55616-7\"  #> [19] \"6976-5\"   \"6977-3\"   \"80133-2\"  #>  #> $ddd #> $ddd$oral #> $ddd$oral$amount #> [1] 1.5 #>  #> $ddd$oral$units #> [1] \"g\" #>  #>  #> $ddd$iv #> $ddd$iv$amount #> [1] 3 #>  #> $ddd$iv$units #> [1] \"g\" #>  #>  #>   # all ab_* functions use as.ab() internally, so you can go from 'any' to 'any': ab_atc(\"AMP\") #> [1] \"J01CA01\" \"S01AA19\" ab_group(\"J01CA01\") #> [1] \"Beta-lactams/penicillins\" ab_loinc(\"ampicillin\") #>  [1] \"101477-8\" \"101478-6\" \"18864-9\"  \"18865-6\"  \"20374-5\"  \"21066-6\"  #>  [7] \"23618-2\"  \"27-3\"     \"28-1\"     \"29-9\"     \"30-7\"     \"31-5\"     #> [13] \"32-3\"     \"33-1\"     \"3355-5\"   \"33562-0\"  \"33919-2\"  \"34-9\"     #> [19] \"43883-8\"  \"43884-6\"  \"6979-9\"   \"6980-7\"   \"87604-5\"  ab_name(\"21066-6\") #> [1] \"Ampicillin\" ab_name(6249) #> [1] \"Ampicillin\" ab_name(\"J01CA01\") #> [1] \"Ampicillin\"  # spelling from different languages and dyslexia are no problem ab_atc(\"ceftriaxon\") #> [1] \"J01DD04\" ab_atc(\"cephtriaxone\") #> [1] \"J01DD04\" ab_atc(\"cephthriaxone\") #> [1] \"J01DD04\" ab_atc(\"seephthriaaksone\") #> [1] \"J01DD04\"  # use set_ab_names() for renaming columns colnames(example_isolates) #>  [1] \"date\"    \"patient\" \"age\"     \"gender\"  \"ward\"    \"mo\"      \"PEN\"     #>  [8] \"OXA\"     \"FLC\"     \"AMX\"     \"AMC\"     \"AMP\"     \"TZP\"     \"CZO\"     #> [15] \"FEP\"     \"CXM\"     \"FOX\"     \"CTX\"     \"CAZ\"     \"CRO\"     \"GEN\"     #> [22] \"TOB\"     \"AMK\"     \"KAN\"     \"TMP\"     \"SXT\"     \"NIT\"     \"FOS\"     #> [29] \"LNZ\"     \"CIP\"     \"MFX\"     \"VAN\"     \"TEC\"     \"TCY\"     \"TGC\"     #> [36] \"DOX\"     \"ERY\"     \"CLI\"     \"AZM\"     \"IPM\"     \"MEM\"     \"MTR\"     #> [43] \"CHL\"     \"COL\"     \"MUP\"     \"RIF\"     colnames(set_ab_names(example_isolates)) #>  [1] \"date\"                          \"patient\"                       #>  [3] \"age\"                           \"gender\"                        #>  [5] \"ward\"                          \"mo\"                            #>  [7] \"benzylpenicillin\"              \"oxacillin\"                     #>  [9] \"flucloxacillin\"                \"amoxicillin\"                   #> [11] \"amoxicillin_clavulanic_acid\"   \"ampicillin\"                    #> [13] \"piperacillin_tazobactam\"       \"cefazolin\"                     #> [15] \"cefepime\"                      \"cefuroxime\"                    #> [17] \"cefoxitin\"                     \"cefotaxime\"                    #> [19] \"ceftazidime\"                   \"ceftriaxone\"                   #> [21] \"gentamicin\"                    \"tobramycin\"                    #> [23] \"amikacin\"                      \"kanamycin\"                     #> [25] \"trimethoprim\"                  \"trimethoprim_sulfamethoxazole\" #> [27] \"nitrofurantoin\"                \"fosfomycin\"                    #> [29] \"linezolid\"                     \"ciprofloxacin\"                 #> [31] \"moxifloxacin\"                  \"vancomycin\"                    #> [33] \"teicoplanin\"                   \"tetracycline\"                  #> [35] \"tigecycline\"                   \"doxycycline\"                   #> [37] \"erythromycin\"                  \"clindamycin\"                   #> [39] \"azithromycin\"                  \"imipenem\"                      #> [41] \"meropenem\"                     \"metronidazole\"                 #> [43] \"chloramphenicol\"               \"colistin\"                      #> [45] \"mupirocin\"                     \"rifampicin\"                    colnames(set_ab_names(example_isolates, NIT:VAN)) #>  [1] \"date\"           \"patient\"        \"age\"            \"gender\"         #>  [5] \"ward\"           \"mo\"             \"PEN\"            \"OXA\"            #>  [9] \"FLC\"            \"AMX\"            \"AMC\"            \"AMP\"            #> [13] \"TZP\"            \"CZO\"            \"FEP\"            \"CXM\"            #> [17] \"FOX\"            \"CTX\"            \"CAZ\"            \"CRO\"            #> [21] \"GEN\"            \"TOB\"            \"AMK\"            \"KAN\"            #> [25] \"TMP\"            \"SXT\"            \"nitrofurantoin\" \"fosfomycin\"     #> [29] \"linezolid\"      \"ciprofloxacin\"  \"moxifloxacin\"   \"vancomycin\"     #> [33] \"TEC\"            \"TCY\"            \"TGC\"            \"DOX\"            #> [37] \"ERY\"            \"CLI\"            \"AZM\"            \"IPM\"            #> [41] \"MEM\"            \"MTR\"            \"CHL\"            \"COL\"            #> [45] \"MUP\"            \"RIF\"            # \\donttest{ if (require(\"dplyr\")) {   example_isolates %>%     set_ab_names()    # this does the same:   example_isolates %>%     rename_with(set_ab_names)    # set_ab_names() works with any AB property:   example_isolates %>%     set_ab_names(property = \"atc\")    example_isolates %>%     set_ab_names(where(is.sir)) %>%     colnames()    example_isolates %>%     set_ab_names(NIT:VAN) %>%     colnames() } #>  [1] \"date\"           \"patient\"        \"age\"            \"gender\"         #>  [5] \"ward\"           \"mo\"             \"PEN\"            \"OXA\"            #>  [9] \"FLC\"            \"AMX\"            \"AMC\"            \"AMP\"            #> [13] \"TZP\"            \"CZO\"            \"FEP\"            \"CXM\"            #> [17] \"FOX\"            \"CTX\"            \"CAZ\"            \"CRO\"            #> [21] \"GEN\"            \"TOB\"            \"AMK\"            \"KAN\"            #> [25] \"TMP\"            \"SXT\"            \"nitrofurantoin\" \"fosfomycin\"     #> [29] \"linezolid\"      \"ciprofloxacin\"  \"moxifloxacin\"   \"vancomycin\"     #> [33] \"TEC\"            \"TCY\"            \"TGC\"            \"DOX\"            #> [37] \"ERY\"            \"CLI\"            \"AZM\"            \"IPM\"            #> [41] \"MEM\"            \"MTR\"            \"CHL\"            \"COL\"            #> [45] \"MUP\"            \"RIF\"            # }"},{"path":"https://msberends.github.io/AMR/reference/add_custom_antimicrobials.html","id":null,"dir":"Reference","previous_headings":"","what":"Add Custom Antimicrobials — add_custom_antimicrobials","title":"Add Custom Antimicrobials — add_custom_antimicrobials","text":"add_custom_antimicrobials() can add custom antimicrobial drug names codes.","code":""},{"path":"https://msberends.github.io/AMR/reference/add_custom_antimicrobials.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add Custom Antimicrobials — add_custom_antimicrobials","text":"","code":"add_custom_antimicrobials(x)  clear_custom_antimicrobials()"},{"path":"https://msberends.github.io/AMR/reference/add_custom_antimicrobials.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add Custom Antimicrobials — add_custom_antimicrobials","text":"x data.frame resembling antibiotics data set, least containing columns \"ab\" \"name\"","code":""},{"path":"https://msberends.github.io/AMR/reference/add_custom_antimicrobials.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Add Custom Antimicrobials — add_custom_antimicrobials","text":"Important: Due R works, add_custom_antimicrobials() function run every R session - added antimicrobials stored sessions thus lost R exited. two ways circumvent automate process adding antimicrobials: Method 1: Using package option AMR_custom_ab, preferred method. use method: Create data set structure antibiotics data set (containing least columns \"ab\" \"name\") save saveRDS() location choice, e.g. \"~/my_custom_ab.rds\", remote location. Set file location package option AMR_custom_ab: options(AMR_custom_ab = \"~/my_custom_ab.rds\"). can even remote file location, https URL. Since options saved R sessions, best save option .Rprofile file loaded start-R. , open .Rprofile file using e.g. utils::file.edit(\"~/.Rprofile\"), add text save file:   Upon package load, file loaded run add_custom_antimicrobials() function. Method 2: Loading antimicrobial additions directly .Rprofile file. Note definitions stored user-specific R file, suboptimal workflow. use method: Edit .Rprofile file using e.g. utils::file.edit(\"~/.Rprofile\"). Add text like save file:   Use clear_custom_antimicrobials() clear previously added antimicrobials.","code":"# Add custom antimicrobial codes: options(AMR_custom_ab = \"~/my_custom_ab.rds\") # Add custom antibiotic drug codes:  AMR::add_custom_antimicrobials(    data.frame(ab = \"TESTAB\",               name = \"Test Antibiotic\",               group = \"Test Group\")  )"},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/add_custom_antimicrobials.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add Custom Antimicrobials — add_custom_antimicrobials","text":"","code":"# \\donttest{  # returns NA and throws a warning (which is suppressed here): suppressWarnings(   as.ab(\"testab\") ) #> Class 'ab' #> [1] <NA>  # now add a custom entry - it will be considered by as.ab() and # all ab_*() functions add_custom_antimicrobials(   data.frame(     ab = \"TESTAB\",     name = \"Test Antibiotic\",     # you can add any property present in the     # 'antibiotics' data set, such as 'group':     group = \"Test Group\"   ) ) #> ℹ Added one record to the internal antibiotics data set.  # \"testab\" is now a new antibiotic: as.ab(\"testab\") #> Class 'ab' #> [1] TESTAB ab_name(\"testab\") #> [1] \"Test Antibiotic\" ab_group(\"testab\") #> [1] \"Test Group\"  ab_info(\"testab\") #> $ab #> [1] \"TESTAB\" #>  #> $cid #> [1] NA #>  #> $name #> [1] \"Test Antibiotic\" #>  #> $group #> [1] \"Test Group\" #>  #> $atc #> [1] NA #>  #> $atc_group1 #> [1] NA #>  #> $atc_group2 #> [1] NA #>  #> $tradenames #> [1] NA #>  #> $loinc #> [1] NA #>  #> $ddd #> $ddd$oral #> $ddd$oral$amount #> [1] NA #>  #> $ddd$oral$units #> [1] NA #>  #>  #> $ddd$iv #> $ddd$iv$amount #> [1] NA #>  #> $ddd$iv$units #> [1] NA #>  #>  #>    # Add Co-fluampicil, which is one of the many J01CR50 codes, see # https://atcddd.fhi.no/ddd/list_of_ddds_combined_products/ add_custom_antimicrobials(   data.frame(     ab = \"COFLU\",     name = \"Co-fluampicil\",     atc = \"J01CR50\",     group = \"Beta-lactams/penicillins\"   ) ) #> ℹ Added one record to the internal antibiotics data set. ab_atc(\"Co-fluampicil\") #> [1] \"J01CR50\" ab_name(\"J01CR50\") #> [1] \"Co-fluampicil\"  # even antibiotic selectors work x <- data.frame(   random_column = \"some value\",   coflu = as.sir(\"S\"),   ampicillin = as.sir(\"R\") ) x #>   random_column coflu ampicillin #> 1    some value     S          R x[, betalactams()] #> ℹ For betalactams() using columns 'coflu' (co-fluampicil) and #>   'ampicillin' #>   coflu ampicillin #> 1     S          R # }"},{"path":"https://msberends.github.io/AMR/reference/add_custom_microorganisms.html","id":null,"dir":"Reference","previous_headings":"","what":"Add Custom Microorganisms — add_custom_microorganisms","title":"Add Custom Microorganisms — add_custom_microorganisms","text":"add_custom_microorganisms() can add custom microorganisms, non-taxonomic outcome laboratory analysis.","code":""},{"path":"https://msberends.github.io/AMR/reference/add_custom_microorganisms.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add Custom Microorganisms — add_custom_microorganisms","text":"","code":"add_custom_microorganisms(x)  clear_custom_microorganisms()"},{"path":"https://msberends.github.io/AMR/reference/add_custom_microorganisms.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add Custom Microorganisms — add_custom_microorganisms","text":"x data.frame resembling microorganisms data set, least containing column \"genus\" (case-insensitive)","code":""},{"path":"https://msberends.github.io/AMR/reference/add_custom_microorganisms.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Add Custom Microorganisms — add_custom_microorganisms","text":"function fill missing taxonomy , specific taxonomic columns missing, see Examples. Important: Due R works, add_custom_microorganisms() function run every R session - added microorganisms stored sessions thus lost R exited. two ways circumvent automate process adding microorganisms: Method 1: Using package option AMR_custom_mo, preferred method. use method: Create data set structure microorganisms data set (containing least column \"genus\") save saveRDS() location choice, e.g. \"~/my_custom_mo.rds\", remote location. Set file location package option AMR_custom_mo: options(AMR_custom_mo = \"~/my_custom_mo.rds\"). can even remote file location, https URL. Since options saved R sessions, best save option .Rprofile file loaded start-R. , open .Rprofile file using e.g. utils::file.edit(\"~/.Rprofile\"), add text save file:   Upon package load, file loaded run add_custom_microorganisms() function. Method 2: Loading microorganism directly .Rprofile file. Note definitions stored user-specific R file, suboptimal workflow. use method: Edit .Rprofile file using e.g. utils::file.edit(\"~/.Rprofile\"). Add text like save file:   Use clear_custom_microorganisms() clear previously added microorganisms.","code":"# Add custom microorganism codes: options(AMR_custom_mo = \"~/my_custom_mo.rds\") # Add custom antibiotic drug codes:  AMR::add_custom_microorganisms(    data.frame(genus = \"Enterobacter\",               species = \"asburiae/cloacae\")  )"},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/add_custom_microorganisms.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add Custom Microorganisms — add_custom_microorganisms","text":"","code":"# \\donttest{ # a combination of species is not formal taxonomy, so # this will result in \"Enterobacter cloacae cloacae\", # since it resembles the input best: mo_name(\"Enterobacter asburiae/cloacae\") #> [1] \"Enterobacter asburiae\"  # now add a custom entry - it will be considered by as.mo() and # all mo_*() functions add_custom_microorganisms(   data.frame(     genus = \"Enterobacter\",     species = \"asburiae/cloacae\"   ) ) #> ℹ Added Enterobacter asburiae/cloacae to the internal microorganisms data #>   set.  # E. asburiae/cloacae is now a new microorganism: mo_name(\"Enterobacter asburiae/cloacae\") #> [1] \"Enterobacter asburiae/cloacae\"  # its code: as.mo(\"Enterobacter asburiae/cloacae\") #> Class 'mo' #> [1] CUSTOM1_ENTRB_ASB/  # all internal algorithms will work as well: mo_name(\"Ent asburia cloacae\") #> [1] \"Enterobacter asburiae/cloacae\"  # and even the taxonomy was added based on the genus! mo_family(\"E. asburiae/cloacae\") #> [1] \"Enterobacteriaceae\" mo_gramstain(\"Enterobacter asburiae/cloacae\") #> [1] \"Gram-negative\"  mo_info(\"Enterobacter asburiae/cloacae\") #> $mo #> [1] \"CUSTOM1_ENTRB_ASB/\" #>  #> $kingdom #> [1] \"Bacteria\" #>  #> $phylum #> [1] \"Pseudomonadota\" #>  #> $class #> [1] \"Gammaproteobacteria\" #>  #> $order #> [1] \"Enterobacterales\" #>  #> $family #> [1] \"Enterobacteriaceae\" #>  #> $genus #> [1] \"Enterobacter\" #>  #> $species #> [1] \"asburiae/cloacae\" #>  #> $subspecies #> [1] \"\" #>  #> $status #> [1] \"accepted\" #>  #> $synonyms #> NULL #>  #> $gramstain #> [1] \"Gram-negative\" #>  #> $oxygen_tolerance #> [1] NA #>  #> $url #> [1] \"\" #>  #> $ref #> [1] \"Self-added, 2024\" #>  #> $snomed #> [1] NA #>  #> $lpsn #> [1] NA #>  #> $gbif #> [1] NA #>  #> $group_members #> character(0) #>    # the function tries to be forgiving: add_custom_microorganisms(   data.frame(     GENUS = \"BACTEROIDES / PARABACTEROIDES SLASHLINE\",     SPECIES = \"SPECIES\"   ) ) #> ℹ Added Bacteroides/Parabacteroides to the internal microorganisms data #>   set. mo_name(\"BACTEROIDES / PARABACTEROIDES\") #> [1] \"Bacteroides/Parabacteroides\" mo_rank(\"BACTEROIDES / PARABACTEROIDES\") #> [1] \"genus\"  # taxonomy still works, even though a slashline genus was given as input: mo_family(\"Bacteroides/Parabacteroides\") #> [1] \"Bacteroidaceae\"   # for groups and complexes, set them as species or subspecies: add_custom_microorganisms(   data.frame(     genus = \"Citrobacter\",     species = c(\"freundii\", \"braakii complex\"),     subspecies = c(\"complex\", \"\")   ) ) #> ℹ Added Citrobacter braakii complex and Citrobacter freundii complex to the #>   internal microorganisms data set. mo_name(c(\"C. freundii complex\", \"C. braakii complex\")) #> [1] \"Citrobacter freundii complex\" \"Citrobacter braakii complex\"  mo_species(c(\"C. freundii complex\", \"C. braakii complex\")) #> [1] \"freundii complex\" \"braakii complex\"  mo_gramstain(c(\"C. freundii complex\", \"C. braakii complex\")) #> [1] \"Gram-negative\" \"Gram-negative\" # }"},{"path":"https://msberends.github.io/AMR/reference/age.html","id":null,"dir":"Reference","previous_headings":"","what":"Age in Years of Individuals — age","title":"Age in Years of Individuals — age","text":"Calculates age years based reference date, system date default.","code":""},{"path":"https://msberends.github.io/AMR/reference/age.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Age in Years of Individuals — age","text":"","code":"age(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...)"},{"path":"https://msberends.github.io/AMR/reference/age.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Age in Years of Individuals — age","text":"x date(s), character (vectors) coerced .POSIXlt() reference reference date(s) (default today), character (vectors) coerced .POSIXlt() exact logical indicate whether age calculation exact, .e. decimals. divides number days year--date (YTD) x number days year reference (either 365 366). na.rm logical indicate whether missing values removed ... arguments passed .POSIXlt(), origin","code":""},{"path":"https://msberends.github.io/AMR/reference/age.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Age in Years of Individuals — age","text":"integer (decimals) exact = FALSE, double (decimals) otherwise","code":""},{"path":"https://msberends.github.io/AMR/reference/age.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Age in Years of Individuals — age","text":"Ages 0 returned NA warning. Ages 120 give warning. function vectorises x reference, meaning either can length 1 argument larger length.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/age.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Age in Years of Individuals — age","text":"","code":"# 10 random pre-Y2K birth dates df <- data.frame(birth_date = as.Date(\"2000-01-01\") - runif(10) * 25000)  # add ages df$age <- age(df$birth_date)  # add exact ages df$age_exact <- age(df$birth_date, exact = TRUE)  # add age at millenium switch df$age_at_y2k <- age(df$birth_date, \"2000-01-01\")  df #>    birth_date age age_exact age_at_y2k #> 1  1965-12-05  58  58.61202         34 #> 2  1980-03-01  44  44.37432         19 #> 3  1949-11-01  74  74.70492         50 #> 4  1947-02-14  77  77.41803         52 #> 5  1940-02-19  84  84.40437         59 #> 6  1988-01-10  36  36.51366         11 #> 7  1997-08-27  26  26.88525          2 #> 8  1978-01-26  46  46.46995         21 #> 9  1972-06-17  52  52.07923         27 #> 10 1986-08-10  37  37.93169         13"},{"path":"https://msberends.github.io/AMR/reference/age_groups.html","id":null,"dir":"Reference","previous_headings":"","what":"Split Ages into Age Groups — age_groups","title":"Split Ages into Age Groups — age_groups","text":"Split ages age groups defined split argument. allows easier demographic (antimicrobial resistance) analysis.","code":""},{"path":"https://msberends.github.io/AMR/reference/age_groups.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Split Ages into Age Groups — age_groups","text":"","code":"age_groups(x, split_at = c(12, 25, 55, 75), na.rm = FALSE)"},{"path":"https://msberends.github.io/AMR/reference/age_groups.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Split Ages into Age Groups — age_groups","text":"x age, e.g. calculated age() split_at values split x - default age groups 0-11, 12-24, 25-54, 55-74 75+. See Details. na.rm logical indicate whether missing values removed","code":""},{"path":"https://msberends.github.io/AMR/reference/age_groups.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Split Ages into Age Groups — age_groups","text":"Ordered factor","code":""},{"path":"https://msberends.github.io/AMR/reference/age_groups.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Split Ages into Age Groups — age_groups","text":"split ages, input split_at argument can : numeric vector. value e.g. c(10, 20) split x 0-9, 10-19 20+. value 50 split x 0-49 50+. default split young children (0-11), youth (12-24), young adults (25-54), middle-aged adults (55-74) elderly (75+). character: \"children\" \"kids\", equivalent : c(0, 1, 2, 4, 6, 13, 18). split 0, 1, 2-3, 4-5, 6-12, 13-17 18+. \"elderly\" \"seniors\", equivalent : c(65, 75, 85). split 0-64, 65-74, 75-84, 85+. \"fives\", equivalent : 1:20 * 5. split 0-4, 5-9, ..., 95-99, 100+. \"tens\", equivalent : 1:10 * 10. split 0-9, 10-19, ..., 90-99, 100+.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/age_groups.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Split Ages into Age Groups — age_groups","text":"","code":"ages <- c(3, 8, 16, 54, 31, 76, 101, 43, 21)  # split into 0-49 and 50+ age_groups(ages, 50) #> [1] 0-49 0-49 0-49 50+  0-49 50+  50+  0-49 0-49 #> Levels: 0-49 < 50+  # split into 0-19, 20-49 and 50+ age_groups(ages, c(20, 50)) #> [1] 0-19  0-19  0-19  50+   20-49 50+   50+   20-49 20-49 #> Levels: 0-19 < 20-49 < 50+  # split into groups of ten years age_groups(ages, 1:10 * 10) #> [1] 0-9   0-9   10-19 50-59 30-39 70-79 100+  40-49 20-29 #> 11 Levels: 0-9 < 10-19 < 20-29 < 30-39 < 40-49 < 50-59 < 60-69 < ... < 100+ age_groups(ages, split_at = \"tens\") #> [1] 0-9   0-9   10-19 50-59 30-39 70-79 100+  40-49 20-29 #> 11 Levels: 0-9 < 10-19 < 20-29 < 30-39 < 40-49 < 50-59 < 60-69 < ... < 100+  # split into groups of five years age_groups(ages, 1:20 * 5) #> [1] 0-4   5-9   15-19 50-54 30-34 75-79 100+  40-44 20-24 #> 21 Levels: 0-4 < 5-9 < 10-14 < 15-19 < 20-24 < 25-29 < 30-34 < ... < 100+ age_groups(ages, split_at = \"fives\") #> [1] 0-4   5-9   15-19 50-54 30-34 75-79 100+  40-44 20-24 #> 21 Levels: 0-4 < 5-9 < 10-14 < 15-19 < 20-24 < 25-29 < 30-34 < ... < 100+  # split specifically for children age_groups(ages, c(1, 2, 4, 6, 13, 18)) #> [1] 2-3   6-12  13-17 18+   18+   18+   18+   18+   18+   #> Levels: 0 < 1 < 2-3 < 4-5 < 6-12 < 13-17 < 18+ age_groups(ages, \"children\") #> [1] 2-3   6-12  13-17 18+   18+   18+   18+   18+   18+   #> Levels: 0 < 1 < 2-3 < 4-5 < 6-12 < 13-17 < 18+  # \\donttest{ # resistance of ciprofloxacin per age group if (require(\"dplyr\") && require(\"ggplot2\")) {   example_isolates %>%     filter_first_isolate() %>%     filter(mo == as.mo(\"Escherichia coli\")) %>%     group_by(age_group = age_groups(age)) %>%     select(age_group, CIP) %>%     ggplot_sir(       x = \"age_group\",       minimum = 0,       x.title = \"Age Group\",       title = \"Ciprofloxacin resistance per age group\"     ) } #> Loading required package: ggplot2  # }"},{"path":"https://msberends.github.io/AMR/reference/antibiogram.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted-Incidence Syndromic Combination (WISCA) — antibiogram","title":"Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted-Incidence Syndromic Combination (WISCA) — antibiogram","text":"Generate antibiogram, communicate results plots tables. functions follow logic Klinker et al. Barbieri et al. (see Source), allow reporting e.g. R Markdown Quarto well.","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiogram.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted-Incidence Syndromic Combination (WISCA) — antibiogram","text":"","code":"antibiogram(   x,   antibiotics = where(is.sir),   mo_transform = \"shortname\",   ab_transform = NULL,   syndromic_group = NULL,   add_total_n = TRUE,   only_all_tested = FALSE,   digits = 0,   col_mo = NULL,   language = get_AMR_locale(),   minimum = 30,   combine_SI = TRUE,   sep = \" + \",   info = interactive() )  # S3 method for class 'antibiogram' plot(x, ...)  # S3 method for class 'antibiogram' autoplot(object, ...)  # S3 method for class 'antibiogram' knit_print(   x,   italicise = TRUE,   na = getOption(\"knitr.kable.NA\", default = \"\"),   ... )"},{"path":"https://msberends.github.io/AMR/reference/antibiogram.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted-Incidence Syndromic Combination (WISCA) — antibiogram","text":"Klinker KP et al. (2021). Antimicrobial stewardship antibiograms: importance moving beyond traditional antibiograms. Therapeutic Advances Infectious Disease, May 5;8:20499361211011373; doi:10.1177/20499361211011373 Barbieri E et al. (2021). Development Weighted-Incidence Syndromic Combination Antibiogram (WISCA) guide choice empiric antibiotic treatment urinary tract infection paediatric patients: Bayesian approach Antimicrobial Resistance & Infection Control May 1;10(1):74; doi:10.1186/s13756-021-00939-2 M39 Analysis Presentation Cumulative Antimicrobial Susceptibility Test Data, 5th Edition, 2022, Clinical Laboratory Standards Institute (CLSI). https://clsi.org/standards/products/microbiology/documents/m39/.","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiogram.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted-Incidence Syndromic Combination (WISCA) — antibiogram","text":"x data.frame containing least column microorganisms columns antibiotic results (class 'sir', see .sir()) antibiotics vector antibiotic name code (evaluated .ab(), column name x, (combinations ) antibiotic selectors aminoglycosides() carbapenems(). combination antibiograms, can also set values separated \"+\", \"TZP+TOB\" \"cipro + genta\", given columns resembling antibiotics exist x. See Examples. mo_transform character transform microorganism input - must \"name\", \"shortname\", \"gramstain\", one column names microorganisms data set: \"mo\", \"fullname\", \"status\", \"kingdom\", \"phylum\", \"class\", \"order\", \"family\", \"genus\", \"species\", \"subspecies\", \"rank\", \"ref\", \"oxygen_tolerance\", \"source\", \"lpsn\", \"lpsn_parent\", \"lpsn_renamed_to\", \"mycobank\", \"mycobank_parent\", \"mycobank_renamed_to\", \"gbif\", \"gbif_parent\", \"gbif_renamed_to\", \"prevalence\", \"snomed\". Can also NULL transform input. ab_transform character transform antibiotic input - must one column names antibiotics data set: \"ab\", \"cid\", \"name\", \"group\", \"atc\", \"atc_group1\", \"atc_group2\", \"abbreviations\", \"synonyms\", \"oral_ddd\", \"oral_units\", \"iv_ddd\", \"iv_units\", \"loinc\". Can also NULL transform input. syndromic_group column name x, values calculated split rows x, e.g. using ifelse() case_when(). See Examples. add_total_n logical indicate whether total available numbers per pathogen added table (default TRUE). add lowest highest number available isolate per antibiotic (e.g, E. coli 200 isolates available ciprofloxacin 150 amoxicillin, returned number \"150-200\"). only_all_tested (combination antibiograms): logical indicate isolates must tested antibiotics, see Details digits number digits use rounding col_mo column name names codes microorganisms (see .mo()) - default first column class mo. Values coerced using .mo(). language language translate text, defaults system language (see get_AMR_locale()) minimum minimum allowed number available (tested) isolates. isolate count lower minimum return NA warning. default number 30 isolates advised Clinical Laboratory Standards Institute (CLSI) best practice, see Source. combine_SI logical indicate whether susceptibility determined results either S , instead S (default TRUE) sep separating character antibiotic columns combination antibiograms info logical indicate info printed - default TRUE interactive mode ... used R Markdown Quarto: arguments passed knitr::kable() (otherwise, use) object antibiogram() object italicise logical indicate whether microorganism names knitr table made italic, using italicise_taxonomy(). na character use showing NA values","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiogram.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted-Incidence Syndromic Combination (WISCA) — antibiogram","text":"function returns table values 0 100 susceptibility, resistance. Remember filter data let contain first isolates! needed exclude duplicates reduce selection bias. Use first_isolate() determine data set one four available algorithms. types antibiograms listed can plotted (using ggplot2::autoplot() base R plot()/barplot()). antibiogram object can also used directly R Markdown / Quarto (.e., knitr) reports. case, knitr::kable() applied automatically microorganism names even printed italics default (see argument italicise). can also use functions specific 'table reporting' packages transform output antibiogram() needs, e.g. flextable::as_flextable() gt::gt().","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiogram.html","id":"antibiogram-types","dir":"Reference","previous_headings":"","what":"Antibiogram Types","title":"Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted-Incidence Syndromic Combination (WISCA) — antibiogram","text":"four antibiogram types, proposed Klinker et al. (2021, doi:10.1177/20499361211011373 ), supported antibiogram(): Traditional Antibiogram Case example: Susceptibility Pseudomonas aeruginosa piperacillin/tazobactam (TZP) Code example:   Combination Antibiogram Case example: Additional susceptibility Pseudomonas aeruginosa TZP + tobramycin versus TZP alone Code example:   Syndromic Antibiogram Case example: Susceptibility Pseudomonas aeruginosa TZP among respiratory specimens (obtained among ICU patients ) Code example:   Weighted-Incidence Syndromic Combination Antibiogram (WISCA) Case example: Susceptibility Pseudomonas aeruginosa TZP among respiratory specimens (obtained among ICU patients ) male patients age >=65 years heart failure Code example:   Note combination antibiograms, important realise susceptibility can calculated two ways, can set only_all_tested argument (default FALSE). See example two antibiotics, Drug Drug B, antibiogram() works calculate %SI:","code":"antibiogram(your_data,             antibiotics = \"TZP\") antibiogram(your_data,             antibiotics = c(\"TZP\", \"TZP+TOB\", \"TZP+GEN\")) antibiogram(your_data,             antibiotics = penicillins(),             syndromic_group = \"ward\") library(dplyr) your_data %>%   filter(ward == \"ICU\" & specimen_type == \"Respiratory\") %>%   antibiogram(antibiotics = c(\"TZP\", \"TZP+TOB\", \"TZP+GEN\"),               syndromic_group = ifelse(.$age >= 65 &                                          .$gender == \"Male\" &                                          .$condition == \"Heart Disease\",                                        \"Study Group\", \"Control Group\")) --------------------------------------------------------------------                     only_all_tested = FALSE  only_all_tested = TRUE                     -----------------------  -----------------------  Drug A    Drug B   include as  include as   include as  include as                     numerator   denominator  numerator   denominator --------  --------  ----------  -----------  ----------  -----------  S or I    S or I       X            X            X            X    R       S or I       X            X            X            X   <NA>     S or I       X            X            -            -  S or I      R          X            X            X            X    R         R          -            X            -            X   <NA>       R          -            -            -            -  S or I     <NA>        X            X            -            -    R        <NA>        -            -            -            -   <NA>      <NA>        -            -            -            - --------------------------------------------------------------------"},{"path":"https://msberends.github.io/AMR/reference/antibiogram.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted-Incidence Syndromic Combination (WISCA) — antibiogram","text":"","code":"# example_isolates is a data set available in the AMR package. # run ?example_isolates for more info. example_isolates #> # A tibble: 2,000 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-03 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  3 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  4 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  5 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  6 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  7 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  8 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  9 2002-01-16 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #> 10 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R     NA    S     NA    #> # ℹ 1,990 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, …  # \\donttest{ # Traditional antibiogram ----------------------------------------------  antibiogram(example_isolates,   antibiotics = c(aminoglycosides(), carbapenems()) ) #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> # An Antibiogram: 10 × 7 #>    `Pathogen (N min-max)`   AMK   GEN   IPM   KAN   MEM   TOB #>  * <chr>                  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #>  1 CoNS (43-309)              0    86    52     0    52    22 #>  2 E. coli (0-462)          100    98   100    NA   100    97 #>  3 E. faecalis (0-39)         0     0   100     0    NA     0 #>  4 K. pneumoniae (0-58)      NA    90   100    NA   100    90 #>  5 P. aeruginosa (17-30)     NA   100    NA     0    NA   100 #>  6 P. mirabilis (0-34)       NA    94    94    NA    NA    94 #>  7 S. aureus (2-233)         NA    99    NA    NA    NA    98 #>  8 S. epidermidis (8-163)     0    79    NA     0    NA    51 #>  9 S. hominis (3-80)         NA    92    NA    NA    NA    85 #> 10 S. pneumoniae (11-117)     0     0    NA     0    NA     0 #> # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram, #> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram  antibiogram(example_isolates,   antibiotics = aminoglycosides(),   ab_transform = \"atc\",   mo_transform = \"gramstain\" ) #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> # An Antibiogram: 2 × 5 #>   `Pathogen (N min-max)`   J01GB01 J01GB03 J01GB04 J01GB06 #> * <chr>                      <dbl>   <dbl>   <dbl>   <dbl> #> 1 Gram-negative (35-686)        96      96       0      98 #> 2 Gram-positive (436-1170)      34      63       0       0 #> # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram, #> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram  antibiogram(example_isolates,   antibiotics = carbapenems(),   ab_transform = \"name\",   mo_transform = \"name\" ) #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> # An Antibiogram: 5 × 3 #>   `Pathogen (N min-max)`                           Imipenem Meropenem #> * <chr>                                               <dbl>     <dbl> #> 1 Coagulase-negative Staphylococcus (CoNS) (48-48)       52        52 #> 2 Enterococcus faecalis (0-38)                          100        NA #> 3 Escherichia coli (418-422)                            100       100 #> 4 Klebsiella pneumoniae (51-53)                         100       100 #> 5 Proteus mirabilis (27-32)                              94        NA #> # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram, #> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram   # Combined antibiogram -------------------------------------------------  # combined antibiotics yield higher empiric coverage antibiogram(example_isolates,   antibiotics = c(\"TZP\", \"TZP+TOB\", \"TZP+GEN\"),   mo_transform = \"gramstain\" ) #> # An Antibiogram: 2 × 4 #>   `Pathogen (N min-max)`     TZP `TZP + GEN` `TZP + TOB` #> * <chr>                    <dbl>       <dbl>       <dbl> #> 1 Gram-negative (641-693)     88          99          98 #> 2 Gram-positive (345-1044)    86          98          95 #> # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram, #> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram  # names of antibiotics do not need to resemble columns exactly: antibiogram(example_isolates,   antibiotics = c(\"Cipro\", \"cipro + genta\"),   mo_transform = \"gramstain\",   ab_transform = \"name\",   sep = \" & \" ) #> # An Antibiogram: 2 × 3 #>   `Pathogen (N min-max)`  Ciprofloxacin `Ciprofloxacin & Gentamicin` #> * <chr>                           <dbl>                        <dbl> #> 1 Gram-negative (684-694)            91                           99 #> 2 Gram-positive (724-847)            77                           93 #> # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram, #> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram   # Syndromic antibiogram ------------------------------------------------  # the data set could contain a filter for e.g. respiratory specimens antibiogram(example_isolates,   antibiotics = c(aminoglycosides(), carbapenems()),   syndromic_group = \"ward\" ) #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> # An Antibiogram: 14 × 8 #>    `Syndromic Group` `Pathogen (N min-max)`   AMK   GEN   IPM   KAN   MEM   TOB #>  * <chr>             <chr>                  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #>  1 Clinical          CoNS (23-205)             NA    89    57    NA    57    26 #>  2 ICU               CoNS (10-73)              NA    79    NA    NA    NA    NA #>  3 Outpatient        CoNS (3-31)               NA    84    NA    NA    NA    NA #>  4 Clinical          E. coli (0-299)          100    98   100    NA   100    98 #>  5 ICU               E. coli (0-137)          100    99   100    NA   100    96 #>  6 Clinical          K. pneumoniae (0-51)      NA    92   100    NA   100    92 #>  7 Clinical          P. mirabilis (0-30)       NA   100    NA    NA    NA   100 #>  8 Clinical          S. aureus (2-150)         NA    99    NA    NA    NA    97 #>  9 ICU               S. aureus (0-66)          NA   100    NA    NA    NA    NA #> 10 Clinical          S. epidermidis (4-79)     NA    82    NA    NA    NA    55 #> 11 ICU               S. epidermidis (4-75)     NA    72    NA    NA    NA    41 #> 12 Clinical          S. hominis (1-45)         NA    96    NA    NA    NA    94 #> 13 Clinical          S. pneumoniae (5-78)       0     0    NA     0    NA     0 #> 14 ICU               S. pneumoniae (5-30)       0     0    NA     0    NA     0 #> # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram, #> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram  # now define a data set with only E. coli ex1 <- example_isolates[which(mo_genus() == \"Escherichia\"), ] #> ℹ Using column 'mo' as input for mo_genus()  # with a custom language, though this will be determined automatically # (i.e., this table will be in Spanish on Spanish systems) antibiogram(ex1,   antibiotics = aminoglycosides(),   ab_transform = \"name\",   syndromic_group = ifelse(ex1$ward == \"ICU\",     \"UCI\", \"No UCI\"   ),   language = \"es\" ) #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> # An Antibiogram: 2 × 5 #>   `Grupo sindrómico` `Patógeno (N min-max)` Amikacina Gentamicina Tobramicina #> * <chr>              <chr>                      <dbl>       <dbl>       <dbl> #> 1 No UCI             E. coli (0-325)              100          98          98 #> 2 UCI                E. coli (0-137)              100          99          96 #> # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram, #> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram   # Weighted-incidence syndromic combination antibiogram (WISCA) ---------  # the data set could contain a filter for e.g. respiratory specimens/ICU antibiogram(example_isolates,   antibiotics = c(\"AMC\", \"AMC+CIP\", \"TZP\", \"TZP+TOB\"),   mo_transform = \"gramstain\",   minimum = 10, # this should be >=30, but now just as example   syndromic_group = ifelse(example_isolates$age >= 65 &     example_isolates$gender == \"M\",   \"WISCA Group 1\", \"WISCA Group 2\"   ) ) #> # An Antibiogram: 4 × 6 #>   `Syndromic Group` `Pathogen (N min-max)`    AMC `AMC + CIP`   TZP `TZP + TOB` #> * <chr>             <chr>                   <dbl>       <dbl> <dbl>       <dbl> #> 1 WISCA Group 1     Gram-negative (261-285)    76          95    89          99 #> 2 WISCA Group 2     Gram-negative (380-442)    76          98    88          98 #> 3 WISCA Group 1     Gram-positive (123-406)    76          89    81          95 #> 4 WISCA Group 2     Gram-positive (222-732)    76          89    88          95 #> # Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram, #> # or use it directly in R Markdown or https://quarto.org, see ?antibiogram   # Print the output for R Markdown / Quarto -----------------------------  ureido <- antibiogram(example_isolates,   antibiotics = ureidopenicillins(),   ab_transform = \"name\" ) #> ℹ For ureidopenicillins() using column 'TZP' (piperacillin/tazobactam)  # in an Rmd file, you would just need to return `ureido` in a chunk, # but to be explicit here: if (requireNamespace(\"knitr\")) {   cat(knitr::knit_print(ureido)) } #>  #>  #> |Pathogen (N)          | Piperacillin/tazobactam| #> |:---------------------|-----------------------:| #> |CoNS (33)             |                      30| #> |*E. coli* (416)       |                      94| #> |*K. pneumoniae* (53)  |                      89| #> |*S. pneumoniae* (112) |                     100|   # Generate plots with ggplot2 or base R --------------------------------  ab1 <- antibiogram(example_isolates,   antibiotics = c(\"AMC\", \"CIP\", \"TZP\", \"TZP+TOB\"),   mo_transform = \"gramstain\" ) ab2 <- antibiogram(example_isolates,   antibiotics = c(\"AMC\", \"CIP\", \"TZP\", \"TZP+TOB\"),   mo_transform = \"gramstain\",   syndromic_group = \"ward\" )  if (requireNamespace(\"ggplot2\")) {   ggplot2::autoplot(ab1) }  if (requireNamespace(\"ggplot2\")) {   ggplot2::autoplot(ab2) }   plot(ab1)  plot(ab2)  # }"},{"path":"https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html","id":null,"dir":"Reference","previous_headings":"","what":"Antibiotic Selectors — antibiotic_class_selectors","title":"Antibiotic Selectors — antibiotic_class_selectors","text":"functions allow filtering rows selecting columns based antibiotic test results specific antibiotic class group (according antibiotics data set), without need define columns antibiotic abbreviations. short, column name resembles antimicrobial drug, picked functions matches pharmaceutical class: \"cefazolin\", \"kefzol\", \"CZO\" \"J01DB04\" picked cephalosporins().","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Antibiotic Selectors — antibiotic_class_selectors","text":"","code":"ab_class(ab_class, only_sir_columns = FALSE, only_treatable = TRUE, ...)  ab_selector(filter, only_sir_columns = FALSE, only_treatable = TRUE, ...)  aminoglycosides(only_sir_columns = FALSE, only_treatable = TRUE, ...)  aminopenicillins(only_sir_columns = FALSE, ...)  antifungals(only_sir_columns = FALSE, ...)  antimycobacterials(only_sir_columns = FALSE, ...)  betalactams(only_sir_columns = FALSE, only_treatable = TRUE, ...)  carbapenems(only_sir_columns = FALSE, only_treatable = TRUE, ...)  cephalosporins(only_sir_columns = FALSE, ...)  cephalosporins_1st(only_sir_columns = FALSE, ...)  cephalosporins_2nd(only_sir_columns = FALSE, ...)  cephalosporins_3rd(only_sir_columns = FALSE, ...)  cephalosporins_4th(only_sir_columns = FALSE, ...)  cephalosporins_5th(only_sir_columns = FALSE, ...)  fluoroquinolones(only_sir_columns = FALSE, ...)  glycopeptides(only_sir_columns = FALSE, ...)  lincosamides(only_sir_columns = FALSE, only_treatable = TRUE, ...)  lipoglycopeptides(only_sir_columns = FALSE, ...)  macrolides(only_sir_columns = FALSE, ...)  nitrofurans(only_sir_columns = FALSE, ...)  oxazolidinones(only_sir_columns = FALSE, ...)  penicillins(only_sir_columns = FALSE, ...)  polymyxins(only_sir_columns = FALSE, only_treatable = TRUE, ...)  quinolones(only_sir_columns = FALSE, ...)  rifamycins(only_sir_columns = FALSE, ...)  streptogramins(only_sir_columns = FALSE, ...)  tetracyclines(only_sir_columns = FALSE, ...)  trimethoprims(only_sir_columns = FALSE, ...)  ureidopenicillins(only_sir_columns = FALSE, ...)  administrable_per_os(only_sir_columns = FALSE, ...)  administrable_iv(only_sir_columns = FALSE, ...)  not_intrinsic_resistant(   only_sir_columns = FALSE,   col_mo = NULL,   version_expertrules = 3.3,   ... )"},{"path":"https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Antibiotic Selectors — antibiotic_class_selectors","text":"ab_class antimicrobial class part , \"carba\" \"carbapenems\". columns group, atc_group1 atc_group2 antibiotics data set searched (case-insensitive) value. only_sir_columns logical indicate whether columns class sir must selected (default FALSE), see .sir() only_treatable logical indicate whether antimicrobial drugs excluded laboratory tests (default TRUE), gentamicin-high (GEH) imipenem/EDTA (IPE) ... ignored, place allow future extensions filter expression evaluated antibiotics data set, name %like% \"trim\" col_mo column name names codes microorganisms (see .mo()) - default first column class mo. Values coerced using .mo(). version_expertrules version number use EUCAST Expert Rules Intrinsic Resistance guideline. Can \"3.3\", \"3.2\", \"3.1\".","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Antibiotic Selectors — antibiotic_class_selectors","text":"(internally) character vector column names, additional class \"ab_selector\"","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Antibiotic Selectors — antibiotic_class_selectors","text":"functions can used data set calls selecting columns filtering rows. work base R, Tidyverse, data.table. heavily inspired Tidyverse selection helpers everything(), limited dplyr verbs. Nonetheless, convenient use dplyr functions select(), filter() summarise(), see Examples. columns data functions called searched known antibiotic names, abbreviations, brand names, codes (ATC, EARS-Net, , etc.) according antibiotics data set. means selector aminoglycosides() pick column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc. ab_class() function can used filter/select manually defined antibiotic class. searches results antibiotics data set within columns group, atc_group1 atc_group2. ab_selector() function can used internally filter antibiotics data set results, see Examples. allows filtering (part ) certain name, /group name even minimum DDDs oral treatment. function yields highest flexibility, also least user-friendly, since requires hard-coded filter set. administrable_per_os() administrable_iv() functions also rely antibiotics data set - antibiotic columns matched DDD (defined daily dose) resp. oral IV treatment available antibiotics data set. not_intrinsic_resistant() function can used select antibiotic columns pose intrinsic resistance microorganisms data set. example, data set contains microorganism codes names E. coli K. pneumoniae contains column \"vancomycin\", column removed (rather, unselected) using function. currently applies 'EUCAST Expert Rules' 'EUCAST Intrinsic Resistance Unusual Phenotypes' v3.3 (2021) determine intrinsic resistance, using eucast_rules() function internally. determination, function quite slow terms performance.","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html","id":"full-list-of-supported-antibiotic-classes","dir":"Reference","previous_headings":"","what":"Full list of supported (antibiotic) classes","title":"Antibiotic Selectors — antibiotic_class_selectors","text":"aminoglycosides() can select:  amikacin (AMK), amikacin/fosfomycin (AKF), apramycin (APR), arbekacin (ARB), astromicin (AST), bekanamycin (BEK), dibekacin (DKB), framycetin (FRM), gentamicin (GEN), gentamicin-high (GEH), habekacin (HAB), hygromycin (HYG), isepamicin (ISE), kanamycin (KAN), kanamycin-high (KAH), kanamycin/cephalexin (KAC), micronomicin (MCR), neomycin (NEO), netilmicin (NET), pentisomicin (PIM), plazomicin (PLZ), propikacin (PKA), ribostamycin (RST), sisomicin (SIS), streptoduocin (STR), streptomycin (STR1), streptomycin-high (STH), tobramycin (TOB), tobramycin-high (TOH) aminopenicillins() can select:  amoxicillin (AMX) ampicillin (AMP) antifungals() can select:  amorolfine (AMO), amphotericin B (AMB), amphotericin B-high (AMH), anidulafungin (ANI), butoconazole (), caspofungin (CAS), ciclopirox (CIX), clotrimazole (CTR), econazole (ECO), fluconazole (FLU), flucytosine (FCT), fosfluconazole (FFL), griseofulvin (GRI), hachimycin (HCH), ibrexafungerp (IBX), isavuconazole (ISV), isoconazole (ISO), itraconazole (ITR), ketoconazole (KET), manogepix (MGX), micafungin (MIF), miconazole (MCZ), nystatin (NYS), oteseconazole (OTE), pimaricin (PMR), posaconazole (POS), rezafungin (RZF), ribociclib (RBC), sulconazole (SUC), terbinafine (TRB), terconazole (TRC), voriconazole (VOR) antimycobacterials() can select:  4-aminosalicylic acid (AMA), calcium aminosalicylate (CLA), capreomycin (CAP), clofazimine (CLF), delamanid (DLM), enviomycin (ENV), ethambutol (ETH), ethambutol/isoniazid (ETI), ethionamide (ETI1), isoniazid (INH), isoniazid/sulfamethoxazole/trimethoprim/pyridoxine (IST), morinamide (MRN), p-aminosalicylic acid (PAS), pretomanid (PMD), protionamide (PTH), pyrazinamide (PZA), rifabutin (RIB), rifampicin (RIF), rifampicin/ethambutol/isoniazid (REI), rifampicin/isoniazid (RFI), rifampicin/pyrazinamide/ethambutol/isoniazid (RPEI), rifampicin/pyrazinamide/isoniazid (RPI), rifamycin (RFM), rifapentine (RFP), simvastatin/fenofibrate (SMF), sodium aminosalicylate (SDA), streptomycin/isoniazid (STI), terizidone (TRZ), thioacetazone (TAT), thioacetazone/isoniazid (THI1), tiocarlide (TCR), viomycin (VIO) betalactams() can select:  amoxicillin (AMX), amoxicillin/clavulanic acid (AMC), amoxicillin/sulbactam (AXS), ampicillin (AMP), ampicillin/sulbactam (SAM), apalcillin (APL), aspoxicillin (APX), avibactam (AVB), azidocillin (AZD), azlocillin (AZL), aztreonam (ATM), aztreonam/avibactam (AZA), aztreonam/nacubactam (ANC), bacampicillin (BAM), benzathine benzylpenicillin (BNB), benzathine phenoxymethylpenicillin (BNP), benzylpenicillin (PEN), biapenem (BIA), carbenicillin (CRB), carindacillin (CRN), cefacetrile (CAC), cefaclor (CEC), cefadroxil (CFR), cefalexin (LEX), cefaloridine (RID), cefalotin (CEP), cefamandole (MAN), cefapirin (HAP), cefatrizine (CTZ), cefazedone (CZD), cefazolin (CZO), cefcapene (CCP), cefcapene pivoxil (CCX), cefdinir (CDR), cefditoren (DIT), cefditoren pivoxil (DIX), cefepime (FEP), cefepime/clavulanic acid (CPC), cefepime/nacubactam (FNC), cefepime/tazobactam (FPT), cefetamet (CAT), cefetamet pivoxil (CPI), cefetecol (CCL), cefetrizole (CZL), cefixime (CFM), cefmenoxime (CMX), cefmetazole (CMZ), cefodizime (DIZ), cefonicid (CID), cefoperazone (CFP), cefoperazone/sulbactam (CSL), ceforanide (CND), cefoselis (CSE), cefotaxime (CTX), cefotaxime/clavulanic acid (CTC), cefotaxime/sulbactam (CTS), cefotetan (CTT), cefotiam (CTF), cefotiam hexetil (CHE), cefovecin (FOV), cefoxitin (FOX), cefoxitin screening (FOX1), cefozopran (ZOP), cefpimizole (CFZ), cefpiramide (CPM), cefpirome (CPO), cefpodoxime (CPD), cefpodoxime proxetil (CPX), cefpodoxime/clavulanic acid (CDC), cefprozil (CPR), cefquinome (CEQ), cefroxadine (CRD), cefsulodin (CFS), cefsumide (CSU), ceftaroline (CPT), ceftaroline/avibactam (CPA), ceftazidime (CAZ), ceftazidime/avibactam (CZA), ceftazidime/clavulanic acid (CCV), cefteram (CEM), cefteram pivoxil (CPL), ceftezole (CTL), ceftibuten (CTB), ceftiofur (TIO), ceftizoxime (CZX), ceftizoxime alapivoxil (CZP), ceftobiprole (BPR), ceftobiprole medocaril (CFM1), ceftolozane/tazobactam (CZT), ceftriaxone (CRO), ceftriaxone/beta-lactamase inhibitor (CEB), cefuroxime (CXM), cefuroxime axetil (CXA), cephradine (CED), ciclacillin (CIC), clometocillin (CLM), cloxacillin (CLO), dicloxacillin (DIC), doripenem (DOR), epicillin (EPC), ertapenem (ETP), flucloxacillin (FLC), hetacillin (HET), imipenem (IPM), imipenem/EDTA (IPE), imipenem/relebactam (IMR), latamoxef (LTM), lenampicillin (LEN), loracarbef (LOR), mecillinam (MEC), meropenem (MEM), meropenem/nacubactam (MNC), meropenem/vaborbactam (MEV), metampicillin (MTM), meticillin (MET), mezlocillin (MEZ), mezlocillin/sulbactam (MSU), nacubactam (NAC), nafcillin (NAF), oxacillin (OXA), panipenem (PAN), penamecillin (PNM), penicillin/novobiocin (PNO), penicillin/sulbactam (PSU), pheneticillin (PHE), phenoxymethylpenicillin (PHN), piperacillin (PIP), piperacillin/sulbactam (PIS), piperacillin/tazobactam (TZP), piridicillin (PRC), pivampicillin (PVM), pivmecillinam (PME), procaine benzylpenicillin (PRB), propicillin (PRP), razupenem (RZM), ritipenem (RIT), ritipenem acoxil (RIA), sarmoxicillin (SRX), sulbactam (SUL), sulbenicillin (SBC), sultamicillin (SLT6), talampicillin (TAL), tazobactam (TAZ), tebipenem (TBP), temocillin (TEM), ticarcillin (TIC), ticarcillin/clavulanic acid (TCC) carbapenems() can select:  biapenem (BIA), doripenem (DOR), ertapenem (ETP), imipenem (IPM), imipenem/EDTA (IPE), imipenem/relebactam (IMR), meropenem (MEM), meropenem/nacubactam (MNC), meropenem/vaborbactam (MEV), panipenem (PAN), razupenem (RZM), ritipenem (RIT), ritipenem acoxil (RIA), tebipenem (TBP) cephalosporins() can select:  cefacetrile (CAC), cefaclor (CEC), cefadroxil (CFR), cefalexin (LEX), cefaloridine (RID), cefalotin (CEP), cefamandole (MAN), cefapirin (HAP), cefatrizine (CTZ), cefazedone (CZD), cefazolin (CZO), cefcapene (CCP), cefcapene pivoxil (CCX), cefdinir (CDR), cefditoren (DIT), cefditoren pivoxil (DIX), cefepime (FEP), cefepime/clavulanic acid (CPC), cefepime/tazobactam (FPT), cefetamet (CAT), cefetamet pivoxil (CPI), cefetecol (CCL), cefetrizole (CZL), cefixime (CFM), cefmenoxime (CMX), cefmetazole (CMZ), cefodizime (DIZ), cefonicid (CID), cefoperazone (CFP), cefoperazone/sulbactam (CSL), ceforanide (CND), cefoselis (CSE), cefotaxime (CTX), cefotaxime/clavulanic acid (CTC), cefotaxime/sulbactam (CTS), cefotetan (CTT), cefotiam (CTF), cefotiam hexetil (CHE), cefovecin (FOV), cefoxitin (FOX), cefoxitin screening (FOX1), cefozopran (ZOP), cefpimizole (CFZ), cefpiramide (CPM), cefpirome (CPO), cefpodoxime (CPD), cefpodoxime proxetil (CPX), cefpodoxime/clavulanic acid (CDC), cefprozil (CPR), cefquinome (CEQ), cefroxadine (CRD), cefsulodin (CFS), cefsumide (CSU), ceftaroline (CPT), ceftaroline/avibactam (CPA), ceftazidime (CAZ), ceftazidime/avibactam (CZA), ceftazidime/clavulanic acid (CCV), cefteram (CEM), cefteram pivoxil (CPL), ceftezole (CTL), ceftibuten (CTB), ceftiofur (TIO), ceftizoxime (CZX), ceftizoxime alapivoxil (CZP), ceftobiprole (BPR), ceftobiprole medocaril (CFM1), ceftolozane/tazobactam (CZT), ceftriaxone (CRO), ceftriaxone/beta-lactamase inhibitor (CEB), cefuroxime (CXM), cefuroxime axetil (CXA), cephradine (CED), latamoxef (LTM), loracarbef (LOR) cephalosporins_1st() can select:  cefacetrile (CAC), cefadroxil (CFR), cefalexin (LEX), cefaloridine (RID), cefalotin (CEP), cefapirin (HAP), cefatrizine (CTZ), cefazedone (CZD), cefazolin (CZO), cefroxadine (CRD), ceftezole (CTL), cephradine (CED) cephalosporins_2nd() can select:  cefaclor (CEC), cefamandole (MAN), cefmetazole (CMZ), cefonicid (CID), ceforanide (CND), cefotetan (CTT), cefotiam (CTF), cefoxitin (FOX), cefoxitin screening (FOX1), cefprozil (CPR), cefuroxime (CXM), cefuroxime axetil (CXA), loracarbef (LOR) cephalosporins_3rd() can select:  cefcapene (CCP), cefcapene pivoxil (CCX), cefdinir (CDR), cefditoren (DIT), cefditoren pivoxil (DIX), cefetamet (CAT), cefetamet pivoxil (CPI), cefixime (CFM), cefmenoxime (CMX), cefodizime (DIZ), cefoperazone (CFP), cefoperazone/sulbactam (CSL), cefotaxime (CTX), cefotaxime/clavulanic acid (CTC), cefotaxime/sulbactam (CTS), cefotiam hexetil (CHE), cefovecin (FOV), cefpimizole (CFZ), cefpiramide (CPM), cefpodoxime (CPD), cefpodoxime proxetil (CPX), cefpodoxime/clavulanic acid (CDC), cefsulodin (CFS), ceftazidime (CAZ), ceftazidime/avibactam (CZA), ceftazidime/clavulanic acid (CCV), cefteram (CEM), cefteram pivoxil (CPL), ceftibuten (CTB), ceftiofur (TIO), ceftizoxime (CZX), ceftizoxime alapivoxil (CZP), ceftriaxone (CRO), ceftriaxone/beta-lactamase inhibitor (CEB), latamoxef (LTM) cephalosporins_4th() can select:  cefepime (FEP), cefepime/clavulanic acid (CPC), cefepime/tazobactam (FPT), cefetecol (CCL), cefoselis (CSE), cefozopran (ZOP), cefpirome (CPO), cefquinome (CEQ) cephalosporins_5th() can select:  ceftaroline (CPT), ceftaroline/avibactam (CPA), ceftobiprole (BPR), ceftobiprole medocaril (CFM1), ceftolozane/tazobactam (CZT) fluoroquinolones() can select:  besifloxacin (BES), ciprofloxacin (CIP), clinafloxacin (CLX), danofloxacin (DAN), delafloxacin (DFX), difloxacin (DIF), enoxacin (ENX), enrofloxacin (ENR), finafloxacin (FIN), fleroxacin (FLE), garenoxacin (GRN), gatifloxacin (GAT), gemifloxacin (GEM), grepafloxacin (GRX), lascufloxacin (LSC), levofloxacin (LVX), levonadifloxacin (LND), lomefloxacin (LOM), marbofloxacin (MAR), metioxate (MXT), miloxacin (MIL), moxifloxacin (MFX), nadifloxacin (NAD), nifuroquine (NIF), norfloxacin (), ofloxacin (OFX), orbifloxacin (ORB), pazufloxacin (PAZ), pefloxacin (PEF), pradofloxacin (PRA), premafloxacin (PRX), prulifloxacin (PRU), rufloxacin (RFL), sarafloxacin (SAR), sitafloxacin (SIT), sparfloxacin (SPX), temafloxacin (TMX), tilbroquinol (TBQ), tioxacin (TXC), tosufloxacin (TFX), trovafloxacin (TVA) glycopeptides() can select:  avoparcin (AVO), dalbavancin (DAL), norvancomycin (NVA), oritavancin (ORI), ramoplanin (RAM), teicoplanin (TEC), teicoplanin-macromethod (TCM), telavancin (TLV), vancomycin (VAN), vancomycin-macromethod (VAM) lincosamides() can select:  acetylmidecamycin (ACM), acetylspiramycin (ASP), clindamycin (CLI), clindamycin inducible screening (CLI1), gamithromycin (GAM), kitasamycin (KIT), lincomycin (LIN), meleumycin (MEL), nafithromycin (ZWK), pirlimycin (PRL), primycin (PRM), solithromycin (SOL), tildipirosin (TIP), tilmicosin (TIL), tulathromycin (TUL), tylosin (TYL), tylvalosin (TYL1) lipoglycopeptides() can select:  dalbavancin (DAL), oritavancin (ORI), telavancin (TLV) macrolides() can select:  acetylmidecamycin (ACM), acetylspiramycin (ASP), azithromycin (AZM), clarithromycin (CLR), dirithromycin (DIR), erythromycin (ERY), flurithromycin (FLR1), gamithromycin (GAM), josamycin (JOS), kitasamycin (KIT), meleumycin (MEL), midecamycin (MID), miocamycin (MCM), nafithromycin (ZWK), oleandomycin (OLE), pirlimycin (PRL), primycin (PRM), rokitamycin (ROK), roxithromycin (RXT), solithromycin (SOL), spiramycin (SPI), telithromycin (TLT), tildipirosin (TIP), tilmicosin (TIL), troleandomycin (TRL), tulathromycin (TUL), tylosin (TYL), tylvalosin (TYL1) nitrofurans() can select:  furazidin (FUR), furazolidone (FRZ), nifurtoinol (NFR), nitrofurantoin (NIT), nitrofurazone (NIZ) oxazolidinones() can select:  cadazolid (CDZ), cycloserine (CYC), linezolid (LNZ), tedizolid (TZD), thiacetazone (THA) penicillins() can select:  amoxicillin (AMX), amoxicillin/clavulanic acid (AMC), amoxicillin/sulbactam (AXS), ampicillin (AMP), ampicillin/sulbactam (SAM), apalcillin (APL), aspoxicillin (APX), avibactam (AVB), azidocillin (AZD), azlocillin (AZL), aztreonam (ATM), aztreonam/avibactam (AZA), aztreonam/nacubactam (ANC), bacampicillin (BAM), benzathine benzylpenicillin (BNB), benzathine phenoxymethylpenicillin (BNP), benzylpenicillin (PEN), carbenicillin (CRB), carindacillin (CRN), cefepime/nacubactam (FNC), ciclacillin (CIC), clometocillin (CLM), cloxacillin (CLO), dicloxacillin (DIC), epicillin (EPC), flucloxacillin (FLC), hetacillin (HET), lenampicillin (LEN), mecillinam (MEC), metampicillin (MTM), meticillin (MET), mezlocillin (MEZ), mezlocillin/sulbactam (MSU), nacubactam (NAC), nafcillin (NAF), oxacillin (OXA), penamecillin (PNM), penicillin/novobiocin (PNO), penicillin/sulbactam (PSU), pheneticillin (PHE), phenoxymethylpenicillin (PHN), piperacillin (PIP), piperacillin/sulbactam (PIS), piperacillin/tazobactam (TZP), piridicillin (PRC), pivampicillin (PVM), pivmecillinam (PME), procaine benzylpenicillin (PRB), propicillin (PRP), sarmoxicillin (SRX), sulbactam (SUL), sulbenicillin (SBC), sultamicillin (SLT6), talampicillin (TAL), tazobactam (TAZ), temocillin (TEM), ticarcillin (TIC), ticarcillin/clavulanic acid (TCC) polymyxins() can select:  colistin (COL), polymyxin B (PLB), polymyxin B/polysorbate 80 (POP) quinolones() can select:  besifloxacin (BES), cinoxacin (CIN), ciprofloxacin (CIP), ciprofloxacin/metronidazole (CIM), ciprofloxacin/ornidazole (CIO), ciprofloxacin/tinidazole (CIT), clinafloxacin (CLX), danofloxacin (DAN), delafloxacin (DFX), difloxacin (DIF), enoxacin (ENX), enrofloxacin (ENR), finafloxacin (FIN), fleroxacin (FLE), flumequine (FLM), garenoxacin (GRN), gatifloxacin (GAT), gemifloxacin (GEM), grepafloxacin (GRX), lascufloxacin (LSC), levofloxacin (LVX), levonadifloxacin (LND), lomefloxacin (LOM), marbofloxacin (MAR), metioxate (MXT), miloxacin (MIL), moxifloxacin (MFX), nadifloxacin (NAD), nalidixic acid (NAL), nemonoxacin (NEM), nifuroquine (NIF), nitroxoline (NTR), norfloxacin (), ofloxacin (OFX), orbifloxacin (ORB), oxolinic acid (OXO), pazufloxacin (PAZ), pefloxacin (PEF), pipemidic acid (PPA), piromidic acid (PIR), pradofloxacin (PRA), premafloxacin (PRX), prulifloxacin (PRU), rosoxacin (ROS), rufloxacin (RFL), sarafloxacin (SAR), sitafloxacin (SIT), sparfloxacin (SPX), temafloxacin (TMX), tilbroquinol (TBQ), tioxacin (TXC), tosufloxacin (TFX), trovafloxacin (TVA) rifamycins() can select:  rifabutin (RIB), rifampicin (RIF), rifampicin/ethambutol/isoniazid (REI), rifampicin/isoniazid (RFI), rifampicin/pyrazinamide/ethambutol/isoniazid (RPEI), rifampicin/pyrazinamide/isoniazid (RPI), rifamycin (RFM), rifapentine (RFP) streptogramins() can select:  pristinamycin (PRI) quinupristin/dalfopristin (QDA) tetracyclines() can select:  cetocycline (CTO), chlortetracycline (CTE), clomocycline (CLM1), demeclocycline (DEM), doxycycline (DOX), eravacycline (ERV), lymecycline (LYM), metacycline (MTC), minocycline (MNO), omadacycline (OMC), oxytetracycline (OXY), penimepicycline (PNM1), rolitetracycline (RLT), sarecycline (SRC), tetracycline (TCY), tigecycline (TGC) trimethoprims() can select:  brodimoprim (BDP), sulfadiazine (SDI), sulfadiazine/tetroxoprim (SLT), sulfadiazine/trimethoprim (SLT1), sulfadimethoxine (SUD), sulfadimidine (SDM), sulfadimidine/trimethoprim (SLT2), sulfafurazole (SLF), sulfaisodimidine (SLF1), sulfalene (SLF2), sulfamazone (SZO), sulfamerazine (SLF3), sulfamerazine/trimethoprim (SLT3), sulfamethizole (SLF4), sulfamethoxazole (SMX), sulfamethoxypyridazine (SLF5), sulfametomidine (SLF6), sulfametoxydiazine (SLF7), sulfametrole/trimethoprim (SLT4), sulfamoxole (SLF8), sulfamoxole/trimethoprim (SLT5), sulfanilamide (SLF9), sulfaperin (SLF10), sulfaphenazole (SLF11), sulfapyridine (SLF12), sulfathiazole (SUT), sulfathiourea (SLF13), trimethoprim (TMP), trimethoprim/sulfamethoxazole (SXT) ureidopenicillins() can select:  azlocillin (AZL), mezlocillin (MEZ), piperacillin (PIP), piperacillin/tazobactam (TZP)","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html","id":"reference-data-publicly-available","dir":"Reference","previous_headings":"","what":"Reference Data Publicly Available","title":"Antibiotic Selectors — antibiotic_class_selectors","text":"data sets AMR package (microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) publicly freely available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. also provide tab-separated plain text files machine-readable suitable input software program, laboratory information systems. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Antibiotic Selectors — antibiotic_class_selectors","text":"","code":"# `example_isolates` is a data set available in the AMR package. # See ?example_isolates. example_isolates #> # A tibble: 2,000 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-03 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  3 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  4 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  5 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  6 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  7 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  8 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  9 2002-01-16 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #> 10 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R     NA    S     NA    #> # ℹ 1,990 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, …   # Examples sections below are split into 'dplyr', 'base R', and 'data.table':  # \\donttest{ # dplyr -------------------------------------------------------------------  if (require(\"dplyr\")) {   example_isolates %>% select(carbapenems()) } #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> # A tibble: 2,000 × 2 #>    IPM   MEM   #>    <sir> <sir> #>  1 NA    NA    #>  2 NA    NA    #>  3 NA    NA    #>  4 NA    NA    #>  5 NA    NA    #>  6 NA    NA    #>  7 NA    NA    #>  8 NA    NA    #>  9 NA    NA    #> 10 NA    NA    #> # ℹ 1,990 more rows  if (require(\"dplyr\")) {   # select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB'   example_isolates %>% select(mo, aminoglycosides()) } #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> # A tibble: 2,000 × 5 #>    mo           GEN   TOB   AMK   KAN   #>    <mo>         <sir> <sir> <sir> <sir> #>  1 B_ESCHR_COLI NA    NA    NA    NA    #>  2 B_ESCHR_COLI NA    NA    NA    NA    #>  3 B_STPHY_EPDR NA    NA    NA    NA    #>  4 B_STPHY_EPDR NA    NA    NA    NA    #>  5 B_STPHY_EPDR NA    NA    NA    NA    #>  6 B_STPHY_EPDR NA    NA    NA    NA    #>  7 B_STPHY_AURS NA    S     NA    NA    #>  8 B_STPHY_AURS NA    S     NA    NA    #>  9 B_STPHY_EPDR NA    NA    NA    NA    #> 10 B_STPHY_EPDR NA    NA    NA    NA    #> # ℹ 1,990 more rows  if (require(\"dplyr\")) {   # select only antibiotic columns with DDDs for oral treatment   example_isolates %>% select(administrable_per_os()) } #> ℹ For administrable_per_os() using columns 'OXA' (oxacillin), 'FLC' #>   (flucloxacillin), 'AMX' (amoxicillin), 'AMC' (amoxicillin/clavulanic acid), #>   'AMP' (ampicillin), 'CXM' (cefuroxime), 'KAN' (kanamycin), 'TMP' #>   (trimethoprim), 'NIT' (nitrofurantoin), 'FOS' (fosfomycin), 'LNZ' #>   (linezolid), 'CIP' (ciprofloxacin), 'MFX' (moxifloxacin), 'VAN' #>   (vancomycin), 'TCY' (tetracycline), 'DOX' (doxycycline), 'ERY' #>   (erythromycin), 'CLI' (clindamycin), 'AZM' (azithromycin), 'MTR' #>   (metronidazole), 'CHL' (chloramphenicol), 'COL' (colistin), and 'RIF' #>   (rifampicin) #> # A tibble: 2,000 × 23 #>    OXA   FLC   AMX   AMC   AMP   CXM   KAN   TMP   NIT   FOS   LNZ   CIP   MFX   #>    <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> #>  1 NA    NA    NA    I     NA    I     NA    R     NA    NA    R     NA    NA    #>  2 NA    NA    NA    I     NA    I     NA    R     NA    NA    R     NA    NA    #>  3 NA    R     NA    NA    NA    R     NA    S     NA    NA    NA    NA    NA    #>  4 NA    R     NA    NA    NA    R     NA    S     NA    NA    NA    NA    NA    #>  5 NA    R     NA    NA    NA    R     NA    R     NA    NA    NA    NA    NA    #>  6 NA    R     NA    NA    NA    R     NA    R     NA    NA    NA    NA    NA    #>  7 NA    S     R     S     R     S     NA    R     NA    NA    NA    NA    NA    #>  8 NA    S     R     S     R     S     NA    R     NA    NA    NA    NA    NA    #>  9 NA    R     NA    NA    NA    R     NA    S     NA    NA    NA    S     NA    #> 10 NA    S     NA    NA    NA    S     NA    S     NA    NA    NA    S     NA    #> # ℹ 1,990 more rows #> # ℹ 10 more variables: VAN <sir>, TCY <sir>, DOX <sir>, ERY <sir>, CLI <sir>, #> #   AZM <sir>, MTR <sir>, CHL <sir>, COL <sir>, RIF <sir>  if (require(\"dplyr\")) {   # get AMR for all aminoglycosides e.g., per ward:   example_isolates %>%     group_by(ward) %>%     summarise(across(aminoglycosides(),                      resistance)) } #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> Warning: There was 1 warning in `summarise()`. #> ℹ In argument: `across(aminoglycosides(), resistance)`. #> ℹ In group 3: `ward = \"Outpatient\"`. #> Caused by warning: #> ! Introducing NA: only 23 results available for KAN in group: ward = #> \"Outpatient\" (minimum = 30). #> # A tibble: 3 × 5 #>   ward         GEN   TOB   AMK   KAN #>   <chr>      <dbl> <dbl> <dbl> <dbl> #> 1 Clinical   0.229 0.315 0.626     1 #> 2 ICU        0.290 0.400 0.662     1 #> 3 Outpatient 0.2   0.368 0.605    NA if (require(\"dplyr\")) {   # You can combine selectors with '&' to be more specific:   example_isolates %>%     select(penicillins() & administrable_per_os()) } #> ℹ For penicillins() using columns 'PEN' (benzylpenicillin), 'OXA' #>   (oxacillin), 'FLC' (flucloxacillin), 'AMX' (amoxicillin), 'AMC' #>   (amoxicillin/clavulanic acid), 'AMP' (ampicillin), and 'TZP' #>   (piperacillin/tazobactam) #> ℹ For administrable_per_os() using columns 'OXA' (oxacillin), 'FLC' #>   (flucloxacillin), 'AMX' (amoxicillin), 'AMC' (amoxicillin/clavulanic acid), #>   'AMP' (ampicillin), 'CXM' (cefuroxime), 'KAN' (kanamycin), 'TMP' #>   (trimethoprim), 'NIT' (nitrofurantoin), 'FOS' (fosfomycin), 'LNZ' #>   (linezolid), 'CIP' (ciprofloxacin), 'MFX' (moxifloxacin), 'VAN' #>   (vancomycin), 'TCY' (tetracycline), 'DOX' (doxycycline), 'ERY' #>   (erythromycin), 'CLI' (clindamycin), 'AZM' (azithromycin), 'MTR' #>   (metronidazole), 'CHL' (chloramphenicol), 'COL' (colistin), and 'RIF' #>   (rifampicin) #> # A tibble: 2,000 × 5 #>    OXA   FLC   AMX   AMC   AMP   #>    <sir> <sir> <sir> <sir> <sir> #>  1 NA    NA    NA    I     NA    #>  2 NA    NA    NA    I     NA    #>  3 NA    R     NA    NA    NA    #>  4 NA    R     NA    NA    NA    #>  5 NA    R     NA    NA    NA    #>  6 NA    R     NA    NA    NA    #>  7 NA    S     R     S     R     #>  8 NA    S     R     S     R     #>  9 NA    R     NA    NA    NA    #> 10 NA    S     NA    NA    NA    #> # ℹ 1,990 more rows if (require(\"dplyr\")) {   # get AMR for only drugs that matter - no intrinsic resistance:   example_isolates %>%     filter(mo_genus() %in% c(\"Escherichia\", \"Klebsiella\")) %>%     group_by(ward) %>%     summarise_at(not_intrinsic_resistant(),                  resistance) } #> ℹ Using column 'mo' as input for mo_genus() #> ℹ For not_intrinsic_resistant() removing columns 'PEN' #>   (benzylpenicillin), 'LNZ' (linezolid), 'VAN' (vancomycin), 'TEC' #>   (teicoplanin), 'ERY' (erythromycin), 'CLI' (clindamycin), 'AZM' #>   (azithromycin), and 'RIF' (rifampicin) #> Warning: There were 52 warnings in `summarise()`. #> The first warning was: #> ℹ In argument: `OXA = (function (..., minimum = 30, as_percent = FALSE, #>   only_all_tested = FALSE) ...`. #> ℹ In group 1: `ward = \"Clinical\"`. #> Caused by warning: #> ! Introducing NA: no results available for OXA in group: ward = \"Clinical\" #> (minimum = 30). #> ℹ Run `dplyr::last_dplyr_warnings()` to see the 51 remaining warnings. #> # A tibble: 3 × 33 #>   ward    OXA   FLC    AMX    AMC    AMP     TZP     CZO     FEP     CXM     FOX #>   <chr> <dbl> <dbl>  <dbl>  <dbl>  <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl> #> 1 Clin…    NA    NA  0.606  0.121  0.606  0.0504  0.0656  0.0159  0.0622  0.0648 #> 2 ICU      NA    NA  0.535  0.172  0.535  0.119  NA       0.0722  0.0828  0.0992 #> 3 Outp…    NA    NA NA     NA     NA     NA      NA      NA      NA      NA      #> # ℹ 22 more variables: CTX <dbl>, CAZ <dbl>, CRO <dbl>, GEN <dbl>, TOB <dbl>, #> #   AMK <dbl>, KAN <dbl>, TMP <dbl>, SXT <dbl>, NIT <dbl>, FOS <dbl>, #> #   CIP <dbl>, MFX <dbl>, TCY <dbl>, TGC <dbl>, DOX <dbl>, IPM <dbl>, #> #   MEM <dbl>, MTR <dbl>, CHL <dbl>, COL <dbl>, MUP <dbl> if (require(\"dplyr\")) {   # get susceptibility for antibiotics whose name contains \"trim\":   example_isolates %>%     filter(first_isolate()) %>%     group_by(ward) %>%     summarise(across(ab_selector(name %like% \"trim\"), susceptibility)) } #> ℹ For ab_selector(name %like% \"trim\") using columns 'TMP' (trimethoprim) #>   and 'SXT' (trimethoprim/sulfamethoxazole) #> # A tibble: 3 × 3 #>   ward         TMP   SXT #>   <chr>      <dbl> <dbl> #> 1 Clinical   0.627 0.807 #> 2 ICU        0.551 0.780 #> 3 Outpatient 0.667 0.821 if (require(\"dplyr\")) {   # this will select columns 'IPM' (imipenem) and 'MEM' (meropenem):   example_isolates %>%     select(carbapenems()) } #> # A tibble: 2,000 × 2 #>    IPM   MEM   #>    <sir> <sir> #>  1 NA    NA    #>  2 NA    NA    #>  3 NA    NA    #>  4 NA    NA    #>  5 NA    NA    #>  6 NA    NA    #>  7 NA    NA    #>  8 NA    NA    #>  9 NA    NA    #> 10 NA    NA    #> # ℹ 1,990 more rows if (require(\"dplyr\")) {   # this will select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB':   example_isolates %>%     select(mo, aminoglycosides()) } #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> # A tibble: 2,000 × 5 #>    mo           GEN   TOB   AMK   KAN   #>    <mo>         <sir> <sir> <sir> <sir> #>  1 B_ESCHR_COLI NA    NA    NA    NA    #>  2 B_ESCHR_COLI NA    NA    NA    NA    #>  3 B_STPHY_EPDR NA    NA    NA    NA    #>  4 B_STPHY_EPDR NA    NA    NA    NA    #>  5 B_STPHY_EPDR NA    NA    NA    NA    #>  6 B_STPHY_EPDR NA    NA    NA    NA    #>  7 B_STPHY_AURS NA    S     NA    NA    #>  8 B_STPHY_AURS NA    S     NA    NA    #>  9 B_STPHY_EPDR NA    NA    NA    NA    #> 10 B_STPHY_EPDR NA    NA    NA    NA    #> # ℹ 1,990 more rows if (require(\"dplyr\")) {   # any() and all() work in dplyr's filter() too:   example_isolates %>%     filter(       any(aminoglycosides() == \"R\"),       all(cephalosporins_2nd() == \"R\")     ) } #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> ℹ For cephalosporins_2nd() using columns 'CXM' (cefuroxime) and 'FOX' #>   (cefoxitin) #> # A tibble: 112 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-02-21 4FC193     69 M      Clinical B_ENTRC_FACM NA    NA    NA    NA    #>  2 2002-03-16 4FC193     69 M      Clinical B_PSDMN_AERG R     NA    NA    R     #>  3 2002-04-08 130252     78 M      ICU      B_ENTRC_FCLS NA    NA    NA    NA    #>  4 2002-06-23 798871     82 M      Clinical B_ENTRC_FCLS NA    NA    NA    NA    #>  5 2002-06-23 798871     82 M      Clinical B_ENTRC_FCLS NA    NA    NA    NA    #>  6 2002-07-21 955940     82 F      Clinical B_PSDMN_AERG R     NA    NA    R     #>  7 2002-07-21 955940     82 F      Clinical B_PSDMN_AERG R     NA    NA    R     #>  8 2003-08-13 F35553     52 M      ICU      B_ENTRC_FCLS NA    NA    NA    NA    #>  9 2003-09-05 F35553     52 M      ICU      B_ENTRC_FCLS NA    NA    NA    NA    #> 10 2004-06-09 529296     69 M      ICU      B_ENTRC_FACM NA    NA    NA    NA    #> # ℹ 102 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, … if (require(\"dplyr\")) {   # also works with c():   example_isolates %>%     filter(any(c(carbapenems(), aminoglycosides()) == \"R\")) } #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> # A tibble: 531 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-02-21 4FC193     69 M      Clinical B_ENTRC_FACM NA    NA    NA    NA    #>  2 2002-03-16 4FC193     69 M      Clinical B_PSDMN_AERG R     NA    NA    R     #>  3 2002-03-17 B30560     78 M      Clinical B_STPHY_CONS R     NA    R     R     #>  4 2002-04-04 E61143     67 M      Clinical B_STRPT_SNGN S     NA    NA    S     #>  5 2002-04-08 130252     78 M      ICU      B_ENTRC_FCLS NA    NA    NA    NA    #>  6 2002-04-14 F30196     73 M      Outpati… B_STRPT_GRPB S     NA    S     S     #>  7 2002-05-07 D91570     83 M      Clinical B_STPHY_CONS R     NA    R     R     #>  8 2002-05-07 D91570     83 M      Clinical B_STPHY_CONS R     NA    R     R     #>  9 2002-05-14 077552     86 F      Clinical B_STRPT_PNMN S     NA    NA    S     #> 10 2002-05-14 077552     86 F      Clinical B_STRPT_PNMN S     NA    NA    S     #> # ℹ 521 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, … if (require(\"dplyr\")) {   # not setting any/all will automatically apply all():   example_isolates %>%     filter(aminoglycosides() == \"R\") } #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> ℹ Assuming a filter on all 4 aminoglycosides. Wrap around all() or #>   any() to prevent this note. #> # A tibble: 427 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-02-21 4FC193     69 M      Clinical B_ENTRC_FACM NA    NA    NA    NA    #>  2 2002-03-17 B30560     78 M      Clinical B_STPHY_CONS R     NA    R     R     #>  3 2002-04-04 E61143     67 M      Clinical B_STRPT_SNGN S     NA    NA    S     #>  4 2002-04-08 130252     78 M      ICU      B_ENTRC_FCLS NA    NA    NA    NA    #>  5 2002-04-14 F30196     73 M      Outpati… B_STRPT_GRPB S     NA    S     S     #>  6 2002-05-07 D91570     83 M      Clinical B_STPHY_CONS R     NA    R     R     #>  7 2002-05-07 D91570     83 M      Clinical B_STPHY_CONS R     NA    R     R     #>  8 2002-05-14 077552     86 F      Clinical B_STRPT_PNMN S     NA    NA    S     #>  9 2002-05-14 077552     86 F      Clinical B_STRPT_PNMN S     NA    NA    S     #> 10 2002-05-16 D25302     65 F      ICU      B_STRPT_ANGN S     NA    NA    S     #> # ℹ 417 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, … if (require(\"dplyr\")) {   # this will select columns 'mo' and all antimycobacterial drugs ('RIF'):   example_isolates %>%     select(mo, ab_class(\"mycobact\")) } #> ℹ For ab_class(\"mycobact\") using column 'RIF' (rifampicin) #> # A tibble: 2,000 × 2 #>    mo           RIF   #>    <mo>         <sir> #>  1 B_ESCHR_COLI R     #>  2 B_ESCHR_COLI R     #>  3 B_STPHY_EPDR NA    #>  4 B_STPHY_EPDR NA    #>  5 B_STPHY_EPDR NA    #>  6 B_STPHY_EPDR NA    #>  7 B_STPHY_AURS NA    #>  8 B_STPHY_AURS NA    #>  9 B_STPHY_EPDR NA    #> 10 B_STPHY_EPDR NA    #> # ℹ 1,990 more rows if (require(\"dplyr\")) {   # get bug/drug combinations for only glycopeptides in Gram-positives:   example_isolates %>%     filter(mo_is_gram_positive()) %>%     select(mo, glycopeptides()) %>%     bug_drug_combinations() %>%     format() } #> ℹ Using column 'mo' as input for mo_is_gram_positive() #> ℹ For glycopeptides() using columns 'VAN' (vancomycin) and 'TEC' #>   (teicoplanin) #> # A tibble: 2 × 8 #>   Group      Drug  CoNS  `E. faecalis` `S. aureus` `S. epidermidis` `S. hominis` #>   <chr>      <chr> <chr> <chr>         <chr>       <chr>            <chr>        #> 1 \"Glycopep… Teic… \"\"    \"\"            \" 0.0% (0/… \"64.1% (25/39)\"  \" 6.8% (4/5… #> 2 \"\"         Vanc… \" 0.… \" 0.0% (0/39… \" 0.0% (0/… \" 0.0% (0/171)\"  \" 0.0% (0/8… #> # ℹ 1 more variable: `S. pneumoniae` <chr> if (require(\"dplyr\")) {   data.frame(     some_column = \"some_value\",     J01CA01 = \"S\"   ) %>% # ATC code of ampicillin     select(penicillins()) # only the 'J01CA01' column will be selected } #> ℹ For penicillins() using column 'J01CA01' (ampicillin) #>   J01CA01 #> 1       S if (require(\"dplyr\")) {   # with recent versions of dplyr, this is all equal:   x <- example_isolates[carbapenems() == \"R\", ]   y <- example_isolates %>% filter(carbapenems() == \"R\")   z <- example_isolates %>% filter(if_all(carbapenems(), ~ .x == \"R\"))   identical(x, y) && identical(y, z) } #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> ℹ Assuming a filter on all 2 carbapenems. Wrap around all() or any() to #>   prevent this note. #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> ℹ Assuming a filter on all 2 carbapenems. Wrap around all() or any() to #>   prevent this note. #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> [1] TRUE   # base R ------------------------------------------------------------------  # select columns 'IPM' (imipenem) and 'MEM' (meropenem) example_isolates[, carbapenems()] #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> # A tibble: 2,000 × 2 #>    IPM   MEM   #>    <sir> <sir> #>  1 NA    NA    #>  2 NA    NA    #>  3 NA    NA    #>  4 NA    NA    #>  5 NA    NA    #>  6 NA    NA    #>  7 NA    NA    #>  8 NA    NA    #>  9 NA    NA    #> 10 NA    NA    #> # ℹ 1,990 more rows  # select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB' example_isolates[, c(\"mo\", aminoglycosides())] #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> # A tibble: 2,000 × 5 #>    mo           GEN   TOB   AMK   KAN   #>    <mo>         <sir> <sir> <sir> <sir> #>  1 B_ESCHR_COLI NA    NA    NA    NA    #>  2 B_ESCHR_COLI NA    NA    NA    NA    #>  3 B_STPHY_EPDR NA    NA    NA    NA    #>  4 B_STPHY_EPDR NA    NA    NA    NA    #>  5 B_STPHY_EPDR NA    NA    NA    NA    #>  6 B_STPHY_EPDR NA    NA    NA    NA    #>  7 B_STPHY_AURS NA    S     NA    NA    #>  8 B_STPHY_AURS NA    S     NA    NA    #>  9 B_STPHY_EPDR NA    NA    NA    NA    #> 10 B_STPHY_EPDR NA    NA    NA    NA    #> # ℹ 1,990 more rows  # select only antibiotic columns with DDDs for oral treatment example_isolates[, administrable_per_os()] #> ℹ For administrable_per_os() using columns 'OXA' (oxacillin), 'FLC' #>   (flucloxacillin), 'AMX' (amoxicillin), 'AMC' (amoxicillin/clavulanic acid), #>   'AMP' (ampicillin), 'CXM' (cefuroxime), 'KAN' (kanamycin), 'TMP' #>   (trimethoprim), 'NIT' (nitrofurantoin), 'FOS' (fosfomycin), 'LNZ' #>   (linezolid), 'CIP' (ciprofloxacin), 'MFX' (moxifloxacin), 'VAN' #>   (vancomycin), 'TCY' (tetracycline), 'DOX' (doxycycline), 'ERY' #>   (erythromycin), 'CLI' (clindamycin), 'AZM' (azithromycin), 'MTR' #>   (metronidazole), 'CHL' (chloramphenicol), 'COL' (colistin), and 'RIF' #>   (rifampicin) #> # A tibble: 2,000 × 23 #>    OXA   FLC   AMX   AMC   AMP   CXM   KAN   TMP   NIT   FOS   LNZ   CIP   MFX   #>    <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> #>  1 NA    NA    NA    I     NA    I     NA    R     NA    NA    R     NA    NA    #>  2 NA    NA    NA    I     NA    I     NA    R     NA    NA    R     NA    NA    #>  3 NA    R     NA    NA    NA    R     NA    S     NA    NA    NA    NA    NA    #>  4 NA    R     NA    NA    NA    R     NA    S     NA    NA    NA    NA    NA    #>  5 NA    R     NA    NA    NA    R     NA    R     NA    NA    NA    NA    NA    #>  6 NA    R     NA    NA    NA    R     NA    R     NA    NA    NA    NA    NA    #>  7 NA    S     R     S     R     S     NA    R     NA    NA    NA    NA    NA    #>  8 NA    S     R     S     R     S     NA    R     NA    NA    NA    NA    NA    #>  9 NA    R     NA    NA    NA    R     NA    S     NA    NA    NA    S     NA    #> 10 NA    S     NA    NA    NA    S     NA    S     NA    NA    NA    S     NA    #> # ℹ 1,990 more rows #> # ℹ 10 more variables: VAN <sir>, TCY <sir>, DOX <sir>, ERY <sir>, CLI <sir>, #> #   AZM <sir>, MTR <sir>, CHL <sir>, COL <sir>, RIF <sir>  # filter using any() or all() example_isolates[any(carbapenems() == \"R\"), ] #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> # A tibble: 55 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2004-06-09 529296     69 M      ICU      B_ENTRC_FACM NA    NA    NA    NA    #>  2 2004-06-09 529296     69 M      ICU      B_ENTRC_FACM NA    NA    NA    NA    #>  3 2004-11-03 D65308     80 F      ICU      B_STNTR_MLTP R     NA    NA    R     #>  4 2005-04-21 452212     82 F      ICU      B_ENTRC      NA    NA    NA    NA    #>  5 2005-04-22 452212     82 F      ICU      B_ENTRC      NA    NA    NA    NA    #>  6 2005-04-22 452212     82 F      ICU      B_ENTRC_FACM NA    NA    NA    NA    #>  7 2007-02-21 8BBC46     61 F      Clinical B_ENTRC_FACM NA    NA    NA    NA    #>  8 2007-12-15 401043     72 M      Clinical B_ENTRC_FACM NA    NA    NA    NA    #>  9 2008-01-22 1710B8     82 M      Clinical B_PROTS_MRBL R     NA    NA    NA    #> 10 2008-01-22 1710B8     82 M      Clinical B_PROTS_MRBL R     NA    NA    NA    #> # ℹ 45 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, … subset(example_isolates, any(carbapenems() == \"R\")) #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> # A tibble: 55 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2004-06-09 529296     69 M      ICU      B_ENTRC_FACM NA    NA    NA    NA    #>  2 2004-06-09 529296     69 M      ICU      B_ENTRC_FACM NA    NA    NA    NA    #>  3 2004-11-03 D65308     80 F      ICU      B_STNTR_MLTP R     NA    NA    R     #>  4 2005-04-21 452212     82 F      ICU      B_ENTRC      NA    NA    NA    NA    #>  5 2005-04-22 452212     82 F      ICU      B_ENTRC      NA    NA    NA    NA    #>  6 2005-04-22 452212     82 F      ICU      B_ENTRC_FACM NA    NA    NA    NA    #>  7 2007-02-21 8BBC46     61 F      Clinical B_ENTRC_FACM NA    NA    NA    NA    #>  8 2007-12-15 401043     72 M      Clinical B_ENTRC_FACM NA    NA    NA    NA    #>  9 2008-01-22 1710B8     82 M      Clinical B_PROTS_MRBL R     NA    NA    NA    #> 10 2008-01-22 1710B8     82 M      Clinical B_PROTS_MRBL R     NA    NA    NA    #> # ℹ 45 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, …  # filter on any or all results in the carbapenem columns (i.e., IPM, MEM): example_isolates[any(carbapenems()), ] #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> ℹ Filtering any of columns 'IPM' and 'MEM' to contain value \"S\", \"I\" or \"R\" #> # A tibble: 962 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-19 738003     71 M      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-19 738003     71 M      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  3 2002-01-22 F35553     50 M      ICU      B_PROTS_MRBL R     NA    NA    NA    #>  4 2002-01-22 F35553     50 M      ICU      B_PROTS_MRBL R     NA    NA    NA    #>  5 2002-02-05 067927     45 F      ICU      B_SERRT_MRCS R     NA    NA    R     #>  6 2002-02-05 067927     45 F      ICU      B_SERRT_MRCS R     NA    NA    R     #>  7 2002-02-05 067927     45 F      ICU      B_SERRT_MRCS R     NA    NA    R     #>  8 2002-02-27 066895     85 F      Clinical B_KLBSL_PNMN R     NA    NA    R     #>  9 2002-02-27 066895     85 F      Clinical B_KLBSL_PNMN R     NA    NA    R     #> 10 2002-03-08 4FC193     69 M      Clinical B_ESCHR_COLI R     NA    NA    R     #> # ℹ 952 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, … example_isolates[all(carbapenems()), ] #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> ℹ Filtering all of columns 'IPM' and 'MEM' to contain value \"S\", \"I\" or \"R\" #> # A tibble: 756 × 46 #>    date       patient   age gender ward    mo            PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>   <mo>          <sir> <sir> <sir> <sir> #>  1 2002-04-14 F30196     73 M      Outpat… B_STRPT_GRPB  S     NA    S     S     #>  2 2003-04-08 114570     74 M      ICU     B_STRPT_PYGN  S     NA    S     S     #>  3 2003-04-08 114570     74 M      ICU     B_STRPT_GRPA  S     NA    S     S     #>  4 2003-04-08 114570     74 M      ICU     B_STRPT_GRPA  S     NA    S     S     #>  5 2003-08-14 F71508      0 F      Clinic… B_STRPT_GRPB  S     NA    S     S     #>  6 2003-10-16 650870     63 F      ICU     B_ESCHR_COLI  R     NA    NA    R     #>  7 2003-10-20 F35553     52 M      ICU     B_ENTRBC_CLOC R     NA    NA    R     #>  8 2003-10-20 F35553     52 M      ICU     B_ENTRBC_CLOC R     NA    NA    R     #>  9 2003-11-04 2FC253     87 F      ICU     B_ESCHR_COLI  R     NA    NA    NA    #> 10 2003-11-04 2FC253     87 F      ICU     B_ESCHR_COLI  R     NA    NA    NA    #> # ℹ 746 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, …  # filter with multiple antibiotic selectors using c() example_isolates[all(c(carbapenems(), aminoglycosides()) == \"R\"), ] #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> # A tibble: 26 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2004-11-03 D65308     80 F      ICU      B_STNTR_MLTP R     NA    NA    R     #>  2 2005-04-22 452212     82 F      ICU      B_ENTRC_FACM NA    NA    NA    NA    #>  3 2007-02-21 8BBC46     61 F      Clinical B_ENTRC_FACM NA    NA    NA    NA    #>  4 2007-12-15 401043     72 M      Clinical B_ENTRC_FACM NA    NA    NA    NA    #>  5 2008-12-06 501361     43 F      Clinical B_STNTR_MLTP R     NA    NA    R     #>  6 2011-05-09 207325     82 F      ICU      B_ENTRC_FACM NA    NA    NA    NA    #>  7 2012-03-12 582258     80 M      ICU      B_STPHY_CONS R     R     R     R     #>  8 2012-05-19 C25552     89 F      Outpati… B_STPHY_CONS R     R     R     R     #>  9 2012-07-17 F05015     83 M      ICU      B_STPHY_CONS R     R     R     R     #> 10 2012-07-20 404299     66 F      Clinical B_STPHY_CONS R     R     R     R     #> # ℹ 16 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, …  # filter + select in one go: get penicillins in carbapenem-resistant strains example_isolates[any(carbapenems() == \"R\"), penicillins()] #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> ℹ For penicillins() using columns 'PEN' (benzylpenicillin), 'OXA' #>   (oxacillin), 'FLC' (flucloxacillin), 'AMX' (amoxicillin), 'AMC' #>   (amoxicillin/clavulanic acid), 'AMP' (ampicillin), and 'TZP' #>   (piperacillin/tazobactam) #> # A tibble: 55 × 7 #>    PEN   OXA   FLC   AMX   AMC   AMP   TZP   #>    <sir> <sir> <sir> <sir> <sir> <sir> <sir> #>  1 NA    NA    NA    NA    NA    NA    NA    #>  2 NA    NA    NA    NA    NA    NA    NA    #>  3 R     NA    NA    R     R     R     R     #>  4 NA    NA    NA    NA    NA    NA    R     #>  5 NA    NA    NA    NA    NA    NA    R     #>  6 NA    NA    NA    NA    NA    NA    R     #>  7 NA    NA    NA    NA    NA    NA    R     #>  8 NA    NA    NA    NA    NA    NA    R     #>  9 R     NA    NA    NA    S     NA    S     #> 10 R     NA    NA    NA    S     NA    S     #> # ℹ 45 more rows  # You can combine selectors with '&' to be more specific. For example, # penicillins() would select benzylpenicillin ('peni G') and # administrable_per_os() would select erythromycin. Yet, when combined these # drugs are both omitted since benzylpenicillin is not administrable per os # and erythromycin is not a penicillin: example_isolates[, penicillins() & administrable_per_os()] #> ℹ For penicillins() using columns 'PEN' (benzylpenicillin), 'OXA' #>   (oxacillin), 'FLC' (flucloxacillin), 'AMX' (amoxicillin), 'AMC' #>   (amoxicillin/clavulanic acid), 'AMP' (ampicillin), and 'TZP' #>   (piperacillin/tazobactam) #> ℹ For administrable_per_os() using columns 'OXA' (oxacillin), 'FLC' #>   (flucloxacillin), 'AMX' (amoxicillin), 'AMC' (amoxicillin/clavulanic acid), #>   'AMP' (ampicillin), 'CXM' (cefuroxime), 'KAN' (kanamycin), 'TMP' #>   (trimethoprim), 'NIT' (nitrofurantoin), 'FOS' (fosfomycin), 'LNZ' #>   (linezolid), 'CIP' (ciprofloxacin), 'MFX' (moxifloxacin), 'VAN' #>   (vancomycin), 'TCY' (tetracycline), 'DOX' (doxycycline), 'ERY' #>   (erythromycin), 'CLI' (clindamycin), 'AZM' (azithromycin), 'MTR' #>   (metronidazole), 'CHL' (chloramphenicol), 'COL' (colistin), and 'RIF' #>   (rifampicin) #> # A tibble: 2,000 × 5 #>    OXA   FLC   AMX   AMC   AMP   #>    <sir> <sir> <sir> <sir> <sir> #>  1 NA    NA    NA    I     NA    #>  2 NA    NA    NA    I     NA    #>  3 NA    R     NA    NA    NA    #>  4 NA    R     NA    NA    NA    #>  5 NA    R     NA    NA    NA    #>  6 NA    R     NA    NA    NA    #>  7 NA    S     R     S     R     #>  8 NA    S     R     S     R     #>  9 NA    R     NA    NA    NA    #> 10 NA    S     NA    NA    NA    #> # ℹ 1,990 more rows  # ab_selector() applies a filter in the `antibiotics` data set and is thus # very flexible. For instance, to select antibiotic columns with an oral DDD # of at least 1 gram: example_isolates[, ab_selector(oral_ddd > 1 & oral_units == \"g\")] #> ℹ For ab_selector(oral_ddd > 1 & oral_units == \"g\") using columns 'OXA' #>   (oxacillin), 'FLC' (flucloxacillin), 'AMX' (amoxicillin), 'AMC' #>   (amoxicillin/clavulanic acid), 'AMP' (ampicillin), 'KAN' (kanamycin), 'FOS' #>   (fosfomycin), 'LNZ' (linezolid), 'VAN' (vancomycin), 'ERY' (erythromycin), #>   'CLI' (clindamycin), 'MTR' (metronidazole), and 'CHL' (chloramphenicol) #> # A tibble: 2,000 × 13 #>    OXA   FLC   AMX   AMC   AMP   KAN   FOS   LNZ   VAN   ERY   CLI   MTR   CHL   #>    <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> #>  1 NA    NA    NA    I     NA    NA    NA    R     R     R     R     NA    NA    #>  2 NA    NA    NA    I     NA    NA    NA    R     R     R     R     NA    NA    #>  3 NA    R     NA    NA    NA    NA    NA    NA    S     R     NA    NA    NA    #>  4 NA    R     NA    NA    NA    NA    NA    NA    S     R     NA    NA    NA    #>  5 NA    R     NA    NA    NA    NA    NA    NA    S     R     NA    NA    NA    #>  6 NA    R     NA    NA    NA    NA    NA    NA    S     R     R     NA    NA    #>  7 NA    S     R     S     R     NA    NA    NA    S     S     NA    NA    NA    #>  8 NA    S     R     S     R     NA    NA    NA    S     S     NA    NA    NA    #>  9 NA    R     NA    NA    NA    NA    NA    NA    S     R     NA    NA    NA    #> 10 NA    S     NA    NA    NA    NA    NA    NA    S     S     NA    NA    NA    #> # ℹ 1,990 more rows   # data.table --------------------------------------------------------------  # data.table is supported as well, just use it in the same way as with # base R, but add `with = FALSE` if using a single AB selector.  if (require(\"data.table\")) {   dt <- as.data.table(example_isolates)    # this does not work, it returns column *names*   dt[, carbapenems()] } #> Loading required package: data.table #>  #> Attaching package: ‘data.table’ #> The following objects are masked from ‘package:dplyr’: #>  #>     between, first, last #> The following objects are masked from ‘package:AMR’: #>  #>     %like%, like #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> Warning: It should never be needed to print an antibiotic selector class. Are you #> using data.table? Then add the argument with = FALSE, see our examples at #> ?ab_selector. #> Class 'ab_selector' #> [1] IPM MEM if (require(\"data.table\")) {   # so `with = FALSE` is required   dt[, carbapenems(), with = FALSE] } #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #>         IPM   MEM #>       <sir> <sir> #>    1:  <NA>  <NA> #>    2:  <NA>  <NA> #>    3:  <NA>  <NA> #>    4:  <NA>  <NA> #>    5:  <NA>  <NA> #>   ---             #> 1996:  <NA>  <NA> #> 1997:     S     S #> 1998:     S     S #> 1999:     S     S #> 2000:     S     S  # for multiple selections or AB selectors, `with = FALSE` is not needed: if (require(\"data.table\")) {   dt[, c(\"mo\", aminoglycosides())] } #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #>                 mo   GEN   TOB   AMK   KAN #>               <mo> <sir> <sir> <sir> <sir> #>    1: B_ESCHR_COLI  <NA>  <NA>  <NA>  <NA> #>    2: B_ESCHR_COLI  <NA>  <NA>  <NA>  <NA> #>    3: B_STPHY_EPDR  <NA>  <NA>  <NA>  <NA> #>    4: B_STPHY_EPDR  <NA>  <NA>  <NA>  <NA> #>    5: B_STPHY_EPDR  <NA>  <NA>  <NA>  <NA> #>   ---                                      #> 1996: B_STRPT_PNMN     R     R     R     R #> 1997: B_ESCHR_COLI     S     S     S  <NA> #> 1998: B_STPHY_CONS     S  <NA>  <NA>  <NA> #> 1999: B_ESCHR_COLI     S     S  <NA>  <NA> #> 2000: B_KLBSL_PNMN     S     S  <NA>  <NA> if (require(\"data.table\")) {   dt[, c(carbapenems(), aminoglycosides())] } #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #>         IPM   MEM   GEN   TOB   AMK   KAN #>       <sir> <sir> <sir> <sir> <sir> <sir> #>    1:  <NA>  <NA>  <NA>  <NA>  <NA>  <NA> #>    2:  <NA>  <NA>  <NA>  <NA>  <NA>  <NA> #>    3:  <NA>  <NA>  <NA>  <NA>  <NA>  <NA> #>    4:  <NA>  <NA>  <NA>  <NA>  <NA>  <NA> #>    5:  <NA>  <NA>  <NA>  <NA>  <NA>  <NA> #>   ---                                     #> 1996:  <NA>  <NA>     R     R     R     R #> 1997:     S     S     S     S     S  <NA> #> 1998:     S     S     S  <NA>  <NA>  <NA> #> 1999:     S     S     S     S  <NA>  <NA> #> 2000:     S     S     S     S  <NA>  <NA>  # row filters are also supported: if (require(\"data.table\")) {   dt[any(carbapenems() == \"S\"), ] } #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #>            date patient   age gender       ward           mo   PEN   OXA   FLC #>          <Date>  <char> <num> <char>     <char>         <mo> <sir> <sir> <sir> #>   1: 2002-01-19  738003    71      M   Clinical B_ESCHR_COLI     R  <NA>  <NA> #>   2: 2002-01-19  738003    71      M   Clinical B_ESCHR_COLI     R  <NA>  <NA> #>   3: 2002-01-22  F35553    50      M        ICU B_PROTS_MRBL     R  <NA>  <NA> #>   4: 2002-01-22  F35553    50      M        ICU B_PROTS_MRBL     R  <NA>  <NA> #>   5: 2002-02-05  067927    45      F        ICU B_SERRT_MRCS     R  <NA>  <NA> #>  ---                                                                           #> 905: 2005-04-12  D71461    70      M        ICU B_ESCHR_COLI     R  <NA>  <NA> #> 906: 2009-11-12  650870    69      F Outpatient B_ESCHR_COLI     R  <NA>  <NA> #> 907: 2012-06-14  8CBCF2    41      F   Clinical B_STPHY_CONS     R     S     S #> 908: 2012-10-11  175532    78      M   Clinical B_ESCHR_COLI     R  <NA>  <NA> #> 909: 2013-11-23  A97263    77      M   Clinical B_KLBSL_PNMN     R  <NA>  <NA> #>        AMX   AMC   AMP   TZP   CZO   FEP   CXM   FOX   CTX   CAZ   CRO   GEN #>      <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> #>   1:  <NA>     I  <NA>  <NA>  <NA>  <NA>     S  <NA>     S  <NA>     S  <NA> #>   2:  <NA>     I  <NA>  <NA>  <NA>  <NA>     S  <NA>     S  <NA>     S  <NA> #>   3:  <NA>     I  <NA>  <NA>  <NA>  <NA>     S  <NA>     S     S     S  <NA> #>   4:  <NA>     I  <NA>  <NA>  <NA>  <NA>     S  <NA>     S     S     S  <NA> #>   5:     R     R     R  <NA>     R  <NA>     R     R  <NA>  <NA>  <NA>  <NA> #>  ---                                                                         #> 905:     S     S     S     S  <NA>     S     S     S     S     S     S     S #> 906:     S     S     S     S     S     S     S     S     S     S     S     S #> 907:  <NA>     S  <NA>  <NA>     S     S     S     S     S     R     S     S #> 908:     R     S     R     S  <NA>     S     R     R     S     S     S     S #> 909:     R     S     R     S  <NA>     S     S     S     S     S     S     S #>        TOB   AMK   KAN   TMP   SXT   NIT   FOS   LNZ   CIP   MFX   VAN   TEC #>      <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> #>   1:     S  <NA>  <NA>     S     S  <NA>  <NA>     R  <NA>  <NA>     R     R #>   2:     S  <NA>  <NA>     S     S  <NA>  <NA>     R  <NA>  <NA>     R     R #>   3:  <NA>  <NA>  <NA>     S     S     R  <NA>     R     S  <NA>     R     R #>   4:  <NA>  <NA>  <NA>     S     S     R  <NA>     R     S  <NA>     R     R #>   5:  <NA>  <NA>  <NA>     S     S     R  <NA>     R     S  <NA>     R     R #>  ---                                                                         #> 905:     S     S  <NA>  <NA>     S     S  <NA>     R     S  <NA>     R     R #> 906:     S     S  <NA>     S     S     S  <NA>     R     S  <NA>     R     R #> 907:  <NA>  <NA>  <NA>     S     S  <NA>  <NA>  <NA>     S  <NA>     S  <NA> #> 908:     S  <NA>  <NA>     R     R     R  <NA>     R     R     R     R     R #> 909:     S  <NA>  <NA>     S     S     S  <NA>     R     S  <NA>     R     R #>        TCY   TGC   DOX   ERY   CLI   AZM   IPM   MEM   MTR   CHL   COL   MUP #>      <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> <sir> #>   1:  <NA>  <NA>  <NA>     R     R     R     S  <NA>  <NA>  <NA>  <NA>  <NA> #>   2:  <NA>  <NA>  <NA>     R     R     R     S  <NA>  <NA>  <NA>  <NA>  <NA> #>   3:     R     R     R     R     R     R     S  <NA>  <NA>  <NA>     R  <NA> #>   4:     R     R     R     R     R     R     S  <NA>  <NA>  <NA>     R  <NA> #>   5:     R     R     R     R     R     R     S  <NA>  <NA>  <NA>     R  <NA> #>  ---                                                                         #> 905:  <NA>  <NA>  <NA>     R     R     R     S     S  <NA>  <NA>  <NA>  <NA> #> 906:  <NA>  <NA>  <NA>     R     R     R     S     S  <NA>  <NA>  <NA>  <NA> #> 907:  <NA>  <NA>  <NA>     S     S     S     S     S  <NA>  <NA>     R  <NA> #> 908:  <NA>  <NA>  <NA>     R     R     R     S     S  <NA>  <NA>     S  <NA> #> 909:  <NA>  <NA>  <NA>     R     R     R     S     S  <NA>  <NA>     S  <NA> #>        RIF #>      <sir> #>   1:     R #>   2:     R #>   3:     R #>   4:     R #>   5:     R #>  ---       #> 905:     R #> 906:     R #> 907:  <NA> #> 908:     R #> 909:     R if (require(\"data.table\")) {   dt[any(carbapenems() == \"S\"), penicillins(), with = FALSE] } #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> ℹ For penicillins() using columns 'PEN' (benzylpenicillin), 'OXA' #>   (oxacillin), 'FLC' (flucloxacillin), 'AMX' (amoxicillin), 'AMC' #>   (amoxicillin/clavulanic acid), 'AMP' (ampicillin), and 'TZP' #>   (piperacillin/tazobactam) #>        PEN   OXA   FLC   AMX   AMC   AMP   TZP #>      <sir> <sir> <sir> <sir> <sir> <sir> <sir> #>   1:     R  <NA>  <NA>  <NA>     I  <NA>  <NA> #>   2:     R  <NA>  <NA>  <NA>     I  <NA>  <NA> #>   3:     R  <NA>  <NA>  <NA>     I  <NA>  <NA> #>   4:     R  <NA>  <NA>  <NA>     I  <NA>  <NA> #>   5:     R  <NA>  <NA>     R     R     R  <NA> #>  ---                                           #> 905:     R  <NA>  <NA>     S     S     S     S #> 906:     R  <NA>  <NA>     S     S     S     S #> 907:     R     S     S  <NA>     S  <NA>  <NA> #> 908:     R  <NA>  <NA>     R     S     R     S #> 909:     R  <NA>  <NA>     R     S     R     S # }"},{"path":"https://msberends.github.io/AMR/reference/antibiotics.html","id":null,"dir":"Reference","previous_headings":"","what":"Data Sets with 605 Antimicrobial Drugs — antibiotics","title":"Data Sets with 605 Antimicrobial Drugs — antibiotics","text":"Two data sets containing antibiotics/antimycotics antivirals. Use .ab() one ab_* functions retrieve values antibiotics data set. Three identifiers included data set: antibiotic ID (ab, primarily used package) defined WHONET/EARS-Net, ATC code (atc) defined , Compound ID (cid) found PubChem. properties data set derived one codes. Note drugs multiple ATC codes.","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotics.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Data Sets with 605 Antimicrobial Drugs — antibiotics","text":"","code":"antibiotics  antivirals"},{"path":"https://msberends.github.io/AMR/reference/antibiotics.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data Sets with 605 Antimicrobial Drugs — antibiotics","text":"object class tbl_df (inherits tbl, data.frame) 120 rows 11 columns.","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotics.html","id":"for-the-antibiotics-data-set-a-tibble-with-observations-and-variables-","dir":"Reference","previous_headings":"","what":"For the antibiotics data set: a tibble with 485 observations and 14 variables:","title":"Data Sets with 605 Antimicrobial Drugs — antibiotics","text":"ab Antibiotic ID used package (AMC), using official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes available. unique identifier. cid Compound ID found PubChem. unique identifier. name Official name used WHONET/EARS-Net . unique identifier. group short concise group name, based WHONET WHOCC definitions atc ATC codes (Anatomical Therapeutic Chemical) defined WHOCC, like J01CR02 atc_group1 Official pharmacological subgroup (3rd level ATC code) defined WHOCC, like \"Macrolides, lincosamides streptogramins\" atc_group2 Official chemical subgroup (4th level ATC code) defined WHOCC, like \"Macrolides\" abbr List abbreviations used many countries, also antibiotic susceptibility testing (AST) synonyms Synonyms (often trade names) drug, found PubChem based compound ID oral_ddd Defined Daily Dose (DDD), oral treatment, currently available 179 drugs oral_units Units oral_ddd iv_ddd Defined Daily Dose (DDD), parenteral (intravenous) treatment, currently available 153 drugs iv_units Units iv_ddd loinc codes associated name antimicrobial drug Logical Observation Identifiers Names Codes (LOINC), Version 2.76 (18 September, 2023). Use ab_loinc() retrieve quickly, see ab_property().","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotics.html","id":"for-the-antivirals-data-set-a-tibble-with-observations-and-variables-","dir":"Reference","previous_headings":"","what":"For the antivirals data set: a tibble with 120 observations and 11 variables:","title":"Data Sets with 605 Antimicrobial Drugs — antibiotics","text":"av Antiviral ID used package (ACI), using official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes available. unique identifier. Combinations codes contain + indicate , ATA+COBI atazanavir/cobicistat. name Official name used WHONET/EARS-Net . unique identifier. atc ATC codes (Anatomical Therapeutic Chemical) defined WHOCC cid Compound ID found PubChem. unique identifier. atc_group Official pharmacological subgroup (3rd level ATC code) defined WHOCC synonyms Synonyms (often trade names) drug, found PubChem based compound ID oral_ddd Defined Daily Dose (DDD), oral treatment oral_units Units oral_ddd iv_ddd Defined Daily Dose (DDD), parenteral treatment iv_units Units iv_ddd loinc codes associated name antiviral drug Logical Observation Identifiers Names Codes (LOINC), Version 2.76 (18 September, 2023). Use av_loinc() retrieve quickly, see av_property().","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotics.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data Sets with 605 Antimicrobial Drugs — antibiotics","text":"World Health Organization () Collaborating Centre Drug Statistics Methodology (WHOCC): https://atcddd.fhi./atc_ddd_index/ Logical Observation Identifiers Names Codes (LOINC), Version 2.76 (18 September, 2023). Accessed https://loinc.org October 19th, 2023. European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotics.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Data Sets with 605 Antimicrobial Drugs — antibiotics","text":"Properties based ATC code available ATC available. properties : atc_group1, atc_group2, oral_ddd, oral_units, iv_ddd iv_units. Synonyms (.e. trade names) derived PubChem Compound ID (column cid) consequently available CID available.","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotics.html","id":"direct-download","dir":"Reference","previous_headings":"","what":"Direct download","title":"Data Sets with 605 Antimicrobial Drugs — antibiotics","text":"Like data sets package, data sets publicly available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":"https://msberends.github.io/AMR/reference/antibiotics.html","id":"whocc","dir":"Reference","previous_headings":"","what":"WHOCC","title":"Data Sets with 605 Antimicrobial Drugs — antibiotics","text":"package contains ~550 antibiotic, antimycotic antiviral drugs Anatomical Therapeutic Chemical (ATC) codes, ATC groups Defined Daily Dose (DDD) World Health Organization Collaborating Centre Drug Statistics Methodology (WHOCC, https://atcddd.fhi.) Pharmaceuticals Community Register European Commission (https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm). become gold standard international drug utilisation monitoring research. WHOCC located Oslo Norwegian Institute Public Health funded Norwegian government. European Commission executive European Union promotes general interest. NOTE: WHOCC copyright allow use commercial purposes, unlike info package. See https://atcddd.fhi./copyright_disclaimer/.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/antibiotics.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Data Sets with 605 Antimicrobial Drugs — antibiotics","text":"","code":"antibiotics #> # A tibble: 485 × 14 #>    ab        cid name   group atc   atc_group1 atc_group2 abbreviations synonyms #>    <ab>    <dbl> <chr>  <chr> <lis> <chr>      <chr>      <list>        <named > #>  1 AMA      4649 4-ami… Anti… <chr> Drugs for… Aminosali… <chr [1]>     <chr>    #>  2 ACM   6450012 Acety… Macr… <chr> NA         NA         <chr [1]>     <chr>    #>  3 ASP  49787020 Acety… Macr… <chr> NA         NA         <chr [1]>     <chr>    #>  4 ALS      8954 Aldes… Othe… <chr> Drugs for… Drugs for… <chr [1]>     <chr>    #>  5 AMK     37768 Amika… Amin… <chr> Aminoglyc… Other ami… <chr [5]>     <chr>    #>  6 AKF        NA Amika… Amin… <chr> NA         NA         <chr [1]>     <chr>    #>  7 AMO     54260 Amoro… Anti… <chr> Antifunga… Other ant… <chr [1]>     <chr>    #>  8 AMX     33613 Amoxi… Beta… <chr> Beta-lact… Penicilli… <chr [3]>     <chr>    #>  9 AMC  23665637 Amoxi… Beta… <chr> Beta-lact… Combinati… <chr [5]>     <chr>    #> 10 AXS    465441 Amoxi… Beta… <chr> NA         NA         <chr [1]>     <chr>    #> # ℹ 475 more rows #> # ℹ 5 more variables: oral_ddd <dbl>, oral_units <chr>, iv_ddd <dbl>, #> #   iv_units <chr>, loinc <list> antivirals #> # A tibble: 120 × 11 #>    av       name      atc      cid atc_group synonyms oral_ddd oral_units iv_ddd #>    <av>     <chr>     <chr>  <dbl> <chr>     <list>      <dbl> <chr>       <dbl> #>  1 ABA      Abacavir  J05A… 4.41e5 Nucleosi… <chr>         0.6 g              NA #>  2 ACI      Aciclovir J05A… 1.35e8 Nucleosi… <chr>         4   g               4 #>  3 ADD      Adefovir… J05A… 6.09e4 Nucleosi… <chr>        10   mg             NA #>  4 AME      Amenamev… J05A… 1.14e7 Other an… <chr>         0.4 g              NA #>  5 AMP      Amprenav… J05A… 6.50e4 Protease… <chr>         1.2 g              NA #>  6 ASU      Asunapre… J05A… 1.61e7 Antivira… <chr>         0.2 g              NA #>  7 ATA      Atazanav… J05A… 1.48e5 Protease… <chr>         0.3 g              NA #>  8 ATA+COBI Atazanav… J05A… 8.66e7 Antivira… <chr>        NA   NA             NA #>  9 ATA+RIT  Atazanav… J05A… 2.51e7 Antivira… <chr>         0.3 g              NA #> 10 BAM      Baloxavi… J05A… 1.24e8 Other an… <chr>        40   mg             NA #> # ℹ 110 more rows #> # ℹ 2 more variables: iv_units <chr>, loinc <list>"},{"path":"https://msberends.github.io/AMR/reference/as.ab.html","id":null,"dir":"Reference","previous_headings":"","what":"Transform Input to an Antibiotic ID — as.ab","title":"Transform Input to an Antibiotic ID — as.ab","text":"Use function determine antibiotic drug code one antibiotics. data set antibiotics searched abbreviations, official names synonyms (brand names).","code":""},{"path":"https://msberends.github.io/AMR/reference/as.ab.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transform Input to an Antibiotic ID — as.ab","text":"","code":"as.ab(x, flag_multiple_results = TRUE, info = interactive(), ...)  is.ab(x)"},{"path":"https://msberends.github.io/AMR/reference/as.ab.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transform Input to an Antibiotic ID — as.ab","text":"x character vector determine antibiotic ID flag_multiple_results logical indicate whether note printed console probably one antibiotic drug code name can retrieved single input value. info logical indicate whether progress bar printed - default TRUE interactive mode ... arguments passed internal functions","code":""},{"path":"https://msberends.github.io/AMR/reference/as.ab.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transform Input to an Antibiotic ID — as.ab","text":"character vector additional class ab","code":""},{"path":"https://msberends.github.io/AMR/reference/as.ab.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Transform Input to an Antibiotic ID — as.ab","text":"entries antibiotics data set three different identifiers: human readable EARS-Net code (column ab, used ECDC WHONET), ATC code (column atc, used ), CID code (column cid, Compound ID, used PubChem). data set contains 5,000 official brand names many different countries, found PubChem. drugs contain multiple ATC codes. properties searched user input. .ab() can correct different forms misspelling: Wrong spelling drug names (\"tobramicin\" \"gentamycin\"), corrects audible similarities f/ph, x/ks, c/z/s, t/th, etc. many vowels consonants Switching two characters (\"mreopenem\", often case clinical data, doctors typed fast) Digitalised paper records, leaving artefacts like 0/o/O (zero O's), B/8, n/r, etc. Use ab_* functions get properties based returned antibiotic ID, see Examples. Note: .ab() ab_* functions may use long regular expression match brand names antimicrobial drugs. may fail systems. can add manual codes considered .ab() ab_* functions, see add_custom_antimicrobials().","code":""},{"path":"https://msberends.github.io/AMR/reference/as.ab.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Transform Input to an Antibiotic ID — as.ab","text":"World Health Organization () Collaborating Centre Drug Statistics Methodology: https://atcddd.fhi./atc_ddd_index/ European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm","code":""},{"path":"https://msberends.github.io/AMR/reference/as.ab.html","id":"whocc","dir":"Reference","previous_headings":"","what":"WHOCC","title":"Transform Input to an Antibiotic ID — as.ab","text":"package contains ~550 antibiotic, antimycotic antiviral drugs Anatomical Therapeutic Chemical (ATC) codes, ATC groups Defined Daily Dose (DDD) World Health Organization Collaborating Centre Drug Statistics Methodology (WHOCC, https://atcddd.fhi.) Pharmaceuticals Community Register European Commission (https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm). become gold standard international drug utilisation monitoring research. WHOCC located Oslo Norwegian Institute Public Health funded Norwegian government. European Commission executive European Union promotes general interest. NOTE: WHOCC copyright allow use commercial purposes, unlike info package. See https://atcddd.fhi./copyright_disclaimer/.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.ab.html","id":"reference-data-publicly-available","dir":"Reference","previous_headings":"","what":"Reference Data Publicly Available","title":"Transform Input to an Antibiotic ID — as.ab","text":"data sets AMR package (microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) publicly freely available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. also provide tab-separated plain text files machine-readable suitable input software program, laboratory information systems. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/as.ab.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Transform Input to an Antibiotic ID — as.ab","text":"","code":"# these examples all return \"ERY\", the ID of erythromycin: as.ab(\"J01FA01\") #> Class 'ab' #> [1] ERY as.ab(\"J 01 FA 01\") #> Class 'ab' #> [1] ERY as.ab(\"Erythromycin\") #> Class 'ab' #> [1] ERY as.ab(\"eryt\") #> Class 'ab' #> [1] ERY as.ab(\"   eryt 123\") #> Class 'ab' #> [1] ERY as.ab(\"ERYT\") #> Class 'ab' #> [1] ERY as.ab(\"ERY\") #> Class 'ab' #> [1] ERY as.ab(\"eritromicine\") # spelled wrong, yet works #> Class 'ab' #> [1] ERY as.ab(\"Erythrocin\") # trade name #> Class 'ab' #> [1] ERY as.ab(\"Romycin\") # trade name #> Class 'ab' #> [1] ERY  # spelling from different languages and dyslexia are no problem ab_atc(\"ceftriaxon\") #> [1] \"J01DD04\" ab_atc(\"cephtriaxone\") # small spelling error #> [1] \"J01DD04\" ab_atc(\"cephthriaxone\") # or a bit more severe #> [1] \"J01DD04\" ab_atc(\"seephthriaaksone\") # and even this works #> [1] \"J01DD04\"  # use ab_* functions to get a specific properties (see ?ab_property); # they use as.ab() internally: ab_name(\"J01FA01\") #> [1] \"Erythromycin\" ab_name(\"eryt\") #> [1] \"Erythromycin\"  # \\donttest{ if (require(\"dplyr\")) {   # you can quickly rename 'sir' columns using set_ab_names() with dplyr:   example_isolates %>%     set_ab_names(where(is.sir), property = \"atc\") } #> # A tibble: 2,000 × 46 #>    date       patient   age gender ward     mo           J01CE01 J01CF04 J01CF05 #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir>   <sir>   <sir>   #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R       NA      NA      #>  2 2002-01-03 A77334     65 F      Clinical B_ESCHR_COLI R       NA      NA      #>  3 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R       NA      R       #>  4 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R       NA      R       #>  5 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R       NA      R       #>  6 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R       NA      R       #>  7 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R       NA      S       #>  8 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R       NA      S       #>  9 2002-01-16 067927     45 F      ICU      B_STPHY_EPDR R       NA      R       #> 10 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R       NA      S       #> # ℹ 1,990 more rows #> # ℹ 37 more variables: J01CA04 <sir>, J01CR02 <sir>, J01CA01 <sir>, #> #   J01CR05 <sir>, J01DB04 <sir>, J01DE01 <sir>, J01DC02 <sir>, J01DC01 <sir>, #> #   J01DD01 <sir>, J01DD02 <sir>, J01DD04 <sir>, J01GB03 <sir>, J01GB01 <sir>, #> #   J01GB06 <sir>, J01GB04 <sir>, J01EA01 <sir>, J01EE01 <sir>, J01XE01 <sir>, #> #   J01XX01 <sir>, J01XX08 <sir>, J01MA02 <sir>, J01MA14 <sir>, J01XA01 <sir>, #> #   J01XA02 <sir>, J01AA07 <sir>, J01AA12 <sir>, J01AA02 <sir>, … # }"},{"path":"https://msberends.github.io/AMR/reference/as.av.html","id":null,"dir":"Reference","previous_headings":"","what":"Transform Input to an Antiviral Drug ID — as.av","title":"Transform Input to an Antiviral Drug ID — as.av","text":"Use function determine antiviral drug code one antiviral drugs. data set antivirals searched abbreviations, official names synonyms (brand names).","code":""},{"path":"https://msberends.github.io/AMR/reference/as.av.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transform Input to an Antiviral Drug ID — as.av","text":"","code":"as.av(x, flag_multiple_results = TRUE, info = interactive(), ...)  is.av(x)"},{"path":"https://msberends.github.io/AMR/reference/as.av.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transform Input to an Antiviral Drug ID — as.av","text":"x character vector determine antiviral drug ID flag_multiple_results logical indicate whether note printed console probably one antiviral drug code name can retrieved single input value. info logical indicate whether progress bar printed - default TRUE interactive mode ... arguments passed internal functions","code":""},{"path":"https://msberends.github.io/AMR/reference/as.av.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transform Input to an Antiviral Drug ID — as.av","text":"character vector additional class ab","code":""},{"path":"https://msberends.github.io/AMR/reference/as.av.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Transform Input to an Antiviral Drug ID — as.av","text":"entries antivirals data set three different identifiers: human readable EARS-Net code (column ab, used ECDC WHONET), ATC code (column atc, used ), CID code (column cid, Compound ID, used PubChem). data set contains 5,000 official brand names many different countries, found PubChem. drugs contain multiple ATC codes. properties searched user input. .av() can correct different forms misspelling: Wrong spelling drug names (\"acyclovir\"), corrects audible similarities f/ph, x/ks, c/z/s, t/th, etc. many vowels consonants Switching two characters (\"aycclovir\", often case clinical data, doctors typed fast) Digitalised paper records, leaving artefacts like 0/o/O (zero O's), B/8, n/r, etc. Use av_* functions get properties based returned antiviral drug ID, see Examples. Note: .av() av_* functions may use long regular expression match brand names antimicrobial drugs. may fail systems.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.av.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Transform Input to an Antiviral Drug ID — as.av","text":"World Health Organization () Collaborating Centre Drug Statistics Methodology: https://atcddd.fhi./atc_ddd_index/ European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm","code":""},{"path":"https://msberends.github.io/AMR/reference/as.av.html","id":"whocc","dir":"Reference","previous_headings":"","what":"WHOCC","title":"Transform Input to an Antiviral Drug ID — as.av","text":"package contains ~550 antibiotic, antimycotic antiviral drugs Anatomical Therapeutic Chemical (ATC) codes, ATC groups Defined Daily Dose (DDD) World Health Organization Collaborating Centre Drug Statistics Methodology (WHOCC, https://atcddd.fhi.) Pharmaceuticals Community Register European Commission (https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm). become gold standard international drug utilisation monitoring research. WHOCC located Oslo Norwegian Institute Public Health funded Norwegian government. European Commission executive European Union promotes general interest. NOTE: WHOCC copyright allow use commercial purposes, unlike info package. See https://atcddd.fhi./copyright_disclaimer/.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.av.html","id":"reference-data-publicly-available","dir":"Reference","previous_headings":"","what":"Reference Data Publicly Available","title":"Transform Input to an Antiviral Drug ID — as.av","text":"data sets AMR package (microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) publicly freely available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. also provide tab-separated plain text files machine-readable suitable input software program, laboratory information systems. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/as.av.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Transform Input to an Antiviral Drug ID — as.av","text":"","code":"# these examples all return \"ACI\", the ID of aciclovir: as.av(\"J05AB01\") #> Class 'av' #> [1] ACI as.av(\"J 05 AB 01\") #> Class 'av' #> [1] ACI as.av(\"Aciclovir\") #> Class 'av' #> [1] ACI as.av(\"aciclo\") #> Class 'av' #> [1] ACI as.av(\"   aciclo 123\") #> Class 'av' #> [1] ACI as.av(\"ACICL\") #> Class 'av' #> [1] ACI as.av(\"ACI\") #> Class 'av' #> [1] ACI as.av(\"Virorax\") # trade name #> Class 'av' #> [1] ACI as.av(\"Zovirax\") # trade name #> Class 'av' #> [1] ACI  as.av(\"acyklofir\") # severe spelling error, yet works #> Class 'av' #> [1] ACI  # use av_* functions to get a specific properties (see ?av_property); # they use as.av() internally: av_name(\"J05AB01\") #> [1] \"Aciclovir\" av_name(\"acicl\") #> [1] \"Aciclovir\""},{"path":"https://msberends.github.io/AMR/reference/as.disk.html","id":null,"dir":"Reference","previous_headings":"","what":"Transform Input to Disk Diffusion Diameters — as.disk","title":"Transform Input to Disk Diffusion Diameters — as.disk","text":"transforms vector new class disk, disk diffusion growth zone size (around antibiotic disk) millimetres 6 50.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.disk.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transform Input to Disk Diffusion Diameters — as.disk","text":"","code":"as.disk(x, na.rm = FALSE)  NA_disk_  is.disk(x)"},{"path":"https://msberends.github.io/AMR/reference/as.disk.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Transform Input to Disk Diffusion Diameters — as.disk","text":"object class disk (inherits integer) length 1.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.disk.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transform Input to Disk Diffusion Diameters — as.disk","text":"x vector na.rm logical indicating whether missing values removed","code":""},{"path":"https://msberends.github.io/AMR/reference/as.disk.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transform Input to Disk Diffusion Diameters — as.disk","text":"integer additional class disk","code":""},{"path":"https://msberends.github.io/AMR/reference/as.disk.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Transform Input to Disk Diffusion Diameters — as.disk","text":"Interpret disk values SIR values .sir(). supports guidelines EUCAST CLSI. Disk diffusion growth zone sizes must 6 50 millimetres. Values higher 50 lower 100 maximised 50. others input values outside 6-50 range return NA. NA_disk_ missing value new disk class.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/as.disk.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Transform Input to Disk Diffusion Diameters — as.disk","text":"","code":"# transform existing disk zones to the `disk` class (using base R) df <- data.frame(   microorganism = \"Escherichia coli\",   AMP = 20,   CIP = 14,   GEN = 18,   TOB = 16 ) df[, 2:5] <- lapply(df[, 2:5], as.disk) str(df) #> 'data.frame':\t1 obs. of  5 variables: #>  $ microorganism: chr \"Escherichia coli\" #>  $ AMP          : 'disk' int 20 #>  $ CIP          : 'disk' int 14 #>  $ GEN          : 'disk' int 18 #>  $ TOB          : 'disk' int 16  # \\donttest{ # transforming is easier with dplyr: if (require(\"dplyr\")) {   df %>% mutate(across(AMP:TOB, as.disk)) } #>      microorganism AMP CIP GEN TOB #> 1 Escherichia coli  20  14  18  16 # }  # interpret disk values, see ?as.sir as.sir(   x = as.disk(18),   mo = \"Strep pneu\", # `mo` will be coerced with as.mo()   ab = \"ampicillin\", # and `ab` with as.ab()   guideline = \"EUCAST\" ) #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting disk diffusion zones: 'ampicillin' (AMP), EUCAST 2024... #>  OK  #> Class 'sir' #> [1] R  # interpret whole data set, pretend to be all from urinary tract infections: as.sir(df, uti = TRUE) #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting disk diffusion zones: column 'AMP' (ampicillin), EUCAST #> 2024... #>  OK  #> Interpreting disk diffusion zones: column 'CIP' (ciprofloxacin), EUCAST #> 2024... #>  OK  #> Interpreting disk diffusion zones: column 'GEN' (gentamicin), EUCAST #> 2024... #>  OK  #> Interpreting disk diffusion zones: column 'TOB' (tobramycin), EUCAST #> 2024... #>  OK  #>      microorganism AMP  CIP GEN TOB #> 1 Escherichia coli   S <NA>   S   S"},{"path":"https://msberends.github.io/AMR/reference/as.mic.html","id":null,"dir":"Reference","previous_headings":"","what":"Transform Input to Minimum Inhibitory Concentrations (MIC) — as.mic","title":"Transform Input to Minimum Inhibitory Concentrations (MIC) — as.mic","text":"transforms vectors new class mic, treats input decimal numbers, maintaining operators (\">=\") allowing valid MIC values known field (medical) microbiology.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.mic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transform Input to Minimum Inhibitory Concentrations (MIC) — as.mic","text":"","code":"as.mic(x, na.rm = FALSE, keep_operators = \"all\")  is.mic(x)  NA_mic_  rescale_mic(x, mic_range, keep_operators = \"edges\", as.mic = TRUE)  # S3 method for class 'mic' droplevels(x, as.mic = FALSE, ...)"},{"path":"https://msberends.github.io/AMR/reference/as.mic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transform Input to Minimum Inhibitory Concentrations (MIC) — as.mic","text":"x character numeric vector na.rm logical indicating whether missing values removed keep_operators character specifying handle operators (> <=) input. Accepts one three values: \"\" (TRUE) keep operators, \"none\" (FALSE) remove operators, \"edges\" keep operators ends range. mic_range manual range limit MIC values, e.g., mic_range = c(0.001, 32). Use NA set limit one side, e.g., mic_range = c(NA, 32). .mic logical indicate whether mic class kept - default FALSE ... arguments passed methods","code":""},{"path":"https://msberends.github.io/AMR/reference/as.mic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transform Input to Minimum Inhibitory Concentrations (MIC) — as.mic","text":"Ordered factor additional class mic, mathematical operations acts numeric vector. Bear mind outcome mathematical operation MICs return numeric value.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.mic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Transform Input to Minimum Inhibitory Concentrations (MIC) — as.mic","text":"interpret MIC values SIR values, use .sir() MIC values. supports guidelines EUCAST (2011-2024) CLSI (2011-2024). class MIC values quite special data type: formally ordered factor valid MIC values factor levels (make sure valid MIC values retained), mathematical operation acts decimal numbers:   makes possible maintain operators often come MIC values, \">=\" \"<=\", even filtering using numeric values data analysis, e.g.:   -called group generic functions implemented MIC class (!, !=, <, >=, exp(), log2()). functions stats package also implemented (quantile(), median(), fivenum()). Since sd() var() non-generic functions, extended. Use mad() alternative, use e.g. sd(.numeric(x)) x vector MIC values. Using .double() .numeric() MIC values remove operators return numeric vector. use .integer() MIC values R convention factors, return index factor levels (often useless regular users). Use droplevels() drop unused levels. default, return plain factor. Use droplevels(..., .mic = TRUE) maintain mic class. rescale_mic(), existing MIC ranges can limited defined range MIC values. can useful better compare MIC distributions. ggplot2, use one scale_*_mic() functions plot MIC values. allows custom MIC ranges plot intermediate log2 levels missing MIC values. NA_mic_ missing value new mic class, analogous e.g. base R's NA_character_.","code":"x <- random_mic(10) x #> Class 'mic' #>  [1] 16     1      8      8      64     >=128  0.0625 32     32     16  is.factor(x) #> [1] TRUE  x[1] * 2 #> [1] 32  median(x) #> [1] 26 x[x > 4] #> Class 'mic' #> [1] 16    8     8     64    >=128 32    32    16  df <- data.frame(x, hospital = \"A\") subset(df, x > 4) # or with dplyr: df %>% filter(x > 4) #>        x hospital #> 1     16        A #> 5     64        A #> 6  >=128        A #> 8     32        A #> 9     32        A #> 10    16        A"},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/as.mic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Transform Input to Minimum Inhibitory Concentrations (MIC) — as.mic","text":"","code":"mic_data <- as.mic(c(\">=32\", \"1.0\", \"1\", \"1.00\", 8, \"<=0.128\", \"8\", \"16\", \"16\")) mic_data #> Class 'mic' #> [1] >=32    1       1       1       8       <=0.128 8       16      16      is.mic(mic_data) #> [1] TRUE  # this can also coerce combined MIC/SIR values: as.mic(\"<=0.002; S\") #> Class 'mic' #> [1] <=0.002  # mathematical processing treats MICs as numeric values fivenum(mic_data) #> [1]  0.128  1.000  8.000 16.000 32.000 quantile(mic_data) #>     0%    25%    50%    75%   100%  #>  0.128  1.000  8.000 16.000 32.000  all(mic_data < 512) #> [1] TRUE  # rescale MICs using rescale_mic() rescale_mic(mic_data, mic_range = c(4, 16)) #> Class 'mic' #> [1] >=16 <=4  <=4  <=4  8    <=4  8    >=16 >=16  # interpret MIC values as.sir(   x = as.mic(2),   mo = as.mo(\"Streptococcus pneumoniae\"),   ab = \"AMX\",   guideline = \"EUCAST\" ) #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'AMX' (amoxicillin), EUCAST 2024... #>  NOTE  #>   • Multiple breakpoints available for amoxicillin (AMX) in Streptococcus pneumoniae - assuming body site 'Meningitis'. #> Class 'sir' #> [1] R as.sir(   x = as.mic(c(0.01, 2, 4, 8)),   mo = as.mo(\"Streptococcus pneumoniae\"),   ab = \"AMX\",   guideline = \"EUCAST\" ) #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'AMX' (amoxicillin), EUCAST 2024... #>  NOTE  #>   • Multiple breakpoints available for amoxicillin (AMX) in Streptococcus pneumoniae - assuming body site 'Meningitis'. #> Class 'sir' #> [1] S R R R  # plot MIC values, see ?plot plot(mic_data)  plot(mic_data, mo = \"E. coli\", ab = \"cipro\")   if (require(\"ggplot2\")) {   autoplot(mic_data, mo = \"E. coli\", ab = \"cipro\") }  if (require(\"ggplot2\")) {   autoplot(mic_data, mo = \"E. coli\", ab = \"cipro\", language = \"nl\") # Dutch }"},{"path":"https://msberends.github.io/AMR/reference/as.mo.html","id":null,"dir":"Reference","previous_headings":"","what":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","title":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","text":"Use function get valid microorganism code (mo) based arbitrary user input. Determination done using intelligent rules complete taxonomic tree kingdoms Animalia, Archaea, Bacteria, Chromista, Protozoa, microbial species kingdom Fungi (see Source). input can almost anything: full name (like \"Staphylococcus aureus\"), abbreviated name (\"S. aureus\"), abbreviation known field (\"MRSA\"), just genus. See Examples.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.mo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","text":"","code":"as.mo(   x,   Becker = FALSE,   Lancefield = FALSE,   minimum_matching_score = NULL,   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   reference_df = get_mo_source(),   ignore_pattern = getOption(\"AMR_ignore_pattern\", NULL),   cleaning_regex = getOption(\"AMR_cleaning_regex\", mo_cleaning_regex()),   language = get_AMR_locale(),   info = interactive(),   ... )  is.mo(x)  mo_uncertainties()  mo_renamed()  mo_failures()  mo_reset_session()  mo_cleaning_regex()"},{"path":"https://msberends.github.io/AMR/reference/as.mo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","text":"x character vector data.frame one two columns Becker logical indicate whether staphylococci categorised coagulase-negative staphylococci (\"CoNS\") coagulase-positive staphylococci (\"CoPS\") instead species, according Karsten Becker et al. (see Source). Please see Details full list staphylococcal species converted. excludes Staphylococcus aureus default, use Becker = \"\" also categorise S. aureus \"CoPS\". Lancefield logical indicate whether beta-haemolytic Streptococcus categorised Lancefield groups instead species, according Rebecca C. Lancefield (see Source). streptococci categorised first group, e.g. Streptococcus dysgalactiae group C, although officially also categorised groups G L. . Please see Details full list streptococcal species converted. excludes enterococci default (group D), use Lancefield = \"\" also categorise enterococci group D. minimum_matching_score numeric value set lower limit MO matching score. left blank, determined automatically based character length x, taxonomic kingdom human pathogenicity. keep_synonyms logical indicate old, previously valid taxonomic names must preserved corrected currently accepted names. default FALSE, return note old taxonomic names processed. default can set package option AMR_keep_synonyms, .e. options(AMR_keep_synonyms = TRUE) options(AMR_keep_synonyms = FALSE). reference_df data.frame used extra reference translating x valid mo. See set_mo_source() get_mo_source() automate usage codes (e.g. used analysis organisation). ignore_pattern Perl-compatible regular expression (case-insensitive) matches x must return NA. can convenient exclude known non-relevant input can also set package option AMR_ignore_pattern, e.g. options(AMR_ignore_pattern = \"(reported|contaminated flora)\"). cleaning_regex Perl-compatible regular expression (case-insensitive) clean input x. Every matched part x removed. default, outcome mo_cleaning_regex(), removes texts brackets texts \"species\" \"serovar\". default can set package option AMR_cleaning_regex. language language translate text like \"growth\", defaults system language (see get_AMR_locale()) info logical indicate progress bar printed 25 items coerced - default TRUE interactive mode ... arguments passed functions","code":""},{"path":"https://msberends.github.io/AMR/reference/as.mo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","text":"character vector additional class mo","code":""},{"path":"https://msberends.github.io/AMR/reference/as.mo.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","text":"microorganism (MO) code package (class: mo) human readable typically looks like examples:   Values coerced considered 'unknown' returned MO code UNKNOWN warning. Use mo_* functions get properties based returned code, see Examples. .mo() function uses novel matching score algorithm (see Matching Score Microorganisms ) match input available microbial taxonomy package. lead effect e.g. \"E. coli\" (microorganism highly prevalent humans) return microbial ID Escherichia coli Entamoeba coli (microorganism less prevalent humans), although latter alphabetically come first. Becker = TRUE, following 85 staphylococci converted coagulase-negative group: S. argensis, S. arlettae, S. auricularis, S. borealis, S. caeli, S. caledonicus, S. canis, S. capitis, S. capitis capitis, S. capitis urealyticus, S. capitis ureolyticus, S. caprae, S. carnosus, S. carnosus carnosus, S. carnosus utilis, S. casei, S. caseolyticus, S. chromogenes, S. cohnii, S. cohnii cohnii, S. cohnii urealyticum, S. cohnii urealyticus, S. condimenti, S. croceilyticus, S. debuckii, S. devriesei, S. durrellii, S. edaphicus, S. epidermidis, S. equorum, S. equorum equorum, S. equorum linens, S. felis, S. fleurettii, S. gallinarum, S. haemolyticus, S. hominis, S. hominis hominis, S. hominis novobiosepticus, S. jettensis, S. kloosii, S. lentus, S. lloydii, S. lugdunensis, S. massiliensis, S. microti, S. muscae, S. nepalensis, S. pasteuri, S. petrasii, S. petrasii croceilyticus, S. petrasii jettensis, S. petrasii petrasii, S. petrasii pragensis, S. pettenkoferi, S. piscifermentans, S. pragensis, S. pseudoxylosus, S. pulvereri, S. ratti, S. rostri, S. saccharolyticus, S. saprophyticus, S. saprophyticus bovis, S. saprophyticus saprophyticus, S. schleiferi, S. schleiferi schleiferi, S. sciuri, S. sciuri carnaticus, S. sciuri lentus, S. sciuri rodentium, S. sciuri sciuri, S. simulans, S. stepanovicii, S. succinus, S. succinus casei, S. succinus succinus, S. taiwanensis, S. urealyticus, S. ureilyticus, S. veratri, S. vitulinus, S. vitulus, S. warneri, S. xylosus. following 16 staphylococci converted coagulase-positive group: S. agnetis, S. argenteus, S. coagulans, S. cornubiensis, S. delphini, S. hyicus, S. hyicus chromogenes, S. hyicus hyicus, S. intermedius, S. lutrae, S. pseudintermedius, S. roterodami, S. schleiferi coagulans, S. schweitzeri, S. simiae, S. singaporensis. Lancefield = TRUE, following streptococci converted corresponding Lancefield group: S. agalactiae (Group B), S. anginosus anginosus (Group F), S. anginosus whileyi (Group F), S. anginosus (Group F), S. canis (Group G), S. dysgalactiae dysgalactiae (Group C), S. dysgalactiae equisimilis (Group C), S. dysgalactiae (Group C), S. equi equi (Group C), S. equi ruminatorum (Group C), S. equi zooepidemicus (Group C), S. equi (Group C), S. pyogenes (Group ), S. salivarius salivarius (Group K), S. salivarius thermophilus (Group K), S. salivarius (Group K), S. sanguinis (Group H).","code":"Code               Full name   ---------------    --------------------------------------   B_KLBSL            Klebsiella   B_KLBSL_PNMN       Klebsiella pneumoniae   B_KLBSL_PNMN_RHNS  Klebsiella pneumoniae rhinoscleromatis   |   |    |    |   |   |    |    |   |   |    |    \\---> subspecies, a 3-5 letter acronym   |   |    \\----> species, a 3-6 letter acronym   |   \\----> genus, a 4-8 letter acronym   \\----> taxonomic kingdom: A (Archaea), AN (Animalia), B (Bacteria),                             F (Fungi), PL (Plantae), P (Protozoa)"},{"path":"https://msberends.github.io/AMR/reference/as.mo.html","id":"coping-with-uncertain-results","dir":"Reference","previous_headings":"","what":"Coping with Uncertain Results","title":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","text":"Results non-exact taxonomic input based matching score. lowest allowed score can set minimum_matching_score argument. default determined based character length input, taxonomic kingdom human pathogenicity taxonomic outcome. values matched uncertainty, message shown suggest user evaluate results mo_uncertainties(), returns data.frame specifications. increase quality matching, cleaning_regex argument can used clean input (.e., x). must regular expression matches parts input removed input matched available microbial taxonomy. matched Perl-compatible case-insensitive. default value cleaning_regex outcome helper function mo_cleaning_regex(). three helper functions can run using .mo() function: Use mo_uncertainties() get data.frame prints pretty format taxonomic names guessed. output contains matching score matches (see Matching Score Microorganisms ). Use mo_failures() get character vector values coerced valid value. Use mo_renamed() get data.frame values coerced based old, previously accepted taxonomic names.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.mo.html","id":"microbial-prevalence-of-pathogens-in-humans","dir":"Reference","previous_headings":"","what":"Microbial Prevalence of Pathogens in Humans","title":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","text":"coercion rules consider prevalence microorganisms humans, available prevalence column microorganisms data set. grouping human pathogenic prevalence explained section Matching Score Microorganisms .","code":""},{"path":"https://msberends.github.io/AMR/reference/as.mo.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","text":"Berends MS et al. (2022). AMR: R Package Working Antimicrobial Resistance Data. Journal Statistical Software, 104(3), 1-31; doi:10.18637/jss.v104.i03 Becker K et al. (2014). Coagulase-Negative Staphylococci. Clin Microbiol Rev. 27(4): 870-926; doi:10.1128/CMR.00109-13 Becker K et al. (2019). Implications identifying recently defined members S. aureus complex, S. argenteus S. schweitzeri: position paper members ESCMID Study Group staphylococci Staphylococcal Diseases (ESGS). Clin Microbiol Infect; doi:10.1016/j.cmi.2019.02.028 Becker K et al. (2020). Emergence coagulase-negative staphylococci. Expert Rev Anti Infect Ther. 18(4):349-366; doi:10.1080/14787210.2020.1730813 Lancefield RC (1933). serological differentiation human groups hemolytic streptococci. J Exp Med. 57(4): 571-95; doi:10.1084/jem.57.4.571 Berends MS et al. (2022). Trends Occurrence Phenotypic Resistance Coagulase-Negative Staphylococci (CoNS) Found Human Blood Northern Netherlands 2013 2019/ Micro.rganisms 10(9), 1801; doi:10.3390/microorganisms10091801 Parte, AC et al. (2020). List Prokaryotic names Standing Nomenclature (LPSN) moves DSMZ. International Journal Systematic Evolutionary Microbiology, 70, 5607-5612; doi:10.1099/ijsem.0.004332 . Accessed https://lpsn.dsmz.de June 24th, 2024. GBIF Secretariat (2023). GBIF Backbone Taxonomy. Checklist dataset doi:10.15468/39omei . Accessed https://www.gbif.org June 24th, 2024. Reimer, LC et al. (2022). BacDive 2022: knowledge base standardized bacterial archaeal data. Nucleic Acids Res., 50(D1):D741-D74; doi:10.1093/nar/gkab961 . Accessed https://bacdive.dsmz.de July 16th, 2024. Public Health Information Network Vocabulary Access Distribution System (PHIN VADS). US Edition SNOMED CT 1 September 2020. Value Set Name 'Microorganism', OID 2.16.840.1.114222.4.11.1009 (v12). URL: https://phinvads.cdc.gov Bartlett et al. (2022). comprehensive list bacterial pathogens infecting humans Microbiology 168:001269; doi:10.1099/mic.0.001269","code":""},{"path":"https://msberends.github.io/AMR/reference/as.mo.html","id":"matching-score-for-microorganisms","dir":"Reference","previous_headings":"","what":"Matching Score for Microorganisms","title":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","text":"ambiguous user input .mo() mo_* functions, returned results chosen based matching score using mo_matching_score(). matching score \\(m\\), calculated :  : \\(x\\) user input; \\(n\\) taxonomic name (genus, species, subspecies); \\(l_n\\) length \\(n\\); \\(lev\\) Levenshtein distance function (counting insertion 1, deletion substitution 2) needed change \\(x\\) \\(n\\); \\(p_n\\) human pathogenic prevalence group \\(n\\), described ; \\(k_n\\) taxonomic kingdom \\(n\\), set Bacteria = 1, Fungi = 1.25, Protozoa = 1.5, Archaea = 2, others = 3. grouping human pathogenic prevalence \\(p\\) based recent work Bartlett et al. (2022, doi:10.1099/mic.0.001269 ) extensively studied medical-scientific literature categorise bacterial species groups: Established, taxonomic species infected least three persons three references. records prevalence = 1.0 microorganisms data set; Putative, taxonomic species fewer three known cases. records prevalence = 1.25 microorganisms data set. Furthermore, genus present established list also prevalence = 1.0 microorganisms data set; genus present putative list prevalence = 1.25 microorganisms data set; species subspecies genus present two aforementioned groups, prevalence = 1.5 microorganisms data set; non-bacterial genus, species subspecies genus present following list, prevalence = 1.25 microorganisms data set: Absidia, Acanthamoeba, Acremonium, Aedes, Alternaria, Amoeba, Ancylostoma, Angiostrongylus, Anisakis, Anopheles, Apophysomyces, Arthroderma, Aspergillus, Aureobasidium, Basidiobolus, Beauveria, Blastocystis, Blastomyces, Candida, Capillaria, Chaetomium, Chrysonilia, Chrysosporium, Cladophialophora, Cladosporium, Conidiobolus, Contracaecum, Cordylobia, Cryptococcus, Curvularia, Demodex, Dermatobia, Dientamoeba, Diphyllobothrium, Dirofilaria, Echinostoma, Entamoeba, Enterobius, Exophiala, Exserohilum, Fasciola, Fonsecaea, Fusarium, Geotrichum, Giardia, Haloarcula, Halobacterium, Halococcus, Hansenula, Hendersonula, Heterophyes, Histomonas, Histoplasma, Hymenolepis, Hypomyces, Hysterothylacium, Kloeckera, Kluyveromyces, Kodamaea, Leishmania, Lichtheimia, Lodderomyces, Lomentospora, Malassezia, Malbranchea, Metagonimus, Meyerozyma, Microsporidium, Microsporum, Millerozyma, Mortierella, Mucor, Mycocentrospora, Necator, Nectria, Ochroconis, Oesophagostomum, Oidiodendron, Opisthorchis, Paecilomyces, Pediculus, Penicillium, Phlebotomus, Phoma, Pichia, Piedraia, Pithomyces, Pityrosporum, Pneumocystis, Pseudallescheria, Pseudoscopulariopsis, Pseudoterranova, Pulex, Rhizomucor, Rhizopus, Rhodotorula, Saccharomyces, Saprochaete, Sarcoptes, Scedosporium, Scolecobasidium, Scopulariopsis, Scytalidium, Spirometra, Sporobolomyces, Sporotrichum, Stachybotrys, Strongyloides, Syngamus, Taenia, Talaromyces, Toxocara, Trichinella, Trichobilharzia, Trichoderma, Trichomonas, Trichophyton, Trichosporon, Trichostrongylus, Trichuris, Tritirachium, Trombicula, Trypanosoma, Tunga, Verticillium, Wuchereria; records prevalence = 2.0 microorganisms data set. calculating matching score, characters \\(x\\) \\(n\\) ignored -Z, -z, 0-9, spaces parentheses. matches sorted descending matching score user input values, top match returned. lead effect e.g., \"E. coli\" return microbial ID Escherichia coli (\\(m = 0.688\\), highly prevalent microorganism found humans) Entamoeba coli (\\(m = 0.381\\), less prevalent microorganism humans), although latter alphabetically come first.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.mo.html","id":"reference-data-publicly-available","dir":"Reference","previous_headings":"","what":"Reference Data Publicly Available","title":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","text":"data sets AMR package (microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) publicly freely available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. also provide tab-separated plain text files machine-readable suitable input software program, laboratory information systems. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/as.mo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Transform Arbitrary Input to Valid Microbial Taxonomy — as.mo","text":"","code":"# \\donttest{ # These examples all return \"B_STPHY_AURS\", the ID of S. aureus: as.mo(c(   \"sau\", # WHONET code   \"stau\",   \"STAU\",   \"staaur\",   \"S. aureus\",   \"S aureus\",   \"Sthafilokkockus aureus\", # handles incorrect spelling   \"Staphylococcus aureus (MRSA)\",   \"MRSA\", # Methicillin Resistant S. aureus   \"VISA\", # Vancomycin Intermediate S. aureus   \"VRSA\", # Vancomycin Resistant S. aureus   115329001 # SNOMED CT code )) #> Class 'mo' #>  [1] B_STPHY_AURS B_STPHY_AURS B_STPHY_AURS B_STPHY_AURS B_STPHY_AURS #>  [6] B_STPHY_AURS B_STPHY_AURS B_STPHY_AURS B_STPHY_AURS B_STPHY_AURS #> [11] B_STPHY_AURS B_STPHY_AURS  # Dyslexia is no problem - these all work: as.mo(c(   \"Ureaplasma urealyticum\",   \"Ureaplasma urealyticus\",   \"Ureaplasmium urealytica\",   \"Ureaplazma urealitycium\" )) #> Class 'mo' #> [1] B_URPLS_URLY B_URPLS_URLY B_URPLS_URLY B_URPLS_URLY  # input will get cleaned up with the input given in the `cleaning_regex` argument, # which defaults to `mo_cleaning_regex()`: cat(mo_cleaning_regex(), \"\\n\") #> ([^A-Za-z- \\(\\)\\[\\]{}]+|([({]|\\[).+([})]|\\])|(^| )(e?spp([^a-z]+|$)|e?ssp([^a-z]+|$)|serogr.?up[a-z]*|e?ss([^a-z]+|$)|e?sp([^a-z]+|$)|var([^a-z]+|$)|serovar[a-z]*|sube?species|biovar[a-z]*|e?species|Ig[ADEGM]|e?subsp|biotype|titer|dummy))   as.mo(\"Streptococcus group A\") #> Class 'mo' #> [1] B_STRPT_GRPA  as.mo(\"S. epidermidis\") # will remain species: B_STPHY_EPDR #> Class 'mo' #> [1] B_STPHY_EPDR as.mo(\"S. epidermidis\", Becker = TRUE) # will not remain species: B_STPHY_CONS #> Class 'mo' #> [1] B_STPHY_CONS  as.mo(\"S. pyogenes\") # will remain species: B_STRPT_PYGN #> Class 'mo' #> [1] B_STRPT_PYGN as.mo(\"S. pyogenes\", Lancefield = TRUE) # will not remain species: B_STRPT_GRPA #> Class 'mo' #> [1] B_STRPT_GRPA  # All mo_* functions use as.mo() internally too (see ?mo_property): mo_genus(\"E. coli\") #> [1] \"Escherichia\" mo_gramstain(\"ESCO\") #> [1] \"Gram-negative\" mo_is_intrinsic_resistant(\"ESCCOL\", ab = \"vanco\") #> ℹ Determining intrinsic resistance based on 'EUCAST Expert Rules' and #>   'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3 (2021). This note #>   will be shown once per session. #> [1] TRUE # }"},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":null,"dir":"Reference","previous_headings":"","what":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"Clean existing SIR values, interpret minimum inhibitory concentration (MIC) values disk diffusion diameters according EUCAST CLSI. .sir() transforms input new class sir, ordered factor containing levels S, SDD, , R, NI. breakpoints currently implemented: clinical microbiology: EUCAST 2011-2024 CLSI 2011-2024; veterinary microbiology: EUCAST 2021-2024 CLSI 2019-2024; ECOFFs (Epidemiological cut-values): EUCAST 2020-2024 CLSI 2022-2024. breakpoints used interpretation available clinical_breakpoints data set.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"","code":"as.sir(x, ...)  NA_sir_  is.sir(x)  is_sir_eligible(x, threshold = 0.05)  # Default S3 method as.sir(   x,   S = \"^(S|U)+$\",   I = \"^(I)+$\",   R = \"^(R)+$\",   NI = \"^(N|NI|V)+$\",   SDD = \"^(SDD|D|H)+$\",   ... )  # S3 method for class 'mic' as.sir(   x,   mo = NULL,   ab = deparse(substitute(x)),   guideline = getOption(\"AMR_guideline\", \"EUCAST\"),   uti = NULL,   conserve_capped_values = FALSE,   add_intrinsic_resistance = FALSE,   reference_data = AMR::clinical_breakpoints,   include_screening = getOption(\"AMR_include_screening\", FALSE),   include_PKPD = getOption(\"AMR_include_PKPD\", TRUE),   breakpoint_type = getOption(\"AMR_breakpoint_type\", \"human\"),   host = NULL,   verbose = FALSE,   ... )  # S3 method for class 'disk' as.sir(   x,   mo = NULL,   ab = deparse(substitute(x)),   guideline = getOption(\"AMR_guideline\", \"EUCAST\"),   uti = NULL,   add_intrinsic_resistance = FALSE,   reference_data = AMR::clinical_breakpoints,   include_screening = getOption(\"AMR_include_screening\", FALSE),   include_PKPD = getOption(\"AMR_include_PKPD\", TRUE),   breakpoint_type = getOption(\"AMR_breakpoint_type\", \"human\"),   host = NULL,   verbose = FALSE,   ... )  # S3 method for class 'data.frame' as.sir(   x,   ...,   col_mo = NULL,   guideline = getOption(\"AMR_guideline\", \"EUCAST\"),   uti = NULL,   conserve_capped_values = FALSE,   add_intrinsic_resistance = FALSE,   reference_data = AMR::clinical_breakpoints,   include_screening = getOption(\"AMR_include_screening\", FALSE),   include_PKPD = getOption(\"AMR_include_PKPD\", TRUE),   breakpoint_type = getOption(\"AMR_breakpoint_type\", \"human\"),   host = NULL,   verbose = FALSE )  sir_interpretation_history(clean = FALSE)"},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"interpretations minimum inhibitory concentration (MIC) values disk diffusion diameters: CLSI M39: Analysis Presentation Cumulative Antimicrobial Susceptibility Test Data, 2011-2024, Clinical Laboratory Standards Institute (CLSI). https://clsi.org/standards/products/microbiology/documents/m39/. CLSI M100: Performance Standard Antimicrobial Susceptibility Testing, 2011-2024, Clinical Laboratory Standards Institute (CLSI). https://clsi.org/standards/products/microbiology/documents/m100/. CLSI VET01: Performance Standards Antimicrobial Disk Dilution Susceptibility Tests Bacteria Isolated Animals, 2019-2024, Clinical Laboratory Standards Institute (CLSI). https://clsi.org/standards/products/veterinary-medicine/documents/vet01//. EUCAST Breakpoint tables interpretation MICs zone diameters, 2011-2024, European Committee Antimicrobial Susceptibility Testing (EUCAST). https://www.eucast.org/clinical_breakpoints. WHONET source machine-reading clinical breakpoints (read ), 1989-2024, Collaborating Centre Surveillance Antimicrobial Resistance. https://whonet.org/.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"x vector values (class mic: MIC values mg/L, class disk: disk diffusion radius millimetres) ... using data.frame: names columns apply .sir() (supports tidy selection column1:column4). Otherwise: arguments passed methods. threshold maximum fraction invalid antimicrobial interpretations x, see Examples S, , R, NI, SDD case-independent regular expression translate input result. regular expression run non-letters whitespaces removed input. mo vector (column name) characters can coerced valid microorganism codes .mo(), can left empty determine automatically ab vector (column name) characters can coerced valid antimicrobial drug code .ab() guideline defaults EUCAST 2024 (latest implemented EUCAST guideline clinical_breakpoints data set), can set package option AMR_guideline. Currently supports EUCAST (2011-2024) CLSI (2011-2024), see Details. uti (Urinary Tract Infection) vector (column name) logicals (TRUE FALSE) specify whether UTI specific interpretation guideline chosen. using .sir() data.frame, can also column containing logicals left blank, data set searched column 'specimen', rows within column containing 'urin' ('urine', 'urina') regarded isolates UTI. See Examples. conserve_capped_values logical indicate MIC values starting \">\" (\">=\") must always return \"R\" , MIC values starting \"<\" (\"<=\") must always return \"S\" add_intrinsic_resistance (useful using EUCAST guideline) logical indicate whether intrinsic antibiotic resistance must also considered applicable bug-drug combinations, meaning e.g. ampicillin always return \"R\" Klebsiella species. Determination based intrinsic_resistant data set, based 'EUCAST Expert Rules' 'EUCAST Intrinsic Resistance Unusual Phenotypes' v3.3 (2021). reference_data data.frame used interpretation, defaults clinical_breakpoints data set. Changing argument allows using interpretation guidelines. argument must contain data set equal structure clinical_breakpoints data set (column names column types). Please note guideline argument ignored reference_data manually set. include_screening logical indicate clinical breakpoints screening allowed - default FALSE. Can also set package option AMR_include_screening. include_PKPD logical indicate PK/PD clinical breakpoints must applied last resort - default TRUE. Can also set package option AMR_include_PKPD. breakpoint_type type breakpoints use, either \"ECOFF\", \"animal\", \"human\". ECOFF stands Epidemiological Cut-values. default \"human\", can also set package option AMR_breakpoint_type. host set values veterinary species, automatically set \"animal\". host vector (column name) characters indicate host. useful veterinary breakpoints, requires breakpoint_type = \"animal\". values can text resembling animal species, even 20 supported languages package. foreign languages, sure set language set_AMR_locale() (though automatically guessed based system language). verbose logical indicate notes printed interpretation MIC values disk diffusion values. col_mo column name names codes microorganisms (see .mo()) - default first column class mo. Values coerced using .mo(). clean logical indicate whether previously stored results forgotten returning 'logbook' results","code":""},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"Ordered factor new class sir","code":""},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"Note: clinical breakpoints package validated , imported , WHONET. public use AMR package endorsed CLSI EUCAST. See clinical_breakpoints information. NA_sir_ missing value new sir class, analogous e.g. base R's NA_character_.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"how-it-works","dir":"Reference","previous_headings":"","what":"How it Works","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":".sir() function can work four ways: cleaning raw / untransformed data. data cleaned contain valid values, namely: S susceptible, intermediate 'susceptible, increased exposure', R resistant, NI non-interpretable, SDD susceptible dose-dependent. can set using regular expression. Furthermore, .sir() try best clean intelligence. example, mixed values SIR interpretations MIC values \"<0.25; S\" coerced \"S\". Combined interpretations multiple test methods (seen laboratory records) \"S; S\" coerced \"S\", value like \"S; \" return NA warning input invalid. interpreting minimum inhibitory concentration (MIC) values according EUCAST CLSI. must clean MIC values first using .mic(), also gives columns new data class mic. Also, sure column microorganism names codes. found automatically, can set manually using mo argument. Using dplyr, SIR interpretation can done easily either:   Operators like \"<=\" stripped interpretation. using conserve_capped_values = TRUE, MIC value e.g. \">2\" always return \"R\", even breakpoint according chosen guideline \">=4\". prevent capped values raw laboratory data treated conservatively. default behaviour (conserve_capped_values = FALSE) considers \">2\" lower \">=4\" might case return \"S\" \"\". interpreting disk diffusion diameters according EUCAST CLSI. must clean disk zones first using .disk(), also gives columns new data class disk. Also, sure column microorganism names codes. found automatically, can set manually using mo argument. Using dplyr, SIR interpretation can done easily either:   interpreting complete data set, automatic determination MIC values, disk diffusion diameters, microorganism names codes, antimicrobial test results. done simply running .sir(your_data). points 2, 3 4: Use sir_interpretation_history() retrieve data.frame (tibble tibble package installed) results last .sir() call.","code":"your_data %>% mutate_if(is.mic, as.sir) your_data %>% mutate(across(where(is.mic), as.sir)) your_data %>% mutate_if(is.mic, as.sir, ab = \"column_with_antibiotics\", mo = \"column_with_microorganisms\") your_data %>% mutate_if(is.mic, as.sir, ab = c(\"cipro\", \"ampicillin\", ...), mo = c(\"E. coli\", \"K. pneumoniae\", ...))  # for veterinary breakpoints, also set `host`: your_data %>% mutate_if(is.mic, as.sir, host = \"column_with_animal_hosts\", guideline = \"CLSI\") your_data %>% mutate_if(is.disk, as.sir) your_data %>% mutate(across(where(is.disk), as.sir)) your_data %>% mutate_if(is.disk, as.sir, ab = \"column_with_antibiotics\", mo = \"column_with_microorganisms\") your_data %>% mutate_if(is.disk, as.sir, ab = c(\"cipro\", \"ampicillin\", ...), mo = c(\"E. coli\", \"K. pneumoniae\", ...))  # for veterinary breakpoints, also set `host`: your_data %>% mutate_if(is.disk, as.sir, host = \"column_with_animal_hosts\", guideline = \"CLSI\")"},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"supported-guidelines","dir":"Reference","previous_headings":"","what":"Supported Guidelines","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"interpreting MIC values well disk diffusion diameters, currently implemented guidelines clinical microbiology: EUCAST 2011-2024 CLSI 2011-2024, veterinary microbiology: EUCAST 2021-2024 CLSI 2019-2024. Thus, guideline argument must set e.g., \"EUCAST 2024\" \"CLSI 2024\". simply using \"EUCAST\" (default) \"CLSI\" input, latest included version guideline automatically selected. can set data set using reference_data argument. guideline argument ignored. can set default guideline package option AMR_guideline (e.g. .Rprofile file), :   veterinary guidelines, might best options:","code":"options(AMR_guideline = \"CLSI\")   options(AMR_guideline = \"CLSI 2018\")   options(AMR_guideline = \"EUCAST 2020\")   # or to reset:   options(AMR_guideline = NULL) options(AMR_guideline = \"CLSI\")   options(AMR_breakpoint_type = \"animal\")"},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"after-interpretation","dir":"Reference","previous_headings":"","what":"After Interpretation","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"using .sir(), can use eucast_rules() defined EUCAST (1) apply inferred susceptibility resistance based results antimicrobials (2) apply intrinsic resistance based taxonomic properties microorganism.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"machine-readable-clinical-breakpoints","dir":"Reference","previous_headings":"","what":"Machine-Readable Clinical Breakpoints","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"repository package contains machine-readable version guidelines. CSV file consisting 34 063 rows 14 columns. file machine-readable, since contains one row every unique combination test method (MIC disk diffusion), antimicrobial drug microorganism. allows easy implementation rules laboratory information systems (LIS). Note contains interpretation guidelines humans - interpretation guidelines CLSI animals removed.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"other","dir":"Reference","previous_headings":"","what":"Other","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"function .sir() detects input contains class sir. input data.frame, iterates columns returns logical vector. base R function .double() can used retrieve quantitative values sir object: \"S\" = 1, \"\"/\"SDD\" = 2, \"R\" = 3. values rendered NA . Note: use .integer(), since (R works internally) return factor level indices, aforementioned quantitative values. function is_sir_eligible() returns TRUE column contains 5% invalid antimicrobial interpretations (S //R /NI /SDD), FALSE otherwise. threshold 5% can set threshold argument. input data.frame, iterates columns returns logical vector.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"interpretation-of-sir","dir":"Reference","previous_headings":"","what":"Interpretation of SIR","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"2019, European Committee Antimicrobial Susceptibility Testing (EUCAST) decided change definitions susceptibility testing categories S, , R shown (https://www.eucast.org/newsiandr): S - Susceptible, standard dosing regimen microorganism categorised \"Susceptible, standard dosing regimen\", high likelihood therapeutic success using standard dosing regimen agent. - Susceptible, increased exposure  microorganism categorised \"Susceptible, Increased exposure\" high likelihood therapeutic success exposure agent increased adjusting dosing regimen concentration site infection. R = Resistant microorganism categorised \"Resistant\" high likelihood therapeutic failure even increased exposure. Exposure function mode administration, dose, dosing interval, infusion time, well distribution excretion antimicrobial agent influence infecting organism site infection. AMR package honours insight. Use susceptibility() (equal proportion_SI()) determine antimicrobial susceptibility count_susceptible() (equal count_SI()) count susceptible isolates.","code":""},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"reference-data-publicly-available","dir":"Reference","previous_headings":"","what":"Reference Data Publicly Available","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"data sets AMR package (microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) publicly freely available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. also provide tab-separated plain text files machine-readable suitable input software program, laboratory information systems. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/as.sir.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data — as.sir","text":"","code":"example_isolates #> # A tibble: 2,000 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-03 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  3 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  4 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  5 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  6 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  7 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  8 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  9 2002-01-16 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #> 10 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R     NA    S     NA    #> # ℹ 1,990 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, … summary(example_isolates) # see all SIR results at a glance #>       date              patient               age           gender          #>  Min.   :2002-01-02   Length:2000        Min.   : 0.00   Length:2000        #>  1st Qu.:2005-07-31   Class :character   1st Qu.:63.00   Class :character   #>  Median :2009-07-31   Mode  :character   Median :74.00   Mode  :character   #>  Mean   :2009-11-20                      Mean   :70.69                      #>  3rd Qu.:2014-05-30                      3rd Qu.:82.00                      #>  Max.   :2017-12-28                      Max.   :97.00                      #>      ward                mo                  PEN                 #>  Length:2000        Class :mo             Class:sir              #>  Class :character   <NA>  :0              %S   :25.6% (n=417)    #>  Mode  :character   Unique:90             %SDD : 0.0% (n=0)      #>                     #1    :B_ESCHR_COLI   %I   : 0.7% (n=11)     #>                     #2    :B_STPHY_CONS   %R   :73.7% (n=1201)   #>                     #3    :B_STPHY_AURS   %NI  : 0.0% (n=0)      #>     OXA                   FLC                   AMX                #>  Class:sir             Class:sir             Class:sir             #>  %S   :68.8% (n=251)   %S   :70.5% (n=665)   %S   :40.2% (n=543)   #>  %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)     #>  %I   : 0.0% (n=0)     %I   : 0.0% (n=0)     %I   : 0.2% (n=3)     #>  %R   :31.2% (n=114)   %R   :29.5% (n=278)   %R   :59.6% (n=804)   #>  %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)     #>     AMC                    AMP                   TZP                #>  Class:sir              Class:sir             Class:sir             #>  %S   :71.4% (n=1342)   %S   :40.2% (n=543)   %S   :86.1% (n=862)   #>  %SDD : 0.0% (n=0)      %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)     #>  %I   : 4.8% (n=91)     %I   : 0.2% (n=3)     %I   : 1.3% (n=13)    #>  %R   :23.7% (n=446)    %R   :59.6% (n=804)   %R   :12.6% (n=126)   #>  %NI  : 0.0% (n=0)      %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)     #>     CZO                   FEP                   CXM                 #>  Class:sir             Class:sir             Class:sir              #>  %S   :54.9% (n=245)   %S   :85.6% (n=620)   %S   :72.5% (n=1297)   #>  %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)      #>  %I   : 0.4% (n=2)     %I   : 0.1% (n=1)     %I   : 1.2% (n=22)     #>  %R   :44.6% (n=199)   %R   :14.2% (n=103)   %R   :26.3% (n=470)    #>  %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)      #>     FOX                   CTX                   CAZ                 #>  Class:sir             Class:sir             Class:sir              #>  %S   :71.6% (n=586)   %S   :84.4% (n=796)   %S   :33.5% (n=607)    #>  %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)      #>  %I   : 1.0% (n=8)     %I   : 0.1% (n=1)     %I   : 0.0% (n=0)      #>  %R   :27.4% (n=224)   %R   :15.5% (n=146)   %R   :66.5% (n=1204)   #>  %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)      #>     CRO                   GEN                    TOB                #>  Class:sir             Class:sir              Class:sir             #>  %S   :84.4% (n=796)   %S   :74.0% (n=1372)   %S   :65.1% (n=879)   #>  %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)      %SDD : 0.0% (n=0)     #>  %I   : 0.1% (n=1)     %I   : 1.5% (n=27)     %I   : 0.5% (n=7)     #>  %R   :15.5% (n=146)   %R   :24.6% (n=456)    %R   :34.4% (n=465)   #>  %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)      %NI  : 0.0% (n=0)     #>     AMK                   KAN                    TMP                #>  Class:sir             Class:sir              Class:sir             #>  %S   :36.3% (n=251)   %S   : 0.0% (n=0)      %S   :61.2% (n=918)   #>  %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)      %SDD : 0.0% (n=0)     #>  %I   : 0.0% (n=0)     %I   : 0.0% (n=0)      %I   : 0.7% (n=10)    #>  %R   :63.7% (n=441)   %R   :100.0% (n=471)   %R   :38.1% (n=571)   #>  %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)      %NI  : 0.0% (n=0)     #>     SXT                    NIT                   FOS                #>  Class:sir              Class:sir             Class:sir             #>  %S   :79.1% (n=1392)   %S   :76.0% (n=565)   %S   :57.8% (n=203)   #>  %SDD : 0.0% (n=0)      %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)     #>  %I   : 0.3% (n=6)      %I   : 6.9% (n=51)    %I   : 0.0% (n=0)     #>  %R   :20.5% (n=361)    %R   :17.1% (n=127)   %R   :42.2% (n=148)   #>  %NI  : 0.0% (n=0)      %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)     #>     LNZ                   CIP                    MFX                #>  Class:sir             Class:sir              Class:sir             #>  %S   :30.7% (n=314)   %S   :78.9% (n=1112)   %S   :64.5% (n=136)   #>  %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)      %SDD : 0.0% (n=0)     #>  %I   : 0.0% (n=0)     %I   : 4.9% (n=69)     %I   : 1.9% (n=4)     #>  %R   :69.3% (n=709)   %R   :16.2% (n=228)    %R   :33.6% (n=71)    #>  %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)      %NI  : 0.0% (n=0)     #>     VAN                    TEC                   TCY                #>  Class:sir              Class:sir             Class:sir             #>  %S   :61.7% (n=1149)   %S   :24.3% (n=237)   %S   :68.3% (n=820)   #>  %SDD : 0.0% (n=0)      %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)     #>  %I   : 0.0% (n=0)      %I   : 0.0% (n=0)     %I   : 1.9% (n=23)    #>  %R   :38.3% (n=712)    %R   :75.7% (n=739)   %R   :29.8% (n=357)   #>  %NI  : 0.0% (n=0)      %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)     #>     TGC                   DOX                   ERY                 #>  Class:sir             Class:sir             Class:sir              #>  %S   :87.3% (n=697)   %S   :71.7% (n=814)   %S   :42.3% (n=801)    #>  %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)      #>  %I   : 0.0% (n=0)     %I   : 0.6% (n=7)     %I   : 0.5% (n=9)      #>  %R   :12.7% (n=101)   %R   :27.7% (n=315)   %R   :57.2% (n=1084)   #>  %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)      #>     CLI                   AZM                    IPM                #>  Class:sir             Class:sir              Class:sir             #>  %S   :38.6% (n=586)   %S   :42.3% (n=801)    %S   :92.7% (n=824)   #>  %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)      %SDD : 0.0% (n=0)     #>  %I   : 0.3% (n=4)     %I   : 0.5% (n=9)      %I   : 1.1% (n=10)    #>  %R   :61.2% (n=930)   %R   :57.2% (n=1084)   %R   : 6.2% (n=55)    #>  %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)      %NI  : 0.0% (n=0)     #>     MEM                   MTR                  CHL                #>  Class:sir             Class:sir            Class:sir             #>  %S   :94.1% (n=780)   %S   :85.3% (n=29)   %S   :78.6% (n=121)   #>  %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)    %SDD : 0.0% (n=0)     #>  %I   : 0.0% (n=0)     %I   : 0.0% (n=0)    %I   : 0.0% (n=0)     #>  %R   : 5.9% (n=49)    %R   :14.7% (n=5)    %R   :21.4% (n=33)    #>  %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)    %NI  : 0.0% (n=0)     #>     COL                    MUP                   RIF                #>  Class:sir              Class:sir             Class:sir             #>  %S   :18.8% (n=309)    %S   :93.0% (n=251)   %S   :30.2% (n=303)   #>  %SDD : 0.0% (n=0)      %SDD : 0.0% (n=0)     %SDD : 0.0% (n=0)     #>  %I   : 0.0% (n=0)      %I   : 1.1% (n=3)     %I   : 0.2% (n=2)     #>  %R   :81.2% (n=1331)   %R   : 5.9% (n=16)    %R   :69.6% (n=698)   #>  %NI  : 0.0% (n=0)      %NI  : 0.0% (n=0)     %NI  : 0.0% (n=0)      # For INTERPRETING disk diffusion and MIC values -----------------------  # example data sets, with combined MIC values and disk zones df_wide <- data.frame(   microorganism = \"Escherichia coli\",   amoxicillin = as.mic(8),   cipro = as.mic(0.256),   tobra = as.disk(16),   genta = as.disk(18),   ERY = \"R\" ) df_long <- data.frame(   bacteria = rep(\"Escherichia coli\", 4),   antibiotic = c(\"amoxicillin\", \"cipro\", \"tobra\", \"genta\"),   mics = as.mic(c(0.01, 1, 4, 8)),   disks = as.disk(c(6, 10, 14, 18)) )  # \\donttest{ ## Using dplyr ------------------------------------------------- if (require(\"dplyr\")) {   # approaches that all work without additional arguments:   df_wide %>% mutate_if(is.mic, as.sir)   df_wide %>% mutate_if(function(x) is.mic(x) | is.disk(x), as.sir)   df_wide %>% mutate(across(where(is.mic), as.sir))   df_wide %>% mutate_at(vars(amoxicillin:tobra), as.sir)   df_wide %>% mutate(across(amoxicillin:tobra, as.sir))      # approaches that all work with additional arguments:   df_long %>%     # given a certain data type, e.g. MIC values     mutate_if(is.mic, as.sir,               mo = \"bacteria\",               ab = \"antibiotic\",               guideline = \"CLSI\")   df_long %>%     mutate(across(where(is.mic),                   function(x) as.sir(x,                                      mo = \"bacteria\",                                      ab = \"antibiotic\",                                      guideline = \"CLSI\")))   df_wide %>%     # given certain columns, e.g. from 'cipro' to 'genta'     mutate_at(vars(cipro:genta), as.sir,               mo = \"bacteria\",               guideline = \"CLSI\")   df_wide %>%     mutate(across(cipro:genta,                        function(x) as.sir(x,                                           mo = \"bacteria\",                                           guideline = \"CLSI\")))                           # for veterinary breakpoints, add 'host':   df_long$animal_species <- c(\"cats\", \"dogs\", \"horses\", \"cattle\")   df_long %>%     # given a certain data type, e.g. MIC values     mutate_if(is.mic, as.sir,               mo = \"bacteria\",               ab = \"antibiotic\",               host = \"animal_species\",               guideline = \"CLSI\")   df_long %>%     mutate(across(where(is.mic),                   function(x) as.sir(x,                                      mo = \"bacteria\",                                      ab = \"antibiotic\",                                      host = \"animal_species\",                                      guideline = \"CLSI\")))   df_wide %>%     mutate_at(vars(cipro:genta), as.sir,               mo = \"bacteria\",               ab = \"antibiotic\",               host = \"animal_species\",               guideline = \"CLSI\")   df_wide %>%     mutate(across(cipro:genta,                        function(x) as.sir(x,                                           mo = \"bacteria\",                                           host = \"animal_species\",                                           guideline = \"CLSI\")))      # to include information about urinary tract infections (UTI)   data.frame(mo = \"E. coli\",              nitrofuratoin = c(\"<= 2\", 32),              from_the_bladder = c(TRUE, FALSE)) %>%     as.sir(uti = \"from_the_bladder\")    data.frame(mo = \"E. coli\",              nitrofuratoin = c(\"<= 2\", 32),              specimen = c(\"urine\", \"blood\")) %>%     as.sir() # automatically determines urine isolates    df_wide %>%     mutate_at(vars(cipro:genta), as.sir, mo = \"E. coli\", uti = TRUE) } #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'amoxicillin' (AMX) based on column #> 'microorganism', EUCAST 2024... #>  OK  #> Interpreting MIC values: 'cipro' (CIP, ciprofloxacin) based on column #> 'microorganism', EUCAST 2024... #>  NOTE  #>   • Multiple breakpoints available for ciprofloxacin (CIP) in Escherichia coli - assuming body site 'Non-meningitis'. #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'amoxicillin' (AMX) based on column #> 'microorganism', EUCAST 2024... #>  OK  #> Interpreting MIC values: 'cipro' (CIP, ciprofloxacin) based on column #> 'microorganism', EUCAST 2024... #>  NOTE  #>   • Multiple breakpoints available for ciprofloxacin (CIP) in Escherichia coli - assuming body site 'Non-meningitis'. #> Interpreting disk diffusion zones: 'tobra' (TOB, tobramycin) based on #> column 'microorganism', EUCAST 2024... #>  OK  #> Interpreting disk diffusion zones: 'genta' (GEN, gentamicin) based on #> column 'microorganism', EUCAST 2024... #>  OK  #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'amoxicillin' (AMX) based on column #> 'microorganism', EUCAST 2024... #>  OK  #> Interpreting MIC values: 'cipro' (CIP, ciprofloxacin) based on column #> 'microorganism', EUCAST 2024... #>  NOTE  #>   • Multiple breakpoints available for ciprofloxacin (CIP) in Escherichia coli - assuming body site 'Non-meningitis'. #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'amoxicillin' (AMX) based on column #> 'microorganism', EUCAST 2024... #>  OK  #> Interpreting MIC values: 'cipro' (CIP, ciprofloxacin) based on column #> 'microorganism', EUCAST 2024... #>  NOTE  #>   • Multiple breakpoints available for ciprofloxacin (CIP) in Escherichia coli - assuming body site 'Non-meningitis'. #> Interpreting disk diffusion zones: 'tobra' (TOB, tobramycin) based on #> column 'microorganism', EUCAST 2024... #>  OK  #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'amoxicillin' (AMX) based on column #> 'microorganism', EUCAST 2024... #>  OK  #> Interpreting MIC values: 'cipro' (CIP, ciprofloxacin) based on column #> 'microorganism', EUCAST 2024... #>  NOTE  #>   • Multiple breakpoints available for ciprofloxacin (CIP) in Escherichia coli - assuming body site 'Non-meningitis'. #> Interpreting disk diffusion zones: 'tobra' (TOB, tobramycin) based on #> column 'microorganism', EUCAST 2024... #>  OK  #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'amoxicillin' (AMX), 'cipro' (CIP, ciprofloxacin), #> 'tobra' (TOB, tobramycin), and 'genta' (GEN, gentamicin) based on column #> 'bacteria', CLSI 2024... #>  OK  #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'amoxicillin' (AMX), 'cipro' (CIP, ciprofloxacin), #> 'tobra' (TOB, tobramycin), and 'genta' (GEN, gentamicin) based on column #> 'bacteria', CLSI 2024... #>  OK  #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'cipro' (CIP, ciprofloxacin), CLSI 2024... #>  OK  #> Interpreting disk diffusion zones: 'tobra' (TOB, tobramycin), CLSI 2024... #>  OK  #> Interpreting disk diffusion zones: 'genta' (GEN, gentamicin), CLSI 2024... #>  OK  #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'cipro' (CIP, ciprofloxacin), CLSI 2024... #>  OK  #> Interpreting disk diffusion zones: 'tobra' (TOB, tobramycin), CLSI 2024... #>  OK  #> Interpreting disk diffusion zones: 'genta' (GEN, gentamicin), CLSI 2024... #>  OK  #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> ℹ Assuming breakpoint_type = \"animal\", since host is set. #> ℹ Please note that in the absence of specific veterinary breakpoints for #>   certain animal hosts, breakpoints for dogs, cattle, swine, cats, horse, #>   aquatic, and poultry, in that order, are used as substitutes. #> Interpreting MIC values: 'amoxicillin' (AMX), 'cipro' (CIP, ciprofloxacin), #> 'tobra' (TOB, tobramycin), and 'genta' (GEN, gentamicin) based on column #> 'bacteria', CLSI 2024... #>  NOTE  #>   • Using dogs breakpoints since cattle for gentamicin (GEN) in Escherichia coli are not available. #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> ℹ Assuming breakpoint_type = \"animal\", since host is set. #> ℹ Please note that in the absence of specific veterinary breakpoints for #>   certain animal hosts, breakpoints for dogs, cattle, swine, cats, horse, #>   aquatic, and poultry, in that order, are used as substitutes. #> Interpreting MIC values: 'amoxicillin' (AMX), 'cipro' (CIP, ciprofloxacin), #> 'tobra' (TOB, tobramycin), and 'genta' (GEN, gentamicin) based on column #> 'bacteria', CLSI 2024... #>  NOTE  #>   • Using dogs breakpoints since cattle for gentamicin (GEN) in Escherichia coli are not available. #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> ℹ Assuming breakpoint_type = \"animal\", since host is set. #> ℹ The following host(s) are invalid: \"animalspecies\". For missing animal #>   hosts, assuming \"dogs\", since these have the highest breakpoint #>   availability. #> ℹ Please note that in the absence of specific veterinary breakpoints for #>   certain animal hosts, breakpoints for dogs, cattle, swine, cats, horse, #>   aquatic, and poultry, in that order, are used as substitutes. #> Interpreting MIC values: 'antibiotic' (TESTAB, test Antibiotic), CLSI #> 2024... #>  WARNING  #>   • No CLSI 2024 MIC breakpoints available for test Antibiotic (TESTAB). #> Interpreting disk diffusion zones: 'antibiotic' (TESTAB, test Antibiotic), #> CLSI 2024... #>  WARNING  #>   • No CLSI 2024 DISK breakpoints available for test Antibiotic (TESTAB). #> Interpreting disk diffusion zones: 'antibiotic' (TESTAB, test Antibiotic), #> CLSI 2024... #>  WARNING  #>   • No CLSI 2024 DISK breakpoints available for test Antibiotic (TESTAB). #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> ℹ Assuming breakpoint_type = \"animal\", since host is set. #> ℹ The following host(s) are invalid: \"animalspecies\". For missing animal #>   hosts, assuming \"dogs\", since these have the highest breakpoint #>   availability. #> ℹ Please note that in the absence of specific veterinary breakpoints for #>   certain animal hosts, breakpoints for dogs, cattle, swine, cats, horse, #>   aquatic, and poultry, in that order, are used as substitutes. #> Interpreting MIC values: 'cipro' (CIP, ciprofloxacin), CLSI 2024... #>  WARNING  #>   • No CLSI 2024 MIC breakpoints available for ciprofloxacin (CIP). #> Interpreting disk diffusion zones: 'tobra' (TOB, tobramycin), CLSI 2024... #>  OK  #> Interpreting disk diffusion zones: 'genta' (GEN, gentamicin), CLSI 2024... #>  OK  #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: column 'nitrofuratoin' (NIT, nitrofurantoin), #> EUCAST 2024... #>  NOTE  #>   • Breakpoints for nitrofurantoin (NIT) in Escherichia coli are only available for (uncomplicated) urinary tract infections (UTI); assuming uti = TRUE. #> ℹ Assuming value \"urine\" in column 'specimen' reflects a urinary tract #>   infection. #>   Use as.sir(uti = FALSE) to prevent this. #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: column 'nitrofuratoin' (NIT, nitrofurantoin), #> EUCAST 2024... #>  NOTE  #>   • Breakpoints for nitrofurantoin (NIT) in Escherichia coli are only available for (uncomplicated) urinary tract infections (UTI); assuming uti = TRUE. #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'cipro' (CIP, ciprofloxacin), EUCAST 2024... #>  OK  #> Interpreting disk diffusion zones: 'tobra' (TOB, tobramycin), EUCAST #> 2024... #>  OK  #> Interpreting disk diffusion zones: 'genta' (GEN, gentamicin), EUCAST #> 2024... #>  OK  #>      microorganism amoxicillin cipro tobra genta ERY #> 1 Escherichia coli           8  <NA>     S     S   R   ## Using base R ------------------------------------------------  as.sir(df_wide) #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: column 'amoxicillin' (AMX), EUCAST 2024... #>  OK  #> Interpreting MIC values: column 'cipro' (CIP, ciprofloxacin), EUCAST #> 2024... #>  NOTE  #>   • Multiple breakpoints available for ciprofloxacin (CIP) in Escherichia coli - assuming body site 'Non-meningitis'. #> Interpreting disk diffusion zones: column 'tobra' (TOB, tobramycin), EUCAST #> 2024... #>  OK  #> Interpreting disk diffusion zones: column 'genta' (GEN, gentamicin), EUCAST #> 2024... #>  OK  #> Assigning class 'sir' to already clean column 'ERY' (erythromycin)... #>  OK  #>      microorganism amoxicillin cipro tobra genta ERY #> 1 Escherichia coli           S     I     S     S   R  # return a 'logbook' about the results: sir_interpretation_history() #> # A tibble: 59 × 16 #>    datetime            index ab_given mo_given host_given ab   mo               #>  * <dttm>              <int> <chr>    <chr>    <chr>      <ab> <mo>             #>  1 2024-07-16 12:58:17     4 AMX      B_STRPT… human      AMX  B_STRPT_PNMN     #>  2 2024-07-16 12:58:23     4 genta    Escheri… human      GEN  B_[ORD]_ENTRBCTR #>  3 2024-07-16 12:58:24     4 genta    Escheri… human      GEN  B_[ORD]_ENTRBCTR #>  4 2024-07-16 12:58:24     4 genta    Escheri… cattle     GEN  B_[ORD]_ENTRBCTR #>  5 2024-07-16 12:58:25     4 genta    Escheri… cattle     GEN  B_[ORD]_ENTRBCTR #>  6 2024-07-16 12:58:17     3 AMX      B_STRPT… human      AMX  B_STRPT_PNMN     #>  7 2024-07-16 12:58:23     3 tobra    Escheri… human      TOB  B_[ORD]_ENTRBCTR #>  8 2024-07-16 12:58:24     3 tobra    Escheri… human      TOB  B_[ORD]_ENTRBCTR #>  9 2024-07-16 12:58:24     3 tobra    Escheri… horses     TOB  B_ESCHR_COLI     #> 10 2024-07-16 12:58:25     3 tobra    Escheri… horses     TOB  B_ESCHR_COLI     #> # ℹ 49 more rows #> # ℹ 9 more variables: host <chr>, method <chr>, input <dbl>, outcome <sir>, #> #   notes <chr>, guideline <chr>, ref_table <chr>, uti <lgl>, #> #   breakpoint_S_R <chr>  # for single values as.sir(   x = as.mic(2),   mo = as.mo(\"S. pneumoniae\"),   ab = \"AMP\",   guideline = \"EUCAST\" ) #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting MIC values: 'AMP' (ampicillin), EUCAST 2024... #>  NOTE  #>   • Multiple breakpoints available for ampicillin (AMP) in Streptococcus pneumoniae - assuming body site 'Non-meningitis'. #> Class 'sir' #> [1] R  as.sir(   x = as.disk(18),   mo = \"Strep pneu\", # `mo` will be coerced with as.mo()   ab = \"ampicillin\", # and `ab` with as.ab()   guideline = \"EUCAST\" ) #> ℹ Run sir_interpretation_history() afterwards to retrieve a logbook with #>   all the details of the breakpoint interpretations. #> Interpreting disk diffusion zones: 'ampicillin' (AMP), EUCAST 2024... #>  OK  #> Class 'sir' #> [1] R   # For CLEANING existing SIR values ------------------------------------  as.sir(c(\"S\", \"SDD\", \"I\", \"R\", \"NI\", \"A\", \"B\", \"C\")) #> Warning: in as.sir(): 3 results in column '30' truncated (38%) that were invalid #> antimicrobial interpretations: \"A\", \"B\", and \"C\" #> Class 'sir' #> [1] S    SDD  I    R    NI   <NA> <NA> <NA> as.sir(\"<= 0.002; S\") # will return \"S\" #> Class 'sir' #> [1] S sir_data <- as.sir(c(rep(\"S\", 474), rep(\"I\", 36), rep(\"R\", 370))) is.sir(sir_data) #> [1] TRUE plot(sir_data) # for percentages  barplot(sir_data) # for frequencies   # as common in R, you can use as.integer() to return factor indices: as.integer(as.sir(c(\"S\", \"SDD\", \"I\", \"R\", \"NI\", NA))) #> [1]  1  2  3  4  5 NA # but for computational use, as.double() will return 1 for S, 2 for I/SDD, and 3 for R: as.double(as.sir(c(\"S\", \"SDD\", \"I\", \"R\", \"NI\", NA))) #> [1]  1  2  2  3 NA NA  # the dplyr way if (require(\"dplyr\")) {   example_isolates %>%     mutate_at(vars(PEN:RIF), as.sir)   # same:   example_isolates %>%     as.sir(PEN:RIF)    # fastest way to transform all columns with already valid AMR results to class `sir`:   example_isolates %>%     mutate_if(is_sir_eligible, as.sir)    # since dplyr 1.0.0, this can also be:   # example_isolates %>%   #   mutate(across(where(is_sir_eligible), as.sir)) } #> # A tibble: 2,000 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-03 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  3 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  4 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  5 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  6 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  7 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  8 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  9 2002-01-16 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #> 10 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R     NA    S     NA    #> # ℹ 1,990 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, … # }"},{"path":"https://msberends.github.io/AMR/reference/atc_online.html","id":null,"dir":"Reference","previous_headings":"","what":"Get ATC Properties from WHOCC Website — atc_online_property","title":"Get ATC Properties from WHOCC Website — atc_online_property","text":"Gets data WHOCC website determine properties Anatomical Therapeutic Chemical (ATC) (e.g. antibiotic), name, defined daily dose (DDD) standard unit.","code":""},{"path":"https://msberends.github.io/AMR/reference/atc_online.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get ATC Properties from WHOCC Website — atc_online_property","text":"","code":"atc_online_property(   atc_code,   property,   administration = \"O\",   url = \"https://atcddd.fhi.no/atc_ddd_index/?code=%s&showdescription=no\",   url_vet = \"https://atcddd.fhi.no/atcvet/atcvet_index/?code=%s&showdescription=no\" )  atc_online_groups(atc_code, ...)  atc_online_ddd(atc_code, ...)  atc_online_ddd_units(atc_code, ...)"},{"path":"https://msberends.github.io/AMR/reference/atc_online.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get ATC Properties from WHOCC Website — atc_online_property","text":"https://atcddd.fhi./atc_ddd_alterations__cumulative/ddd_alterations/abbrevations/","code":""},{"path":"https://msberends.github.io/AMR/reference/atc_online.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get ATC Properties from WHOCC Website — atc_online_property","text":"atc_code character (vector) ATC code(s) antibiotics, coerced .ab() ab_atc() internally valid ATC code property property ATC code. Valid values \"ATC\", \"Name\", \"DDD\", \"U\" (\"unit\"), \"Adm.R\", \"Note\" groups. last option, hierarchical groups ATC code returned, see Examples. administration type administration using property = \"Adm.R\", see Details url url website WHOCC. sign %s can used placeholder ATC codes. url_vet url website WHOCC veterinary medicine. sign %s can used placeholder ATC_vet codes (start \"Q\"). ... arguments pass atc_property","code":""},{"path":"https://msberends.github.io/AMR/reference/atc_online.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get ATC Properties from WHOCC Website — atc_online_property","text":"Options argument administration: \"Implant\" = Implant \"Inhal\" = Inhalation \"Instill\" = Instillation \"N\" = nasal \"O\" = oral \"P\" = parenteral \"R\" = rectal \"SL\" = sublingual/buccal \"TD\" = transdermal \"V\" = vaginal Abbreviations return values using property = \"U\" (unit): \"g\" = gram \"mg\" = milligram \"mcg\" = microgram \"U\" = unit \"TU\" = thousand units \"MU\" = million units \"mmol\" = millimole \"ml\" = millilitre (e.g. eyedrops) N.B. function requires internet connection works following packages installed: curl, rvest, xml2.","code":""},{"path":"https://msberends.github.io/AMR/reference/atc_online.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get ATC Properties from WHOCC Website — atc_online_property","text":"","code":"# \\donttest{ if (requireNamespace(\"curl\") && requireNamespace(\"rvest\") && requireNamespace(\"xml2\")) {   # oral DDD (Defined Daily Dose) of amoxicillin   atc_online_property(\"J01CA04\", \"DDD\", \"O\")   atc_online_ddd(ab_atc(\"amox\"))    # parenteral DDD (Defined Daily Dose) of amoxicillin   atc_online_property(\"J01CA04\", \"DDD\", \"P\")    atc_online_property(\"J01CA04\", property = \"groups\") # search hierarchical groups of amoxicillin } #> Loading required namespace: rvest #> [1] \"ANTIINFECTIVES FOR SYSTEMIC USE\"         #> [2] \"ANTIBACTERIALS FOR SYSTEMIC USE\"         #> [3] \"BETA-LACTAM ANTIBACTERIALS, PENICILLINS\" #> [4] \"Penicillins with extended spectrum\"      # }"},{"path":"https://msberends.github.io/AMR/reference/av_from_text.html","id":null,"dir":"Reference","previous_headings":"","what":"Retrieve Antiviral Drug Names and Doses from Clinical Text — av_from_text","title":"Retrieve Antiviral Drug Names and Doses from Clinical Text — av_from_text","text":"Use function e.g. clinical texts health care records. returns list antiviral drugs, doses forms administration found texts.","code":""},{"path":"https://msberends.github.io/AMR/reference/av_from_text.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Retrieve Antiviral Drug Names and Doses from Clinical Text — av_from_text","text":"","code":"av_from_text(   text,   type = c(\"drug\", \"dose\", \"administration\"),   collapse = NULL,   translate_av = FALSE,   thorough_search = NULL,   info = interactive(),   ... )"},{"path":"https://msberends.github.io/AMR/reference/av_from_text.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Retrieve Antiviral Drug Names and Doses from Clinical Text — av_from_text","text":"text text analyse type type property search , either \"drug\", \"dose\" \"administration\", see Examples collapse character pass paste(, collapse = ...) return one character per element text, see Examples translate_av type = \"drug\": column name antivirals data set translate antibiotic abbreviations , using av_property(). default FALSE. Using TRUE equal using \"name\". thorough_search logical indicate whether input must extensively searched misspelling faulty input values. Setting TRUE take considerably time using FALSE. default, turn TRUE input elements contain maximum three words. info logical indicate whether progress bar printed - default TRUE interactive mode ... arguments passed .av()","code":""},{"path":"https://msberends.github.io/AMR/reference/av_from_text.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Retrieve Antiviral Drug Names and Doses from Clinical Text — av_from_text","text":"list,  character collapse NULL","code":""},{"path":"https://msberends.github.io/AMR/reference/av_from_text.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Retrieve Antiviral Drug Names and Doses from Clinical Text — av_from_text","text":"function also internally used .av(), although searches first drug name throw note drug names returned. Note: .av() function may use long regular expression match brand names antiviral drugs. may fail systems.","code":""},{"path":"https://msberends.github.io/AMR/reference/av_from_text.html","id":"argument-type","dir":"Reference","previous_headings":"","what":"Argument type","title":"Retrieve Antiviral Drug Names and Doses from Clinical Text — av_from_text","text":"default, function search antiviral drug names. text elements searched official names, ATC codes brand names. uses .av() internally, correct misspelling. type = \"dose\" (similar, like \"dosing\", \"doses\"), text elements searched numeric values higher 100 resemble years. output numeric. supports unit (g, mg, IE, etc.) multiple values one clinical text, see Examples. type = \"administration\" (abbreviations, like \"admin\", \"adm\"), text elements searched form drug administration. supports following forms (including common abbreviations): buccal, implant, inhalation, instillation, intravenous, nasal, oral, parenteral, rectal, sublingual, transdermal vaginal. Abbreviations oral ('po', 'per os') become \"oral\", values intravenous ('iv', 'intraven') become \"iv\". supports multiple values one clinical text, see Examples.","code":""},{"path":"https://msberends.github.io/AMR/reference/av_from_text.html","id":"argument-collapse","dir":"Reference","previous_headings":"","what":"Argument collapse","title":"Retrieve Antiviral Drug Names and Doses from Clinical Text — av_from_text","text":"Without using collapse, function return list. can convenient use e.g. inside mutate()):df %>% mutate(avx = av_from_text(clinical_text)) returned AV codes can transformed official names, groups, etc. av_* functions av_name() av_group(), using translate_av argument. using collapse, function return character:df %>% mutate(avx = av_from_text(clinical_text, collapse = \"|\"))","code":""},{"path":"https://msberends.github.io/AMR/reference/av_from_text.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Retrieve Antiviral Drug Names and Doses from Clinical Text — av_from_text","text":"","code":"av_from_text(\"28/03/2020 valaciclovir po tid\") #> [[1]] #> Class 'av' #> [1] VALA #>  av_from_text(\"28/03/2020 valaciclovir po tid\", type = \"admin\") #> [[1]] #> [1] \"oral\" #>"},{"path":"https://msberends.github.io/AMR/reference/av_property.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Properties of an Antiviral Drug — av_property","title":"Get Properties of an Antiviral Drug — av_property","text":"Use functions return specific property antiviral drug antivirals data set. input values evaluated internally .av().","code":""},{"path":"https://msberends.github.io/AMR/reference/av_property.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Properties of an Antiviral Drug — av_property","text":"","code":"av_name(x, language = get_AMR_locale(), tolower = FALSE, ...)  av_cid(x, ...)  av_synonyms(x, ...)  av_tradenames(x, ...)  av_group(x, language = get_AMR_locale(), ...)  av_atc(x, ...)  av_loinc(x, ...)  av_ddd(x, administration = \"oral\", ...)  av_ddd_units(x, administration = \"oral\", ...)  av_info(x, language = get_AMR_locale(), ...)  av_url(x, open = FALSE, ...)  av_property(x, property = \"name\", language = get_AMR_locale(), ...)"},{"path":"https://msberends.github.io/AMR/reference/av_property.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Properties of an Antiviral Drug — av_property","text":"x (vector ) text can coerced valid antiviral drug code .av() language language returned text - default system language (see get_AMR_locale()) can also set package option AMR_locale. Use language = NULL language = \"\" prevent translation. tolower logical indicate whether first character every output transformed lower case character. ... arguments passed .av() administration way administration, either \"oral\" \"iv\" open browse URL using utils::browseURL() property one column names one antivirals data set: vector_or(colnames(antivirals), sort = FALSE).","code":""},{"path":"https://msberends.github.io/AMR/reference/av_property.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Properties of an Antiviral Drug — av_property","text":"integer case av_cid() named list case av_info() multiple av_atc()/av_synonyms()/av_tradenames() double case av_ddd() character cases","code":""},{"path":"https://msberends.github.io/AMR/reference/av_property.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get Properties of an Antiviral Drug — av_property","text":"output translated possible. function av_url() return direct URL official website. warning returned required ATC code available.","code":""},{"path":"https://msberends.github.io/AMR/reference/av_property.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get Properties of an Antiviral Drug — av_property","text":"World Health Organization () Collaborating Centre Drug Statistics Methodology: https://atcddd.fhi./atc_ddd_index/ European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm","code":""},{"path":"https://msberends.github.io/AMR/reference/av_property.html","id":"reference-data-publicly-available","dir":"Reference","previous_headings":"","what":"Reference Data Publicly Available","title":"Get Properties of an Antiviral Drug — av_property","text":"data sets AMR package (microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) publicly freely available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. also provide tab-separated plain text files machine-readable suitable input software program, laboratory information systems. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/av_property.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Properties of an Antiviral Drug — av_property","text":"","code":"# all properties: av_name(\"ACI\") #> [1] \"Aciclovir\" av_atc(\"ACI\") #> [1] \"J05AB01\" av_cid(\"ACI\") #> [1] 135398513 av_synonyms(\"ACI\") #>  [1] \"acicloftal\"        \"aciclovier\"        \"aciclovirum\"       #>  [4] \"activir\"           \"acyclofoam\"        \"acycloguanosine\"   #>  [7] \"acyclovir\"         \"acyclovir lauriad\" \"avaclyr\"           #> [10] \"cargosil\"          \"cyclovir\"          \"genvir\"            #> [13] \"gerpevir\"          \"hascovir\"          \"maynar\"            #> [16] \"novirus\"           \"poviral\"           \"sitavig\"           #> [19] \"sitavir\"           \"vipral\"            \"viropump\"          #> [22] \"virorax\"           \"zovirax\"           \"zyclir\"            av_tradenames(\"ACI\") #>  [1] \"acicloftal\"        \"aciclovier\"        \"aciclovirum\"       #>  [4] \"activir\"           \"acyclofoam\"        \"acycloguanosine\"   #>  [7] \"acyclovir\"         \"acyclovir lauriad\" \"avaclyr\"           #> [10] \"cargosil\"          \"cyclovir\"          \"genvir\"            #> [13] \"gerpevir\"          \"hascovir\"          \"maynar\"            #> [16] \"novirus\"           \"poviral\"           \"sitavig\"           #> [19] \"sitavir\"           \"vipral\"            \"viropump\"          #> [22] \"virorax\"           \"zovirax\"           \"zyclir\"            av_group(\"ACI\") #> [1] \"Nucleosides and nucleotides excl. reverse transcriptase inhibitors\" av_url(\"ACI\") #>                                                              Aciclovir  #> \"https://atcddd.fhi.no/atc_ddd_index/?code=J05AB01&showdescription=no\"   # lowercase transformation av_name(x = c(\"ACI\", \"VALA\")) #> [1] \"Aciclovir\"    \"Valaciclovir\" av_name(x = c(\"ACI\", \"VALA\"), tolower = TRUE) #> [1] \"aciclovir\"    \"valaciclovir\"  # defined daily doses (DDD) av_ddd(\"ACI\", \"oral\") #> [1] 4 av_ddd_units(\"ACI\", \"oral\") #> [1] \"g\" av_ddd(\"ACI\", \"iv\") #> [1] 4 av_ddd_units(\"ACI\", \"iv\") #> [1] \"g\"  av_info(\"ACI\") # all properties as a list #> $av #> [1] \"ACI\" #>  #> $cid #> [1] 135398513 #>  #> $name #> [1] \"Aciclovir\" #>  #> $group #> [1] \"Nucleosides and nucleotides excl. reverse transcriptase inhibitors\" #>  #> $atc #> [1] \"J05AB01\" #>  #> $tradenames #>  [1] \"acicloftal\"        \"aciclovier\"        \"aciclovirum\"       #>  [4] \"activir\"           \"acyclofoam\"        \"acycloguanosine\"   #>  [7] \"acyclovir\"         \"acyclovir lauriad\" \"avaclyr\"           #> [10] \"cargosil\"          \"cyclovir\"          \"genvir\"            #> [13] \"gerpevir\"          \"hascovir\"          \"maynar\"            #> [16] \"novirus\"           \"poviral\"           \"sitavig\"           #> [19] \"sitavir\"           \"vipral\"            \"viropump\"          #> [22] \"virorax\"           \"zovirax\"           \"zyclir\"            #>  #> $loinc #> [1] \"\" #>  #> $ddd #> $ddd$oral #> $ddd$oral$amount #> [1] 4 #>  #> $ddd$oral$units #> [1] \"g\" #>  #>  #> $ddd$iv #> $ddd$iv$amount #> [1] 4 #>  #> $ddd$iv$units #> [1] \"g\" #>  #>  #>   # all av_* functions use as.av() internally, so you can go from 'any' to 'any': av_atc(\"ACI\") #> [1] \"J05AB01\" av_group(\"J05AB01\") #> [1] \"Nucleosides and nucleotides excl. reverse transcriptase inhibitors\" av_loinc(\"abacavir\") #> [1] \"29113-8\" \"30273-7\" \"30287-7\" \"30303-2\" \"78772-1\" \"78773-9\" \"79134-3\" #> [8] \"80118-3\" av_name(\"29113-8\") #> [1] \"Abacavir\" av_name(135398513) #> [1] \"Aciclovir\" av_name(\"J05AB01\") #> [1] \"Aciclovir\""},{"path":"https://msberends.github.io/AMR/reference/availability.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Availability of Columns — availability","title":"Check Availability of Columns — availability","text":"Easy check data availability columns data set. makes easy get idea antimicrobial combinations can used calculation e.g. susceptibility() resistance().","code":""},{"path":"https://msberends.github.io/AMR/reference/availability.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Availability of Columns — availability","text":"","code":"availability(tbl, width = NULL)"},{"path":"https://msberends.github.io/AMR/reference/availability.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Availability of Columns — availability","text":"tbl data.frame list width number characters present visual availability - default filling width console","code":""},{"path":"https://msberends.github.io/AMR/reference/availability.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Availability of Columns — availability","text":"data.frame column names tbl row names","code":""},{"path":"https://msberends.github.io/AMR/reference/availability.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Check Availability of Columns — availability","text":"function returns data.frame columns \"resistant\" \"visual_resistance\". values columns calculated resistance().","code":""},{"path":"https://msberends.github.io/AMR/reference/availability.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check Availability of Columns — availability","text":"","code":"availability(example_isolates) #>         count available     visual_availabilty resistant      visual_resistance #> date     2000    100.0% |####################|                                  #> patient  2000    100.0% |####################|                                  #> age      2000    100.0% |####################|                                  #> gender   2000    100.0% |####################|                                  #> ward     2000    100.0% |####################|                                  #> mo       2000    100.0% |####################|                                  #> PEN      1629     81.5% |################----|     73.7% |##############------| #> OXA       365     18.3% |###-----------------|     31.2% |######--------------| #> FLC       943     47.2% |#########-----------|     29.5% |#####---------------| #> AMX      1350     67.5% |#############-------|     59.6% |###########---------| #> AMC      1879     94.0% |##################--|     23.7% |####----------------| #> AMP      1350     67.5% |#############-------|     59.6% |###########---------| #> TZP      1001     50.0% |##########----------|     12.6% |##------------------| #> CZO       446     22.3% |####----------------|     44.6% |########------------| #> FEP       724     36.2% |#######-------------|     14.2% |##------------------| #> CXM      1789     89.5% |#################---|     26.3% |#####---------------| #> FOX       818     40.9% |########------------|     27.4% |#####---------------| #> CTX       943     47.2% |#########-----------|     15.5% |###-----------------| #> CAZ      1811     90.6% |##################--|     66.5% |#############-------| #> CRO       943     47.2% |#########-----------|     15.5% |###-----------------| #> GEN      1855     92.8% |##################--|     24.6% |####----------------| #> TOB      1351     67.6% |#############-------|     34.4% |######--------------| #> AMK       692     34.6% |######--------------|     63.7% |############--------| #> KAN       471     23.6% |####----------------|    100.0% |####################| #> TMP      1499     75.0% |###############-----|     38.1% |#######-------------| #> SXT      1759     88.0% |#################---|     20.5% |####----------------| #> NIT       743     37.2% |#######-------------|     17.1% |###-----------------| #> FOS       351     17.6% |###-----------------|     42.2% |########------------| #> LNZ      1023     51.2% |##########----------|     69.3% |#############-------| #> CIP      1409     70.5% |#############-------|     16.2% |###-----------------| #> MFX       211     10.6% |##------------------|     33.6% |######--------------| #> VAN      1861     93.1% |##################--|     38.3% |#######-------------| #> TEC       976     48.8% |#########-----------|     75.7% |###############-----| #> TCY      1200     60.0% |###########---------|     29.8% |#####---------------| #> TGC       798     39.9% |########------------|     12.7% |##------------------| #> DOX      1136     56.8% |###########---------|     27.7% |#####---------------| #> ERY      1894     94.7% |##################--|     57.2% |###########---------| #> CLI      1520     76.0% |###############-----|     61.2% |############--------| #> AZM      1894     94.7% |##################--|     57.2% |###########---------| #> IPM       889     44.5% |########------------|      6.2% |#-------------------| #> MEM       829     41.5% |########------------|      5.9% |#-------------------| #> MTR        34      1.7% |--------------------|     14.7% |##------------------| #> CHL       154      7.7% |#-------------------|     21.4% |####----------------| #> COL      1640     82.0% |################----|     81.2% |################----| #> MUP       270     13.5% |##------------------|      5.9% |#-------------------| #> RIF      1003     50.2% |##########----------|     69.6% |#############-------| # \\donttest{ if (require(\"dplyr\")) {   example_isolates %>%     filter(mo == as.mo(\"Escherichia coli\")) %>%     select_if(is.sir) %>%     availability() } #>     count available       visual_availabilty resistant        visual_resistance #> PEN   467    100.0% |######################|    100.0% |######################| #> OXA     0      0.0% |----------------------|                                    #> FLC     0      0.0% |----------------------|                                    #> AMX   392     83.9% |##################----|     50.0% |###########-----------| #> AMC   467    100.0% |######################|     13.1% |##--------------------| #> AMP   392     83.9% |##################----|     50.0% |###########-----------| #> TZP   416     89.1% |###################---|      5.5% |#---------------------| #> CZO    82     17.6% |###-------------------|      2.4% |----------------------| #> FEP   317     67.9% |##############--------|      2.8% |----------------------| #> CXM   465     99.6% |######################|      5.4% |#---------------------| #> FOX   377     80.7% |#################-----|      6.9% |#---------------------| #> CTX   459     98.3% |#####################-|      2.4% |----------------------| #> CAZ   460     98.5% |#####################-|      2.4% |----------------------| #> CRO   459     98.3% |#####################-|      2.4% |----------------------| #> GEN   460     98.5% |#####################-|      2.0% |----------------------| #> TOB   462     98.9% |#####################-|      2.6% |----------------------| #> AMK   171     36.6% |########--------------|      0.0% |----------------------| #> KAN     0      0.0% |----------------------|                                    #> TMP   396     84.8% |##################----|     39.1% |########--------------| #> SXT   465     99.6% |######################|     31.6% |######----------------| #> NIT   458     98.1% |#####################-|      2.8% |----------------------| #> FOS    61     13.1% |##--------------------|      0.0% |----------------------| #> LNZ   467    100.0% |######################|    100.0% |######################| #> CIP   456     97.6% |#####################-|     12.5% |##--------------------| #> MFX    57     12.2% |##--------------------|    100.0% |######################| #> VAN   467    100.0% |######################|    100.0% |######################| #> TEC   467    100.0% |######################|    100.0% |######################| #> TCY     3      0.6% |----------------------|     66.7% |##############--------| #> TGC    68     14.6% |###-------------------|      0.0% |----------------------| #> DOX     0      0.0% |----------------------|                                    #> ERY   467    100.0% |######################|    100.0% |######################| #> CLI   467    100.0% |######################|    100.0% |######################| #> AZM   467    100.0% |######################|    100.0% |######################| #> IPM   422     90.4% |###################---|      0.0% |----------------------| #> MEM   418     89.5% |###################---|      0.0% |----------------------| #> MTR     2      0.4% |----------------------|      0.0% |----------------------| #> CHL     0      0.0% |----------------------|                                    #> COL   240     51.4% |###########-----------|      0.0% |----------------------| #> MUP     0      0.0% |----------------------|                                    #> RIF   467    100.0% |######################|    100.0% |######################| # }"},{"path":"https://msberends.github.io/AMR/reference/bug_drug_combinations.html","id":null,"dir":"Reference","previous_headings":"","what":"Determine Bug-Drug Combinations — bug_drug_combinations","title":"Determine Bug-Drug Combinations — bug_drug_combinations","text":"Determine antimicrobial resistance (AMR) bug-drug combinations data set least 30 (default) isolates available per species. Use format() result prettify publishable/printable format, see Examples.","code":""},{"path":"https://msberends.github.io/AMR/reference/bug_drug_combinations.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Determine Bug-Drug Combinations — bug_drug_combinations","text":"","code":"bug_drug_combinations(x, col_mo = NULL, FUN = mo_shortname, ...)  # S3 method for class 'bug_drug_combinations' format(   x,   translate_ab = \"name (ab, atc)\",   language = get_AMR_locale(),   minimum = 30,   combine_SI = TRUE,   add_ab_group = TRUE,   remove_intrinsic_resistant = FALSE,   decimal.mark = getOption(\"OutDec\"),   big.mark = ifelse(decimal.mark == \",\", \".\", \",\"),   ... )"},{"path":"https://msberends.github.io/AMR/reference/bug_drug_combinations.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Determine Bug-Drug Combinations — bug_drug_combinations","text":"x data set antibiotic columns, amox, AMX AMC col_mo column name names codes microorganisms (see .mo()) - default first column class mo. Values coerced using .mo(). FUN function call mo column transform microorganism codes - default mo_shortname() ... arguments passed FUN translate_ab character length 1 containing column names antibiotics data set language language returned text - default current system language (see get_AMR_locale()) can also set package option AMR_locale. Use language = NULL language = \"\" prevent translation. minimum minimum allowed number available (tested) isolates. isolate count lower minimum return NA warning. default number 30 isolates advised Clinical Laboratory Standards Institute (CLSI) best practice, see Source. combine_SI logical indicate whether values S summed, resistance based R - default TRUE add_ab_group logical indicate group antimicrobials must included first column remove_intrinsic_resistant logical indicate rows columns 100% resistance tested antimicrobials must removed table decimal.mark character used indicate numeric     decimal point. big.mark character; empty used mark every     big.interval decimals (hence big)     decimal point.","code":""},{"path":"https://msberends.github.io/AMR/reference/bug_drug_combinations.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Determine Bug-Drug Combinations — bug_drug_combinations","text":"function bug_drug_combinations() returns data.frame columns \"mo\", \"ab\", \"S\", \"SDD\", \"\", \"R\", \"total\".","code":""},{"path":"https://msberends.github.io/AMR/reference/bug_drug_combinations.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Determine Bug-Drug Combinations — bug_drug_combinations","text":"function format() calculates resistance per bug-drug combination returns table ready reporting/publishing. Use combine_SI = TRUE (default) test R vs. S+combine_SI = FALSE test R+vs. S. table can also directly used R Markdown / Quarto without need e.g. knitr::kable().","code":""},{"path":"https://msberends.github.io/AMR/reference/bug_drug_combinations.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Determine Bug-Drug Combinations — bug_drug_combinations","text":"","code":"# example_isolates is a data set available in the AMR package. # run ?example_isolates for more info. example_isolates #> # A tibble: 2,000 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-03 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  3 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  4 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  5 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  6 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  7 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  8 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  9 2002-01-16 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #> 10 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R     NA    S     NA    #> # ℹ 1,990 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, …  # \\donttest{ x <- bug_drug_combinations(example_isolates) head(x) #> # A tibble: 6 × 9 #>   mo                ab        S   SDD     I     R    NI total N     #>   <chr>             <chr> <int> <int> <int> <int> <int> <int> <lgl> #> 1 (unknown species) AMC      15     0     0     0     0    15 NA    #> 2 (unknown species) AMK       0     0     0     0     0     0 NA    #> 3 (unknown species) AMP      15     0     0     1     0    16 NA    #> 4 (unknown species) AMX      15     0     0     1     0    16 NA    #> 5 (unknown species) AZM       3     0     0     3     0     6 NA    #> 6 (unknown species) CAZ       0     0     0     0     0     0 NA    #> Use 'format()' on this result to get a publishable/printable format. format(x, translate_ab = \"name (atc)\") #> # A tibble: 39 × 12 #>    Group     Drug  CoNS  `E. coli` `E. faecalis` `K. pneumoniae` `P. aeruginosa` #>    <chr>     <chr> <chr> <chr>     <chr>         <chr>           <chr>           #>  1 \"Aminogl… Amik… \"100… \"  0.0% … \"100.0% (39/… \"\"              \"\"              #>  2 \"\"        Gent… \" 13… \"  2.0% … \"100.0% (39/… \" 10.3% (6/58)\" \"  0.0% (0/30)\" #>  3 \"\"        Kana… \"100… \"\"        \"100.0% (39/… \"\"              \"100.0% (30/30… #>  4 \"\"        Tobr… \" 78… \"  2.6% … \"100.0% (39/… \" 10.3% (6/58)\" \"  0.0% (0/30)\" #>  5 \"Ampheni… Chlo… \"\"    \"\"        \"\"            \"\"              \"100.0% (30/30… #>  6 \"Antimyc… Rifa… \"\"    \"100.0% … \"\"            \"100.0% (58/58… \"100.0% (30/30… #>  7 \"Beta-la… Amox… \" 93… \" 50.0% … \"\"            \"100.0% (58/58… \"100.0% (30/30… #>  8 \"\"        Amox… \" 42… \" 13.1% … \"\"            \" 10.3% (6/58)\" \"100.0% (30/30… #>  9 \"\"        Ampi… \" 93… \" 50.0% … \"\"            \"100.0% (58/58… \"100.0% (30/30… #> 10 \"\"        Benz… \" 77… \"100.0% … \"\"            \"100.0% (58/58… \"100.0% (30/30… #> # ℹ 29 more rows #> # ℹ 5 more variables: `P. mirabilis` <chr>, `S. aureus` <chr>, #> #   `S. epidermidis` <chr>, `S. hominis` <chr>, `S. pneumoniae` <chr>  # Use FUN to change to transformation of microorganism codes bug_drug_combinations(example_isolates,   FUN = mo_gramstain ) #> # A tibble: 80 × 9 #>    mo            ab        S   SDD     I     R    NI total N     #>  * <chr>         <chr> <int> <int> <int> <int> <int> <int> <lgl> #>  1 Gram-negative AMC     463     0    89   174     0   726 NA    #>  2 Gram-negative AMK     251     0     0     5     0   256 NA    #>  3 Gram-negative AMP     226     0     0   405     0   631 NA    #>  4 Gram-negative AMX     226     0     0   405     0   631 NA    #>  5 Gram-negative AZM       1     0     2   696     0   699 NA    #>  6 Gram-negative CAZ     607     0     0    27     0   634 NA    #>  7 Gram-negative CHL       1     0     0    30     0    31 NA    #>  8 Gram-negative CIP     610     0    11    63     0   684 NA    #>  9 Gram-negative CLI      18     0     1   709     0   728 NA    #> 10 Gram-negative COL     309     0     0    78     0   387 NA    #> # ℹ 70 more rows #> Use 'format()' on this result to get a publishable/printable format.  bug_drug_combinations(example_isolates,   FUN = function(x) {     ifelse(x == as.mo(\"Escherichia coli\"),       \"E. coli\",       \"Others\"     )   } ) #> # A tibble: 80 × 9 #>    mo      ab        S   SDD     I     R    NI total N     #>  * <chr>   <chr> <int> <int> <int> <int> <int> <int> <lgl> #>  1 E. coli AMC     332     0    74    61     0   467 NA    #>  2 E. coli AMK     171     0     0     0     0   171 NA    #>  3 E. coli AMP     196     0     0   196     0   392 NA    #>  4 E. coli AMX     196     0     0   196     0   392 NA    #>  5 E. coli AZM       0     0     0   467     0   467 NA    #>  6 E. coli CAZ     449     0     0    11     0   460 NA    #>  7 E. coli CHL       0     0     0     0     0     0 NA    #>  8 E. coli CIP     398     0     1    57     0   456 NA    #>  9 E. coli CLI       0     0     0   467     0   467 NA    #> 10 E. coli COL     240     0     0     0     0   240 NA    #> # ℹ 70 more rows #> Use 'format()' on this result to get a publishable/printable format. # }"},{"path":"https://msberends.github.io/AMR/reference/clinical_breakpoints.html","id":null,"dir":"Reference","previous_headings":"","what":"Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints","title":"Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints","text":"Data set containing clinical breakpoints interpret MIC disk diffusion SIR values, according international guidelines. dataset contain breakpoints humans, 7 different animal groups, ECOFFs. Currently available breakpoint guidelines clinical microbiology EUCAST 2011-2024 CLSI 2011-2024. Currently available breakpoint guidelines veterinary microbiology EUCAST 2021-2024 CLSI 2019-2024. Use .sir() transform MICs disks measurements SIR values.","code":""},{"path":"https://msberends.github.io/AMR/reference/clinical_breakpoints.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints","text":"","code":"clinical_breakpoints"},{"path":"https://msberends.github.io/AMR/reference/clinical_breakpoints.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints","text":"tibble 34 063 observations 14 variables: guideline Name guideline type Breakpoint type, either \"ECOFF\", \"animal\", \"human\" host Host infectious agent. mostly useful veterinary breakpoints either \"ECOFF\", \"aquatic\", \"cats\", \"cattle\", \"dogs\", \"horse\", \"human\", \"poultry\", \"swine\" method Testing method, either \"DISK\" \"MIC\" site Body site breakpoint must applied, e.g. \"Oral\" \"Respiratory\" mo Microbial ID, see .mo() rank_index Taxonomic rank index mo 1 (subspecies/infraspecies) 5 (unknown microorganism) ab Antibiotic code used package, EARS-Net WHONET, see .ab() ref_tbl Info guideline rule can found disk_dose Dose used disk diffusion method breakpoint_S Lowest MIC value highest number millimetres leads \"S\" breakpoint_R Highest MIC value lowest number millimetres leads \"R\" uti logical value (TRUE/FALSE) indicate whether rule applies urinary tract infection (UTI) is_SDD logical value (TRUE/FALSE) indicate whether intermediate range \"S\" \"R\" interpreted \"SDD\", instead \"\". currently applies 24 breakpoints.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/clinical_breakpoints.html","id":"different-types-of-breakpoints","dir":"Reference","previous_headings":"","what":"Different types of breakpoints","title":"Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints","text":"Supported types breakpoints ECOFF, animal, human. ECOFF (Epidemiological cut-) values used antimicrobial susceptibility testing differentiate wild-type non-wild-type strains bacteria fungi. default \"human\", can also set package option AMR_breakpoint_type. Use .sir(..., breakpoint_type = ...) interpret raw data using specific breakpoint type, e.g. .sir(..., breakpoint_type = \"ECOFF\") use ECOFFs.","code":""},{"path":"https://msberends.github.io/AMR/reference/clinical_breakpoints.html","id":"imported-from-whonet","dir":"Reference","previous_headings":"","what":"Imported from WHONET","title":"Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints","text":"Clinical breakpoints package validated imported WHONET, free desktop Windows application developed supported Collaborating Centre Surveillance Antimicrobial Resistance. can read website. developers WHONET AMR package contact sharing work. highly appreciate great development WHONET software.","code":""},{"path":"https://msberends.github.io/AMR/reference/clinical_breakpoints.html","id":"response-from-clsi-and-eucast","dir":"Reference","previous_headings":"","what":"Response from CLSI and EUCAST","title":"Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints","text":"CEO CLSI chairman EUCAST endorsed work public use AMR package (consequently use breakpoints) June 2023, future development distributing clinical breakpoints discussed meeting CLSI, EUCAST, , developers WHONET software, developers AMR package.","code":""},{"path":"https://msberends.github.io/AMR/reference/clinical_breakpoints.html","id":"download","dir":"Reference","previous_headings":"","what":"Download","title":"Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints","text":"Like data sets package, data set publicly available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. Please visit website download links. actual files course available GitHub repository. allow machine reading EUCAST CLSI guidelines, almost impossible MS Excel PDF files distributed EUCAST CLSI, though initiatives started overcome burdens. NOTE: AMR package (WHONET software well) contains rather complex internal methods apply guidelines. example, breakpoints must applied certain species groups (case package available microorganisms.groups data set). important considered using breakpoints use.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/clinical_breakpoints.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints","text":"","code":"clinical_breakpoints #> # A tibble: 34,063 × 14 #>    guideline   type  host  method site    mo            rank_index ab   ref_tbl  #>    <chr>       <chr> <chr> <chr>  <chr>   <mo>               <dbl> <ab> <chr>    #>  1 EUCAST 2024 human human DISK   NA      B_ACHRMB_XYLS          2 MEM  A. xylo… #>  2 EUCAST 2024 human human MIC    NA      B_ACHRMB_XYLS          2 MEM  A. xylo… #>  3 EUCAST 2024 human human DISK   NA      B_ACHRMB_XYLS          2 SXT  A. xylo… #>  4 EUCAST 2024 human human MIC    NA      B_ACHRMB_XYLS          2 SXT  A. xylo… #>  5 EUCAST 2024 human human DISK   NA      B_ACHRMB_XYLS          2 TZP  A. xylo… #>  6 EUCAST 2024 human human MIC    NA      B_ACHRMB_XYLS          2 TZP  A. xylo… #>  7 EUCAST 2024 human human DISK   NA      B_ACNTB                3 AMK  Acineto… #>  8 EUCAST 2024 human human DISK   Uncomp… B_ACNTB                3 AMK  Acineto… #>  9 EUCAST 2024 human human MIC    NA      B_ACNTB                3 AMK  Acineto… #> 10 EUCAST 2024 human human MIC    Uncomp… B_ACNTB                3 AMK  Acineto… #> # ℹ 34,053 more rows #> # ℹ 5 more variables: disk_dose <chr>, breakpoint_S <dbl>, breakpoint_R <dbl>, #> #   uti <lgl>, is_SDD <lgl>"},{"path":"https://msberends.github.io/AMR/reference/count.html","id":null,"dir":"Reference","previous_headings":"","what":"Count Available Isolates — count","title":"Count Available Isolates — count","text":"functions can used count resistant/susceptible microbial isolates. functions support quasiquotation pipes, can used summarise() dplyr package also support grouped variables, see Examples. count_resistant() used count resistant isolates, count_susceptible() used count susceptible isolates.","code":""},{"path":"https://msberends.github.io/AMR/reference/count.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Count Available Isolates — count","text":"","code":"count_resistant(..., only_all_tested = FALSE)  count_susceptible(..., only_all_tested = FALSE)  count_S(..., only_all_tested = FALSE)  count_SI(..., only_all_tested = FALSE)  count_I(..., only_all_tested = FALSE)  count_IR(..., only_all_tested = FALSE)  count_R(..., only_all_tested = FALSE)  count_all(..., only_all_tested = FALSE)  n_sir(..., only_all_tested = FALSE)  count_df(   data,   translate_ab = \"name\",   language = get_AMR_locale(),   combine_SI = TRUE )"},{"path":"https://msberends.github.io/AMR/reference/count.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Count Available Isolates — count","text":"... one vectors (columns) antibiotic interpretations. transformed internally .sir() needed. only_all_tested (combination therapies, .e. using one variable ...): logical indicate isolates must tested antibiotics, see section Combination Therapy data data.frame containing columns class sir (see .sir()) translate_ab column name antibiotics data set translate antibiotic abbreviations , using ab_property() language language returned text - default current system language (see get_AMR_locale()) can also set package option AMR_locale. Use language = NULL language = \"\" prevent translation. combine_SI logical indicate whether values S must merged one, output consists S+vs. R (susceptible vs. resistant) - default TRUE","code":""},{"path":"https://msberends.github.io/AMR/reference/count.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Count Available Isolates — count","text":"integer","code":""},{"path":"https://msberends.github.io/AMR/reference/count.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Count Available Isolates — count","text":"functions meant count isolates. Use resistance()/susceptibility() functions calculate microbial resistance/susceptibility. function count_resistant() equal function count_R(). function count_susceptible() equal function count_SI(). function n_sir() alias count_all(). can used count available isolates, .e. input antibiotics available result (S, R). use equal n_distinct(). function equal count_susceptible(...) + count_resistant(...). function count_df() takes variable data sir class (created .sir()) counts number S's, 's R's. also supports grouped variables. function sir_df() works exactly like count_df(), adds percentage S, R.","code":""},{"path":"https://msberends.github.io/AMR/reference/count.html","id":"interpretation-of-sir","dir":"Reference","previous_headings":"","what":"Interpretation of SIR","title":"Count Available Isolates — count","text":"2019, European Committee Antimicrobial Susceptibility Testing (EUCAST) decided change definitions susceptibility testing categories S, , R shown (https://www.eucast.org/newsiandr): S - Susceptible, standard dosing regimen microorganism categorised \"Susceptible, standard dosing regimen\", high likelihood therapeutic success using standard dosing regimen agent. - Susceptible, increased exposure  microorganism categorised \"Susceptible, Increased exposure\" high likelihood therapeutic success exposure agent increased adjusting dosing regimen concentration site infection. R = Resistant microorganism categorised \"Resistant\" high likelihood therapeutic failure even increased exposure. Exposure function mode administration, dose, dosing interval, infusion time, well distribution excretion antimicrobial agent influence infecting organism site infection. AMR package honours insight. Use susceptibility() (equal proportion_SI()) determine antimicrobial susceptibility count_susceptible() (equal count_SI()) count susceptible isolates.","code":""},{"path":"https://msberends.github.io/AMR/reference/count.html","id":"combination-therapy","dir":"Reference","previous_headings":"","what":"Combination Therapy","title":"Count Available Isolates — count","text":"using one variable ... (= combination therapy), use only_all_tested count isolates tested antibiotics/variables test . See example two antibiotics, Drug Drug B, susceptibility() works calculate %SI:   Please note , combination therapies, only_all_tested = TRUE applies :   , combination therapies, only_all_tested = FALSE applies :   Using only_all_tested impact using one antibiotic input.","code":"--------------------------------------------------------------------                     only_all_tested = FALSE  only_all_tested = TRUE                     -----------------------  -----------------------  Drug A    Drug B   include as  include as   include as  include as                     numerator   denominator  numerator   denominator --------  --------  ----------  -----------  ----------  -----------  S or I    S or I       X            X            X            X    R       S or I       X            X            X            X   <NA>     S or I       X            X            -            -  S or I      R          X            X            X            X    R         R          -            X            -            X   <NA>       R          -            -            -            -  S or I     <NA>        X            X            -            -    R        <NA>        -            -            -            -   <NA>      <NA>        -            -            -            - -------------------------------------------------------------------- count_S()    +   count_I()    +   count_R()    = count_all()   proportion_S() + proportion_I() + proportion_R() = 1 count_S()    +   count_I()    +   count_R()    >= count_all()   proportion_S() + proportion_I() + proportion_R() >= 1"},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/count.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Count Available Isolates — count","text":"","code":"# example_isolates is a data set available in the AMR package. # run ?example_isolates for more info.  # base R ------------------------------------------------------------ count_resistant(example_isolates$AMX) # counts \"R\" #> [1] 804 count_susceptible(example_isolates$AMX) # counts \"S\" and \"I\" #> [1] 546 count_all(example_isolates$AMX) # counts \"S\", \"I\" and \"R\" #> [1] 1350  # be more specific count_S(example_isolates$AMX) #> Using count_S() is discouraged; use count_susceptible() instead to also #> consider \"I\" and \"SDD\" being susceptible. This note will be shown once for #> this session. #> [1] 543 count_SI(example_isolates$AMX) #> Note that count_SI() will also count dose-dependent susceptibility, #> 'SDD'. This note will be shown once for this session. #> [1] 546 count_I(example_isolates$AMX) #> Note that count_I() will also count dose-dependent susceptibility, 'SDD'. #> This note will be shown once for this session. #> [1] 3 count_IR(example_isolates$AMX) #> Using count_IR() is discouraged; use count_resistant() instead to not #> consider \"I\" and \"SDD\" being resistant. This note will be shown once for #> this session. #> [1] 807 count_R(example_isolates$AMX) #> [1] 804  # Count all available isolates count_all(example_isolates$AMX) #> [1] 1350 n_sir(example_isolates$AMX) #> [1] 1350  # n_sir() is an alias of count_all(). # Since it counts all available isolates, you can # calculate back to count e.g. susceptible isolates. # These results are the same: count_susceptible(example_isolates$AMX) #> [1] 546 susceptibility(example_isolates$AMX) * n_sir(example_isolates$AMX) #> [1] 546  # dplyr ------------------------------------------------------------- # \\donttest{ if (require(\"dplyr\")) {   example_isolates %>%     group_by(ward) %>%     summarise(       R = count_R(CIP),       I = count_I(CIP),       S = count_S(CIP),       n1 = count_all(CIP), # the actual total; sum of all three       n2 = n_sir(CIP), # same - analogous to n_distinct       total = n()     ) # NOT the number of tested isolates!    # Number of available isolates for a whole antibiotic class   # (i.e., in this data set columns GEN, TOB, AMK, KAN)   example_isolates %>%     group_by(ward) %>%     summarise(across(aminoglycosides(), n_sir))    # Count co-resistance between amoxicillin/clav acid and gentamicin,   # so we can see that combination therapy does a lot more than mono therapy.   # Please mind that `susceptibility()` calculates percentages right away instead.   example_isolates %>% count_susceptible(AMC) # 1433   example_isolates %>% count_all(AMC) # 1879    example_isolates %>% count_susceptible(GEN) # 1399   example_isolates %>% count_all(GEN) # 1855    example_isolates %>% count_susceptible(AMC, GEN) # 1764   example_isolates %>% count_all(AMC, GEN) # 1936    # Get number of S+I vs. R immediately of selected columns   example_isolates %>%     select(AMX, CIP) %>%     count_df(translate = FALSE)    # It also supports grouping variables   example_isolates %>%     select(ward, AMX, CIP) %>%     group_by(ward) %>%     count_df(translate = FALSE) } #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> # A tibble: 12 × 4 #>    ward       antibiotic interpretation value #>  * <chr>      <chr>      <ord>          <int> #>  1 Clinical   AMX        SI               357 #>  2 Clinical   AMX        R                487 #>  3 Clinical   CIP        SI               741 #>  4 Clinical   CIP        R                128 #>  5 ICU        AMX        SI               158 #>  6 ICU        AMX        R                270 #>  7 ICU        CIP        SI               362 #>  8 ICU        CIP        R                 85 #>  9 Outpatient AMX        SI                31 #> 10 Outpatient AMX        R                 47 #> 11 Outpatient CIP        SI                78 #> 12 Outpatient CIP        R                 15 # }"},{"path":"https://msberends.github.io/AMR/reference/custom_eucast_rules.html","id":null,"dir":"Reference","previous_headings":"","what":"Define Custom EUCAST Rules — custom_eucast_rules","title":"Define Custom EUCAST Rules — custom_eucast_rules","text":"Define custom EUCAST rules organisation specific analysis use output function eucast_rules().","code":""},{"path":"https://msberends.github.io/AMR/reference/custom_eucast_rules.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Define Custom EUCAST Rules — custom_eucast_rules","text":"","code":"custom_eucast_rules(...)"},{"path":"https://msberends.github.io/AMR/reference/custom_eucast_rules.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Define Custom EUCAST Rules — custom_eucast_rules","text":"... rules formula notation, see instructions, Examples","code":""},{"path":"https://msberends.github.io/AMR/reference/custom_eucast_rules.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Define Custom EUCAST Rules — custom_eucast_rules","text":"list containing custom rules","code":""},{"path":"https://msberends.github.io/AMR/reference/custom_eucast_rules.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Define Custom EUCAST Rules — custom_eucast_rules","text":"organisations adoption EUCAST rules. function can used define custom EUCAST rules used eucast_rules() function.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/custom_eucast_rules.html","id":"basics","dir":"Reference","previous_headings":"","what":"Basics","title":"Define Custom EUCAST Rules — custom_eucast_rules","text":"familiar case_when() function dplyr package, recognise input method set rules. Rules must set using R considers 'formula notation'. rule written tilde (~) consequence rule written tilde:   two custom EUCAST rules: TZP (piperacillin/tazobactam) \"S\", aminopenicillins (ampicillin amoxicillin) must made \"S\", TZP \"R\", aminopenicillins must made \"R\". rules can also printed console, immediately clear work:   rules (part tilde, example TZP == \"S\" TZP == \"R\") must evaluable data set: able run filter data set without errors. means example column TZP must exist. create sample data set test rules set:","code":"x <- custom_eucast_rules(TZP == \"S\" ~ aminopenicillins == \"S\",                          TZP == \"R\" ~ aminopenicillins == \"R\") x #> A set of custom EUCAST rules: #> #>   1. If TZP is \"S\" then set to  S : #>      amoxicillin (AMX), ampicillin (AMP) #> #>   2. If TZP is \"R\" then set to  R : #>      amoxicillin (AMX), ampicillin (AMP) df <- data.frame(mo = c(\"Escherichia coli\", \"Klebsiella pneumoniae\"),                  TZP = as.sir(\"R\"),                  ampi = as.sir(\"S\"),                  cipro = as.sir(\"S\")) df #>                      mo TZP ampi cipro #> 1      Escherichia coli   R    S     S #> 2 Klebsiella pneumoniae   R    S     S  eucast_rules(df, rules = \"custom\", custom_rules = x, info = FALSE) #>                      mo TZP ampi cipro #> 1      Escherichia coli   R    R     S #> 2 Klebsiella pneumoniae   R    R     S"},{"path":"https://msberends.github.io/AMR/reference/custom_eucast_rules.html","id":"using-taxonomic-properties-in-rules","dir":"Reference","previous_headings":"","what":"Using taxonomic properties in rules","title":"Define Custom EUCAST Rules — custom_eucast_rules","text":"one exception columns used rules: column names microorganisms data set can also used, exist data set. column names : \"mo\", \"fullname\", \"status\", \"kingdom\", \"phylum\", \"class\", \"order\", \"family\", \"genus\", \"species\", \"subspecies\", \"rank\", \"ref\", \"oxygen_tolerance\", \"source\", \"lpsn\", \"lpsn_parent\", \"lpsn_renamed_to\", \"mycobank\", \"mycobank_parent\", \"mycobank_renamed_to\", \"gbif\", \"gbif_parent\", \"gbif_renamed_to\", \"prevalence\", \"snomed\". Thus, next example work well, despite fact df data set contain column genus:","code":"y <- custom_eucast_rules(TZP == \"S\" & genus == \"Klebsiella\" ~ aminopenicillins == \"S\",                          TZP == \"R\" & genus == \"Klebsiella\" ~ aminopenicillins == \"R\")  eucast_rules(df, rules = \"custom\", custom_rules = y, info = FALSE) #>                      mo TZP ampi cipro #> 1      Escherichia coli   R    S     S #> 2 Klebsiella pneumoniae   R    R     S"},{"path":"https://msberends.github.io/AMR/reference/custom_eucast_rules.html","id":"usage-of-multiple-antibiotics-and-antibiotic-group-names","dir":"Reference","previous_headings":"","what":"Usage of multiple antibiotics and antibiotic group names","title":"Define Custom EUCAST Rules — custom_eucast_rules","text":"can define antibiotic groups instead single antibiotics rule consequence, part tilde (~). examples , antibiotic group aminopenicillins includes ampicillin amoxicillin. Rules can also applied multiple antibiotics antibiotic groups simultaneously. Use c() function combine multiple antibiotics. instance, following example sets aminopenicillins ureidopenicillins \"R\" column TZP (piperacillin/tazobactam) \"R\":   30 antibiotic groups allowed rules (case-insensitive) can used combination: aminoglycosides(amikacin, amikacin/fosfomycin, apramycin, arbekacin, astromicin, bekanamycin, dibekacin, framycetin, gentamicin, gentamicin-high, habekacin, hygromycin, isepamicin, kanamycin, kanamycin-high, kanamycin/cephalexin, micronomicin, neomycin, netilmicin, pentisomicin, plazomicin, propikacin, ribostamycin, sisomicin, streptoduocin, streptomycin, streptomycin-high, tobramycin, tobramycin-high) aminopenicillins(amoxicillin ampicillin) antifungals(amorolfine, amphotericin B, amphotericin B-high, anidulafungin, butoconazole, caspofungin, ciclopirox, clotrimazole, econazole, fluconazole, flucytosine, fosfluconazole, griseofulvin, hachimycin, ibrexafungerp, isavuconazole, isoconazole, itraconazole, ketoconazole, manogepix, micafungin, miconazole, nystatin, oteseconazole, pimaricin, posaconazole, rezafungin, ribociclib, sulconazole, terbinafine, terconazole, voriconazole) antimycobacterials(4-aminosalicylic acid, calcium aminosalicylate, capreomycin, clofazimine, delamanid, enviomycin, ethambutol, ethambutol/isoniazid, ethionamide, isoniazid, isoniazid/sulfamethoxazole/trimethoprim/pyridoxine, morinamide, p-aminosalicylic acid, pretomanid, protionamide, pyrazinamide, rifabutin, rifampicin, rifampicin/ethambutol/isoniazid, rifampicin/isoniazid, rifampicin/pyrazinamide/ethambutol/isoniazid, rifampicin/pyrazinamide/isoniazid, rifamycin, rifapentine, simvastatin/fenofibrate, sodium aminosalicylate, streptomycin/isoniazid, terizidone, thioacetazone, thioacetazone/isoniazid, tiocarlide, viomycin) betalactams(amoxicillin, amoxicillin/clavulanic acid, amoxicillin/sulbactam, ampicillin, ampicillin/sulbactam, apalcillin, aspoxicillin, avibactam, azidocillin, azlocillin, aztreonam, aztreonam/avibactam, aztreonam/nacubactam, bacampicillin, benzathine benzylpenicillin, benzathine phenoxymethylpenicillin, benzylpenicillin, biapenem, carbenicillin, carindacillin, cefacetrile, cefaclor, cefadroxil, cefalexin, cefaloridine, cefalotin, cefamandole, cefapirin, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/nacubactam, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol, cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/tazobactam, ceftriaxone, ceftriaxone/beta-lactamase inhibitor, cefuroxime, cefuroxime axetil, cephradine, ciclacillin, clometocillin, cloxacillin, dicloxacillin, doripenem, epicillin, ertapenem, flucloxacillin, hetacillin, imipenem, imipenem/EDTA, imipenem/relebactam, latamoxef, lenampicillin, loracarbef, mecillinam, meropenem, meropenem/nacubactam, meropenem/vaborbactam, metampicillin, meticillin, mezlocillin, mezlocillin/sulbactam, nacubactam, nafcillin, oxacillin, panipenem, penamecillin, penicillin/novobiocin, penicillin/sulbactam, pheneticillin, phenoxymethylpenicillin, piperacillin, piperacillin/sulbactam, piperacillin/tazobactam, piridicillin, pivampicillin, pivmecillinam, procaine benzylpenicillin, propicillin, razupenem, ritipenem, ritipenem acoxil, sarmoxicillin, sulbactam, sulbenicillin, sultamicillin, talampicillin, tazobactam, tebipenem, temocillin, ticarcillin, ticarcillin/clavulanic acid) carbapenems(biapenem, doripenem, ertapenem, imipenem, imipenem/EDTA, imipenem/relebactam, meropenem, meropenem/nacubactam, meropenem/vaborbactam, panipenem, razupenem, ritipenem, ritipenem acoxil, tebipenem) cephalosporins(cefacetrile, cefaclor, cefadroxil, cefalexin, cefaloridine, cefalotin, cefamandole, cefapirin, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol, cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/tazobactam, ceftriaxone, ceftriaxone/beta-lactamase inhibitor, cefuroxime, cefuroxime axetil, cephradine, latamoxef, loracarbef) cephalosporins_1st(cefacetrile, cefadroxil, cefalexin, cefaloridine, cefalotin, cefapirin, cefatrizine, cefazedone, cefazolin, cefroxadine, ceftezole, cephradine) cephalosporins_2nd(cefaclor, cefamandole, cefmetazole, cefonicid, ceforanide, cefotetan, cefotiam, cefoxitin, cefoxitin screening, cefprozil, cefuroxime, cefuroxime axetil, loracarbef) cephalosporins_3rd(cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefetamet, cefetamet pivoxil, cefixime, cefmenoxime, cefodizime, cefoperazone, cefoperazone/sulbactam, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotiam hexetil, cefovecin, cefpimizole, cefpiramide, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefsulodin, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftriaxone, ceftriaxone/beta-lactamase inhibitor, latamoxef) cephalosporins_4th(cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetecol, cefoselis, cefozopran, cefpirome, cefquinome) cephalosporins_5th(ceftaroline, ceftaroline/avibactam, ceftobiprole, ceftobiprole medocaril, ceftolozane/tazobactam) cephalosporins_except_caz(cefacetrile, cefaclor, cefadroxil, cefalexin, cefaloridine, cefalotin, cefamandole, cefapirin, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol, cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/tazobactam, ceftriaxone, ceftriaxone/beta-lactamase inhibitor, cefuroxime, cefuroxime axetil, cephradine, latamoxef, loracarbef) fluoroquinolones(besifloxacin, ciprofloxacin, clinafloxacin, danofloxacin, delafloxacin, difloxacin, enoxacin, enrofloxacin, finafloxacin, fleroxacin, garenoxacin, gatifloxacin, gemifloxacin, grepafloxacin, lascufloxacin, levofloxacin, levonadifloxacin, lomefloxacin, marbofloxacin, metioxate, miloxacin, moxifloxacin, nadifloxacin, nifuroquine, norfloxacin, ofloxacin, orbifloxacin, pazufloxacin, pefloxacin, pradofloxacin, premafloxacin, prulifloxacin, rufloxacin, sarafloxacin, sitafloxacin, sparfloxacin, temafloxacin, tilbroquinol, tioxacin, tosufloxacin, trovafloxacin) glycopeptides(avoparcin, dalbavancin, norvancomycin, oritavancin, ramoplanin, teicoplanin, teicoplanin-macromethod, telavancin, vancomycin, vancomycin-macromethod) glycopeptides_except_lipo(avoparcin, norvancomycin, ramoplanin, teicoplanin, teicoplanin-macromethod, vancomycin, vancomycin-macromethod) lincosamides(acetylmidecamycin, acetylspiramycin, clindamycin, clindamycin inducible screening, gamithromycin, kitasamycin, lincomycin, meleumycin, nafithromycin, pirlimycin, primycin, solithromycin, tildipirosin, tilmicosin, tulathromycin, tylosin, tylvalosin) lipoglycopeptides(dalbavancin, oritavancin, telavancin) macrolides(acetylmidecamycin, acetylspiramycin, azithromycin, clarithromycin, dirithromycin, erythromycin, flurithromycin, gamithromycin, josamycin, kitasamycin, meleumycin, midecamycin, miocamycin, nafithromycin, oleandomycin, pirlimycin, primycin, rokitamycin, roxithromycin, solithromycin, spiramycin, telithromycin, tildipirosin, tilmicosin, troleandomycin, tulathromycin, tylosin, tylvalosin) nitrofurans(furazidin, furazolidone, nifurtoinol, nitrofurantoin, nitrofurazone) oxazolidinones(cadazolid, cycloserine, linezolid, tedizolid, thiacetazone) penicillins(amoxicillin, amoxicillin/clavulanic acid, amoxicillin/sulbactam, ampicillin, ampicillin/sulbactam, apalcillin, aspoxicillin, avibactam, azidocillin, azlocillin, aztreonam, aztreonam/avibactam, aztreonam/nacubactam, bacampicillin, benzathine benzylpenicillin, benzathine phenoxymethylpenicillin, benzylpenicillin, carbenicillin, carindacillin, cefepime/nacubactam, ciclacillin, clometocillin, cloxacillin, dicloxacillin, epicillin, flucloxacillin, hetacillin, lenampicillin, mecillinam, metampicillin, meticillin, mezlocillin, mezlocillin/sulbactam, nacubactam, nafcillin, oxacillin, penamecillin, penicillin/novobiocin, penicillin/sulbactam, pheneticillin, phenoxymethylpenicillin, piperacillin, piperacillin/sulbactam, piperacillin/tazobactam, piridicillin, pivampicillin, pivmecillinam, procaine benzylpenicillin, propicillin, sarmoxicillin, sulbactam, sulbenicillin, sultamicillin, talampicillin, tazobactam, temocillin, ticarcillin, ticarcillin/clavulanic acid) polymyxins(colistin, polymyxin B, polymyxin B/polysorbate 80) quinolones(besifloxacin, cinoxacin, ciprofloxacin, ciprofloxacin/metronidazole, ciprofloxacin/ornidazole, ciprofloxacin/tinidazole, clinafloxacin, danofloxacin, delafloxacin, difloxacin, enoxacin, enrofloxacin, finafloxacin, fleroxacin, flumequine, garenoxacin, gatifloxacin, gemifloxacin, grepafloxacin, lascufloxacin, levofloxacin, levonadifloxacin, lomefloxacin, marbofloxacin, metioxate, miloxacin, moxifloxacin, nadifloxacin, nalidixic acid, nemonoxacin, nifuroquine, nitroxoline, norfloxacin, ofloxacin, orbifloxacin, oxolinic acid, pazufloxacin, pefloxacin, pipemidic acid, piromidic acid, pradofloxacin, premafloxacin, prulifloxacin, rosoxacin, rufloxacin, sarafloxacin, sitafloxacin, sparfloxacin, temafloxacin, tilbroquinol, tioxacin, tosufloxacin, trovafloxacin) rifamycins(rifabutin, rifampicin, rifampicin/ethambutol/isoniazid, rifampicin/isoniazid, rifampicin/pyrazinamide/ethambutol/isoniazid, rifampicin/pyrazinamide/isoniazid, rifamycin, rifapentine) streptogramins(pristinamycin quinupristin/dalfopristin) tetracyclines(cetocycline, chlortetracycline, clomocycline, demeclocycline, doxycycline, eravacycline, lymecycline, metacycline, minocycline, omadacycline, oxytetracycline, penimepicycline, rolitetracycline, sarecycline, tetracycline, tigecycline) tetracyclines_except_tgc(cetocycline, chlortetracycline, clomocycline, demeclocycline, doxycycline, eravacycline, lymecycline, metacycline, minocycline, omadacycline, oxytetracycline, penimepicycline, rolitetracycline, sarecycline, tetracycline) trimethoprims(brodimoprim, sulfadiazine, sulfadiazine/tetroxoprim, sulfadiazine/trimethoprim, sulfadimethoxine, sulfadimidine, sulfadimidine/trimethoprim, sulfafurazole, sulfaisodimidine, sulfalene, sulfamazone, sulfamerazine, sulfamerazine/trimethoprim, sulfamethizole, sulfamethoxazole, sulfamethoxypyridazine, sulfametomidine, sulfametoxydiazine, sulfametrole/trimethoprim, sulfamoxole, sulfamoxole/trimethoprim, sulfanilamide, sulfaperin, sulfaphenazole, sulfapyridine, sulfathiazole, sulfathiourea, trimethoprim, trimethoprim/sulfamethoxazole) ureidopenicillins(azlocillin, mezlocillin, piperacillin, piperacillin/tazobactam)","code":"x <- custom_eucast_rules(TZP == \"R\" ~ c(aminopenicillins, ureidopenicillins) == \"R\") x #> A set of custom EUCAST rules: #> #>   1. If TZP is \"R\" then set to \"R\": #>      amoxicillin (AMX), ampicillin (AMP), azlocillin (AZL), mezlocillin (MEZ), piperacillin (PIP), piperacillin/tazobactam (TZP)"},{"path":"https://msberends.github.io/AMR/reference/custom_eucast_rules.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Define Custom EUCAST Rules — custom_eucast_rules","text":"","code":"x <- custom_eucast_rules(   AMC == \"R\" & genus == \"Klebsiella\" ~ aminopenicillins == \"R\",   AMC == \"I\" & genus == \"Klebsiella\" ~ aminopenicillins == \"I\" ) x #> A set of custom EUCAST rules: #>  #>   1. If AMC is \"R\" and genus is \"Klebsiella\" then set to  R : #>      amoxicillin (AMX), ampicillin (AMP) #>  #>   2. If AMC is \"I\" and genus is \"Klebsiella\" then set to  I : #>      amoxicillin (AMX), ampicillin (AMP)  # run the custom rule set (verbose = TRUE will return a logbook instead of the data set): eucast_rules(example_isolates,   rules = \"custom\",   custom_rules = x,   info = FALSE,   verbose = TRUE ) #> # A tibble: 8 × 9 #>     row col   mo_fullname     old   new   rule  rule_group rule_name rule_source #>   <int> <chr> <chr>           <ord> <chr> <chr> <chr>      <chr>     <chr>       #> 1    33 AMP   Klebsiella pne… R     I     \"rep… Custom EU… Custom E… Object 'x'… #> 2    33 AMX   Klebsiella pne… R     I     \"rep… Custom EU… Custom E… Object 'x'… #> 3    34 AMP   Klebsiella pne… R     I     \"rep… Custom EU… Custom E… Object 'x'… #> 4    34 AMX   Klebsiella pne… R     I     \"rep… Custom EU… Custom E… Object 'x'… #> 5   531 AMP   Klebsiella pne… R     I     \"rep… Custom EU… Custom E… Object 'x'… #> 6   531 AMX   Klebsiella pne… R     I     \"rep… Custom EU… Custom E… Object 'x'… #> 7  1485 AMP   Klebsiella oxy… R     I     \"rep… Custom EU… Custom E… Object 'x'… #> 8  1485 AMX   Klebsiella oxy… R     I     \"rep… Custom EU… Custom E… Object 'x'…  # combine rule sets x2 <- c(   x,   custom_eucast_rules(TZP == \"R\" ~ carbapenems == \"R\") ) x2 #> A set of custom EUCAST rules: #>  #>   1. If AMC is \"R\" and genus is \"Klebsiella\" then set to  R : #>      amoxicillin (AMX), ampicillin (AMP) #>  #>   2. If AMC is \"I\" and genus is \"Klebsiella\" then set to  I : #>      amoxicillin (AMX), ampicillin (AMP) #>  #>   3. If TZP is \"R\" then set to  R : #>      biapenem (BIA), doripenem (DOR), ertapenem (ETP), imipenem (IPM), #>      imipenem/EDTA (IPE), imipenem/relebactam (IMR), meropenem (MEM), #>      meropenem/nacubactam (MNC), meropenem/vaborbactam (MEV), panipenem (PAN), #>      razupenem (RZM), ritipenem (RIT), ritipenem acoxil (RIA), tebipenem (TBP)"},{"path":"https://msberends.github.io/AMR/reference/dosage.html","id":null,"dir":"Reference","previous_headings":"","what":"Data Set with Treatment Dosages as Defined by EUCAST — dosage","title":"Data Set with Treatment Dosages as Defined by EUCAST — dosage","text":"EUCAST breakpoints used package based dosages data set. can retrieved eucast_dosage().","code":""},{"path":"https://msberends.github.io/AMR/reference/dosage.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Data Set with Treatment Dosages as Defined by EUCAST — dosage","text":"","code":"dosage"},{"path":"https://msberends.github.io/AMR/reference/dosage.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data Set with Treatment Dosages as Defined by EUCAST — dosage","text":"tibble 503 observations 9 variables: ab Antibiotic ID used package (AMC), using official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes available name Official name antimicrobial drug used WHONET/EARS-Net type Type dosage, either \"high_dosage\", \"standard_dosage\", \"uncomplicated_uti\" dose Dose, \"2 g\" \"25 mg/kg\" dose_times Number times dose must administered administration Route administration, either \"im\", \"iv\", \"oral\" notes Additional dosage notes original_txt Original text PDF file EUCAST eucast_version Version number EUCAST Clinical Breakpoints guideline dosages apply, either 13, 12, 11","code":""},{"path":"https://msberends.github.io/AMR/reference/dosage.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Data Set with Treatment Dosages as Defined by EUCAST — dosage","text":"Like data sets package, data set publicly available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":"https://msberends.github.io/AMR/reference/dosage.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Data Set with Treatment Dosages as Defined by EUCAST — dosage","text":"","code":"dosage #> # A tibble: 503 × 9 #>    ab   name            type  dose  dose_times administration notes original_txt #>    <ab> <chr>           <chr> <chr>      <int> <chr>          <chr> <chr>        #>  1 AMK  Amikacin        stan… 25-3…          1 iv             \"\"    25-30 mg/kg… #>  2 AMX  Amoxicillin     high… 2 g            6 iv             \"\"    2 g x 6 iv   #>  3 AMX  Amoxicillin     stan… 1 g            3 iv             \"\"    1 g x 3-4 iv #>  4 AMX  Amoxicillin     high… 0.75…          3 oral           \"\"    0.75-1 g x … #>  5 AMX  Amoxicillin     stan… 0.5 g          3 oral           \"\"    0.5 g x 3 o… #>  6 AMX  Amoxicillin     unco… 0.5 g          3 oral           \"\"    0.5 g x 3 o… #>  7 AMC  Amoxicillin/cl… high… 2 g …          3 iv             \"\"    (2 g amoxic… #>  8 AMC  Amoxicillin/cl… stan… 1 g …          3 iv             \"\"    (1 g amoxic… #>  9 AMC  Amoxicillin/cl… high… 0.87…          3 oral           \"\"    (0.875 g am… #> 10 AMC  Amoxicillin/cl… stan… 0.5 …          3 oral           \"\"    (0.5 g amox… #> # ℹ 493 more rows #> # ℹ 1 more variable: eucast_version <dbl>"},{"path":"https://msberends.github.io/AMR/reference/eucast_rules.html","id":null,"dir":"Reference","previous_headings":"","what":"Apply EUCAST Rules — eucast_rules","title":"Apply EUCAST Rules — eucast_rules","text":"Apply rules clinical breakpoints intrinsic resistance defined European Committee Antimicrobial Susceptibility Testing (EUCAST, https://www.eucast.org), see Source. Use eucast_dosage() get data.frame advised dosages certain bug-drug combination, based dosage data set. improve interpretation antibiogram EUCAST rules applied, non-EUCAST rules can applied default, see Details.","code":""},{"path":"https://msberends.github.io/AMR/reference/eucast_rules.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Apply EUCAST Rules — eucast_rules","text":"","code":"eucast_rules(   x,   col_mo = NULL,   info = interactive(),   rules = getOption(\"AMR_eucastrules\", default = c(\"breakpoints\", \"expert\")),   verbose = FALSE,   version_breakpoints = 12,   version_expertrules = 3.3,   ampc_cephalosporin_resistance = NA,   only_sir_columns = FALSE,   custom_rules = NULL,   ... )  eucast_dosage(ab, administration = \"iv\", version_breakpoints = 12)"},{"path":"https://msberends.github.io/AMR/reference/eucast_rules.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Apply EUCAST Rules — eucast_rules","text":"EUCAST Expert Rules. Version 2.0, 2012. Leclercq et al. EUCAST expert rules antimicrobial susceptibility testing. Clin Microbiol Infect. 2013;19(2):141-60; doi:10.1111/j.1469-0691.2011.03703.x EUCAST Expert Rules, Intrinsic Resistance Exceptional Phenotypes Tables. Version 3.1, 2016. (link) EUCAST Intrinsic Resistance Unusual Phenotypes. Version 3.2, 2020. (link) EUCAST Intrinsic Resistance Unusual Phenotypes. Version 3.3, 2021. (link) EUCAST Breakpoint tables interpretation MICs zone diameters. Version 9.0, 2019. (link) EUCAST Breakpoint tables interpretation MICs zone diameters. Version 10.0, 2020. (link) EUCAST Breakpoint tables interpretation MICs zone diameters. Version 11.0, 2021. (link) EUCAST Breakpoint tables interpretation MICs zone diameters. Version 12.0, 2022. (link)","code":""},{"path":"https://msberends.github.io/AMR/reference/eucast_rules.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Apply EUCAST Rules — eucast_rules","text":"x data set antibiotic columns, amox, AMX AMC col_mo column name names codes microorganisms (see .mo()) - default first column class mo. Values coerced using .mo(). info logical indicate whether progress printed console - default print interactive sessions rules character vector specifies rules applied. Must one \"breakpoints\", \"expert\", \"\", \"custom\", \"\", defaults c(\"breakpoints\", \"expert\"). default value can set another value using package option AMR_eucastrules: options(AMR_eucastrules = \"\"). using \"custom\", sure fill argument custom_rules . Custom rules can created custom_eucast_rules(). verbose logical turn Verbose mode (default ). Verbose mode, function apply rules data, instead returns data set logbook form extensive info rows columns effected way. Using Verbose mode takes lot time. version_breakpoints version number use EUCAST Clinical Breakpoints guideline. Can \"12.0\", \"11.0\", \"10.0\". version_expertrules version number use EUCAST Expert Rules Intrinsic Resistance guideline. Can \"3.3\", \"3.2\", \"3.1\". ampc_cephalosporin_resistance character value applied cefotaxime, ceftriaxone ceftazidime AmpC de-repressed cephalosporin-resistant mutants - default NA. Currently works version_expertrules 3.2 higher; version 'EUCAST Expert Rules Enterobacterales' state results cefotaxime, ceftriaxone ceftazidime reported note, results suppressed (emptied) three drugs. value NA (default) argument remove results three drugs, e.g. value \"R\" make results drugs resistant. Use NULL FALSE alter results three drugs AmpC de-repressed cephalosporin-resistant mutants. Using TRUE equal using \"R\".  EUCAST Expert Rules v3.2, rule applies : Citrobacter braakii, Citrobacter freundii, Citrobacter gillenii, Citrobacter murliniae, Citrobacter rodenticum, Citrobacter sedlakii, Citrobacter werkmanii, Citrobacter youngae, Enterobacter, Hafnia alvei, Klebsiella aerogenes, Morganella morganii, Providencia, Serratia. only_sir_columns logical indicate whether antibiotic columns must detected transformed class sir (see .sir()) beforehand (default FALSE) custom_rules custom rules apply, created custom_eucast_rules() ... column name antibiotic, see section Antibiotics ab (vector ) text can coerced valid antibiotic drug code .ab() administration route administration, either \"im\", \"iv\", \"oral\"","code":""},{"path":"https://msberends.github.io/AMR/reference/eucast_rules.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Apply EUCAST Rules — eucast_rules","text":"input x, possibly edited values antibiotics. , verbose = TRUE, data.frame original new values affected bug-drug combinations.","code":""},{"path":"https://msberends.github.io/AMR/reference/eucast_rules.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Apply EUCAST Rules — eucast_rules","text":"Note: function translate MIC values SIR values. Use .sir() . Note: ampicillin (AMP, J01CA01) available amoxicillin (AMX, J01CA04) , latter used rules dependency ampicillin. drugs interchangeable comes expression antimicrobial resistance. file containing EUCAST rules located : https://github.com/msberends/AMR/blob/main/data-raw/eucast_rules.tsv.  Note: Old taxonomic names replaced current taxonomy applicable. example, Ochrobactrum anthropi renamed Brucella anthropi 2020; original EUCAST rules v3.1 v3.2 yet contain new taxonomic name. AMR package contains full microbial taxonomy updated June 24th, 2024, see microorganisms.","code":""},{"path":"https://msberends.github.io/AMR/reference/eucast_rules.html","id":"custom-rules","dir":"Reference","previous_headings":"","what":"Custom Rules","title":"Apply EUCAST Rules — eucast_rules","text":"Custom rules can created using custom_eucast_rules(), e.g.:","code":"x <- custom_eucast_rules(AMC == \"R\" & genus == \"Klebsiella\" ~ aminopenicillins == \"R\",                          AMC == \"I\" & genus == \"Klebsiella\" ~ aminopenicillins == \"I\")  eucast_rules(example_isolates, rules = \"custom\", custom_rules = x)"},{"path":"https://msberends.github.io/AMR/reference/eucast_rules.html","id":"-other-rules","dir":"Reference","previous_headings":"","what":"'Other' Rules","title":"Apply EUCAST Rules — eucast_rules","text":"processing, two non-EUCAST rules drug combinations can applied improve efficacy EUCAST rules, reliability data (analysis). rules : drug enzyme inhibitor set S drug without enzyme inhibitor S drug without enzyme inhibitor set R drug enzyme inhibitor R Important examples include amoxicillin amoxicillin/clavulanic acid, trimethoprim trimethoprim/sulfamethoxazole. Needless say, rules work, drugs must available data set. Since rules officially approved EUCAST, applied default. use rules, include \"\" rules argument, use eucast_rules(..., rules = \"\"). can also set package option AMR_eucastrules, .e. run options(AMR_eucastrules = \"\").","code":""},{"path":"https://msberends.github.io/AMR/reference/eucast_rules.html","id":"antibiotics","dir":"Reference","previous_headings":"","what":"Antibiotics","title":"Apply EUCAST Rules — eucast_rules","text":"define antibiotics column names, leave determine automatically guess_ab_col() input text (case-insensitive), use NULL skip column (e.g. TIC = NULL skip ticarcillin). Manually defined non-existing columns skipped warning. following antibiotics eligible functions eucast_rules() mdro(). shown format 'name (antimicrobial ID, ATC code)', sorted alphabetically: Amikacin (AMK, J01GB06), amoxicillin (AMX, J01CA04), amoxicillin/clavulanic acid (AMC, J01CR02), ampicillin (AMP, J01CA01), ampicillin/sulbactam (SAM, J01CR01), apramycin (APR, QA07AA92), arbekacin (ARB, J01GB12), aspoxicillin (APX, J01CA19), azidocillin (AZD, J01CE04), azithromycin (AZM, J01FA10), azlocillin (AZL, J01CA09), aztreonam (ATM, J01DF01), bacampicillin (BAM, J01CA06), bekanamycin (BEK, J01GB13), benzathine benzylpenicillin (BNB, J01CE08), benzathine phenoxymethylpenicillin (BNP, J01CE10), benzylpenicillin (PEN, J01CE01), besifloxacin (BES, S01AE08), biapenem (BIA, J01DH05), carbenicillin (CRB, J01CA03), carindacillin (CRN, J01CA05), cefacetrile (CAC, J01DB10), cefaclor (CEC, J01DC04), cefadroxil (CFR, J01DB05), cefalexin (LEX, J01DB01), cefaloridine (RID, J01DB02), cefalotin (CEP, J01DB03), cefamandole (MAN, J01DC03), cefapirin (HAP, J01DB08), cefatrizine (CTZ, J01DB07), cefazedone (CZD, J01DB06), cefazolin (CZO, J01DB04), cefcapene (CCP, J01DD17), cefdinir (CDR, J01DD15), cefditoren (DIT, J01DD16), cefepime (FEP, J01DE01), cefetamet (CAT, J01DD10), cefixime (CFM, J01DD08), cefmenoxime (CMX, J01DD05), cefmetazole (CMZ, J01DC09), cefodizime (DIZ, J01DD09), cefonicid (CID, J01DC06), cefoperazone (CFP, J01DD12), cefoperazone/sulbactam (CSL, J01DD62), ceforanide (CND, J01DC11), cefotaxime (CTX, J01DD01), cefotaxime/clavulanic acid (CTC, J01DD51), cefotetan (CTT, J01DC05), cefotiam (CTF, J01DC07), cefovecin (FOV, QJ01DD91), cefoxitin (FOX, J01DC01), cefozopran (ZOP, J01DE03), cefpiramide (CPM, J01DD11), cefpirome (CPO, J01DE02), cefpodoxime (CPD, J01DD13), cefprozil (CPR, J01DC10), cefquinome (CEQ, QG51AA07), cefroxadine (CRD, J01DB11), cefsulodin (CFS, J01DD03), ceftaroline (CPT, J01DI02), ceftazidime (CAZ, J01DD02), ceftazidime/clavulanic acid (CCV, J01DD52), cefteram (CEM, J01DD18), ceftezole (CTL, J01DB12), ceftibuten (CTB, J01DD14), ceftiofur (TIO, QJ01DD90), ceftizoxime (CZX, J01DD07), ceftobiprole medocaril (CFM1, J01DI01), ceftolozane/tazobactam (CZT, J01DI54), ceftriaxone (CRO, J01DD04), ceftriaxone/beta-lactamase inhibitor (CEB, J01DD63), cefuroxime (CXM, J01DC02), cephradine (CED, J01DB09), chloramphenicol (CHL, J01BA01), ciprofloxacin (CIP, J01MA02), clarithromycin (CLR, J01FA09), clindamycin (CLI, J01FF01), clometocillin (CLM, J01CE07), cloxacillin (CLO, J01CF02), colistin (COL, J01XB01), cycloserine (CYC, J04AB01), dalbavancin (DAL, J01XA04), danofloxacin (DAN, QJ01MA92), daptomycin (DAP, J01XX09), delafloxacin (DFX, J01MA23), dibekacin (DKB, J01GB09), dicloxacillin (DIC, J01CF01), difloxacin (DIF, QJ01MA94), dirithromycin (DIR, J01FA13), doripenem (DOR, J01DH04), doxycycline (DOX, J01AA02), enoxacin (ENX, J01MA04), enrofloxacin (ENR, QJ01MA90), epicillin (EPC, J01CA07), ertapenem (ETP, J01DH03), erythromycin (ERY, J01FA01), fleroxacin (FLE, J01MA08), flucloxacillin (FLC, J01CF05), flurithromycin (FLR1, J01FA14), fosfomycin (FOS, J01XX01), framycetin (FRM, D09AA01), fusidic acid (FUS, J01XC01), gamithromycin (GAM, QJ01FA95), garenoxacin (GRN, J01MA19), gatifloxacin (GAT, J01MA16), gemifloxacin (GEM, J01MA15), gentamicin (GEN, J01GB03), grepafloxacin (GRX, J01MA11), hetacillin (HET, J01CA18), imipenem (IPM, J01DH51), imipenem/relebactam (IMR, J01DH56), isepamicin (ISE, J01GB11), josamycin (JOS, J01FA07), kanamycin (KAN, J01GB04), kitasamycin (KIT, QJ01FA93), lascufloxacin (LSC, J01MA25), latamoxef (LTM, J01DD06), levofloxacin (LVX, J01MA12), levonadifloxacin (LND, J01MA24), lincomycin (LIN, J01FF02), linezolid (LNZ, J01XX08), lomefloxacin (LOM, J01MA07), loracarbef (LOR, J01DC08), marbofloxacin (MAR, QJ01MA93), mecillinam (MEC, J01CA11), meropenem (MEM, J01DH02), meropenem/vaborbactam (MEV, J01DH52), metampicillin (MTM, J01CA14), meticillin (MET, J01CF03), mezlocillin (MEZ, J01CA10), micronomicin (MCR, S01AA22), midecamycin (MID, J01FA03), minocycline (MNO, J01AA08), miocamycin (MCM, J01FA11), moxifloxacin (MFX, J01MA14), nadifloxacin (NAD, D10AF05), nafcillin (NAF, J01CF06), nalidixic acid (NAL, J01MB02), neomycin (NEO, J01GB05), netilmicin (NET, J01GB07), nitrofurantoin (NIT, J01XE01), norfloxacin (, J01MA06), novobiocin (NOV, QJ01XX95), ofloxacin (OFX, J01MA01), oleandomycin (OLE, J01FA05), orbifloxacin (ORB, QJ01MA95), oritavancin (ORI, J01XA05), oxacillin (OXA, J01CF04), panipenem (PAN, J01DH55), pazufloxacin (PAZ, J01MA18), pefloxacin (PEF, J01MA03), penamecillin (PNM, J01CE06), pheneticillin (PHE, J01CE05), phenoxymethylpenicillin (PHN, J01CE02), piperacillin (PIP, J01CA12), piperacillin/tazobactam (TZP, J01CR05), pirlimycin (PRL, QJ51FF90), pivampicillin (PVM, J01CA02), pivmecillinam (PME, J01CA08), plazomicin (PLZ, J01GB14), polymyxin B (PLB, J01XB02), pradofloxacin (PRA, QJ01MA97), pristinamycin (PRI, J01FG01), procaine benzylpenicillin (PRB, J01CE09), propicillin (PRP, J01CE03), prulifloxacin (PRU, J01MA17), quinupristin/dalfopristin (QDA, QJ01FG02), ribostamycin (RST, J01GB10), rifampicin (RIF, J04AB02), rokitamycin (ROK, J01FA12), roxithromycin (RXT, J01FA06), rufloxacin (RFL, J01MA10), sarafloxacin (SAR, QJ01MA98), sisomicin (SIS, J01GB08), sitafloxacin (SIT, J01MA21), solithromycin (SOL, J01FA16), sparfloxacin (SPX, J01MA09), spiramycin (SPI, J01FA02), streptoduocin (STR, J01GA02), streptomycin (STR1, J01GA01), sulbactam (SUL, J01CG01), sulbenicillin (SBC, J01CA16), sulfadiazine (SDI, J01EC02), sulfadiazine/trimethoprim (SLT1, J01EE02), sulfadimethoxine (SUD, J01ED01), sulfadimidine (SDM, J01EB03), sulfadimidine/trimethoprim (SLT2, J01EE05), sulfafurazole (SLF, J01EB05), sulfaisodimidine (SLF1, J01EB01), sulfalene (SLF2, J01ED02), sulfamazone (SZO, J01ED09), sulfamerazine (SLF3, J01ED07), sulfamerazine/trimethoprim (SLT3, J01EE07), sulfamethizole (SLF4, J01EB02), sulfamethoxazole (SMX, J01EC01), sulfamethoxypyridazine (SLF5, J01ED05), sulfametomidine (SLF6, J01ED03), sulfametoxydiazine (SLF7, J01ED04), sulfametrole/trimethoprim (SLT4, J01EE03), sulfamoxole (SLF8, J01EC03), sulfamoxole/trimethoprim (SLT5, J01EE04), sulfanilamide (SLF9, J01EB06), sulfaperin (SLF10, J01ED06), sulfaphenazole (SLF11, J01ED08), sulfapyridine (SLF12, J01EB04), sulfathiazole (SUT, J01EB07), sulfathiourea (SLF13, J01EB08), sultamicillin (SLT6, J01CR04), talampicillin (TAL, J01CA15), tazobactam (TAZ, J01CG02), tebipenem (TBP, J01DH06), tedizolid (TZD, J01XX11), teicoplanin (TEC, J01XA02), telavancin (TLV, J01XA03), telithromycin (TLT, J01FA15), temafloxacin (TMX, J01MA05), temocillin (TEM, J01CA17), tetracycline (TCY, J01AA07), ticarcillin (TIC, J01CA13), ticarcillin/clavulanic acid (TCC, J01CR03), tigecycline (TGC, J01AA12), tilbroquinol (TBQ, P01AA05), tildipirosin (TIP, QJ01FA96), tilmicosin (TIL, QJ01FA91), tobramycin (TOB, J01GB01), tosufloxacin (TFX, J01MA22), trimethoprim (TMP, J01EA01), trimethoprim/sulfamethoxazole (SXT, J01EE01), troleandomycin (TRL, J01FA08), trovafloxacin (TVA, J01MA13), tulathromycin (TUL, QJ01FA94), tylosin (TYL, QJ01FA90), tylvalosin (TYL1, QJ01FA92), vancomycin (VAN, J01XA01)","code":""},{"path":"https://msberends.github.io/AMR/reference/eucast_rules.html","id":"reference-data-publicly-available","dir":"Reference","previous_headings":"","what":"Reference Data Publicly Available","title":"Apply EUCAST Rules — eucast_rules","text":"data sets AMR package (microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) publicly freely available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. also provide tab-separated plain text files machine-readable suitable input software program, laboratory information systems. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":"https://msberends.github.io/AMR/reference/eucast_rules.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Apply EUCAST Rules — eucast_rules","text":"","code":"# \\donttest{ a <- data.frame(   mo = c(     \"Staphylococcus aureus\",     \"Enterococcus faecalis\",     \"Escherichia coli\",     \"Klebsiella pneumoniae\",     \"Pseudomonas aeruginosa\"   ),   VAN = \"-\", # Vancomycin   AMX = \"-\", # Amoxicillin   COL = \"-\", # Colistin   CAZ = \"-\", # Ceftazidime   CXM = \"-\", # Cefuroxime   PEN = \"S\", # Benzylpenicillin   FOX = \"S\", # Cefoxitin   stringsAsFactors = FALSE )  head(a) #>                       mo VAN AMX COL CAZ CXM PEN FOX #> 1  Staphylococcus aureus   -   -   -   -   -   S   S #> 2  Enterococcus faecalis   -   -   -   -   -   S   S #> 3       Escherichia coli   -   -   -   -   -   S   S #> 4  Klebsiella pneumoniae   -   -   -   -   -   S   S #> 5 Pseudomonas aeruginosa   -   -   -   -   -   S   S   # apply EUCAST rules: some results wil be changed b <- eucast_rules(a) #> Warning: in eucast_rules(): not all columns with antimicrobial results are of #> class 'sir'. Transform them on beforehand, with e.g.: #>   - a %>% as.sir(CXM:AMX) #>   - a %>% mutate_if(is_sir_eligible, as.sir) #>   - a %>% mutate(across(where(is_sir_eligible), as.sir))  head(b) #>                       mo VAN AMX COL CAZ CXM PEN FOX #> 1  Staphylococcus aureus   -   S   R   S   S   S   S #> 2  Enterococcus faecalis   -   -   R   R   R   S   R #> 3       Escherichia coli   R   -   -   -   -   R   S #> 4  Klebsiella pneumoniae   R   R   -   -   -   R   S #> 5 Pseudomonas aeruginosa   R   R   -   -   R   R   R   # do not apply EUCAST rules, but rather get a data.frame # containing all details about the transformations: c <- eucast_rules(a, verbose = TRUE) #> Warning: in eucast_rules(): not all columns with antimicrobial results are of #> class 'sir'. Transform them on beforehand, with e.g.: #>   - a %>% as.sir(CXM:AMX) #>   - a %>% mutate_if(is_sir_eligible, as.sir) #>   - a %>% mutate(across(where(is_sir_eligible), as.sir)) head(c) #>   row col           mo_fullname old new rule   rule_group #> 1   1 AMX Staphylococcus aureus   -   S       Breakpoints #> 2   1 CXM Staphylococcus aureus   -   S       Breakpoints #> 3   1 CAZ Staphylococcus aureus   R   S      Expert Rules #> 4   1 CAZ Staphylococcus aureus   -   R      Expert Rules #> 5   1 COL Staphylococcus aureus   -   R      Expert Rules #> 6   2 CAZ Enterococcus faecalis   -   R      Expert Rules #>                                                 rule_name #> 1                                          Staphylococcus #> 2                                          Staphylococcus #> 3                          Expert Rules on Staphylococcus #> 4 Table 4: Intrinsic resistance in gram-positive bacteria #> 5 Table 4: Intrinsic resistance in gram-positive bacteria #> 6 Table 4: Intrinsic resistance in gram-positive bacteria #>                                                                                 rule_source #> 1                                           'EUCAST Clinical Breakpoint Tables' v12.0, 2022 #> 2                                           'EUCAST Clinical Breakpoint Tables' v12.0, 2022 #> 3 'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3, 2021 #> 4 'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3, 2021 #> 5 'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3, 2021 #> 6 'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3, 2021 # }  # Dosage guidelines:  eucast_dosage(c(\"tobra\", \"genta\", \"cipro\"), \"iv\") #> ℹ Dosages for antimicrobial drugs, as meant for 'EUCAST Clinical Breakpoint #>   Tables' v12.0 (2022). This note will be shown once per session. #> # A tibble: 3 × 4 #>   ab   name          standard_dosage  high_dosage  #>   <ab> <chr>         <chr>            <chr>        #> 1 TOB  Tobramycin    6-7 mg/kg x 1 iv NA           #> 2 GEN  Gentamicin    6-7 mg/kg x 1 iv NA           #> 3 CIP  Ciprofloxacin 0.4 g x 2 iv     0.4 g x 3 iv  eucast_dosage(c(\"tobra\", \"genta\", \"cipro\"), \"iv\", version_breakpoints = 10) #> ℹ Dosages for antimicrobial drugs, as meant for 'EUCAST Clinical Breakpoint #>   Tables' v10.0 (2020). This note will be shown once per session. #> # A tibble: 3 × 4 #>   ab   name          standard_dosage  high_dosage  #>   <ab> <chr>         <chr>            <chr>        #> 1 TOB  Tobramycin    6-7 mg/kg x 1 iv NA           #> 2 GEN  Gentamicin    6-7 mg/kg x 1 iv NA           #> 3 CIP  Ciprofloxacin 0.4 g x 2 iv     0.4 g x 3 iv"},{"path":"https://msberends.github.io/AMR/reference/example_isolates.html","id":null,"dir":"Reference","previous_headings":"","what":"Data Set with 2 000 Example Isolates — example_isolates","title":"Data Set with 2 000 Example Isolates — example_isolates","text":"data set containing 2 000 microbial isolates full antibiograms. data set contains randomised fictitious data, reflects reality can used practise AMR data analysis. examples, please read tutorial website.","code":""},{"path":"https://msberends.github.io/AMR/reference/example_isolates.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Data Set with 2 000 Example Isolates — example_isolates","text":"","code":"example_isolates"},{"path":"https://msberends.github.io/AMR/reference/example_isolates.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data Set with 2 000 Example Isolates — example_isolates","text":"tibble 2 000 observations 46 variables: date Date receipt laboratory patient ID patient age Age patient gender Gender patient, either \"F\" \"M\" ward Ward type patient admitted, either \"Clinical\", \"ICU\", \"Outpatient\" mo ID microorganism created .mo(), see also microorganisms data set PEN:RIF 40 different antibiotics class sir (see .sir()); column names occur antibiotics data set can translated set_ab_names() ab_name()","code":""},{"path":"https://msberends.github.io/AMR/reference/example_isolates.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Data Set with 2 000 Example Isolates — example_isolates","text":"Like data sets package, data set publicly available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":"https://msberends.github.io/AMR/reference/example_isolates.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Data Set with 2 000 Example Isolates — example_isolates","text":"","code":"example_isolates #> # A tibble: 2,000 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-03 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  3 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  4 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  5 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  6 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  7 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  8 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  9 2002-01-16 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #> 10 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R     NA    S     NA    #> # ℹ 1,990 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, …"},{"path":"https://msberends.github.io/AMR/reference/example_isolates_unclean.html","id":null,"dir":"Reference","previous_headings":"","what":"Data Set with Unclean Data — example_isolates_unclean","title":"Data Set with Unclean Data — example_isolates_unclean","text":"data set containing 3 000 microbial isolates cleaned consequently ready AMR data analysis. data set can used practice.","code":""},{"path":"https://msberends.github.io/AMR/reference/example_isolates_unclean.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Data Set with Unclean Data — example_isolates_unclean","text":"","code":"example_isolates_unclean"},{"path":"https://msberends.github.io/AMR/reference/example_isolates_unclean.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data Set with Unclean Data — example_isolates_unclean","text":"tibble 3 000 observations 8 variables: patient_id ID patient date date receipt laboratory hospital ID hospital, C bacteria info microorganism can transformed .mo(), see also microorganisms AMX:GEN 4 different antibiotics transformed .sir()","code":""},{"path":"https://msberends.github.io/AMR/reference/example_isolates_unclean.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Data Set with Unclean Data — example_isolates_unclean","text":"Like data sets package, data set publicly available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":"https://msberends.github.io/AMR/reference/example_isolates_unclean.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Data Set with Unclean Data — example_isolates_unclean","text":"","code":"example_isolates_unclean #> # A tibble: 3,000 × 8 #>    patient_id hospital date       bacteria      AMX   AMC   CIP   GEN   #>    <chr>      <chr>    <date>     <chr>         <chr> <chr> <chr> <chr> #>  1 J3         A        2012-11-21 E. coli       R     I     S     S     #>  2 R7         A        2018-04-03 K. pneumoniae R     I     S     S     #>  3 P3         A        2014-09-19 E. coli       R     S     S     S     #>  4 P10        A        2015-12-10 E. coli       S     I     S     S     #>  5 B7         A        2015-03-02 E. coli       S     S     S     S     #>  6 W3         A        2018-03-31 S. aureus     R     S     R     S     #>  7 J8         A        2016-06-14 E. coli       R     S     S     S     #>  8 M3         A        2015-10-25 E. coli       R     S     S     S     #>  9 J3         A        2019-06-19 E. coli       S     S     S     S     #> 10 G6         A        2015-04-27 S. aureus     S     S     S     S     #> # ℹ 2,990 more rows"},{"path":"https://msberends.github.io/AMR/reference/export_ncbi_biosample.html","id":null,"dir":"Reference","previous_headings":"","what":"Export Data Set as NCBI BioSample Antibiogram — export_ncbi_biosample","title":"Export Data Set as NCBI BioSample Antibiogram — export_ncbi_biosample","text":"Export Data Set NCBI BioSample Antibiogram","code":""},{"path":"https://msberends.github.io/AMR/reference/export_ncbi_biosample.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Export Data Set as NCBI BioSample Antibiogram — export_ncbi_biosample","text":"","code":"export_ncbi_biosample(   x,   filename = paste0(\"biosample_\", format(Sys.time(), \"%Y-%m-%d-%H%M%S\"), \".xlsx\"),   type = \"pathogen MIC\",   columns = where(is.mic),   save_as_xlsx = TRUE )"},{"path":"https://msberends.github.io/AMR/reference/export_ncbi_biosample.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Export Data Set as NCBI BioSample Antibiogram — export_ncbi_biosample","text":"x data set filename character string specifying file name type character string specifying type data set, either \"pathogen MIC\" \"beta-lactamase MIC\", see https://www.ncbi.nlm.nih.gov/biosample/docs/","code":""},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":null,"dir":"Reference","previous_headings":"","what":"Determine First Isolates — first_isolate","title":"Determine First Isolates — first_isolate","text":"Determine first isolates microorganisms every patient per episode (needed) per specimen type. functions support four methods summarised Hindler et al. 2007 (doi:10.1086/511864 ). determine patient episodes necessarily based microorganisms, use is_new_episode() also supports grouping dplyr package.","code":""},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Determine First Isolates — first_isolate","text":"","code":"first_isolate(   x = NULL,   col_date = NULL,   col_patient_id = NULL,   col_mo = NULL,   col_testcode = NULL,   col_specimen = NULL,   col_icu = NULL,   col_keyantimicrobials = NULL,   episode_days = 365,   testcodes_exclude = NULL,   icu_exclude = FALSE,   specimen_group = NULL,   type = \"points\",   method = c(\"phenotype-based\", \"episode-based\", \"patient-based\", \"isolate-based\"),   ignore_I = TRUE,   points_threshold = 2,   info = interactive(),   include_unknown = FALSE,   include_untested_sir = TRUE,   ... )  filter_first_isolate(   x = NULL,   col_date = NULL,   col_patient_id = NULL,   col_mo = NULL,   episode_days = 365,   method = c(\"phenotype-based\", \"episode-based\", \"patient-based\", \"isolate-based\"),   ... )"},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Determine First Isolates — first_isolate","text":"Methodology function strictly based : M39 Analysis Presentation Cumulative Antimicrobial Susceptibility Test Data, 5th Edition, 2022, Clinical Laboratory Standards Institute (CLSI). https://clsi.org/standards/products/microbiology/documents/m39/. Hindler JF Stelling J (2007). Analysis Presentation Cumulative Antibiograms: New Consensus Guideline Clinical Laboratory Standards Institute. Clinical Infectious Diseases, 44(6), 867-873. doi:10.1086/511864","code":""},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Determine First Isolates — first_isolate","text":"x data.frame containing isolates. Can left blank automatic determination, see Examples. col_date column name result date (date received lab) - default first column date class col_patient_id column name unique IDs patients - default first column starts 'patient' 'patid' (case insensitive) col_mo column name names codes microorganisms (see .mo()) - default first column class mo. Values coerced using .mo(). col_testcode column name test codes. Use col_testcode = NULL exclude certain test codes (test codes screening). case testcodes_exclude ignored. col_specimen column name specimen type group col_icu column name logicals (TRUE/FALSE) whether ward department Intensive Care Unit (ICU). can also logical vector length rows x. col_keyantimicrobials (useful method = \"phenotype-based\") column name key antimicrobials determine first isolates, see key_antimicrobials(). default first column starts 'key' followed 'ab' 'antibiotics' 'antimicrobials' (case insensitive). Use col_keyantimicrobials = FALSE prevent . Can also output key_antimicrobials(). episode_days episode days genus/species combination determined 'first isolate' . default 365 days based guideline CLSI, see Source. testcodes_exclude character vector test codes excluded (case-insensitive) icu_exclude logical indicate whether ICU isolates excluded (rows value TRUE column set col_icu) specimen_group value column set col_specimen filter type type determine weighed isolates; can \"keyantimicrobials\" \"points\", see Details method method apply, either \"phenotype-based\", \"episode-based\", \"patient-based\" \"isolate-based\" (can abbreviated), see Details. default \"phenotype-based\" antimicrobial test results present data, \"episode-based\" otherwise. ignore_I logical indicate whether antibiotic interpretations \"\" ignored type = \"keyantimicrobials\", see Details points_threshold minimum number points require differences antibiogram lead inclusion isolate type = \"points\", see Details info logical indicate info printed - default TRUE interactive mode include_unknown logical indicate whether 'unknown' microorganisms included , .e. microbial code \"UNKNOWN\", defaults FALSE. WHONET users, means records organism code \"con\" (contamination) excluded default. Isolates microbial ID NA always excluded first isolate. include_untested_sir logical indicate whether also rows without antibiotic results still eligible becoming first isolate. Use include_untested_sir = FALSE always return FALSE rows. checks data set columns class sir consequently requires transforming columns antibiotic results using .sir() first. ... arguments passed first_isolate() using filter_first_isolate(), otherwise arguments passed key_antimicrobials() (universal, gram_negative, gram_positive)","code":""},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Determine First Isolates — first_isolate","text":"logical vector","code":""},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Determine First Isolates — first_isolate","text":"conduct epidemiological analyses antimicrobial resistance data, -called first isolates included prevent overestimation underestimation antimicrobial resistance. Different methods can used , see . functions context-aware. means x argument can left blank used inside data.frame call, see Examples. first_isolate() function wrapper around is_new_episode() function, efficient data sets containing microorganism codes names. isolates microbial ID NA excluded first isolate.","code":""},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":"different-methods","dir":"Reference","previous_headings":"","what":"Different methods","title":"Determine First Isolates — first_isolate","text":"According Hindler et al. (2007, doi:10.1086/511864 ), different methods (algorithms) select first isolates increasing reliability: isolate-based, patient-based, episode-based phenotype-based. methods select combination taxonomic genus species (subspecies). mentioned methods covered first_isolate() function:","code":""},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":"isolate-based","dir":"Reference","previous_headings":"","what":"Isolate-based","title":"Determine First Isolates — first_isolate","text":"method require selection, isolates included. , however, respect arguments set first_isolate() function. example, default setting include_unknown (FALSE) omit selection rows without microbial ID.","code":""},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":"patient-based","dir":"Reference","previous_headings":"","what":"Patient-based","title":"Determine First Isolates — first_isolate","text":"include every genus-species combination per patient , set episode_days Inf. Although often inappropriate, method makes sure duplicate isolates selected patient. large longitudinal data set, mean isolates excluded found years initial isolate.","code":""},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":"episode-based","dir":"Reference","previous_headings":"","what":"Episode-based","title":"Determine First Isolates — first_isolate","text":"include every genus-species combination per patient episode , set episode_days sensible number days. Depending type analysis, 14, 30, 60 365. Short episodes common analysing specific hospital ward data, long episodes common analysing regional national data. common method correct duplicate isolates. Patients categorised episodes based ID dates (e.g., date specimen receipt laboratory result). common method, take account antimicrobial test results. means e.g. methicillin-resistant Staphylococcus aureus (MRSA) isolate differentiated wildtype Staphylococcus aureus isolate.","code":""},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":"phenotype-based","dir":"Reference","previous_headings":"","what":"Phenotype-based","title":"Determine First Isolates — first_isolate","text":"reliable method, since also weighs antibiogram (antimicrobial test results) yielding -called 'first weighted isolates'. two different methods weigh antibiogram: Using type = \"points\" argument points_threshold (default) method weighs antimicrobial drugs available data set. difference S R (vice versa) counts 0.5 points, difference S R (vice versa) counts 1 point. sum points exceeds points_threshold, defaults 2, isolate selected first weighted isolate. antimicrobials internally selected using all_antimicrobials() function. output function need passed first_isolate() function. Using type = \"keyantimicrobials\" argument ignore_I method weighs specific antimicrobial drugs, called key antimicrobials. difference S R (vice versa) key antimicrobials select isolate first weighted isolate. ignore_I = FALSE, also differences S R (vice versa) lead . Key antimicrobials internally selected using key_antimicrobials() function, can also added manually variable data set col_keyantimicrobials argument. Another option pass output key_antimicrobials() function directly col_keyantimicrobials argument. default method phenotype-based (using type = \"points\") episode-based (using episode_days = 365). makes sure every genus-species combination selected per patient per year, taking account antimicrobial test results. antimicrobial test results available data set, episode-based method applied default.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/first_isolate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Determine First Isolates — first_isolate","text":"","code":"# `example_isolates` is a data set available in the AMR package. # See ?example_isolates.  example_isolates[first_isolate(info = TRUE), ] #> ℹ Determining first isolates using an episode length of 365 days #> ℹ Using column 'date' as input for col_date. #> ℹ Using column 'patient' as input for col_patient_id. #> ℹ Basing inclusion on all antimicrobial results, using a points threshold #>   of 2 #> ℹ Excluding 16 isolates with a microbial ID 'UNKNOWN' (in column 'mo') #> => Found 1,373 'phenotype-based' first isolates (68.7% of total where a #>    microbial ID was available) #> # A tibble: 1,373 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  3 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  4 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R     NA    S     NA    #>  5 2002-01-17 495616     67 M      Clinical B_STPHY_EPDR R     NA    S     NA    #>  6 2002-01-19 738003     71 M      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  7 2002-01-21 462081     75 F      Clinical B_CTRBC_FRND R     NA    NA    R     #>  8 2002-01-22 F35553     50 M      ICU      B_PROTS_MRBL R     NA    NA    NA    #>  9 2002-02-03 481442     76 M      ICU      B_STPHY_CONS R     NA    S     NA    #> 10 2002-02-05 023456     50 M      Clinical B_STPHY_HMNS S     NA    S     NA    #> # ℹ 1,363 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, … # \\donttest{ # get all first Gram-negatives example_isolates[which(first_isolate(info = FALSE) & mo_is_gram_negative()), ] #> ℹ Using column 'mo' as input for mo_is_gram_negative() #> # A tibble: 434 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-19 738003     71 M      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  3 2002-01-21 462081     75 F      Clinical B_CTRBC_FRND R     NA    NA    R     #>  4 2002-01-22 F35553     50 M      ICU      B_PROTS_MRBL R     NA    NA    NA    #>  5 2002-02-05 067927     45 F      ICU      B_SERRT_MRCS R     NA    NA    R     #>  6 2002-02-27 066895     85 F      Clinical B_KLBSL_PNMN R     NA    NA    R     #>  7 2002-03-08 4FC193     69 M      Clinical B_ESCHR_COLI R     NA    NA    R     #>  8 2002-03-16 4FC193     69 M      Clinical B_PSDMN_AERG R     NA    NA    R     #>  9 2002-04-01 496896     46 F      ICU      B_ESCHR_COLI R     NA    NA    NA    #> 10 2002-04-23 EE2510     69 F      ICU      B_ESCHR_COLI R     NA    NA    NA    #> # ℹ 424 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, …  if (require(\"dplyr\")) {   # filter on first isolates using dplyr:   example_isolates %>%     filter(first_isolate(info = TRUE)) } #> ℹ Determining first isolates using an episode length of 365 days #> ℹ Basing inclusion on all antimicrobial results, using a points threshold #>   of 2 #> ℹ Excluding 16 isolates with a microbial ID 'UNKNOWN' (in column 'mo') #> => Found 1,373 'phenotype-based' first isolates (68.7% of total where a #>    microbial ID was available) #> # A tibble: 1,373 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  3 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  4 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R     NA    S     NA    #>  5 2002-01-17 495616     67 M      Clinical B_STPHY_EPDR R     NA    S     NA    #>  6 2002-01-19 738003     71 M      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  7 2002-01-21 462081     75 F      Clinical B_CTRBC_FRND R     NA    NA    R     #>  8 2002-01-22 F35553     50 M      ICU      B_PROTS_MRBL R     NA    NA    NA    #>  9 2002-02-03 481442     76 M      ICU      B_STPHY_CONS R     NA    S     NA    #> 10 2002-02-05 023456     50 M      Clinical B_STPHY_HMNS S     NA    S     NA    #> # ℹ 1,363 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, … if (require(\"dplyr\")) {   # short-hand version:   example_isolates %>%     filter_first_isolate(info = FALSE) } #> # A tibble: 1,373 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  3 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  4 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R     NA    S     NA    #>  5 2002-01-17 495616     67 M      Clinical B_STPHY_EPDR R     NA    S     NA    #>  6 2002-01-19 738003     71 M      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  7 2002-01-21 462081     75 F      Clinical B_CTRBC_FRND R     NA    NA    R     #>  8 2002-01-22 F35553     50 M      ICU      B_PROTS_MRBL R     NA    NA    NA    #>  9 2002-02-03 481442     76 M      ICU      B_STPHY_CONS R     NA    S     NA    #> 10 2002-02-05 023456     50 M      Clinical B_STPHY_HMNS S     NA    S     NA    #> # ℹ 1,363 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, … if (require(\"dplyr\")) {   # flag the first isolates per group:   example_isolates %>%     group_by(ward) %>%     mutate(first = first_isolate(info = TRUE)) %>%     select(ward, date, patient, mo, first) } #> ℹ Determining first isolates using an episode length of 365 days #> ℹ Basing inclusion on all antimicrobial results, using a points threshold #>   of 2 #>  #> Group: ward = \"Clinical\" #> ℹ Excluding 9 isolates with a microbial ID 'UNKNOWN' (in column 'mo') #> => Found 857 'phenotype-based' first isolates (69.4% of total where a #>    microbial ID was available) #>  #> Group: ward = \"ICU\" #> ℹ Excluding 6 isolates with a microbial ID 'UNKNOWN' (in column 'mo') #> => Found 447 'phenotype-based' first isolates (69.2% of total where a #>    microbial ID was available) #>  #> Group: ward = \"Outpatient\" #> ℹ Excluding 1 isolates with a microbial ID 'UNKNOWN' (in column 'mo') #> => Found 98 'phenotype-based' first isolates (81.7% of total where a #>    microbial ID was available) #> # A tibble: 2,000 × 5 #> # Groups:   ward [3] #>    ward     date       patient mo           first #>    <chr>    <date>     <chr>   <mo>         <lgl> #>  1 Clinical 2002-01-02 A77334  B_ESCHR_COLI TRUE  #>  2 Clinical 2002-01-03 A77334  B_ESCHR_COLI FALSE #>  3 ICU      2002-01-07 067927  B_STPHY_EPDR TRUE  #>  4 ICU      2002-01-07 067927  B_STPHY_EPDR FALSE #>  5 ICU      2002-01-13 067927  B_STPHY_EPDR FALSE #>  6 ICU      2002-01-13 067927  B_STPHY_EPDR FALSE #>  7 Clinical 2002-01-14 462729  B_STPHY_AURS TRUE  #>  8 Clinical 2002-01-14 462729  B_STPHY_AURS FALSE #>  9 ICU      2002-01-16 067927  B_STPHY_EPDR FALSE #> 10 ICU      2002-01-17 858515  B_STPHY_EPDR TRUE  #> # ℹ 1,990 more rows # }"},{"path":"https://msberends.github.io/AMR/reference/g.test.html","id":null,"dir":"Reference","previous_headings":"","what":"G-test for Count Data — g.test","title":"G-test for Count Data — g.test","text":"g.test() performs chi-squared contingency table tests goodness--fit tests, just like chisq.test() reliable (1). G-test can used see whether number observations category fits theoretical expectation (called G-test goodness--fit), see whether proportions one variable different different values variable (called G-test independence).","code":""},{"path":"https://msberends.github.io/AMR/reference/g.test.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"G-test for Count Data — g.test","text":"","code":"g.test(x, y = NULL, p = rep(1/length(x), length(x)), rescale.p = FALSE)"},{"path":"https://msberends.github.io/AMR/reference/g.test.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"G-test for Count Data — g.test","text":"code function identical chisq.test(), except : calculation statistic changed \\(2 * sum(x * log(x / E))\\) Yates' continuity correction removed apply G-test possibility simulate p values simulate.p.value removed","code":""},{"path":"https://msberends.github.io/AMR/reference/g.test.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"G-test for Count Data — g.test","text":"x numeric vector matrix. x y can also     factors. y numeric vector; ignored x matrix.      x factor, y factor length. p vector probabilities length x.     error given entry p negative. rescale.p logical scalar; TRUE p rescaled     (necessary) sum 1.  rescale.p FALSE,     p sum 1, error given.","code":""},{"path":"https://msberends.github.io/AMR/reference/g.test.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"G-test for Count Data — g.test","text":"list class \"htest\" containing following   components: statistic value chi-squared test statistic. parameter degrees freedom approximate     chi-squared distribution test statistic, NA     p-value computed Monte Carlo simulation. p.value p-value test. method character string indicating type test     performed, whether Monte Carlo simulation continuity     correction used. data.name character string giving name(s) data. observed observed counts. expected expected counts null hypothesis. residuals Pearson residuals,     (observed - expected) / sqrt(expected). stdres standardized residuals,     (observed - expected) / sqrt(V), V     residual cell variance (Agresti, 2007, section 2.4.5     case x matrix, n * p * (1 - p) otherwise).","code":""},{"path":"https://msberends.github.io/AMR/reference/g.test.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"G-test for Count Data — g.test","text":"x matrix one row column, x vector y given, goodness--fit test performed (x treated one-dimensional contingency table). entries x must non-negative integers. case, hypothesis tested whether population probabilities equal p, equal p given. x matrix least two rows columns, taken two-dimensional contingency table: entries x must non-negative integers.  Otherwise, x y must vectors factors length; cases missing values removed, objects coerced factors, contingency table computed .  Pearson's chi-squared test performed null hypothesis joint distribution cell counts 2-dimensional contingency table product row column marginals. p-value computed asymptotic chi-squared distribution test statistic. contingency table case simulation done random sampling set contingency tables given marginals, works marginals strictly positive. Note usual sampling situation assumed chi-squared test (G-test) rather Fisher's exact test. goodness--fit case simulation done random sampling discrete distribution specified p, sample size n = sum(x). simulation done R may slow.","code":""},{"path":"https://msberends.github.io/AMR/reference/g.test.html","id":"g-test-of-goodness-of-fit-likelihood-ratio-test-","dir":"Reference","previous_headings":"","what":"G-test Of Goodness-of-Fit (Likelihood Ratio Test)","title":"G-test for Count Data — g.test","text":"Use G-test goodness--fit one nominal variable two values (male female, red, pink white flowers). compare observed counts numbers observations category expected counts, calculate using kind theoretical expectation (1:1 sex ratio 1:2:1 ratio genetic cross). expected number observations category small, G-test may give inaccurate results, use exact test instead (fisher.test()). G-test goodness--fit alternative chi-square test goodness--fit (chisq.test()); tests advantages disadvantages, results two tests usually similar.","code":""},{"path":"https://msberends.github.io/AMR/reference/g.test.html","id":"g-test-of-independence","dir":"Reference","previous_headings":"","what":"G-test of Independence","title":"G-test for Count Data — g.test","text":"Use G-test independence two nominal variables, two possible values. want know whether proportions one variable different among values variable. also possible G-test independence two nominal variables. example, Jackson et al. (2013) also data children 3, analysis old vs. young, thigh vs. arm, reaction vs. reaction, analyzed together. Fisher's exact test (fisher.test()) exact test, G-test still approximation. 2x2 table, Fisher's Exact test may slower still run seconds, even sum observations multiple millions. G-test independence alternative chi-square test independence (chisq.test()), give approximately results.","code":""},{"path":"https://msberends.github.io/AMR/reference/g.test.html","id":"how-the-test-works","dir":"Reference","previous_headings":"","what":"How the Test Works","title":"G-test for Count Data — g.test","text":"Unlike exact test goodness--fit (fisher.test()), G-test directly calculate probability obtaining observed results something extreme. Instead, like almost statistical tests, G-test intermediate step; uses data calculate test statistic measures far observed data null expectation. use mathematical relationship, case chi-square distribution, estimate probability obtaining value test statistic. G-test uses log ratio two likelihoods test statistic, also called likelihood ratio test log-likelihood ratio test. formula calculate G-statistic : \\(G = 2 * sum(x * log(x / E))\\) E expected values. Since chi-square distributed, p value can calculated R :   df degrees freedom. two categories want find ones significantly different null expectation, can use method testing category vs. sum categories, Bonferroni correction. use G-tests category, course.","code":"p <- stats::pchisq(G, df, lower.tail = FALSE)"},{"path":"https://msberends.github.io/AMR/reference/g.test.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"G-test for Count Data — g.test","text":"McDonald, J.H. 2014. Handbook Biological Statistics (3rd ed.). Sparky House Publishing, Baltimore, Maryland. http://www.biostathandbook.com/gtestgof.html.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/g.test.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"G-test for Count Data — g.test","text":"","code":"# = EXAMPLE 1 = # Shivrain et al. (2006) crossed clearfield rice (which are resistant # to the herbicide imazethapyr) with red rice (which are susceptible to # imazethapyr). They then crossed the hybrid offspring and examined the # F2 generation, where they found 772 resistant plants, 1611 moderately # resistant plants, and 737 susceptible plants. If resistance is controlled # by a single gene with two co-dominant alleles, you would expect a 1:2:1 # ratio.  x <- c(772, 1611, 737) g.test(x, p = c(1, 2, 1) / 4) #>  #> \tG-test of goodness-of-fit (likelihood ratio test) #>  #> data:  x #> X-squared = 4.1471, p-value = 0.1257 #>   # There is no significant difference from a 1:2:1 ratio. # Meaning: resistance controlled by a single gene with two co-dominant # alleles, is plausible.   # = EXAMPLE 2 = # Red crossbills (Loxia curvirostra) have the tip of the upper bill either # right or left of the lower bill, which helps them extract seeds from pine # cones. Some have hypothesized that frequency-dependent selection would # keep the number of right and left-billed birds at a 1:1 ratio. Groth (1992) # observed 1752 right-billed and 1895 left-billed crossbills.  x <- c(1752, 1895) g.test(x) #>  #> \tG-test of goodness-of-fit (likelihood ratio test) #>  #> data:  x #> X-squared = 5.6085, p-value = 0.01787 #>   # There is a significant difference from a 1:1 ratio. # Meaning: there are significantly more left-billed birds."},{"path":"https://msberends.github.io/AMR/reference/get_episode.html","id":null,"dir":"Reference","previous_headings":"","what":"Determine Clinical or Epidemic Episodes — get_episode","title":"Determine Clinical or Epidemic Episodes — get_episode","text":"functions determine items vector can considered (start ) new episode. can used determine clinical episodes epidemiological analysis. get_episode() function returns index number episode per group, is_new_episode() function returns TRUE every new get_episode() index. absolute relative episode determination supported.","code":""},{"path":"https://msberends.github.io/AMR/reference/get_episode.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Determine Clinical or Epidemic Episodes — get_episode","text":"","code":"get_episode(x, episode_days = NULL, case_free_days = NULL, ...)  is_new_episode(x, episode_days = NULL, case_free_days = NULL, ...)"},{"path":"https://msberends.github.io/AMR/reference/get_episode.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Determine Clinical or Epidemic Episodes — get_episode","text":"x vector dates (class Date POSIXt), sorted internally determine episodes episode_days episode length days specify time period new episode begins, can also less day Inf, see Details case_free_days (inter-epidemic) interval length days new episode start, can also less day Inf, see Details ... ignored, place allow future extensions","code":""},{"path":"https://msberends.github.io/AMR/reference/get_episode.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Determine Clinical or Epidemic Episodes — get_episode","text":"get_episode(): integer vector is_new_episode(): logical vector","code":""},{"path":"https://msberends.github.io/AMR/reference/get_episode.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Determine Clinical or Epidemic Episodes — get_episode","text":"Episodes can determined two ways: absolute relative. Absolute method uses episode_days define episode length days, new episode start. common use case AMR data analysis microbial epidemiology: episodes S. aureus bacteraemia ICU patients example. episode length 30 days, new S. aureus isolates ICU episode 30 days considered different (new) episode. Thus, method counts since start previous episode. Relative method uses case_free_days quantify duration case-free days (inter-epidemic interval), new episode start. common use case infectious disease epidemiology: episodes norovirus outbreaks hospital example. case-free period 14 days, new norovirus cases time considered different (new) episode. Thus, methods counts since last case previous episode. table: ** marks start new episode, 8 January 2023 7 days since start previous episode (1 January 2023).  *** marks start new episode, 21 January 2023 7 days since last case previous episode (8 January 2023). Either episode_days case_free_days must provided function.","code":""},{"path":"https://msberends.github.io/AMR/reference/get_episode.html","id":"difference-between-get-episode-and-is-new-episode-","dir":"Reference","previous_headings":"","what":"Difference between get_episode() and is_new_episode()","title":"Determine Clinical or Epidemic Episodes — get_episode","text":"get_episode() function returns index number episode, cases/patients/isolates first episode number 1, cases/patients/isolates second episode number 2, etc. is_new_episode() function hand, returns TRUE every new get_episode() index. specify, setting episode_days = 365 (using method 1 explained ), two functions differ:","code":""},{"path":"https://msberends.github.io/AMR/reference/get_episode.html","id":"other","dir":"Reference","previous_headings":"","what":"Other","title":"Determine Clinical or Epidemic Episodes — get_episode","text":"first_isolate() function wrapper around is_new_episode() function, efficient data sets containing microorganism codes names allows different isolate selection methods. dplyr package required functions work, episode functions support variable grouping work conveniently inside dplyr verbs filter(), mutate() summarise().","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/get_episode.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Determine Clinical or Epidemic Episodes — get_episode","text":"","code":"# difference between absolute and relative determination of episodes: x <- data.frame(dates = as.Date(c(   \"2021-01-01\",   \"2021-01-02\",   \"2021-01-05\",   \"2021-01-08\",   \"2021-02-21\",   \"2021-02-22\",   \"2021-02-23\",   \"2021-02-24\",   \"2021-03-01\",   \"2021-03-01\" ))) x$absolute <- get_episode(x$dates, episode_days = 7) x$relative <- get_episode(x$dates, case_free_days = 7) x #>         dates absolute relative #> 1  2021-01-01        1        1 #> 2  2021-01-02        1        1 #> 3  2021-01-05        1        1 #> 4  2021-01-08        2        1 #> 5  2021-02-21        3        2 #> 6  2021-02-22        3        2 #> 7  2021-02-23        3        2 #> 8  2021-02-24        3        2 #> 9  2021-03-01        4        2 #> 10 2021-03-01        4        2   # `example_isolates` is a data set available in the AMR package. # See ?example_isolates df <- example_isolates[sample(seq_len(2000), size = 100), ]  get_episode(df$date, episode_days = 60) # indices #>   [1] 39 42 29 45 31 14 41 39 26 40 18 36 15 39 18 45 32 27 10  2 13 24 43 12  8 #>  [26]  5  3 12 31  9 16  4  1 26 32 27 21 45 42 17 16 21  8  4 30  1 17 25 34  5 #>  [51] 10  1 18 44 33  4  6 12 43  2 43 45 37 33 18 38 45 36 46  4 35 40 12  7 11 #>  [76] 23 10 35 20  4  5 29 27 41 12 30 45 18 47 22 28 39 19 27 16  4 21 40 33 39 is_new_episode(df$date, episode_days = 60) # TRUE/FALSE #>   [1]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE #>  [13]  TRUE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE #>  [25]  TRUE  TRUE  TRUE FALSE FALSE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE #>  [37]  TRUE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE  TRUE #>  [49]  TRUE FALSE FALSE FALSE FALSE  TRUE  TRUE FALSE  TRUE FALSE FALSE FALSE #>  [61] FALSE FALSE  TRUE FALSE FALSE  TRUE FALSE FALSE  TRUE FALSE  TRUE FALSE #>  [73] FALSE  TRUE  TRUE  TRUE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE #>  [85] FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE FALSE  TRUE FALSE FALSE FALSE #>  [97] FALSE FALSE FALSE FALSE  # filter on results from the third 60-day episode only, using base R df[which(get_episode(df$date, 60) == 3), ] #> # A tibble: 1 × 46 #>   date       patient   age gender ward  mo           PEN   OXA   FLC   AMX   #>   <date>     <chr>   <dbl> <chr>  <chr> <mo>         <sir> <sir> <sir> <sir> #> 1 2002-12-13 285137     78 F      ICU   B_ESCHR_COLI R     NA    NA    NA    #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, RIF <sir>  # the functions also work for less than a day, e.g. to include one per hour: get_episode(   c(     Sys.time(),     Sys.time() + 60 * 60   ),   episode_days = 1 / 24 ) #> [1] 1 2  # \\donttest{ if (require(\"dplyr\")) {   # is_new_episode() can also be used in dplyr verbs to determine patient   # episodes based on any (combination of) grouping variables:   df %>%     mutate(condition = sample(       x = c(\"A\", \"B\", \"C\"),       size = 100,       replace = TRUE     )) %>%     group_by(patient, condition) %>%     mutate(new_episode = is_new_episode(date, 365)) %>%     select(patient, date, condition, new_episode) %>%     arrange(patient, condition, date) } #> # A tibble: 100 × 4 #> # Groups:   patient, condition [97] #>    patient date       condition new_episode #>    <chr>   <date>     <chr>     <lgl>       #>  1 036063  2010-01-28 A         TRUE        #>  2 077922  2009-08-18 C         TRUE        #>  3 080086  2010-08-08 C         TRUE        #>  4 0DBF93  2015-10-12 B         TRUE        #>  5 105248  2005-06-16 A         TRUE        #>  6 114570  2003-04-08 B         TRUE        #>  7 119392  2010-11-01 C         TRUE        #>  8 161740  2005-06-21 A         TRUE        #>  9 174209  2011-10-03 C         TRUE        #> 10 210105  2009-06-13 C         TRUE        #> # ℹ 90 more rows  if (require(\"dplyr\")) {   df %>%     group_by(ward, patient) %>%     transmute(date,       patient,       new_index = get_episode(date, 60),       new_logical = is_new_episode(date, 60)     ) %>%     arrange(patient, ward, date) } #> # A tibble: 100 × 5 #> # Groups:   ward, patient [96] #>    ward       date       patient new_index new_logical #>    <chr>      <date>     <chr>       <int> <lgl>       #>  1 Clinical   2010-01-28 036063          1 TRUE        #>  2 Clinical   2009-08-18 077922          1 TRUE        #>  3 Clinical   2010-08-08 080086          1 TRUE        #>  4 Clinical   2015-10-12 0DBF93          1 TRUE        #>  5 Clinical   2005-06-16 105248          1 TRUE        #>  6 ICU        2003-04-08 114570          1 TRUE        #>  7 Clinical   2010-11-01 119392          1 TRUE        #>  8 Clinical   2005-06-21 161740          1 TRUE        #>  9 Outpatient 2011-10-03 174209          1 TRUE        #> 10 Clinical   2009-06-13 210105          1 TRUE        #> # ℹ 90 more rows  if (require(\"dplyr\")) {   df %>%     group_by(ward) %>%     summarise(       n_patients = n_distinct(patient),       n_episodes_365 = sum(is_new_episode(date, episode_days = 365)),       n_episodes_60 = sum(is_new_episode(date, episode_days = 60)),       n_episodes_30 = sum(is_new_episode(date, episode_days = 30))     ) } #> # A tibble: 3 × 5 #>   ward       n_patients n_episodes_365 n_episodes_60 n_episodes_30 #>   <chr>           <int>          <int>         <int>         <int> #> 1 Clinical           64             13            37            47 #> 2 ICU                23              9            17            20 #> 3 Outpatient          9              7             7             9  # grouping on patients and microorganisms leads to the same # results as first_isolate() when using 'episode-based': if (require(\"dplyr\")) {   x <- df %>%     filter_first_isolate(       include_unknown = TRUE,       method = \"episode-based\"     )    y <- df %>%     group_by(patient, mo) %>%     filter(is_new_episode(date, 365)) %>%     ungroup()    identical(x, y) } #> [1] TRUE  # but is_new_episode() has a lot more flexibility than first_isolate(), # since you can now group on anything that seems relevant: if (require(\"dplyr\")) {   df %>%     group_by(patient, mo, ward) %>%     mutate(flag_episode = is_new_episode(date, 365)) %>%     select(group_vars(.), flag_episode) } #> # A tibble: 100 × 4 #> # Groups:   patient, mo, ward [96] #>    patient mo           ward     flag_episode #>    <chr>   <mo>         <chr>    <lgl>        #>  1 A76045  B_ENTRC_FACM ICU      TRUE         #>  2 964129  B_SERRT_MRCS Clinical TRUE         #>  3 686445  B_STPHY_CONS Clinical TRUE         #>  4 D39422  B_KLBSL_PNMN Clinical TRUE         #>  5 298662  B_ESCHR_COLI Clinical TRUE         #>  6 5B78D5  B_STPHY_AURS Clinical TRUE         #>  7 E52625  B_STRPT_PNMN Clinical TRUE         #>  8 645121  B_SERRT_MRCS Clinical TRUE         #>  9 807228  B_STRPT_PNMN Clinical TRUE         #> 10 D41749  B_ESCHR_COLI ICU      TRUE         #> # ℹ 90 more rows # }"},{"path":"https://msberends.github.io/AMR/reference/ggplot_pca.html","id":null,"dir":"Reference","previous_headings":"","what":"PCA Biplot with ggplot2 — ggplot_pca","title":"PCA Biplot with ggplot2 — ggplot_pca","text":"Produces ggplot2 variant -called biplot PCA (principal component analysis), flexible appealing base R biplot() function.","code":""},{"path":"https://msberends.github.io/AMR/reference/ggplot_pca.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"PCA Biplot with ggplot2 — ggplot_pca","text":"","code":"ggplot_pca(   x,   choices = 1:2,   scale = 1,   pc.biplot = TRUE,   labels = NULL,   labels_textsize = 3,   labels_text_placement = 1.5,   groups = NULL,   ellipse = TRUE,   ellipse_prob = 0.68,   ellipse_size = 0.5,   ellipse_alpha = 0.5,   points_size = 2,   points_alpha = 0.25,   arrows = TRUE,   arrows_colour = \"darkblue\",   arrows_size = 0.5,   arrows_textsize = 3,   arrows_textangled = TRUE,   arrows_alpha = 0.75,   base_textsize = 10,   ... )"},{"path":"https://msberends.github.io/AMR/reference/ggplot_pca.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"PCA Biplot with ggplot2 — ggplot_pca","text":"ggplot_pca() function based ggbiplot() function ggbiplot package Vince Vu, found GitHub: https://github.com/vqv/ggbiplot (retrieved: 2 March 2020, latest commit: 7325e88; 12 February 2015). per GPL-2 licence demands documentation code changes, changes made based source code : Rewritten code remove dependency packages plyr, scales grid Parametrised options, like arrow ellipse settings Hardened input possibilities defining exact type user input every argument Added total amount explained variance caption plot Cleaned syntax based lintr package, fixed grammatical errors added integrity checks Updated documentation","code":""},{"path":"https://msberends.github.io/AMR/reference/ggplot_pca.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"PCA Biplot with ggplot2 — ggplot_pca","text":"x object returned pca(), prcomp() princomp() choices length 2 vector specifying components plot. default     biplot strict sense. scale variables scaled lambda ^ scale     observations scaled lambda ^ (1-scale)     lambda singular values computed     princomp. Normally 0 <= scale <= 1, warning     issued specified scale outside range. pc.biplot true, use Gabriel (1971) refers \"principal component     biplot\", lambda = 1 observations scaled sqrt(n)     variables scaled sqrt(n).  inner products     variables approximate covariances distances observations     approximate Mahalanobis distance. labels optional vector labels observations. set, labels placed respective points. using pca() function input x, determined automatically based attribute non_numeric_cols, see pca(). labels_textsize size text used labels labels_text_placement adjustment factor placement variable names (>=1 means away arrow head) groups optional vector groups labels, length labels. set, points labels coloured according groups. using pca() function input x, determined automatically based attribute non_numeric_cols, see pca(). ellipse logical indicate whether normal data ellipse drawn group (set groups) ellipse_prob statistical size ellipse normal probability ellipse_size size ellipse line ellipse_alpha alpha (transparency) ellipse line points_size size points points_alpha alpha (transparency) points arrows logical indicate whether arrows drawn arrows_colour colour arrow text arrows_size size (thickness) arrow lines arrows_textsize size text end arrows arrows_textangled logical whether text end arrows angled arrows_alpha alpha (transparency) arrows text base_textsize text size plot elements except labels arrows ... arguments passed functions","code":""},{"path":"https://msberends.github.io/AMR/reference/ggplot_pca.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"PCA Biplot with ggplot2 — ggplot_pca","text":"colours labels points can changed adding another scale layer colour, scale_colour_viridis_d() scale_colour_brewer().","code":""},{"path":"https://msberends.github.io/AMR/reference/ggplot_pca.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"PCA Biplot with ggplot2 — ggplot_pca","text":"","code":"# `example_isolates` is a data set available in the AMR package. # See ?example_isolates.  # \\donttest{ if (require(\"dplyr\")) {   # calculate the resistance per group first   resistance_data <- example_isolates %>%     group_by(       order = mo_order(mo), # group on anything, like order       genus = mo_genus(mo)     ) %>% #   and genus as we do here;     filter(n() >= 30) %>% # filter on only 30 results per group     summarise_if(is.sir, resistance) # then get resistance of all drugs    # now conduct PCA for certain antimicrobial drugs   pca_result <- resistance_data %>%     pca(AMC, CXM, CTX, CAZ, GEN, TOB, TMP, SXT)    summary(pca_result)    # old base R plotting method:   biplot(pca_result, main = \"Base R biplot\")    # new ggplot2 plotting method using this package:   if (require(\"ggplot2\")) {     ggplot_pca(pca_result) +       labs(title = \"ggplot2 biplot\")   }   if (require(\"ggplot2\")) {     # still extendible with any ggplot2 function     ggplot_pca(pca_result) +       scale_colour_viridis_d() +       labs(title = \"ggplot2 biplot\")   } } #> Warning: There were 73 warnings in `summarise()`. #> The first warning was: #> ℹ In argument: `PEN = (function (..., minimum = 30, as_percent = FALSE, #>   only_all_tested = FALSE) ...`. #> ℹ In group 5: `order = \"Lactobacillales\"` and `genus = \"Enterococcus\"`. #> Caused by warning: #> ! Introducing NA: only 14 results available for PEN in group: order = #> \"Lactobacillales\", genus = \"Enterococcus\" (minimum = 30). #> ℹ Run `dplyr::last_dplyr_warnings()` to see the 72 remaining warnings. #> ℹ Columns selected for PCA: \"AMC\", \"CAZ\", \"CTX\", \"CXM\", \"GEN\", \"SXT\", #>   \"TMP\", and \"TOB\". Total observations available: 7. #> Groups (n=4, named as 'order'): #> [1] \"Caryophanales\"    \"Enterobacterales\" \"Lactobacillales\"  \"Pseudomonadales\"  #>    # }"},{"path":"https://msberends.github.io/AMR/reference/ggplot_sir.html","id":null,"dir":"Reference","previous_headings":"","what":"AMR Plots with ggplot2 — ggplot_sir","title":"AMR Plots with ggplot2 — ggplot_sir","text":"Use functions create bar plots AMR data analysis. functions rely ggplot2 functions.","code":""},{"path":"https://msberends.github.io/AMR/reference/ggplot_sir.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"AMR Plots with ggplot2 — ggplot_sir","text":"","code":"ggplot_sir(   data,   position = NULL,   x = \"antibiotic\",   fill = \"interpretation\",   facet = NULL,   breaks = seq(0, 1, 0.1),   limits = NULL,   translate_ab = \"name\",   combine_SI = TRUE,   minimum = 30,   language = get_AMR_locale(),   nrow = NULL,   colours = c(S = \"#3CAEA3\", SI = \"#3CAEA3\", I = \"#F6D55C\", IR = \"#ED553B\", R =     \"#ED553B\"),   datalabels = TRUE,   datalabels.size = 2.5,   datalabels.colour = \"grey15\",   title = NULL,   subtitle = NULL,   caption = NULL,   x.title = \"Antimicrobial\",   y.title = \"Proportion\",   ... )  geom_sir(   position = NULL,   x = c(\"antibiotic\", \"interpretation\"),   fill = \"interpretation\",   translate_ab = \"name\",   minimum = 30,   language = get_AMR_locale(),   combine_SI = TRUE,   ... )  facet_sir(facet = c(\"interpretation\", \"antibiotic\"), nrow = NULL)  scale_y_percent(breaks = seq(0, 1, 0.1), limits = NULL)  scale_sir_colours(..., aesthetics = \"fill\")  theme_sir()  labels_sir_count(   position = NULL,   x = \"antibiotic\",   translate_ab = \"name\",   minimum = 30,   language = get_AMR_locale(),   combine_SI = TRUE,   datalabels.size = 3,   datalabels.colour = \"grey15\" )"},{"path":"https://msberends.github.io/AMR/reference/ggplot_sir.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"AMR Plots with ggplot2 — ggplot_sir","text":"data data.frame column(s) class sir (see .sir()) position position adjustment bars, either \"fill\", \"stack\" \"dodge\" x variable show x axis, either \"antibiotic\" (default) \"interpretation\" grouping variable fill variable categorise using plots legend, either \"antibiotic\" (default) \"interpretation\" grouping variable facet variable split plots , either \"interpretation\" (default) \"antibiotic\" grouping variable breaks numeric vector positions limits numeric vector length two providing limits scale, use NA refer existing minimum maximum translate_ab column name antibiotics data set translate antibiotic abbreviations , using ab_property() combine_SI logical indicate whether values S must merged one, output consists S+vs. R (susceptible vs. resistant) - default TRUE minimum minimum allowed number available (tested) isolates. isolate count lower minimum return NA warning. default number 30 isolates advised Clinical Laboratory Standards Institute (CLSI) best practice, see Source. language language returned text - default current system language (see get_AMR_locale()) can also set package option AMR_locale. Use language = NULL language = \"\" prevent translation. nrow (using facet) number rows colours named vactor colour used filling. default colours colour-blind friendly. datalabels show datalabels using labels_sir_count() datalabels.size size datalabels datalabels.colour colour datalabels title text show title plot subtitle text show subtitle plot caption text show caption plot x.title text show x axis description y.title text show y axis description ... arguments passed geom_sir() , case scale_sir_colours(), named values set colours. default colours colour-blind friendly, maintaining convention e.g. 'susceptible' green 'resistant' red. See Examples. aesthetics aesthetics apply colours - default \"fill\" can also (combination ) \"alpha\", \"colour\", \"fill\", \"linetype\", \"shape\" \"size\"","code":""},{"path":"https://msberends.github.io/AMR/reference/ggplot_sir.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"AMR Plots with ggplot2 — ggplot_sir","text":"default, names antibiotics shown plots using ab_name(). can set translate_ab argument. See count_df().","code":""},{"path":"https://msberends.github.io/AMR/reference/ggplot_sir.html","id":"the-functions","dir":"Reference","previous_headings":"","what":"The Functions","title":"AMR Plots with ggplot2 — ggplot_sir","text":"geom_sir() take variable data sir class (created .sir()) using sir_df() plot bars percentage S, , R. default behaviour bars stacked different antibiotics x axis. facet_sir() creates 2d plots (default based S//R) using ggplot2::facet_wrap(). scale_y_percent() transforms y axis 0 100% range using ggplot2::scale_y_continuous(). scale_sir_colours() sets colours bars (green S, yellow , red R). multilingual support. default colours colour-blind friendly, maintaining convention e.g. 'susceptible' green 'resistant' red. theme_sir() [ggplot2 theme][ggplot2::theme() minimal distraction. labels_sir_count() print datalabels bars percentage amount isolates using ggplot2::geom_text(). ggplot_sir() wrapper around functions uses data first input. makes possible use function pipe (%>%). See Examples.","code":""},{"path":"https://msberends.github.io/AMR/reference/ggplot_sir.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"AMR Plots with ggplot2 — ggplot_sir","text":"","code":"# \\donttest{ if (require(\"ggplot2\") && require(\"dplyr\")) {   # get antimicrobial results for drugs against a UTI:   ggplot(example_isolates %>% select(AMX, NIT, FOS, TMP, CIP)) +     geom_sir() }  if (require(\"ggplot2\") && require(\"dplyr\")) {   # prettify the plot using some additional functions:   df <- example_isolates %>% select(AMX, NIT, FOS, TMP, CIP)   ggplot(df) +     geom_sir() +     scale_y_percent() +     scale_sir_colours() +     labels_sir_count() +     theme_sir() }  if (require(\"ggplot2\") && require(\"dplyr\")) {   # or better yet, simplify this using the wrapper function - a single command:   example_isolates %>%     select(AMX, NIT, FOS, TMP, CIP) %>%     ggplot_sir() }  if (require(\"ggplot2\") && require(\"dplyr\")) {   # get only proportions and no counts:   example_isolates %>%     select(AMX, NIT, FOS, TMP, CIP) %>%     ggplot_sir(datalabels = FALSE) }  if (require(\"ggplot2\") && require(\"dplyr\")) {   # add other ggplot2 arguments as you like:   example_isolates %>%     select(AMX, NIT, FOS, TMP, CIP) %>%     ggplot_sir(       width = 0.5,       colour = \"black\",       size = 1,       linetype = 2,       alpha = 0.25     ) }  if (require(\"ggplot2\") && require(\"dplyr\")) {   # you can alter the colours with colour names:   example_isolates %>%     select(AMX) %>%     ggplot_sir(colours = c(SI = \"yellow\")) }  if (require(\"ggplot2\") && require(\"dplyr\")) {   # but you can also use the built-in colour-blind friendly colours for   # your plots, where \"S\" is green, \"I\" is yellow and \"R\" is red:   data.frame(     x = c(\"Value1\", \"Value2\", \"Value3\"),     y = c(1, 2, 3),     z = c(\"Value4\", \"Value5\", \"Value6\")   ) %>%     ggplot() +     geom_col(aes(x = x, y = y, fill = z)) +     scale_sir_colours(Value4 = \"S\", Value5 = \"I\", Value6 = \"R\") }  if (require(\"ggplot2\") && require(\"dplyr\")) {   # resistance of ciprofloxacine per age group   example_isolates %>%     mutate(first_isolate = first_isolate()) %>%     filter(       first_isolate == TRUE,       mo == as.mo(\"Escherichia coli\")     ) %>%     # age_groups() is also a function in this AMR package:     group_by(age_group = age_groups(age)) %>%     select(age_group, CIP) %>%     ggplot_sir(x = \"age_group\") } #> Warning: Removed 6 rows containing missing values or values outside the scale range #> (`geom_col()`). #> Warning: Removed 6 rows containing missing values or values outside the scale range #> (`geom_text()`).  if (require(\"ggplot2\") && require(\"dplyr\")) {   # a shorter version which also adjusts data label colours:   example_isolates %>%     select(AMX, NIT, FOS, TMP, CIP) %>%     ggplot_sir(colours = FALSE) }  if (require(\"ggplot2\") && require(\"dplyr\")) {   # it also supports groups (don't forget to use the group var on `x` or `facet`):   example_isolates %>%     filter(mo_is_gram_negative(), ward != \"Outpatient\") %>%     # select only UTI-specific drugs     select(ward, AMX, NIT, FOS, TMP, CIP) %>%     group_by(ward) %>%     ggplot_sir(       x = \"ward\",       facet = \"antibiotic\",       nrow = 1,       title = \"AMR of Anti-UTI Drugs Per Ward\",       x.title = \"Ward\",       datalabels = FALSE     ) } #> ℹ Using column 'mo' as input for mo_is_gram_negative()  # }"},{"path":"https://msberends.github.io/AMR/reference/guess_ab_col.html","id":null,"dir":"Reference","previous_headings":"","what":"Guess Antibiotic Column — guess_ab_col","title":"Guess Antibiotic Column — guess_ab_col","text":"tries find column name data set based information antibiotics data set. Also supports WHONET abbreviations.","code":""},{"path":"https://msberends.github.io/AMR/reference/guess_ab_col.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Guess Antibiotic Column — guess_ab_col","text":"","code":"guess_ab_col(   x = NULL,   search_string = NULL,   verbose = FALSE,   only_sir_columns = FALSE )"},{"path":"https://msberends.github.io/AMR/reference/guess_ab_col.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Guess Antibiotic Column — guess_ab_col","text":"x data.frame search_string text search x , checked .ab() value column x verbose logical indicate whether additional info printed only_sir_columns logical indicate whether antibiotic columns must detected transformed class sir (see .sir()) beforehand (default FALSE)","code":""},{"path":"https://msberends.github.io/AMR/reference/guess_ab_col.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Guess Antibiotic Column — guess_ab_col","text":"column name x, NULL result found.","code":""},{"path":"https://msberends.github.io/AMR/reference/guess_ab_col.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Guess Antibiotic Column — guess_ab_col","text":"can look antibiotic (trade) name abbreviation search x antibiotics data set column containing name code antibiotic.","code":""},{"path":"https://msberends.github.io/AMR/reference/guess_ab_col.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Guess Antibiotic Column — guess_ab_col","text":"","code":"df <- data.frame(   amox = \"S\",   tetr = \"R\" )  guess_ab_col(df, \"amoxicillin\") #> [1] \"amox\" guess_ab_col(df, \"J01AA07\") # ATC code of tetracycline #> [1] \"tetr\"  guess_ab_col(df, \"J01AA07\", verbose = TRUE) #> Auto-guessing columns suitable for analysis #> ... #>  OK. #> ℹ Using column 'amox' as input for AMX (amoxicillin). #> ℹ Using column 'tetr' as input for TCY (tetracycline). #> ℹ Using column 'tetr' as input for J01AA07 (tetracycline). #> [1] \"tetr\" # NOTE: Using column 'tetr' as input for J01AA07 (tetracycline).  # WHONET codes df <- data.frame(   AMP_ND10 = \"R\",   AMC_ED20 = \"S\" ) guess_ab_col(df, \"ampicillin\") #> [1] \"AMP_ND10\" guess_ab_col(df, \"J01CR02\") #> [1] \"AMC_ED20\" guess_ab_col(df, as.ab(\"augmentin\")) #> [1] \"AMC_ED20\""},{"path":"https://msberends.github.io/AMR/reference/intrinsic_resistant.html","id":null,"dir":"Reference","previous_headings":"","what":"Data Set with Bacterial Intrinsic Resistance — intrinsic_resistant","title":"Data Set with Bacterial Intrinsic Resistance — intrinsic_resistant","text":"Data set containing defined intrinsic resistance EUCAST bug-drug combinations.","code":""},{"path":"https://msberends.github.io/AMR/reference/intrinsic_resistant.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Data Set with Bacterial Intrinsic Resistance — intrinsic_resistant","text":"","code":"intrinsic_resistant"},{"path":"https://msberends.github.io/AMR/reference/intrinsic_resistant.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data Set with Bacterial Intrinsic Resistance — intrinsic_resistant","text":"tibble 340 804 observations 2 variables: mo Microorganism ID ab Antibiotic ID","code":""},{"path":"https://msberends.github.io/AMR/reference/intrinsic_resistant.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Data Set with Bacterial Intrinsic Resistance — intrinsic_resistant","text":"data set based 'EUCAST Expert Rules' 'EUCAST Intrinsic Resistance Unusual Phenotypes' v3.3 (2021).","code":""},{"path":"https://msberends.github.io/AMR/reference/intrinsic_resistant.html","id":"direct-download","dir":"Reference","previous_headings":"","what":"Direct download","title":"Data Set with Bacterial Intrinsic Resistance — intrinsic_resistant","text":"Like data sets package, data set publicly available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. Please visit website download links. actual files course available GitHub repository. allow machine reading EUCAST CLSI guidelines, almost impossible MS Excel PDF files distributed EUCAST CLSI.","code":""},{"path":"https://msberends.github.io/AMR/reference/intrinsic_resistant.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Data Set with Bacterial Intrinsic Resistance — intrinsic_resistant","text":"","code":"intrinsic_resistant #> # A tibble: 340,804 × 2 #>    mo          ab   #>    <mo>        <ab> #>  1 B_GRAMP     ATM  #>  2 B_GRAMP     COL  #>  3 B_GRAMP     NAL  #>  4 B_GRAMP     PLB  #>  5 B_GRAMP     TEM  #>  6 B_ANAER-POS ATM  #>  7 B_ANAER-POS COL  #>  8 B_ANAER-POS NAL  #>  9 B_ANAER-POS PLB  #> 10 B_ANAER-POS TEM  #> # ℹ 340,794 more rows"},{"path":"https://msberends.github.io/AMR/reference/italicise_taxonomy.html","id":null,"dir":"Reference","previous_headings":"","what":"Italicise Taxonomic Families, Genera, Species, Subspecies — italicise_taxonomy","title":"Italicise Taxonomic Families, Genera, Species, Subspecies — italicise_taxonomy","text":"According binomial nomenclature, lowest four taxonomic levels (family, genus, species, subspecies) printed italics. function finds taxonomic names within strings makes italic.","code":""},{"path":"https://msberends.github.io/AMR/reference/italicise_taxonomy.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Italicise Taxonomic Families, Genera, Species, Subspecies — italicise_taxonomy","text":"","code":"italicise_taxonomy(string, type = c(\"markdown\", \"ansi\", \"html\"))  italicize_taxonomy(string, type = c(\"markdown\", \"ansi\", \"html\"))"},{"path":"https://msberends.github.io/AMR/reference/italicise_taxonomy.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Italicise Taxonomic Families, Genera, Species, Subspecies — italicise_taxonomy","text":"string character (vector) type type conversion taxonomic names, either \"markdown\", \"html\" \"ansi\", see Details","code":""},{"path":"https://msberends.github.io/AMR/reference/italicise_taxonomy.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Italicise Taxonomic Families, Genera, Species, Subspecies — italicise_taxonomy","text":"function finds taxonomic names makes italic based microorganisms data set. taxonomic names can italicised using markdown (default) adding * taxonomic names, <> <\/> using html. using 'ansi', ANSI colours added using \\033[3m \\033[23m taxonomic names. multiple ANSI colours available, conversion occur. function also supports abbreviation genus followed species, \"E. coli\" \"K. pneumoniae ozaenae\".","code":""},{"path":"https://msberends.github.io/AMR/reference/italicise_taxonomy.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Italicise Taxonomic Families, Genera, Species, Subspecies — italicise_taxonomy","text":"","code":"italicise_taxonomy(\"An overview of Staphylococcus aureus isolates\") #> [1] \"An overview of *Staphylococcus aureus* isolates\" italicise_taxonomy(\"An overview of S. aureus isolates\") #> [1] \"An overview of *S. aureus* isolates\"  cat(italicise_taxonomy(\"An overview of S. aureus isolates\", type = \"ansi\")) #> An overview of S. aureus isolates"},{"path":"https://msberends.github.io/AMR/reference/join.html","id":null,"dir":"Reference","previous_headings":"","what":"Join microorganisms to a Data Set — join","title":"Join microorganisms to a Data Set — join","text":"Join data set microorganisms easily existing data set character vector.","code":""},{"path":"https://msberends.github.io/AMR/reference/join.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Join microorganisms to a Data Set — join","text":"","code":"inner_join_microorganisms(x, by = NULL, suffix = c(\"2\", \"\"), ...)  left_join_microorganisms(x, by = NULL, suffix = c(\"2\", \"\"), ...)  right_join_microorganisms(x, by = NULL, suffix = c(\"2\", \"\"), ...)  full_join_microorganisms(x, by = NULL, suffix = c(\"2\", \"\"), ...)  semi_join_microorganisms(x, by = NULL, ...)  anti_join_microorganisms(x, by = NULL, ...)"},{"path":"https://msberends.github.io/AMR/reference/join.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Join microorganisms to a Data Set — join","text":"x existing data set join, character vector. case character vector, resulting data.frame contain column 'x' values. variable join - left empty search column class mo (created .mo()) \"mo\" column name exists x, otherwise column name x values exist microorganisms$mo (= \"bacteria_id\"), another column microorganisms (named, like = c(\"bacteria_id\" = \"fullname\")) suffix non-joined duplicate variables x y, suffixes added output disambiguate . character vector length 2. ... ignored, place allow future extensions","code":""},{"path":"https://msberends.github.io/AMR/reference/join.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Join microorganisms to a Data Set — join","text":"data.frame","code":""},{"path":"https://msberends.github.io/AMR/reference/join.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Join microorganisms to a Data Set — join","text":"Note: opposed join() functions dplyr, character vectors supported default existing columns get suffix \"2\" newly joined columns get suffix. dplyr package installed, join functions used. Otherwise, much slower merge() interaction() functions base R used.","code":""},{"path":"https://msberends.github.io/AMR/reference/join.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Join microorganisms to a Data Set — join","text":"","code":"left_join_microorganisms(as.mo(\"K. pneumoniae\")) #> # A tibble: 1 × 26 #>   mo           fullname   status kingdom phylum class order family genus species #>   <mo>         <chr>      <chr>  <chr>   <chr>  <chr> <chr> <chr>  <chr> <chr>   #> 1 B_KLBSL_PNMN Klebsiell… accep… Bacter… Pseud… Gamm… Ente… Enter… Kleb… pneumo… #> # ℹ 16 more variables: subspecies <chr>, rank <chr>, ref <chr>, #> #   oxygen_tolerance <chr>, source <chr>, lpsn <chr>, lpsn_parent <chr>, #> #   lpsn_renamed_to <chr>, mycobank <chr>, mycobank_parent <chr>, #> #   mycobank_renamed_to <chr>, gbif <chr>, gbif_parent <chr>, #> #   gbif_renamed_to <chr>, prevalence <dbl>, snomed <list> left_join_microorganisms(\"B_KLBSL_PNMN\") #> # A tibble: 1 × 26 #>   mo           fullname   status kingdom phylum class order family genus species #>   <mo>         <chr>      <chr>  <chr>   <chr>  <chr> <chr> <chr>  <chr> <chr>   #> 1 B_KLBSL_PNMN Klebsiell… accep… Bacter… Pseud… Gamm… Ente… Enter… Kleb… pneumo… #> # ℹ 16 more variables: subspecies <chr>, rank <chr>, ref <chr>, #> #   oxygen_tolerance <chr>, source <chr>, lpsn <chr>, lpsn_parent <chr>, #> #   lpsn_renamed_to <chr>, mycobank <chr>, mycobank_parent <chr>, #> #   mycobank_renamed_to <chr>, gbif <chr>, gbif_parent <chr>, #> #   gbif_renamed_to <chr>, prevalence <dbl>, snomed <list>  df <- data.frame(   date = seq(     from = as.Date(\"2018-01-01\"),     to = as.Date(\"2018-01-07\"),     by = 1   ),   bacteria = as.mo(c(     \"S. aureus\", \"MRSA\", \"MSSA\", \"STAAUR\",     \"E. coli\", \"E. coli\", \"E. coli\"   )),   stringsAsFactors = FALSE ) colnames(df) #> [1] \"date\"     \"bacteria\"  df_joined <- left_join_microorganisms(df, \"bacteria\") colnames(df_joined) #>  [1] \"date\"                \"bacteria\"            \"fullname\"            #>  [4] \"status\"              \"kingdom\"             \"phylum\"              #>  [7] \"class\"               \"order\"               \"family\"              #> [10] \"genus\"               \"species\"             \"subspecies\"          #> [13] \"rank\"                \"ref\"                 \"oxygen_tolerance\"    #> [16] \"source\"              \"lpsn\"                \"lpsn_parent\"         #> [19] \"lpsn_renamed_to\"     \"mycobank\"            \"mycobank_parent\"     #> [22] \"mycobank_renamed_to\" \"gbif\"                \"gbif_parent\"         #> [25] \"gbif_renamed_to\"     \"prevalence\"          \"snomed\"               # \\donttest{ if (require(\"dplyr\")) {   example_isolates %>%     left_join_microorganisms() %>%     colnames() } #> Joining, by = \"mo\" #>  [1] \"date\"                \"patient\"             \"age\"                 #>  [4] \"gender\"              \"ward\"                \"mo\"                  #>  [7] \"PEN\"                 \"OXA\"                 \"FLC\"                 #> [10] \"AMX\"                 \"AMC\"                 \"AMP\"                 #> [13] \"TZP\"                 \"CZO\"                 \"FEP\"                 #> [16] \"CXM\"                 \"FOX\"                 \"CTX\"                 #> [19] \"CAZ\"                 \"CRO\"                 \"GEN\"                 #> [22] \"TOB\"                 \"AMK\"                 \"KAN\"                 #> [25] \"TMP\"                 \"SXT\"                 \"NIT\"                 #> [28] \"FOS\"                 \"LNZ\"                 \"CIP\"                 #> [31] \"MFX\"                 \"VAN\"                 \"TEC\"                 #> [34] \"TCY\"                 \"TGC\"                 \"DOX\"                 #> [37] \"ERY\"                 \"CLI\"                 \"AZM\"                 #> [40] \"IPM\"                 \"MEM\"                 \"MTR\"                 #> [43] \"CHL\"                 \"COL\"                 \"MUP\"                 #> [46] \"RIF\"                 \"fullname\"            \"status\"              #> [49] \"kingdom\"             \"phylum\"              \"class\"               #> [52] \"order\"               \"family\"              \"genus\"               #> [55] \"species\"             \"subspecies\"          \"rank\"                #> [58] \"ref\"                 \"oxygen_tolerance\"    \"source\"              #> [61] \"lpsn\"                \"lpsn_parent\"         \"lpsn_renamed_to\"     #> [64] \"mycobank\"            \"mycobank_parent\"     \"mycobank_renamed_to\" #> [67] \"gbif\"                \"gbif_parent\"         \"gbif_renamed_to\"     #> [70] \"prevalence\"          \"snomed\"              # }"},{"path":"https://msberends.github.io/AMR/reference/key_antimicrobials.html","id":null,"dir":"Reference","previous_headings":"","what":"(Key) Antimicrobials for First Weighted Isolates — key_antimicrobials","title":"(Key) Antimicrobials for First Weighted Isolates — key_antimicrobials","text":"functions can used determine first weighted isolates considering phenotype isolate selection (see first_isolate()). Using phenotype-based method determine first isolates reliable methods disregard phenotypes.","code":""},{"path":"https://msberends.github.io/AMR/reference/key_antimicrobials.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"(Key) Antimicrobials for First Weighted Isolates — key_antimicrobials","text":"","code":"key_antimicrobials(   x = NULL,   col_mo = NULL,   universal = c(\"ampicillin\", \"amoxicillin/clavulanic acid\", \"cefuroxime\",     \"piperacillin/tazobactam\", \"ciprofloxacin\", \"trimethoprim/sulfamethoxazole\"),   gram_negative = c(\"gentamicin\", \"tobramycin\", \"colistin\", \"cefotaxime\", \"ceftazidime\",     \"meropenem\"),   gram_positive = c(\"vancomycin\", \"teicoplanin\", \"tetracycline\", \"erythromycin\",     \"oxacillin\", \"rifampin\"),   antifungal = c(\"anidulafungin\", \"caspofungin\", \"fluconazole\", \"miconazole\", \"nystatin\",     \"voriconazole\"),   only_sir_columns = FALSE,   ... )  all_antimicrobials(x = NULL, only_sir_columns = FALSE, ...)  antimicrobials_equal(   y,   z,   type = c(\"points\", \"keyantimicrobials\"),   ignore_I = TRUE,   points_threshold = 2,   ... )"},{"path":"https://msberends.github.io/AMR/reference/key_antimicrobials.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"(Key) Antimicrobials for First Weighted Isolates — key_antimicrobials","text":"x data.frame antibiotics columns, like AMX amox. Can left blank determine automatically col_mo column name names codes microorganisms (see .mo()) - default first column class mo. Values coerced using .mo(). universal names broad-spectrum antimicrobial drugs, case-insensitive. Set NULL ignore. See Details default antimicrobial drugs gram_negative names antibiotic drugs Gram-positives, case-insensitive. Set NULL ignore. See Details default antibiotic drugs gram_positive names antibiotic drugs Gram-negatives, case-insensitive. Set NULL ignore. See Details default antibiotic drugs antifungal names antifungal drugs fungi, case-insensitive. Set NULL ignore. See Details default antifungal drugs only_sir_columns logical indicate whether columns must included transformed class sir (see .sir()) beforehand (default FALSE) ... ignored, place allow future extensions y, z character vectors compare type type determine weighed isolates; can \"keyantimicrobials\" \"points\", see Details ignore_I logical indicate whether antibiotic interpretations \"\" ignored type = \"keyantimicrobials\", see Details points_threshold minimum number points require differences antibiogram lead inclusion isolate type = \"points\", see Details","code":""},{"path":"https://msberends.github.io/AMR/reference/key_antimicrobials.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"(Key) Antimicrobials for First Weighted Isolates — key_antimicrobials","text":"key_antimicrobials() all_antimicrobials() functions context-aware. means x argument can left blank used inside data.frame call, see Examples. function key_antimicrobials() returns character vector 12 antimicrobial results every isolate. function all_antimicrobials() returns character vector antimicrobial drug results every isolate. vectors can compared using antimicrobials_equal(), check two isolates generally antibiogram. Missing invalid values replaced dot (\".\") key_antimicrobials() ignored antimicrobials_equal(). Please see first_isolate() function important functions enable 'phenotype-based' method determination first isolates. default antimicrobial drugs used rows (set universal) : Ampicillin Amoxicillin/clavulanic acid Cefuroxime Ciprofloxacin Piperacillin/tazobactam Trimethoprim/sulfamethoxazole default antimicrobial drugs used Gram-negative bacteria (set gram_negative) : Cefotaxime Ceftazidime Colistin Gentamicin Meropenem Tobramycin default antimicrobial drugs used Gram-positive bacteria (set gram_positive) : Erythromycin Oxacillin Rifampin Teicoplanin Tetracycline Vancomycin default antimicrobial drugs used fungi (set antifungal) : Anidulafungin Caspofungin Fluconazole Miconazole Nystatin Voriconazole","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/key_antimicrobials.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"(Key) Antimicrobials for First Weighted Isolates — key_antimicrobials","text":"","code":"# `example_isolates` is a data set available in the AMR package. # See ?example_isolates.  # output of the `key_antimicrobials()` function could be like this: strainA <- \"SSSRR.S.R..S\" strainB <- \"SSSIRSSSRSSS\"  # those strings can be compared with: antimicrobials_equal(strainA, strainB, type = \"keyantimicrobials\") #> [1] TRUE # TRUE, because I is ignored (as well as missing values)  antimicrobials_equal(strainA, strainB, type = \"keyantimicrobials\", ignore_I = FALSE) #> [1] FALSE # FALSE, because I is not ignored and so the 4th [character] differs  # \\donttest{ if (require(\"dplyr\")) {   # set key antibiotics to a new variable   my_patients <- example_isolates %>%     mutate(keyab = key_antimicrobials(antifungal = NULL)) %>% # no need to define `x`     mutate(       # now calculate first isolates       first_regular = first_isolate(col_keyantimicrobials = FALSE),       # and first WEIGHTED isolates       first_weighted = first_isolate(col_keyantimicrobials = \"keyab\")     )    # Check the difference in this data set, 'weighted' results in more isolates:   sum(my_patients$first_regular, na.rm = TRUE)   sum(my_patients$first_weighted, na.rm = TRUE) } #> [1] 1376 # }"},{"path":"https://msberends.github.io/AMR/reference/kurtosis.html","id":null,"dir":"Reference","previous_headings":"","what":"Kurtosis of the Sample — kurtosis","title":"Kurtosis of the Sample — kurtosis","text":"Kurtosis measure \"tailedness\" probability distribution real-valued random variable. normal distribution kurtosis 3 excess kurtosis 0.","code":""},{"path":"https://msberends.github.io/AMR/reference/kurtosis.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Kurtosis of the Sample — kurtosis","text":"","code":"kurtosis(x, na.rm = FALSE, excess = FALSE)  # Default S3 method kurtosis(x, na.rm = FALSE, excess = FALSE)  # S3 method for class 'matrix' kurtosis(x, na.rm = FALSE, excess = FALSE)  # S3 method for class 'data.frame' kurtosis(x, na.rm = FALSE, excess = FALSE)"},{"path":"https://msberends.github.io/AMR/reference/kurtosis.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Kurtosis of the Sample — kurtosis","text":"x vector values, matrix data.frame na.rm logical indicate whether NA values stripped computation proceeds excess logical indicate whether excess kurtosis returned, defined kurtosis minus 3.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/kurtosis.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Kurtosis of the Sample — kurtosis","text":"","code":"kurtosis(rnorm(10000)) #> [1] 3.021297 kurtosis(rnorm(10000), excess = TRUE) #> [1] 0.08143396"},{"path":"https://msberends.github.io/AMR/reference/like.html","id":null,"dir":"Reference","previous_headings":"","what":"Vectorised Pattern Matching with Keyboard Shortcut — like","title":"Vectorised Pattern Matching with Keyboard Shortcut — like","text":"Convenient wrapper around grepl() match pattern: x %like% pattern. always returns logical vector always case-insensitive (use x %like_case% pattern case-sensitive matching). Also, pattern can long x compare items index vectors, can length iterate cases.","code":""},{"path":"https://msberends.github.io/AMR/reference/like.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Vectorised Pattern Matching with Keyboard Shortcut — like","text":"","code":"like(x, pattern, ignore.case = TRUE)  x %like% pattern  x %unlike% pattern  x %like_case% pattern  x %unlike_case% pattern"},{"path":"https://msberends.github.io/AMR/reference/like.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Vectorised Pattern Matching with Keyboard Shortcut — like","text":"Idea like function data.table package, although altered explained Details.","code":""},{"path":"https://msberends.github.io/AMR/reference/like.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Vectorised Pattern Matching with Keyboard Shortcut — like","text":"x character vector matches sought, object can coerced .character() character vector. pattern character vector containing regular expressions (character string fixed = TRUE) matched given character vector. Coerced .character() character string possible. ignore.case FALSE, pattern matching case sensitive TRUE, case ignored matching.","code":""},{"path":"https://msberends.github.io/AMR/reference/like.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Vectorised Pattern Matching with Keyboard Shortcut — like","text":"logical vector","code":""},{"path":"https://msberends.github.io/AMR/reference/like.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Vectorised Pattern Matching with Keyboard Shortcut — like","text":"like() %like%/%unlike% functions: case-insensitive (use %like_case%/%unlike_case% case-sensitive matching) Support multiple patterns Check pattern valid regular expression sets fixed = TRUE , greatly improve speed (vectorised pattern) Always use compatibility Perl unless fixed = TRUE, greatly improve speed Using RStudio? %like%/%unlike% functions can also directly inserted code Addins menu can keyboard shortcut like Shift+Ctrl+L Shift+Cmd+L (see menu Tools > Modify Keyboard Shortcuts...). keep pressing shortcut, inserted text iterated %like% -> %unlike% -> %like_case% -> %unlike_case%.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/like.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Vectorised Pattern Matching with Keyboard Shortcut — like","text":"","code":"# data.table has a more limited version of %like%, so unload it: try(detach(\"package:data.table\", unload = TRUE), silent = TRUE)  a <- \"This is a test\" b <- \"TEST\" a %like% b #> [1] TRUE b %like% a #> [1] FALSE  # also supports multiple patterns a <- c(\"Test case\", \"Something different\", \"Yet another thing\") b <- c(\"case\", \"diff\", \"yet\") a %like% b #> [1] TRUE TRUE TRUE a %unlike% b #> [1] FALSE FALSE FALSE  a[1] %like% b #> [1]  TRUE FALSE FALSE a %like% b[1] #> [1]  TRUE FALSE FALSE  # \\donttest{ # get isolates whose name start with 'Entero' (case-insensitive) example_isolates[which(mo_name() %like% \"^entero\"), ] #> ℹ Using column 'mo' as input for mo_name() #> # A tibble: 106 × 46 #>    date       patient   age gender ward    mo            PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>   <mo>          <sir> <sir> <sir> <sir> #>  1 2002-02-21 4FC193     69 M      Clinic… B_ENTRC_FACM  NA    NA    NA    NA    #>  2 2002-04-08 130252     78 M      ICU     B_ENTRC_FCLS  NA    NA    NA    NA    #>  3 2002-06-23 798871     82 M      Clinic… B_ENTRC_FCLS  NA    NA    NA    NA    #>  4 2002-06-23 798871     82 M      Clinic… B_ENTRC_FCLS  NA    NA    NA    NA    #>  5 2003-04-20 6BC362     62 M      ICU     B_ENTRC       NA    NA    NA    NA    #>  6 2003-04-21 6BC362     62 M      ICU     B_ENTRC       NA    NA    NA    NA    #>  7 2003-08-13 F35553     52 M      ICU     B_ENTRBC_CLOC R     NA    NA    R     #>  8 2003-08-13 F35553     52 M      ICU     B_ENTRC_FCLS  NA    NA    NA    NA    #>  9 2003-09-05 F35553     52 M      ICU     B_ENTRC       NA    NA    NA    NA    #> 10 2003-09-05 F35553     52 M      ICU     B_ENTRBC_CLOC R     NA    NA    R     #> # ℹ 96 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, …  if (require(\"dplyr\")) {   example_isolates %>%     filter(mo_name() %like% \"^ent\") } #> ℹ Using column 'mo' as input for mo_name() #> # A tibble: 106 × 46 #>    date       patient   age gender ward    mo            PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>   <mo>          <sir> <sir> <sir> <sir> #>  1 2002-02-21 4FC193     69 M      Clinic… B_ENTRC_FACM  NA    NA    NA    NA    #>  2 2002-04-08 130252     78 M      ICU     B_ENTRC_FCLS  NA    NA    NA    NA    #>  3 2002-06-23 798871     82 M      Clinic… B_ENTRC_FCLS  NA    NA    NA    NA    #>  4 2002-06-23 798871     82 M      Clinic… B_ENTRC_FCLS  NA    NA    NA    NA    #>  5 2003-04-20 6BC362     62 M      ICU     B_ENTRC       NA    NA    NA    NA    #>  6 2003-04-21 6BC362     62 M      ICU     B_ENTRC       NA    NA    NA    NA    #>  7 2003-08-13 F35553     52 M      ICU     B_ENTRBC_CLOC R     NA    NA    R     #>  8 2003-08-13 F35553     52 M      ICU     B_ENTRC_FCLS  NA    NA    NA    NA    #>  9 2003-09-05 F35553     52 M      ICU     B_ENTRC       NA    NA    NA    NA    #> 10 2003-09-05 F35553     52 M      ICU     B_ENTRBC_CLOC R     NA    NA    R     #> # ℹ 96 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, … # }"},{"path":"https://msberends.github.io/AMR/reference/mdro.html","id":null,"dir":"Reference","previous_headings":"","what":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","title":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","text":"Determine isolates multidrug-resistant organisms (MDRO) according international, national custom guidelines.","code":""},{"path":"https://msberends.github.io/AMR/reference/mdro.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","text":"","code":"mdro(   x = NULL,   guideline = \"CMI2012\",   col_mo = NULL,   info = interactive(),   pct_required_classes = 0.5,   combine_SI = TRUE,   verbose = FALSE,   only_sir_columns = FALSE,   ... )  custom_mdro_guideline(..., as_factor = TRUE)  brmo(x = NULL, only_sir_columns = FALSE, ...)  mrgn(x = NULL, only_sir_columns = FALSE, ...)  mdr_tb(x = NULL, only_sir_columns = FALSE, ...)  mdr_cmi2012(x = NULL, only_sir_columns = FALSE, ...)  eucast_exceptional_phenotypes(x = NULL, only_sir_columns = FALSE, ...)"},{"path":"https://msberends.github.io/AMR/reference/mdro.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","text":"See supported guidelines list publications used function.","code":""},{"path":"https://msberends.github.io/AMR/reference/mdro.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","text":"x data.frame antibiotics columns, like AMX amox. Can left blank automatic determination. guideline specific guideline follow, see sections Supported international / national guidelines Using Custom Guidelines . left empty, publication Magiorakos et al. (see ) followed. col_mo column name names codes microorganisms (see .mo()) - default first column class mo. Values coerced using .mo(). info logical indicate whether progress printed console - default print interactive sessions pct_required_classes minimal required percentage antimicrobial classes must available per isolate, rounded . example, default guideline, 17 antimicrobial classes must available S. aureus. Setting pct_required_classes argument 0.5 (default) means every S. aureus isolate least 8 different classes must available. lower number available classes return NA isolate. combine_SI logical indicate whether values S must merged one, resistance considered isolates R, . default behaviour mdro() function, follows redefinition EUCAST interpretation (increased exposure) 2019, see section 'Interpretation S, R' . using combine_SI = FALSE, resistance considered isolates R . verbose logical turn Verbose mode (default ). Verbose mode, function return MDRO results, instead returns data set logbook form extensive info isolates MDRO-positive, . only_sir_columns logical indicate whether antibiotic columns must detected transformed class sir (see .sir()) beforehand (default FALSE) ... case custom_mdro_guideline(): set rules, see section Using Custom Guidelines . Otherwise: column name antibiotic, see section Antibiotics . as_factor logical indicate whether returned value ordered factor (TRUE, default), otherwise character vector","code":""},{"path":"https://msberends.github.io/AMR/reference/mdro.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","text":"CMI 2012 paper - function mdr_cmi2012() mdro(): Ordered factor levels Negative < Multi-drug-resistant (MDR) < Extensively drug-resistant (XDR) < Pandrug-resistant (PDR) TB guideline - function mdr_tb() mdro(..., guideline = \"TB\"): Ordered factor levels Negative < Mono-resistant < Poly-resistant < Multi-drug-resistant < Extensively drug-resistant German guideline - function mrgn() mdro(..., guideline = \"MRGN\"): Ordered factor levels Negative < 3MRGN < 4MRGN Everything else, except custom guidelines: Ordered factor levels Negative < Positive, unconfirmed < Positive. value \"Positive, unconfirmed\" means , according guideline, entirely sure isolate multi-drug resistant confirmed additional (e.g. molecular) tests","code":""},{"path":"https://msberends.github.io/AMR/reference/mdro.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","text":"functions context-aware. means x argument can left blank used inside data.frame call, see Examples. pct_required_classes argument, values 1 divided 100. support fractions (0.75 3/4) percentages (75). Note: Every test involves Enterobacteriaceae family, internally performed using newly named order Enterobacterales, since Enterobacteriaceae family taxonomically reclassified Adeolu et al. 2016. , Enterobacteriaceae family Enterobacteriales () order. species old Enterobacteriaceae family still new Enterobacterales (without ) order, divided multiple families. way tests performed now mdro() function makes sure results 2016 2016 identical.","code":""},{"path":"https://msberends.github.io/AMR/reference/mdro.html","id":"supported-international-national-guidelines","dir":"Reference","previous_headings":"","what":"Supported International / National Guidelines","title":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","text":"Currently supported guidelines (case-insensitive): guideline = \"CMI2012\" (default) Magiorakos AP, Srinivasan et al. \"Multidrug-resistant, extensively drug-resistant pandrug-resistant bacteria: international expert proposal interim standard definitions acquired resistance.\" Clinical Microbiology Infection (2012) (doi:10.1111/j.1469-0691.2011.03570.x ) guideline = \"EUCAST3.3\" (simply guideline = \"EUCAST\") European international guideline - EUCAST Expert Rules Version 3.3 \"Intrinsic Resistance Unusual Phenotypes\" (link) guideline = \"EUCAST3.2\" European international guideline - EUCAST Expert Rules Version 3.2 \"Intrinsic Resistance Unusual Phenotypes\" (link) guideline = \"EUCAST3.1\" European international guideline - EUCAST Expert Rules Version 3.1 \"Intrinsic Resistance Exceptional Phenotypes Tables\" (link) guideline = \"TB\" international guideline multi-drug resistant tuberculosis - World Health Organization \"Companion handbook guidelines programmatic management drug-resistant tuberculosis\" (link) guideline = \"MRGN\" German national guideline - Mueller et al. (2015) Antimicrobial Resistance Infection Control 4:7; doi:10.1186/s13756-015-0047-6 guideline = \"BRMO\" Dutch national guideline - Rijksinstituut voor Volksgezondheid en Milieu \"WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen) (ZKH)\" (link) Please suggest (country-specific) guidelines letting us know: https://github.com/msberends/AMR/issues/new.","code":""},{"path":"https://msberends.github.io/AMR/reference/mdro.html","id":"using-custom-guidelines","dir":"Reference","previous_headings":"","what":"Using Custom Guidelines","title":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","text":"Custom guidelines can set custom_mdro_guideline() function. great importance custom rules determine MDROs hospital, e.g., rules dependent ward, state contact isolation variables data. familiar case_when() function dplyr package, recognise input method set rules. Rules must set using R considers 'formula notation'. rule written tilde (~) consequence rule written tilde:   row/isolate matches first rule, value first ~ (case 'Elderly Type ') set MDRO value. Otherwise, second rule tried . number rules unlimited. can print rules set console overview. Colours help reading console supports colours.   outcome function can used guideline argument mdro() function:   Rules can also combined custom rules using c():   rules set (custom object case) exported shared file location using saveRDS() collaborate multiple users. custom rules set imported using readRDS().","code":"custom <- custom_mdro_guideline(CIP == \"R\" & age > 60 ~ \"Elderly Type A\",                                 ERY == \"R\" & age > 60 ~ \"Elderly Type B\") custom #> A set of custom MDRO rules: #>   1. CIP is \"R\" and age is higher than 60 -> Elderly Type A #>   2. ERY is \"R\" and age is higher than 60 -> Elderly Type B #>   3. Otherwise -> Negative #> #> Unmatched rows will return NA. x <- mdro(example_isolates,           guideline = custom) table(x) #>       Negative Elderly Type A Elderly Type B #>           1070            198            732 x <- mdro(example_isolates,           guideline = c(custom,                         custom_mdro_guideline(ERY == \"R\" & age > 50 ~ \"Elderly Type C\"))) table(x) #>       Negative Elderly Type A Elderly Type B Elderly Type C #>            961            198            732            109"},{"path":"https://msberends.github.io/AMR/reference/mdro.html","id":"antibiotics","dir":"Reference","previous_headings":"","what":"Antibiotics","title":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","text":"define antibiotics column names, leave determine automatically guess_ab_col() input text (case-insensitive), use NULL skip column (e.g. TIC = NULL skip ticarcillin). Manually defined non-existing columns skipped warning. following antibiotics eligible functions eucast_rules() mdro(). shown format 'name (antimicrobial ID, ATC code)', sorted alphabetically: Amikacin (AMK, J01GB06), amoxicillin (AMX, J01CA04), amoxicillin/clavulanic acid (AMC, J01CR02), ampicillin (AMP, J01CA01), ampicillin/sulbactam (SAM, J01CR01), apramycin (APR, QA07AA92), arbekacin (ARB, J01GB12), aspoxicillin (APX, J01CA19), azidocillin (AZD, J01CE04), azithromycin (AZM, J01FA10), azlocillin (AZL, J01CA09), aztreonam (ATM, J01DF01), bacampicillin (BAM, J01CA06), bekanamycin (BEK, J01GB13), benzathine benzylpenicillin (BNB, J01CE08), benzathine phenoxymethylpenicillin (BNP, J01CE10), benzylpenicillin (PEN, J01CE01), besifloxacin (BES, S01AE08), biapenem (BIA, J01DH05), carbenicillin (CRB, J01CA03), carindacillin (CRN, J01CA05), cefacetrile (CAC, J01DB10), cefaclor (CEC, J01DC04), cefadroxil (CFR, J01DB05), cefalexin (LEX, J01DB01), cefaloridine (RID, J01DB02), cefalotin (CEP, J01DB03), cefamandole (MAN, J01DC03), cefapirin (HAP, J01DB08), cefatrizine (CTZ, J01DB07), cefazedone (CZD, J01DB06), cefazolin (CZO, J01DB04), cefcapene (CCP, J01DD17), cefdinir (CDR, J01DD15), cefditoren (DIT, J01DD16), cefepime (FEP, J01DE01), cefetamet (CAT, J01DD10), cefixime (CFM, J01DD08), cefmenoxime (CMX, J01DD05), cefmetazole (CMZ, J01DC09), cefodizime (DIZ, J01DD09), cefonicid (CID, J01DC06), cefoperazone (CFP, J01DD12), cefoperazone/sulbactam (CSL, J01DD62), ceforanide (CND, J01DC11), cefotaxime (CTX, J01DD01), cefotaxime/clavulanic acid (CTC, J01DD51), cefotetan (CTT, J01DC05), cefotiam (CTF, J01DC07), cefovecin (FOV, QJ01DD91), cefoxitin (FOX, J01DC01), cefozopran (ZOP, J01DE03), cefpiramide (CPM, J01DD11), cefpirome (CPO, J01DE02), cefpodoxime (CPD, J01DD13), cefprozil (CPR, J01DC10), cefquinome (CEQ, QG51AA07), cefroxadine (CRD, J01DB11), cefsulodin (CFS, J01DD03), ceftaroline (CPT, J01DI02), ceftazidime (CAZ, J01DD02), ceftazidime/clavulanic acid (CCV, J01DD52), cefteram (CEM, J01DD18), ceftezole (CTL, J01DB12), ceftibuten (CTB, J01DD14), ceftiofur (TIO, QJ01DD90), ceftizoxime (CZX, J01DD07), ceftobiprole medocaril (CFM1, J01DI01), ceftolozane/tazobactam (CZT, J01DI54), ceftriaxone (CRO, J01DD04), ceftriaxone/beta-lactamase inhibitor (CEB, J01DD63), cefuroxime (CXM, J01DC02), cephradine (CED, J01DB09), chloramphenicol (CHL, J01BA01), ciprofloxacin (CIP, J01MA02), clarithromycin (CLR, J01FA09), clindamycin (CLI, J01FF01), clometocillin (CLM, J01CE07), cloxacillin (CLO, J01CF02), colistin (COL, J01XB01), cycloserine (CYC, J04AB01), dalbavancin (DAL, J01XA04), danofloxacin (DAN, QJ01MA92), daptomycin (DAP, J01XX09), delafloxacin (DFX, J01MA23), dibekacin (DKB, J01GB09), dicloxacillin (DIC, J01CF01), difloxacin (DIF, QJ01MA94), dirithromycin (DIR, J01FA13), doripenem (DOR, J01DH04), doxycycline (DOX, J01AA02), enoxacin (ENX, J01MA04), enrofloxacin (ENR, QJ01MA90), epicillin (EPC, J01CA07), ertapenem (ETP, J01DH03), erythromycin (ERY, J01FA01), fleroxacin (FLE, J01MA08), flucloxacillin (FLC, J01CF05), flurithromycin (FLR1, J01FA14), fosfomycin (FOS, J01XX01), framycetin (FRM, D09AA01), fusidic acid (FUS, J01XC01), gamithromycin (GAM, QJ01FA95), garenoxacin (GRN, J01MA19), gatifloxacin (GAT, J01MA16), gemifloxacin (GEM, J01MA15), gentamicin (GEN, J01GB03), grepafloxacin (GRX, J01MA11), hetacillin (HET, J01CA18), imipenem (IPM, J01DH51), imipenem/relebactam (IMR, J01DH56), isepamicin (ISE, J01GB11), josamycin (JOS, J01FA07), kanamycin (KAN, J01GB04), kitasamycin (KIT, QJ01FA93), lascufloxacin (LSC, J01MA25), latamoxef (LTM, J01DD06), levofloxacin (LVX, J01MA12), levonadifloxacin (LND, J01MA24), lincomycin (LIN, J01FF02), linezolid (LNZ, J01XX08), lomefloxacin (LOM, J01MA07), loracarbef (LOR, J01DC08), marbofloxacin (MAR, QJ01MA93), mecillinam (MEC, J01CA11), meropenem (MEM, J01DH02), meropenem/vaborbactam (MEV, J01DH52), metampicillin (MTM, J01CA14), meticillin (MET, J01CF03), mezlocillin (MEZ, J01CA10), micronomicin (MCR, S01AA22), midecamycin (MID, J01FA03), minocycline (MNO, J01AA08), miocamycin (MCM, J01FA11), moxifloxacin (MFX, J01MA14), nadifloxacin (NAD, D10AF05), nafcillin (NAF, J01CF06), nalidixic acid (NAL, J01MB02), neomycin (NEO, J01GB05), netilmicin (NET, J01GB07), nitrofurantoin (NIT, J01XE01), norfloxacin (, J01MA06), novobiocin (NOV, QJ01XX95), ofloxacin (OFX, J01MA01), oleandomycin (OLE, J01FA05), orbifloxacin (ORB, QJ01MA95), oritavancin (ORI, J01XA05), oxacillin (OXA, J01CF04), panipenem (PAN, J01DH55), pazufloxacin (PAZ, J01MA18), pefloxacin (PEF, J01MA03), penamecillin (PNM, J01CE06), pheneticillin (PHE, J01CE05), phenoxymethylpenicillin (PHN, J01CE02), piperacillin (PIP, J01CA12), piperacillin/tazobactam (TZP, J01CR05), pirlimycin (PRL, QJ51FF90), pivampicillin (PVM, J01CA02), pivmecillinam (PME, J01CA08), plazomicin (PLZ, J01GB14), polymyxin B (PLB, J01XB02), pradofloxacin (PRA, QJ01MA97), pristinamycin (PRI, J01FG01), procaine benzylpenicillin (PRB, J01CE09), propicillin (PRP, J01CE03), prulifloxacin (PRU, J01MA17), quinupristin/dalfopristin (QDA, QJ01FG02), ribostamycin (RST, J01GB10), rifampicin (RIF, J04AB02), rokitamycin (ROK, J01FA12), roxithromycin (RXT, J01FA06), rufloxacin (RFL, J01MA10), sarafloxacin (SAR, QJ01MA98), sisomicin (SIS, J01GB08), sitafloxacin (SIT, J01MA21), solithromycin (SOL, J01FA16), sparfloxacin (SPX, J01MA09), spiramycin (SPI, J01FA02), streptoduocin (STR, J01GA02), streptomycin (STR1, J01GA01), sulbactam (SUL, J01CG01), sulbenicillin (SBC, J01CA16), sulfadiazine (SDI, J01EC02), sulfadiazine/trimethoprim (SLT1, J01EE02), sulfadimethoxine (SUD, J01ED01), sulfadimidine (SDM, J01EB03), sulfadimidine/trimethoprim (SLT2, J01EE05), sulfafurazole (SLF, J01EB05), sulfaisodimidine (SLF1, J01EB01), sulfalene (SLF2, J01ED02), sulfamazone (SZO, J01ED09), sulfamerazine (SLF3, J01ED07), sulfamerazine/trimethoprim (SLT3, J01EE07), sulfamethizole (SLF4, J01EB02), sulfamethoxazole (SMX, J01EC01), sulfamethoxypyridazine (SLF5, J01ED05), sulfametomidine (SLF6, J01ED03), sulfametoxydiazine (SLF7, J01ED04), sulfametrole/trimethoprim (SLT4, J01EE03), sulfamoxole (SLF8, J01EC03), sulfamoxole/trimethoprim (SLT5, J01EE04), sulfanilamide (SLF9, J01EB06), sulfaperin (SLF10, J01ED06), sulfaphenazole (SLF11, J01ED08), sulfapyridine (SLF12, J01EB04), sulfathiazole (SUT, J01EB07), sulfathiourea (SLF13, J01EB08), sultamicillin (SLT6, J01CR04), talampicillin (TAL, J01CA15), tazobactam (TAZ, J01CG02), tebipenem (TBP, J01DH06), tedizolid (TZD, J01XX11), teicoplanin (TEC, J01XA02), telavancin (TLV, J01XA03), telithromycin (TLT, J01FA15), temafloxacin (TMX, J01MA05), temocillin (TEM, J01CA17), tetracycline (TCY, J01AA07), ticarcillin (TIC, J01CA13), ticarcillin/clavulanic acid (TCC, J01CR03), tigecycline (TGC, J01AA12), tilbroquinol (TBQ, P01AA05), tildipirosin (TIP, QJ01FA96), tilmicosin (TIL, QJ01FA91), tobramycin (TOB, J01GB01), tosufloxacin (TFX, J01MA22), trimethoprim (TMP, J01EA01), trimethoprim/sulfamethoxazole (SXT, J01EE01), troleandomycin (TRL, J01FA08), trovafloxacin (TVA, J01MA13), tulathromycin (TUL, QJ01FA94), tylosin (TYL, QJ01FA90), tylvalosin (TYL1, QJ01FA92), vancomycin (VAN, J01XA01)","code":""},{"path":"https://msberends.github.io/AMR/reference/mdro.html","id":"interpretation-of-sir","dir":"Reference","previous_headings":"","what":"Interpretation of SIR","title":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","text":"2019, European Committee Antimicrobial Susceptibility Testing (EUCAST) decided change definitions susceptibility testing categories S, , R shown (https://www.eucast.org/newsiandr): S - Susceptible, standard dosing regimen microorganism categorised \"Susceptible, standard dosing regimen\", high likelihood therapeutic success using standard dosing regimen agent. - Susceptible, increased exposure  microorganism categorised \"Susceptible, Increased exposure\" high likelihood therapeutic success exposure agent increased adjusting dosing regimen concentration site infection. R = Resistant microorganism categorised \"Resistant\" high likelihood therapeutic failure even increased exposure. Exposure function mode administration, dose, dosing interval, infusion time, well distribution excretion antimicrobial agent influence infecting organism site infection. AMR package honours insight. Use susceptibility() (equal proportion_SI()) determine antimicrobial susceptibility count_susceptible() (equal count_SI()) count susceptible isolates.","code":""},{"path":"https://msberends.github.io/AMR/reference/mdro.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Determine Multidrug-Resistant Organisms (MDRO) — mdro","text":"","code":"out <- mdro(example_isolates, guideline = \"EUCAST\") str(out) #>  Ord.factor w/ 3 levels \"Negative\"<\"Positive, unconfirmed\"<..: 1 1 1 1 1 1 1 1 1 1 ... table(out) #> out #>              Negative Positive, unconfirmed              Positive  #>                  1978                     0                     6   out <- mdro(example_isolates,   guideline = custom_mdro_guideline(     AMX == \"R\" ~ \"Custom MDRO 1\",     VAN == \"R\" ~ \"Custom MDRO 2\"   ) ) table(out) #> out #>      Negative Custom MDRO 1 Custom MDRO 2  #>           870           804           326   # \\donttest{ if (require(\"dplyr\")) {   example_isolates %>%     mdro() %>%     table()    # no need to define `x` when used inside dplyr verbs:   example_isolates %>%     mutate(MDRO = mdro()) %>%     pull(MDRO) %>%     table() } #> Warning: in mdro(): NA introduced for isolates where the available percentage of #> antimicrobial classes was below 50% (set with pct_required_classes) #> Warning: There was 1 warning in `mutate()`. #> ℹ In argument: `MDRO = mdro()`. #> Caused by warning: #> ! in mdro(): NA introduced for isolates where the available percentage of #> antimicrobial classes was below 50% (set with pct_required_classes) #> . #>                         Negative       Multi-drug-resistant (MDR)  #>                             1601                              128  #> Extensively drug-resistant (XDR)          Pandrug-resistant (PDR)  #>                                0                                0  # }"},{"path":"https://msberends.github.io/AMR/reference/mean_amr_distance.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the Mean AMR Distance — mean_amr_distance","title":"Calculate the Mean AMR Distance — mean_amr_distance","text":"Calculates normalised mean antimicrobial resistance multiple observations, help identify similar isolates without comparing antibiograms hand.","code":""},{"path":"https://msberends.github.io/AMR/reference/mean_amr_distance.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate the Mean AMR Distance — mean_amr_distance","text":"","code":"mean_amr_distance(x, ...)  # S3 method for class 'sir' mean_amr_distance(x, ..., combine_SI = TRUE)  # S3 method for class 'data.frame' mean_amr_distance(x, ..., combine_SI = TRUE)  amr_distance_from_row(amr_distance, row)"},{"path":"https://msberends.github.io/AMR/reference/mean_amr_distance.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate the Mean AMR Distance — mean_amr_distance","text":"x vector class sir, mic disk, data.frame containing columns classes ... variables select (supports tidyselect language column1:column4 (.mic), can thus also antibiotic selectors combine_SI logical indicate whether values S must merged one, input consists S+vs. R (susceptible vs. resistant) - default TRUE amr_distance outcome mean_amr_distance() row index, row number","code":""},{"path":"https://msberends.github.io/AMR/reference/mean_amr_distance.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate the Mean AMR Distance — mean_amr_distance","text":"mean AMR distance effectively Z-score; normalised numeric value compare AMR test results can help identify similar isolates, without comparing antibiograms hand. MIC values (see .mic()) transformed log2() first; distance thus calculated (log2(x) - mean(log2(x))) / sd(log2(x)). SIR values (see .sir()) transformed using \"S\" = 1, \"\" = 2, \"R\" = 3. combine_SI TRUE (default), \"\" considered 1. data sets, mean AMR distance calculated per column, mean per row returned, see Examples. Use amr_distance_from_row() subtract distances distance one row, see Examples.","code":""},{"path":"https://msberends.github.io/AMR/reference/mean_amr_distance.html","id":"interpretation","dir":"Reference","previous_headings":"","what":"Interpretation","title":"Calculate the Mean AMR Distance — mean_amr_distance","text":"Isolates distances less 0.01 difference considered similar. Differences lower 0.025 considered suspicious.","code":""},{"path":"https://msberends.github.io/AMR/reference/mean_amr_distance.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate the Mean AMR Distance — mean_amr_distance","text":"","code":"sir <- random_sir(10) sir #> Class 'sir' #>  [1] R R S I I S I I R I mean_amr_distance(sir) #>  [1]  1.449138  1.449138 -0.621059 -0.621059 -0.621059 -0.621059 -0.621059 #>  [8] -0.621059  1.449138 -0.621059  mic <- random_mic(10) mic #> Class 'mic' #>  [1] 0.002 0.5   0.125 128   0.25  0.5   256   0.125 0.125 64    mean_amr_distance(mic) #>  [1] -1.6429088 -0.1673475 -0.5378223  1.3145519 -0.3525849 -0.1673475 #>  [7]  1.4997893 -0.5378223 -0.5378223  1.1293145 # equal to the Z-score of their log2: (log2(mic) - mean(log2(mic))) / sd(log2(mic)) #>  [1] -1.6429088 -0.1673475 -0.5378223  1.3145519 -0.3525849 -0.1673475 #>  [7]  1.4997893 -0.5378223 -0.5378223  1.1293145  disk <- random_disk(10) disk #> Class 'disk' #>  [1] 40 45 43 14 42 40 37 15 42 11 mean_amr_distance(disk) #>  [1]  0.5182957  0.8832927  0.7372939 -1.3796886  0.6642945  0.5182957 #>  [7]  0.2992975 -1.3066892  0.6642945 -1.5986868  y <- data.frame(   id = LETTERS[1:10],   amox = random_sir(10, ab = \"amox\", mo = \"Escherichia coli\"),   cipr = random_disk(10, ab = \"cipr\", mo = \"Escherichia coli\"),   gent = random_mic(10, ab = \"gent\", mo = \"Escherichia coli\"),   tobr = random_mic(10, ab = \"tobr\", mo = \"Escherichia coli\") ) y #>    id amox cipr  gent  tobr #> 1   A    R   17 <=0.5   >=8 #> 2   B    I   26 <=0.5     4 #> 3   C    R   18     4   >=8 #> 4   D    R   22 <=0.5 <=0.5 #> 5   E    I   30 <=0.5     1 #> 6   F    S   18     4     2 #> 7   G    I   26     8     2 #> 8   H    S   29     8     1 #> 9   I    I   22    16     1 #> 10  J    S   31     1     4 mean_amr_distance(y) #> ℹ Calculating mean AMR distance based on columns \"amox\", \"cipr\", \"gent\", #>   and \"tobr\" #>  [1]  0.12957466 -0.14083442  0.55230568 -0.36152662 -0.31478853 -0.33012168 #>  [7]  0.17672648  0.13748045 -0.07163669  0.22282068 y$amr_distance <- mean_amr_distance(y, where(is.mic)) #> Error in .subset(x, j): invalid subscript type 'list' y[order(y$amr_distance), ] #> Error in order(y$amr_distance): argument 1 is not a vector  if (require(\"dplyr\")) {   y %>%     mutate(       amr_distance = mean_amr_distance(y),       check_id_C = amr_distance_from_row(amr_distance, id == \"C\")     ) %>%     arrange(check_id_C) } #> ℹ Calculating mean AMR distance based on columns \"amox\", \"cipr\", \"gent\", #>   and \"tobr\" #>    id amox cipr  gent  tobr amr_distance check_id_C #> 1   C    R   18     4   >=8   0.55230568  0.0000000 #> 2   J    S   31     1     4   0.22282068  0.3294850 #> 3   G    I   26     8     2   0.17672648  0.3755792 #> 4   H    S   29     8     1   0.13748045  0.4148252 #> 5   A    R   17 <=0.5   >=8   0.12957466  0.4227310 #> 6   I    I   22    16     1  -0.07163669  0.6239424 #> 7   B    I   26 <=0.5     4  -0.14083442  0.6931401 #> 8   E    I   30 <=0.5     1  -0.31478853  0.8670942 #> 9   F    S   18     4     2  -0.33012168  0.8824274 #> 10  D    R   22 <=0.5 <=0.5  -0.36152662  0.9138323 if (require(\"dplyr\")) {   # support for groups   example_isolates %>%     filter(mo_genus() == \"Enterococcus\" & mo_species() != \"\") %>%     select(mo, TCY, carbapenems()) %>%     group_by(mo) %>%     mutate(dist = mean_amr_distance(.)) %>%     arrange(mo, dist) } #> ℹ Using column 'mo' as input for mo_genus() #> ℹ Using column 'mo' as input for mo_species() #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> ℹ Calculating mean AMR distance based on columns \"TCY\", \"IPM\", and \"MEM\" #> # A tibble: 63 × 5 #> # Groups:   mo [4] #>    mo           TCY   IPM   MEM     dist #>    <mo>         <sir> <sir> <sir>  <dbl> #>  1 B_ENTRC_AVIM S     S     NA     0     #>  2 B_ENTRC_AVIM S     S     NA     0     #>  3 B_ENTRC_CSSL NA    S     NA    NA     #>  4 B_ENTRC_FACM S     S     NA    -2.66  #>  5 B_ENTRC_FACM S     R     R     -0.423 #>  6 B_ENTRC_FACM S     R     R     -0.423 #>  7 B_ENTRC_FACM NA    R     R      0.224 #>  8 B_ENTRC_FACM NA    R     R      0.224 #>  9 B_ENTRC_FACM NA    R     R      0.224 #> 10 B_ENTRC_FACM NA    R     R      0.224 #> # ℹ 53 more rows"},{"path":"https://msberends.github.io/AMR/reference/microorganisms.codes.html","id":null,"dir":"Reference","previous_headings":"","what":"Data Set with 4 971 Common Microorganism Codes — microorganisms.codes","title":"Data Set with 4 971 Common Microorganism Codes — microorganisms.codes","text":"data set containing commonly used codes microorganisms, laboratory systems WHONET. Define set_mo_source(). searched using .mo() consequently mo_* functions.","code":""},{"path":"https://msberends.github.io/AMR/reference/microorganisms.codes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Data Set with 4 971 Common Microorganism Codes — microorganisms.codes","text":"","code":"microorganisms.codes"},{"path":"https://msberends.github.io/AMR/reference/microorganisms.codes.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data Set with 4 971 Common Microorganism Codes — microorganisms.codes","text":"tibble 4 971 observations 2 variables: code Commonly used code microorganism. unique identifier. mo ID microorganism microorganisms data set","code":""},{"path":"https://msberends.github.io/AMR/reference/microorganisms.codes.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Data Set with 4 971 Common Microorganism Codes — microorganisms.codes","text":"Like data sets package, data set publicly available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/microorganisms.codes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Data Set with 4 971 Common Microorganism Codes — microorganisms.codes","text":"","code":"microorganisms.codes #> # A tibble: 4,971 × 2 #>    code  mo                #>    <chr> <mo>              #>  1 1011  B_GRAMP           #>  2 1012  B_GRAMP           #>  3 1013  B_GRAMN           #>  4 1014  B_GRAMN           #>  5 1015  F_YEAST           #>  6 103   B_ESCHR_COLI      #>  7 104   B_SLMNL_ENTR_ENTR #>  8 1100  B_STRPT           #>  9 1101  B_STRPT_VIRI      #> 10 1102  B_STRPT_HAEM      #> # ℹ 4,961 more rows  # 'ECO' or 'eco' is the WHONET code for E. coli: microorganisms.codes[microorganisms.codes$code == \"ECO\", ] #> # A tibble: 1 × 2 #>   code  mo           #>   <chr> <mo>         #> 1 ECO   B_ESCHR_COLI  # and therefore, 'eco' will be understood as E. coli in this package: mo_info(\"eco\") #> $mo #> [1] \"B_ESCHR_COLI\" #>  #> $kingdom #> [1] \"Bacteria\" #>  #> $phylum #> [1] \"Pseudomonadota\" #>  #> $class #> [1] \"Gammaproteobacteria\" #>  #> $order #> [1] \"Enterobacterales\" #>  #> $family #> [1] \"Enterobacteriaceae\" #>  #> $genus #> [1] \"Escherichia\" #>  #> $species #> [1] \"coli\" #>  #> $subspecies #> [1] \"\" #>  #> $status #> [1] \"accepted\" #>  #> $synonyms #> NULL #>  #> $gramstain #> [1] \"Gram-negative\" #>  #> $oxygen_tolerance #> [1] \"facultative anaerobe\" #>  #> $url #> [1] \"https://lpsn.dsmz.de/species/escherichia-coli\" #>  #> $ref #> [1] \"Castellani et al., 1919\" #>  #> $snomed #>  [1] \"1095001000112106\" \"715307006\"        \"737528008\"        \"416989002\"        #>  [5] \"116397003\"        \"414097009\"        \"414098004\"        \"414099007\"        #>  [9] \"414100004\"        \"116395006\"        \"735270003\"        \"116396007\"        #> [13] \"83285000\"         \"116394005\"        \"112283007\"        \"710886005\"        #> [17] \"710887001\"        \"710888006\"        \"710889003\"        \"414132004\"        #> [21] \"721892009\"        \"416812001\"        \"416740004\"        \"417216001\"        #> [25] \"457541006\"        \"710253004\"        \"416530004\"        \"417189006\"        #> [29] \"409800005\"        \"713925008\"        \"444771000124108\"  \"838549008\"        #>  #> $lpsn #> [1] \"776057\" #>  #> $gbif #> [1] \"11286021\" #>  #> $group_members #> character(0) #>   # works for all AMR functions: mo_is_intrinsic_resistant(\"eco\", ab = \"vancomycin\") #> [1] TRUE"},{"path":"https://msberends.github.io/AMR/reference/microorganisms.groups.html","id":null,"dir":"Reference","previous_headings":"","what":"Data Set with 521 Microorganisms In Species Groups — microorganisms.groups","title":"Data Set with 521 Microorganisms In Species Groups — microorganisms.groups","text":"data set containing species groups microbiological complexes, used clinical breakpoints table.","code":""},{"path":"https://msberends.github.io/AMR/reference/microorganisms.groups.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Data Set with 521 Microorganisms In Species Groups — microorganisms.groups","text":"","code":"microorganisms.groups"},{"path":"https://msberends.github.io/AMR/reference/microorganisms.groups.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data Set with 521 Microorganisms In Species Groups — microorganisms.groups","text":"tibble 521 observations 4 variables: mo_group ID species group / microbiological complex mo ID microorganism belonging species group / microbiological complex mo_group_name Name species group / microbiological complex, retrieved mo_name() mo_name Name microorganism belonging species group / microbiological complex, retrieved mo_name()","code":""},{"path":"https://msberends.github.io/AMR/reference/microorganisms.groups.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Data Set with 521 Microorganisms In Species Groups — microorganisms.groups","text":"Like data sets package, data set publicly available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/microorganisms.groups.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Data Set with 521 Microorganisms In Species Groups — microorganisms.groups","text":"","code":"microorganisms.groups #> # A tibble: 521 × 4 #>    mo_group       mo           mo_group_name                   mo_name           #>    <mo>           <mo>         <chr>                           <chr>             #>  1 B_ACNTB_BMNN-C B_ACNTB_BMNN Acinetobacter baumannii complex Acinetobacter ba… #>  2 B_ACNTB_BMNN-C B_ACNTB_CLCC Acinetobacter baumannii complex Acinetobacter ca… #>  3 B_ACNTB_BMNN-C B_ACNTB_DJKS Acinetobacter baumannii complex Acinetobacter di… #>  4 B_ACNTB_BMNN-C B_ACNTB_NSCM Acinetobacter baumannii complex Acinetobacter no… #>  5 B_ACNTB_BMNN-C B_ACNTB_PITT Acinetobacter baumannii complex Acinetobacter pi… #>  6 B_ACNTB_BMNN-C B_ACNTB_SFRT Acinetobacter baumannii complex Acinetobacter se… #>  7 B_BCTRD_FRGL-C B_BCTRD_FRGL Bacteroides fragilis complex    Bacteroides frag… #>  8 B_BCTRD_FRGL-C B_BCTRD_OVTS Bacteroides fragilis complex    Bacteroides ovat… #>  9 B_BCTRD_FRGL-C B_BCTRD_THTT Bacteroides fragilis complex    Bacteroides thet… #> 10 B_BCTRD_FRGL-C B_BCTRD_VLGT Bacteroides fragilis complex    Bacteroides vulg… #> # ℹ 511 more rows  # these are all species in the Bacteroides fragilis group, as per WHONET: microorganisms.groups[microorganisms.groups$mo_group == \"B_BCTRD_FRGL-C\", ] #> # A tibble: 5 × 4 #>   mo_group       mo           mo_group_name                mo_name               #>   <mo>           <mo>         <chr>                        <chr>                 #> 1 B_BCTRD_FRGL-C B_BCTRD_FRGL Bacteroides fragilis complex Bacteroides fragilis  #> 2 B_BCTRD_FRGL-C B_BCTRD_OVTS Bacteroides fragilis complex Bacteroides ovatus    #> 3 B_BCTRD_FRGL-C B_BCTRD_THTT Bacteroides fragilis complex Bacteroides thetaiot… #> 4 B_BCTRD_FRGL-C B_BCTRD_VLGT Bacteroides fragilis complex Bacteroides vulgatus  #> 5 B_BCTRD_FRGL-C B_PRBCT_DSTS Bacteroides fragilis complex Parabacteroides dist…"},{"path":"https://msberends.github.io/AMR/reference/microorganisms.html","id":null,"dir":"Reference","previous_headings":"","what":"Data Set with 70 547 Taxonomic Records of Microorganisms — microorganisms","title":"Data Set with 70 547 Taxonomic Records of Microorganisms — microorganisms","text":"data set containing full microbial taxonomy (last updated: June 24th, 2024) six kingdoms. data set backbone AMR package. MO codes can looked using .mo() microorganism properties can looked using mo_* functions. data set carefully crafted, yet made 100% reproducible public authoritative taxonomic sources (using script), namely: List Prokaryotic names Standing Nomenclature (LPSN) bacteria, MycoBank fungi, Global Biodiversity Information Facility (GBIF) others taxons.","code":""},{"path":"https://msberends.github.io/AMR/reference/microorganisms.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Data Set with 70 547 Taxonomic Records of Microorganisms — microorganisms","text":"","code":"microorganisms"},{"path":"https://msberends.github.io/AMR/reference/microorganisms.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data Set with 70 547 Taxonomic Records of Microorganisms — microorganisms","text":"tibble 70 547 observations 26 variables: mo ID microorganism used package. unique identifier. fullname Full name, like \"Escherichia coli\". taxonomic ranks genus, species subspecies, 'pasted' text genus, species, subspecies. taxonomic ranks higher genus, name taxon. unique identifier. status  Status taxon, either \"accepted\", \"validly published\", \"synonym\", \"unknown\" kingdom, phylum, class, order, family, genus, species, subspecies Taxonomic rank microorganism. Note fungi, phylum equal taxonomic division. Also, fungi, subkingdom subdivision left since occur bacterial taxonomy. rank Text taxonomic rank microorganism, \"species\" \"genus\" ref Author(s) year related scientific publication. contains first surname year latest authors, e.g. \"Wallis et al. 2006 emend. Smith Jones 2018\" becomes \"Smith et al., 2018\". field directly retrieved source specified column source. Moreover, accents removed comply CRAN allows ASCII characters. oxygen_tolerance  Oxygen tolerance, either \"aerobe\", \"anaerobe\", \"anaerobe/microaerophile\", \"facultative anaerobe\", \"likely facultative anaerobe\", \"microaerophile\". data retrieved BacDive (see Source). Items contain \"likely\" missing BacDive extrapolated species within genus guess oxygen tolerance. Currently 68.3% ~39 000 bacteria data set contain oxygen tolerance. source Either \"GBIF\", \"LPSN\", \"MycoBank\", \"manually added\" (see Source) lpsn Identifier ('Record number') List Prokaryotic names Standing Nomenclature (LPSN). first/highest LPSN identifier keep one identifier per row. example, Acetobacter ascendens LPSN Record number 7864 11011. first available microorganisms data set. unique identifier, though available ~32 000 records. lpsn_parent LPSN identifier parent taxon lpsn_renamed_to LPSN identifier currently valid taxon mycobank Identifier ('MycoBank #') MycoBank. unique identifier, though available ~15 000 records. mycobank_parent MycoBank identifier parent taxon mycobank_renamed_to MycoBank identifier currently valid taxon gbif Identifier ('taxonID') Global Biodiversity Information Facility (GBIF). unique identifier, though available ~46 000 records. gbif_parent GBIF identifier parent taxon gbif_renamed_to GBIF identifier currently valid taxon prevalence Prevalence microorganism based Bartlett et al. (2022, doi:10.1099/mic.0.001269 ), see mo_matching_score() full explanation snomed Systematized Nomenclature Medicine (SNOMED) code microorganism, version July 16th, 2024 (see Source). Use mo_snomed() retrieve quickly, see mo_property().","code":""},{"path":"https://msberends.github.io/AMR/reference/microorganisms.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data Set with 70 547 Taxonomic Records of Microorganisms — microorganisms","text":"Taxonomic entries imported order importance: List Prokaryotic names Standing Nomenclature (LPSN): Parte, AC et al. (2020). List Prokaryotic names Standing Nomenclature (LPSN) moves DSMZ. International Journal Systematic Evolutionary Microbiology, 70, 5607-5612; doi:10.1099/ijsem.0.004332 . Accessed https://lpsn.dsmz.de June 24th, 2024. MycoBank: Vincent, R et al (2013). MycoBank gearing new horizons. IMA Fungus, 4(2), 371-9; doi:10.5598/imafungus.2013.04.02.16 . Accessed https://www.mycobank.org June 24th, 2024. Global Biodiversity Information Facility (GBIF): GBIF Secretariat (2023). GBIF Backbone Taxonomy. Checklist dataset doi:10.15468/39omei . Accessed https://www.gbif.org June 24th, 2024. Furthermore, sources used additional details: BacDive: Reimer, LC et al. (2022). BacDive 2022: knowledge base standardized bacterial archaeal data. Nucleic Acids Res., 50(D1):D741-D74; doi:10.1093/nar/gkab961 . Accessed https://bacdive.dsmz.de July 16th, 2024. Systematized Nomenclature Medicine - Clinical Terms (SNOMED-CT): Public Health Information Network Vocabulary Access Distribution System (PHIN VADS). US Edition SNOMED CT 1 September 2020. Value Set Name 'Microorganism', OID 2.16.840.1.114222.4.11.1009 (v12). Accessed https://phinvads.cdc.gov July 16th, 2024. Grimont et al. (2007). Antigenic Formulae Salmonella Serovars, 9th Edition. Collaborating Centre Reference Research Salmonella (WHOCC-SALM). Bartlett et al. (2022). comprehensive list bacterial pathogens infecting humans Microbiology 168:001269; doi:10.1099/mic.0.001269","code":""},{"path":"https://msberends.github.io/AMR/reference/microorganisms.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Data Set with 70 547 Taxonomic Records of Microorganisms — microorganisms","text":"Please note entries based LPSN, MycoBank, GBIF (see ). Since sources incorporate entries based (recent) publications International Journal Systematic Evolutionary Microbiology (IJSEM), can happen year publication sometimes later one might expect. example, Staphylococcus pettenkoferi described first time Diagnostic Microbiology Infectious Disease 2002 (doi:10.1016/s0732-8893(02)00399-1 ), 2007 publication IJSEM followed (doi:10.1099/ijs.0.64381-0 ). Consequently, AMR package returns 2007 mo_year(\"S. pettenkoferi\").","code":""},{"path":"https://msberends.github.io/AMR/reference/microorganisms.html","id":"included-taxa","dir":"Reference","previous_headings":"","what":"Included Taxa","title":"Data Set with 70 547 Taxonomic Records of Microorganisms — microorganisms","text":"Included taxonomic data LPSN, MycoBank, GBIF : ~39 000 (sub)species kingdoms Archaea Bacteria ~20 000 species kingdom Fungi. kingdom Fungi large taxon almost 300,000 different (sub)species, microbial (rather macroscopic, like mushrooms). , fungi fit scope package. relevant fungi covered (species Aspergillus, Candida, Cryptococcus, Histoplasma, Pneumocystis, Saccharomyces Trichophyton). ~8 100 (sub)species kingdom Protozoa ~1 700 (sub)species 45 relevant genera kingdom Animalia (Strongyloides Taenia) ~17 000 previously accepted names included (sub)species (taxonomically renamed) complete taxonomic tree included (sub)species: kingdom subspecies identifier parent taxons year first author related scientific publication","code":""},{"path":"https://msberends.github.io/AMR/reference/microorganisms.html","id":"manual-additions","dir":"Reference","previous_headings":"","what":"Manual additions","title":"Data Set with 70 547 Taxonomic Records of Microorganisms — microorganisms","text":"convenience, entries added manually: ~1 500 entries Salmonella, city-like serovars groups H 36 species groups (beta-haemolytic Streptococcus groups K, coagulase-negative Staphylococcus (CoNS), Mycobacterium tuberculosis complex, etc.), group compositions stored microorganisms.groups data set 1 entry Blastocystis (B.  hominis), although officially exist (Noel et al. 2005, PMID 15634993) 1 entry Moraxella (M. catarrhalis), formally named Branhamella catarrhalis (Catlin, 1970) though change never accepted within field clinical microbiology 8 'undefined' entries (unknown, unknown Gram-negatives, unknown Gram-positives, unknown yeast, unknown fungus, unknown anaerobic Gram-pos/Gram-neg bacteria) syntax used transform original data cleansed R format, can found .","code":""},{"path":"https://msberends.github.io/AMR/reference/microorganisms.html","id":"direct-download","dir":"Reference","previous_headings":"","what":"Direct download","title":"Data Set with 70 547 Taxonomic Records of Microorganisms — microorganisms","text":"Like data sets package, data set publicly available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/microorganisms.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Data Set with 70 547 Taxonomic Records of Microorganisms — microorganisms","text":"","code":"microorganisms #> # A tibble: 70,547 × 26 #>    mo               fullname      status kingdom phylum class order family genus #>    <mo>             <chr>         <chr>  <chr>   <chr>  <chr> <chr> <chr>  <chr> #>  1 B_GRAMN          (unknown Gra… unkno… Bacter… (unkn… (unk… (unk… \"(unk… \"(un… #>  2 B_GRAMP          (unknown Gra… unkno… Bacter… (unkn… (unk… (unk… \"(unk… \"(un… #>  3 B_ANAER-NEG      (unknown ana… unkno… Bacter… (unkn… (unk… (unk… \"(unk… \"(un… #>  4 B_ANAER-POS      (unknown ana… unkno… Bacter… (unkn… (unk… (unk… \"(unk… \"(un… #>  5 B_ANAER          (unknown ana… unkno… Bacter… (unkn… (unk… (unk… \"(unk… \"(un… #>  6 F_FUNGUS         (unknown fun… unkno… Fungi   (unkn… (unk… (unk… \"(unk… \"(un… #>  7   UNKNOWN        (unknown nam… unkno… (unkno… (unkn… (unk… (unk… \"(unk… \"(un… #>  8 F_YEAST          (unknown yea… unkno… Fungi   (unkn… (unk… (unk… \"(unk… \"(un… #>  9 F_AABRN          Aabaarnia     unkno… Fungi   Ascom… Leca… Ostr… \"\"     \"Aab… #> 10 B_[FAM]_ABDTBCTR Abditibacter… accep… Bacter… Abdit… Abdi… Abdi… \"Abdi… \"\"    #> # ℹ 70,537 more rows #> # ℹ 17 more variables: species <chr>, subspecies <chr>, rank <chr>, ref <chr>, #> #   oxygen_tolerance <chr>, source <chr>, lpsn <chr>, lpsn_parent <chr>, #> #   lpsn_renamed_to <chr>, mycobank <chr>, mycobank_parent <chr>, #> #   mycobank_renamed_to <chr>, gbif <chr>, gbif_parent <chr>, #> #   gbif_renamed_to <chr>, prevalence <dbl>, snomed <list>"},{"path":"https://msberends.github.io/AMR/reference/mo_matching_score.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the Matching Score for Microorganisms — mo_matching_score","title":"Calculate the Matching Score for Microorganisms — mo_matching_score","text":"algorithm used .mo() mo_* functions determine probable match taxonomic records based user input.","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_matching_score.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate the Matching Score for Microorganisms — mo_matching_score","text":"","code":"mo_matching_score(x, n)"},{"path":"https://msberends.github.io/AMR/reference/mo_matching_score.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate the Matching Score for Microorganisms — mo_matching_score","text":"x user input value(s) n full taxonomic name, exists microorganisms$fullname","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_matching_score.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculate the Matching Score for Microorganisms — mo_matching_score","text":"algorithm originally described : Berends MS et al. (2022). AMR: R Package Working Antimicrobial Resistance Data. Journal Statistical Software, 104(3), 1-31; doi:10.18637/jss.v104.i03 . Later, work Bartlett et al. bacterial pathogens infecting humans (2022, doi:10.1099/mic.0.001269 ) incorporated.","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_matching_score.html","id":"matching-score-for-microorganisms","dir":"Reference","previous_headings":"","what":"Matching Score for Microorganisms","title":"Calculate the Matching Score for Microorganisms — mo_matching_score","text":"ambiguous user input .mo() mo_* functions, returned results chosen based matching score using mo_matching_score(). matching score \\(m\\), calculated :  : \\(x\\) user input; \\(n\\) taxonomic name (genus, species, subspecies); \\(l_n\\) length \\(n\\); \\(lev\\) Levenshtein distance function (counting insertion 1, deletion substitution 2) needed change \\(x\\) \\(n\\); \\(p_n\\) human pathogenic prevalence group \\(n\\), described ; \\(k_n\\) taxonomic kingdom \\(n\\), set Bacteria = 1, Fungi = 1.25, Protozoa = 1.5, Archaea = 2, others = 3. grouping human pathogenic prevalence \\(p\\) based recent work Bartlett et al. (2022, doi:10.1099/mic.0.001269 ) extensively studied medical-scientific literature categorise bacterial species groups: Established, taxonomic species infected least three persons three references. records prevalence = 1.0 microorganisms data set; Putative, taxonomic species fewer three known cases. records prevalence = 1.25 microorganisms data set. Furthermore, genus present established list also prevalence = 1.0 microorganisms data set; genus present putative list prevalence = 1.25 microorganisms data set; species subspecies genus present two aforementioned groups, prevalence = 1.5 microorganisms data set; non-bacterial genus, species subspecies genus present following list, prevalence = 1.25 microorganisms data set: Absidia, Acanthamoeba, Acremonium, Aedes, Alternaria, Amoeba, Ancylostoma, Angiostrongylus, Anisakis, Anopheles, Apophysomyces, Arthroderma, Aspergillus, Aureobasidium, Basidiobolus, Beauveria, Blastocystis, Blastomyces, Candida, Capillaria, Chaetomium, Chrysonilia, Chrysosporium, Cladophialophora, Cladosporium, Conidiobolus, Contracaecum, Cordylobia, Cryptococcus, Curvularia, Demodex, Dermatobia, Dientamoeba, Diphyllobothrium, Dirofilaria, Echinostoma, Entamoeba, Enterobius, Exophiala, Exserohilum, Fasciola, Fonsecaea, Fusarium, Geotrichum, Giardia, Haloarcula, Halobacterium, Halococcus, Hansenula, Hendersonula, Heterophyes, Histomonas, Histoplasma, Hymenolepis, Hypomyces, Hysterothylacium, Kloeckera, Kluyveromyces, Kodamaea, Leishmania, Lichtheimia, Lodderomyces, Lomentospora, Malassezia, Malbranchea, Metagonimus, Meyerozyma, Microsporidium, Microsporum, Millerozyma, Mortierella, Mucor, Mycocentrospora, Necator, Nectria, Ochroconis, Oesophagostomum, Oidiodendron, Opisthorchis, Paecilomyces, Pediculus, Penicillium, Phlebotomus, Phoma, Pichia, Piedraia, Pithomyces, Pityrosporum, Pneumocystis, Pseudallescheria, Pseudoscopulariopsis, Pseudoterranova, Pulex, Rhizomucor, Rhizopus, Rhodotorula, Saccharomyces, Saprochaete, Sarcoptes, Scedosporium, Scolecobasidium, Scopulariopsis, Scytalidium, Spirometra, Sporobolomyces, Sporotrichum, Stachybotrys, Strongyloides, Syngamus, Taenia, Talaromyces, Toxocara, Trichinella, Trichobilharzia, Trichoderma, Trichomonas, Trichophyton, Trichosporon, Trichostrongylus, Trichuris, Tritirachium, Trombicula, Trypanosoma, Tunga, Verticillium, Wuchereria; records prevalence = 2.0 microorganisms data set. calculating matching score, characters \\(x\\) \\(n\\) ignored -Z, -z, 0-9, spaces parentheses. matches sorted descending matching score user input values, top match returned. lead effect e.g., \"E. coli\" return microbial ID Escherichia coli (\\(m = 0.688\\), highly prevalent microorganism found humans) Entamoeba coli (\\(m = 0.381\\), less prevalent microorganism humans), although latter alphabetically come first.","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_matching_score.html","id":"reference-data-publicly-available","dir":"Reference","previous_headings":"","what":"Reference Data Publicly Available","title":"Calculate the Matching Score for Microorganisms — mo_matching_score","text":"data sets AMR package (microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) publicly freely available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. also provide tab-separated plain text files machine-readable suitable input software program, laboratory information systems. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_matching_score.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate the Matching Score for Microorganisms — mo_matching_score","text":"Dr. Matthijs Berends, 2018","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_matching_score.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate the Matching Score for Microorganisms — mo_matching_score","text":"","code":"mo_reset_session() #> ℹ Reset 17 previously matched input values.  as.mo(\"E. coli\") #> Class 'mo' #> [1] B_ESCHR_COLI mo_uncertainties() #> Matching scores are based on the resemblance between the input and the full #> taxonomic name, and the pathogenicity in humans. See ?mo_matching_score. #>  #> -------------------------------------------------------------------------------- #> \"E. coli\" -> Escherichia coli (B_ESCHR_COLI, 0.688) #> Also matched: Escherichia coli coli (0.643), Escherichia coli #>               expressing (0.611), Enterobacter cowanii (0.600), Eubacterium combesii #>               (0.600), Eggerthia catenaformis (0.591), Eubacterium callanderi #>               (0.591), Enterocloster citroniae (0.587), Eubacterium cylindroides #>               (0.583), Enterococcus casseliflavus (0.577), and Enterobacter cloacae #>               cloacae (0.571) #>  #> Only the first 10 other matches of each record are shown. Run #> print(mo_uncertainties(), n = ...) to view more entries, or save #> mo_uncertainties() to an object.  mo_matching_score(   x = \"E. coli\",   n = c(\"Escherichia coli\", \"Entamoeba coli\") ) #> [1] 0.6875000 0.3809524"},{"path":"https://msberends.github.io/AMR/reference/mo_property.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Properties of a Microorganism — mo_property","title":"Get Properties of a Microorganism — mo_property","text":"Use functions return specific property microorganism based latest accepted taxonomy. input values evaluated internally .mo(), makes possible use microbial abbreviations, codes names input. See Examples.","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_property.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Properties of a Microorganism — mo_property","text":"","code":"mo_name(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_fullname(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_shortname(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_subspecies(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_species(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_genus(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_family(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_order(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_class(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_phylum(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_kingdom(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_domain(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_type(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_status(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_pathogenicity(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_gramstain(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_is_gram_negative(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_is_gram_positive(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_is_yeast(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_is_intrinsic_resistant(   x,   ab,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_oxygen_tolerance(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_is_anaerobic(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_snomed(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_ref(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_authors(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_year(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_lpsn(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_mycobank(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_gbif(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_rank(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_taxonomy(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_synonyms(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_current(x, language = get_AMR_locale(), ...)  mo_group_members(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_info(   x,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_url(   x,   open = FALSE,   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )  mo_property(   x,   property = \"fullname\",   language = get_AMR_locale(),   keep_synonyms = getOption(\"AMR_keep_synonyms\", FALSE),   ... )"},{"path":"https://msberends.github.io/AMR/reference/mo_property.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Properties of a Microorganism — mo_property","text":"x character (vector) can coerced valid microorganism code .mo(). Can left blank auto-guessing column containing microorganism codes used data set, see Examples. language language translate text like \"growth\", defaults system language (see get_AMR_locale()) keep_synonyms logical indicate old, previously valid taxonomic names must preserved corrected currently accepted names. default FALSE, return note old taxonomic names processed. default can set package option AMR_keep_synonyms, .e. options(AMR_keep_synonyms = TRUE) options(AMR_keep_synonyms = FALSE). ... arguments passed .mo(), 'minimum_matching_score', 'ignore_pattern', 'remove_from_input' ab (vector ) text can coerced valid antibiotic drug code .ab() open browse URL using browseURL() property one column names microorganisms data set: \"mo\", \"fullname\", \"status\", \"kingdom\", \"phylum\", \"class\", \"order\", \"family\", \"genus\", \"species\", \"subspecies\", \"rank\", \"ref\", \"oxygen_tolerance\", \"source\", \"lpsn\", \"lpsn_parent\", \"lpsn_renamed_to\", \"mycobank\", \"mycobank_parent\", \"mycobank_renamed_to\", \"gbif\", \"gbif_parent\", \"gbif_renamed_to\", \"prevalence\", \"snomed\", must \"shortname\"","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_property.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Properties of a Microorganism — mo_property","text":"integer case mo_year() ordered factor case mo_pathogenicity() list case mo_taxonomy(), mo_synonyms(), mo_snomed() mo_info() named character case mo_url() character cases","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_property.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get Properties of a Microorganism — mo_property","text":"functions , default, keep old taxonomic properties, synonyms automatically replaced current taxonomy. Take example Enterobacter aerogenes, initially named 1960 renamed Klebsiella aerogenes 2017: mo_genus(\"Enterobacter aerogenes\") return \"Klebsiella\" (note renaming) mo_genus(\"Enterobacter aerogenes\", keep_synonyms = TRUE) return \"Enterobacter\" (-per-session warning name outdated) mo_ref(\"Enterobacter aerogenes\") return \"Tindall et al., 2017\" (note) mo_ref(\"Enterobacter aerogenes\", keep_synonyms = TRUE) return \"Hormaeche et al., 1960\" (warning) short name (mo_shortname()) returns first character genus full species, \"E. coli\", species subspecies. Exceptions abbreviations staphylococci (\"CoNS\", Coagulase-Negative Staphylococci) beta-haemolytic streptococci (\"GBS\", Group B Streptococci). Please bear mind e.g. E. coli mean Escherichia coli (kingdom Bacteria) well Entamoeba coli (kingdom Protozoa). Returning full name done using .mo() internally, giving priority bacteria human pathogens, .e. \"E. coli\" considered Escherichia coli. result, mo_fullname(mo_shortname(\"Entamoeba coli\")) returns \"Escherichia coli\". Since top-level taxonomy sometimes referred 'kingdom' sometimes 'domain', functions mo_kingdom() mo_domain() return exact results. Determination human pathogenicity (mo_pathogenicity()) strongly based Bartlett et al. (2022, doi:10.1099/mic.0.001269 ). function returns factor levels Pathogenic, Potentially pathogenic, Non-pathogenic, Unknown. Determination Gram stain (mo_gramstain()) based taxonomic kingdom phylum. Originally, Cavalier-Smith defined -called subkingdoms Negibacteria Posibacteria (2002, PMID 11837318), considered phyla Posibacteria: Actinobacteria, Chloroflexi, Firmicutes, Tenericutes. phyla later renamed Actinomycetota, Chloroflexota, Bacillota, Mycoplasmatota (2021, PMID 34694987). Bacteria phyla considered Gram-positive AMR package, except members class Negativicutes (within phylum Bacillota) Gram-negative. bacteria considered Gram-negative. Species outside kingdom Bacteria return value NA. Functions mo_is_gram_negative() mo_is_gram_positive() always return TRUE FALSE (NA input NA MO code UNKNOWN), thus always return FALSE species outside taxonomic kingdom Bacteria. Determination yeasts (mo_is_yeast()) based taxonomic kingdom class. Budding yeasts fungi phylum Ascomycota, class Saccharomycetes (also called Hemiascomycetes). True yeasts aggregated underlying order Saccharomycetales. Thus, microorganisms member taxonomic class Saccharomycetes, function return TRUE. returns FALSE otherwise (NA input NA MO code UNKNOWN). Determination intrinsic resistance (mo_is_intrinsic_resistant()) based intrinsic_resistant data set, based 'EUCAST Expert Rules' 'EUCAST Intrinsic Resistance Unusual Phenotypes' v3.3 (2021). mo_is_intrinsic_resistant() function can vectorised argument x (input microorganisms) ab (input antibiotics). Determination bacterial oxygen tolerance (mo_oxygen_tolerance()) based BacDive, see Source. function mo_is_anaerobic() returns TRUE oxygen tolerance \"anaerobe\", indicting obligate anaerobic species genus. always returns FALSE species outside taxonomic kingdom Bacteria. function mo_url() return direct URL online database entry, also shows scientific reference concerned species. SNOMED codes (mo_snomed()) version July 16th, 2024. See Source microorganisms data set info. Old taxonomic names (-called 'synonyms') can retrieved mo_synonyms() (scientific reference name), current taxonomic name can retrieved mo_current(). functions return full names. output translated possible.","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_property.html","id":"matching-score-for-microorganisms","dir":"Reference","previous_headings":"","what":"Matching Score for Microorganisms","title":"Get Properties of a Microorganism — mo_property","text":"function uses .mo() internally, uses advanced algorithm translate arbitrary user input valid taxonomy using -called matching score. can read public algorithm MO matching score page.","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_property.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get Properties of a Microorganism — mo_property","text":"Berends MS et al. (2022). AMR: R Package Working Antimicrobial Resistance Data. Journal Statistical Software, 104(3), 1-31; doi:10.18637/jss.v104.i03 Becker K et al. (2014). Coagulase-Negative Staphylococci. Clin Microbiol Rev. 27(4): 870-926; doi:10.1128/CMR.00109-13 Becker K et al. (2019). Implications identifying recently defined members S. aureus complex, S. argenteus S. schweitzeri: position paper members ESCMID Study Group staphylococci Staphylococcal Diseases (ESGS). Clin Microbiol Infect; doi:10.1016/j.cmi.2019.02.028 Becker K et al. (2020). Emergence coagulase-negative staphylococci. Expert Rev Anti Infect Ther. 18(4):349-366; doi:10.1080/14787210.2020.1730813 Lancefield RC (1933). serological differentiation human groups hemolytic streptococci. J Exp Med. 57(4): 571-95; doi:10.1084/jem.57.4.571 Berends MS et al. (2022). Trends Occurrence Phenotypic Resistance Coagulase-Negative Staphylococci (CoNS) Found Human Blood Northern Netherlands 2013 2019/ Micro.rganisms 10(9), 1801; doi:10.3390/microorganisms10091801 Parte, AC et al. (2020). List Prokaryotic names Standing Nomenclature (LPSN) moves DSMZ. International Journal Systematic Evolutionary Microbiology, 70, 5607-5612; doi:10.1099/ijsem.0.004332 . Accessed https://lpsn.dsmz.de June 24th, 2024. GBIF Secretariat (2023). GBIF Backbone Taxonomy. Checklist dataset doi:10.15468/39omei . Accessed https://www.gbif.org June 24th, 2024. Reimer, LC et al. (2022). BacDive 2022: knowledge base standardized bacterial archaeal data. Nucleic Acids Res., 50(D1):D741-D74; doi:10.1093/nar/gkab961 . Accessed https://bacdive.dsmz.de July 16th, 2024. Public Health Information Network Vocabulary Access Distribution System (PHIN VADS). US Edition SNOMED CT 1 September 2020. Value Set Name 'Microorganism', OID 2.16.840.1.114222.4.11.1009 (v12). URL: https://phinvads.cdc.gov Bartlett et al. (2022). comprehensive list bacterial pathogens infecting humans Microbiology 168:001269; doi:10.1099/mic.0.001269","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_property.html","id":"reference-data-publicly-available","dir":"Reference","previous_headings":"","what":"Reference Data Publicly Available","title":"Get Properties of a Microorganism — mo_property","text":"data sets AMR package (microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) publicly freely available download following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, Stata. also provide tab-separated plain text files machine-readable suitable input software program, laboratory information systems. Please visit website download links. actual files course available GitHub repository.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/mo_property.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Properties of a Microorganism — mo_property","text":"","code":"# taxonomic tree -----------------------------------------------------------  mo_kingdom(\"Klebsiella pneumoniae\") #> [1] \"Bacteria\" mo_phylum(\"Klebsiella pneumoniae\") #> [1] \"Pseudomonadota\" mo_class(\"Klebsiella pneumoniae\") #> [1] \"Gammaproteobacteria\" mo_order(\"Klebsiella pneumoniae\") #> [1] \"Enterobacterales\" mo_family(\"Klebsiella pneumoniae\") #> [1] \"Enterobacteriaceae\" mo_genus(\"Klebsiella pneumoniae\") #> [1] \"Klebsiella\" mo_species(\"Klebsiella pneumoniae\") #> [1] \"pneumoniae\" mo_subspecies(\"Klebsiella pneumoniae\") #> [1] \"\"   # full names and short names -----------------------------------------------  mo_name(\"Klebsiella pneumoniae\") #> [1] \"Klebsiella pneumoniae\" mo_fullname(\"Klebsiella pneumoniae\") #> [1] \"Klebsiella pneumoniae\" mo_shortname(\"Klebsiella pneumoniae\") #> [1] \"K. pneumoniae\"   # other properties ---------------------------------------------------------  mo_pathogenicity(\"Klebsiella pneumoniae\") #> [1] Pathogenic #> Levels: Pathogenic < Potentially pathogenic < Non-pathogenic < Unknown mo_gramstain(\"Klebsiella pneumoniae\") #> [1] \"Gram-negative\" mo_snomed(\"Klebsiella pneumoniae\") #> [[1]] #> [1] \"1098101000112102\" \"446870005\"        \"1098201000112108\" \"409801009\"        #> [5] \"56415008\"         \"714315002\"        \"713926009\"        #>  mo_type(\"Klebsiella pneumoniae\") #> [1] \"Bacteria\" mo_rank(\"Klebsiella pneumoniae\") #> [1] \"species\" mo_url(\"Klebsiella pneumoniae\") #>                                Klebsiella pneumoniae  #> \"https://lpsn.dsmz.de/species/klebsiella-pneumoniae\"  mo_is_yeast(c(\"Candida\", \"Trichophyton\", \"Klebsiella\")) #> [1] FALSE FALSE FALSE  mo_group_members(\"Streptococcus group A\") #> [1] \"Streptococcus pyogenes\" mo_group_members(c(\"Streptococcus group C\",                    \"Streptococcus group G\",                    \"Streptococcus group L\")) #> $`Streptococcus Group C` #> [1] \"Streptococcus dysgalactiae\"              #> [2] \"Streptococcus dysgalactiae dysgalactiae\" #> [3] \"Streptococcus dysgalactiae equisimilis\"  #> [4] \"Streptococcus equi\"                      #> [5] \"Streptococcus equi equi\"                 #> [6] \"Streptococcus equi ruminatorum\"          #> [7] \"Streptococcus equi zooepidemicus\"        #>  #> $`Streptococcus Group G` #> [1] \"Streptococcus canis\"                     #> [2] \"Streptococcus dysgalactiae\"              #> [3] \"Streptococcus dysgalactiae dysgalactiae\" #> [4] \"Streptococcus dysgalactiae equisimilis\"  #>  #> $`Streptococcus Group L` #> [1] \"Streptococcus dysgalactiae\"              #> [2] \"Streptococcus dysgalactiae dysgalactiae\" #> [3] \"Streptococcus dysgalactiae equisimilis\"  #>    # scientific reference -----------------------------------------------------  mo_ref(\"Klebsiella aerogenes\") #> [1] \"Tindall et al., 2017\" mo_authors(\"Klebsiella aerogenes\") #> [1] \"Tindall et al.\" mo_year(\"Klebsiella aerogenes\") #> [1] 2017 mo_lpsn(\"Klebsiella aerogenes\") #> [1] \"777146\" mo_gbif(\"Klebsiella aerogenes\") #> [1] \"9281703\" mo_mycobank(\"Candida albicans\") #> [1] \"256187\" mo_synonyms(\"Klebsiella aerogenes\") #>   Hormaeche et al., 1960     Bascomb et al., 1971  #> \"Enterobacter aerogenes\"     \"Klebsiella mobilis\"    # abbreviations known in the field -----------------------------------------  mo_genus(\"MRSA\") #> [1] \"Staphylococcus\" mo_species(\"MRSA\") #> [1] \"aureus\" mo_shortname(\"VISA\") #> [1] \"S. aureus\" mo_gramstain(\"VISA\") #> [1] \"Gram-positive\"  mo_genus(\"EHEC\") #> [1] \"Escherichia\" mo_species(\"EIEC\") #> [1] \"coli\" mo_name(\"UPEC\") #> [1] \"Escherichia coli\"   # known subspecies ---------------------------------------------------------  mo_fullname(\"K. pneu rh\") #> [1] \"Klebsiella pneumoniae rhinoscleromatis\" mo_shortname(\"K. pneu rh\") #> [1] \"K. pneumoniae\"  # \\donttest{ # Becker classification, see ?as.mo ----------------------------------------  mo_fullname(\"Staph epidermidis\") #> [1] \"Staphylococcus epidermidis\" mo_fullname(\"Staph epidermidis\", Becker = TRUE) #> [1] \"Coagulase-negative Staphylococcus (CoNS)\" mo_shortname(\"Staph epidermidis\") #> [1] \"S. epidermidis\" mo_shortname(\"Staph epidermidis\", Becker = TRUE) #> [1] \"CoNS\"   # Lancefield classification, see ?as.mo ------------------------------------  mo_fullname(\"Strep agalactiae\") #> [1] \"Streptococcus agalactiae\" mo_fullname(\"Strep agalactiae\", Lancefield = TRUE) #> [1] \"Streptococcus Group B\" mo_shortname(\"Strep agalactiae\") #> [1] \"S. agalactiae\" mo_shortname(\"Strep agalactiae\", Lancefield = TRUE) #> [1] \"GBS\"   # language support  --------------------------------------------------------  mo_gramstain(\"Klebsiella pneumoniae\", language = \"de\") # German #> [1] \"Gramnegativ\" mo_gramstain(\"Klebsiella pneumoniae\", language = \"nl\") # Dutch #> [1] \"Gram-negatief\" mo_gramstain(\"Klebsiella pneumoniae\", language = \"es\") # Spanish #> [1] \"Gram negativo\" mo_gramstain(\"Klebsiella pneumoniae\", language = \"el\") # Greek #> [1] \"Αρνητικό κατά Gram\" mo_gramstain(\"Klebsiella pneumoniae\", language = \"uk\") # Ukrainian #> [1] \"Грамнегативні\"  # mo_type is equal to mo_kingdom, but mo_kingdom will remain untranslated mo_kingdom(\"Klebsiella pneumoniae\") #> [1] \"Bacteria\" mo_type(\"Klebsiella pneumoniae\") #> [1] \"Bacteria\" mo_kingdom(\"Klebsiella pneumoniae\", language = \"zh\") # Chinese, no effect #> [1] \"Bacteria\" mo_type(\"Klebsiella pneumoniae\", language = \"zh\") # Chinese, translated #> [1] \"细菌\"  mo_fullname(\"S. pyogenes\", Lancefield = TRUE, language = \"de\") #> [1] \"Streptococcus Gruppe A\" mo_fullname(\"S. pyogenes\", Lancefield = TRUE, language = \"uk\") #> [1] \"Streptococcus Група A\"   # other --------------------------------------------------------------------  # gram stains and intrinsic resistance can be used as a filter in dplyr verbs if (require(\"dplyr\")) {   example_isolates %>%     filter(mo_is_gram_positive()) %>%     count(mo_genus(), sort = TRUE) } #> ℹ Using column 'mo' as input for mo_is_gram_positive() #> ℹ Using column 'mo' as input for mo_genus() #> # A tibble: 18 × 2 #>    `mo_genus()`        n #>    <chr>           <int> #>  1 Staphylococcus    840 #>  2 Streptococcus     275 #>  3 Enterococcus       83 #>  4 Corynebacterium    17 #>  5 Micrococcus         6 #>  6 Gemella             3 #>  7 Aerococcus          2 #>  8 Cutibacterium       1 #>  9 Dermabacter         1 #> 10 Fusibacter          1 #> 11 Globicatella        1 #> 12 Granulicatella      1 #> 13 Lactobacillus       1 #> 14 Leuconostoc         1 #> 15 Listeria            1 #> 16 Paenibacillus       1 #> 17 Rothia              1 #> 18 Schaalia            1 if (require(\"dplyr\")) {   example_isolates %>%     filter(mo_is_intrinsic_resistant(ab = \"vanco\")) %>%     count(mo_genus(), sort = TRUE) } #> ℹ Using column 'mo' as input for mo_is_intrinsic_resistant() #> ℹ Using column 'mo' as input for mo_genus() #> # A tibble: 20 × 2 #>    `mo_genus()`         n #>    <chr>            <int> #>  1 Escherichia        467 #>  2 Klebsiella          77 #>  3 Proteus             39 #>  4 Pseudomonas         30 #>  5 Serratia            25 #>  6 Enterobacter        23 #>  7 Citrobacter         11 #>  8 Haemophilus          8 #>  9 Acinetobacter        6 #> 10 Morganella           6 #> 11 Pantoea              4 #> 12 Salmonella           3 #> 13 Neisseria            2 #> 14 Stenotrophomonas     2 #> 15 Campylobacter        1 #> 16 Enterococcus         1 #> 17 Hafnia               1 #> 18 Lactobacillus        1 #> 19 Leuconostoc          1 #> 20 Pseudescherichia     1  # get a list with the complete taxonomy (from kingdom to subspecies) mo_taxonomy(\"Klebsiella pneumoniae\") #> $kingdom #> [1] \"Bacteria\" #>  #> $phylum #> [1] \"Pseudomonadota\" #>  #> $class #> [1] \"Gammaproteobacteria\" #>  #> $order #> [1] \"Enterobacterales\" #>  #> $family #> [1] \"Enterobacteriaceae\" #>  #> $genus #> [1] \"Klebsiella\" #>  #> $species #> [1] \"pneumoniae\" #>  #> $subspecies #> [1] \"\" #>   # get a list with the taxonomy, the authors, Gram-stain, # SNOMED codes, and URL to the online database mo_info(\"Klebsiella pneumoniae\") #> $mo #> [1] \"B_KLBSL_PNMN\" #>  #> $kingdom #> [1] \"Bacteria\" #>  #> $phylum #> [1] \"Pseudomonadota\" #>  #> $class #> [1] \"Gammaproteobacteria\" #>  #> $order #> [1] \"Enterobacterales\" #>  #> $family #> [1] \"Enterobacteriaceae\" #>  #> $genus #> [1] \"Klebsiella\" #>  #> $species #> [1] \"pneumoniae\" #>  #> $subspecies #> [1] \"\" #>  #> $status #> [1] \"accepted\" #>  #> $synonyms #> NULL #>  #> $gramstain #> [1] \"Gram-negative\" #>  #> $oxygen_tolerance #> [1] \"facultative anaerobe\" #>  #> $url #> [1] \"https://lpsn.dsmz.de/species/klebsiella-pneumoniae\" #>  #> $ref #> [1] \"Trevisan, 1887\" #>  #> $snomed #> [1] \"1098101000112102\" \"446870005\"        \"1098201000112108\" \"409801009\"        #> [5] \"56415008\"         \"714315002\"        \"713926009\"        #>  #> $lpsn #> [1] \"777151\" #>  #> $gbif #> [1] \"3221874\" #>  #> $group_members #> character(0) #>  # }"},{"path":"https://msberends.github.io/AMR/reference/mo_source.html","id":null,"dir":"Reference","previous_headings":"","what":"User-Defined Reference Data Set for Microorganisms — mo_source","title":"User-Defined Reference Data Set for Microorganisms — mo_source","text":"functions can used predefine reference used .mo() consequently mo_* functions (mo_genus() mo_gramstain()). fastest way organisation (analysis) specific codes picked translated package, since bother setting .","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_source.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"User-Defined Reference Data Set for Microorganisms — mo_source","text":"","code":"set_mo_source(   path,   destination = getOption(\"AMR_mo_source\", \"~/mo_source.rds\") )  get_mo_source(destination = getOption(\"AMR_mo_source\", \"~/mo_source.rds\"))"},{"path":"https://msberends.github.io/AMR/reference/mo_source.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"User-Defined Reference Data Set for Microorganisms — mo_source","text":"path location reference file, can text file (comma-, tab- pipe-separated) Excel file (see Details). Can also \"\", NULL FALSE delete reference file. destination destination compressed data file - default user's home directory.","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_source.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"User-Defined Reference Data Set for Microorganisms — mo_source","text":"reference file can text file separated commas (CSV) tabs pipes, Excel file (either 'xls' 'xlsx' format) R object file (extension '.rds'). use Excel file, need readxl package installed. set_mo_source() check file validity: must data.frame, must column named \"mo\" contains values microorganisms$mo microorganisms$fullname must reference column defined values. tests pass, set_mo_source() read file R ask export \"~/mo_source.rds\". CRAN policy disallows packages write file system, although 'exceptions may allowed interactive sessions package obtains confirmation user'. reason, function works interactive sessions user can specifically confirm allow file created. destination file can set destination argument defaults user's home directory. can also set package option AMR_mo_source, e.g. options(AMR_mo_source = \"/location/file.rds\"). created compressed data file \"mo_source.rds\" used default MO determination (function .mo() consequently mo_* functions like mo_genus() mo_gramstain()). location timestamp original file saved attribute compressed data file. function get_mo_source() return data set reading \"mo_source.rds\" readRDS(). original file changed (checking location timestamp original file), call set_mo_source() update data file automatically used interactive session. Reading Excel file (.xlsx) one row size 8-9 kB. compressed file created set_mo_source() size 0.1 kB can read get_mo_source() couple microseconds (millionths second).","code":""},{"path":"https://msberends.github.io/AMR/reference/mo_source.html","id":"how-to-setup","dir":"Reference","previous_headings":"","what":"How to Setup","title":"User-Defined Reference Data Set for Microorganisms — mo_source","text":"Imagine data sheet Excel file. first column contains organisation specific codes, second column contains valid taxonomic names:   save \"home//ourcodes.xlsx\". Now set source:   now created file \"~/mo_source.rds\" contents Excel file. first column foreign values 'mo' column kept creating RDS file. now can use functions:   edit Excel file , say, adding row 4 like :   ...new usage MO function package update data file:   delete reference data file, just use \"\", NULL FALSE input set_mo_source():   original file (previous case Excel file) moved deleted, mo_source.rds file removed upon next use .mo() mo_* function.","code":"|         A          |            B          | --|--------------------|-----------------------| 1 | Organisation XYZ   | mo                    | 2 | lab_mo_ecoli       | Escherichia coli      | 3 | lab_mo_kpneumoniae | Klebsiella pneumoniae | 4 |                    |                       | set_mo_source(\"home/me/ourcodes.xlsx\") #> NOTE: Created mo_source file '/Users/me/mo_source.rds' (0.3 kB) from #>       '/Users/me/Documents/ourcodes.xlsx' (9 kB), columns #>       \"Organisation XYZ\" and \"mo\" as.mo(\"lab_mo_ecoli\") #> Class 'mo' #> [1] B_ESCHR_COLI  mo_genus(\"lab_mo_kpneumoniae\") #> [1] \"Klebsiella\"  # other input values still work too as.mo(c(\"Escherichia coli\", \"E. coli\", \"lab_mo_ecoli\")) #> NOTE: Translation to one microorganism was guessed with uncertainty. #>       Use mo_uncertainties() to review it. #> Class 'mo' #> [1] B_ESCHR_COLI B_ESCHR_COLI B_ESCHR_COLI |         A          |            B          | --|--------------------|-----------------------| 1 | Organisation XYZ   | mo                    | 2 | lab_mo_ecoli       | Escherichia coli      | 3 | lab_mo_kpneumoniae | Klebsiella pneumoniae | 4 | lab_Staph_aureus   | Staphylococcus aureus | 5 |                    |                       | as.mo(\"lab_mo_ecoli\") #> NOTE: Updated mo_source file '/Users/me/mo_source.rds' (0.3 kB) from #>       '/Users/me/Documents/ourcodes.xlsx' (9 kB), columns #>        \"Organisation XYZ\" and \"mo\" #> Class 'mo' #> [1] B_ESCHR_COLI  mo_genus(\"lab_Staph_aureus\") #> [1] \"Staphylococcus\" set_mo_source(NULL) #> Removed mo_source file '/Users/me/mo_source.rds'"},{"path":"https://msberends.github.io/AMR/reference/pca.html","id":null,"dir":"Reference","previous_headings":"","what":"Principal Component Analysis (for AMR) — pca","title":"Principal Component Analysis (for AMR) — pca","text":"Performs principal component analysis (PCA) based data set automatic determination afterwards plotting groups labels, automatic filtering suitable (.e. non-empty numeric) variables.","code":""},{"path":"https://msberends.github.io/AMR/reference/pca.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Principal Component Analysis (for AMR) — pca","text":"","code":"pca(   x,   ...,   retx = TRUE,   center = TRUE,   scale. = TRUE,   tol = NULL,   rank. = NULL )"},{"path":"https://msberends.github.io/AMR/reference/pca.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Principal Component Analysis (for AMR) — pca","text":"x data.frame containing numeric columns ... columns x selected PCA, can unquoted since supports quasiquotation. retx logical value indicating whether rotated variables     returned. center logical value indicating whether variables     shifted zero centered. Alternately, vector     length equal number columns x can supplied.     value passed scale. scale. logical value indicating whether variables     scaled unit variance analysis takes     place.  default FALSE consistency S,     general scaling advisable.  Alternatively, vector length     equal number columns x can supplied.      value passed scale. tol value indicating magnitude components     omitted. (Components omitted     standard deviations less equal tol times     standard deviation first component.)  default null     setting, components omitted (unless rank. specified     less min(dim(x)).).  settings tol     tol = 0 tol = sqrt(.Machine$double.eps),     omit essentially constant components. rank. optionally, number specifying maximal rank, .e.,     maximal number principal components used.  Can set     alternative addition tol, useful notably     desired rank considerably smaller dimensions matrix.","code":""},{"path":"https://msberends.github.io/AMR/reference/pca.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Principal Component Analysis (for AMR) — pca","text":"object classes pca prcomp","code":""},{"path":"https://msberends.github.io/AMR/reference/pca.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Principal Component Analysis (for AMR) — pca","text":"pca() function takes data.frame input performs actual PCA R function prcomp(). result pca() function prcomp object, additional attribute non_numeric_cols vector column names columns contain numeric values. probably groups labels, used ggplot_pca().","code":""},{"path":"https://msberends.github.io/AMR/reference/pca.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Principal Component Analysis (for AMR) — pca","text":"","code":"# `example_isolates` is a data set available in the AMR package. # See ?example_isolates.  # \\donttest{ if (require(\"dplyr\")) {   # calculate the resistance per group first   resistance_data <- example_isolates %>%     group_by(       order = mo_order(mo), # group on anything, like order       genus = mo_genus(mo)     ) %>% #   and genus as we do here;     filter(n() >= 30) %>% # filter on only 30 results per group     summarise_if(is.sir, resistance) # then get resistance of all drugs    # now conduct PCA for certain antimicrobial drugs   pca_result <- resistance_data %>%     pca(AMC, CXM, CTX, CAZ, GEN, TOB, TMP, SXT)    pca_result   summary(pca_result)    # old base R plotting method:   biplot(pca_result)   # new ggplot2 plotting method using this package:   if (require(\"ggplot2\")) {     ggplot_pca(pca_result)      ggplot_pca(pca_result) +       scale_colour_viridis_d() +       labs(title = \"Title here\")   } } #> Warning: There were 73 warnings in `summarise()`. #> The first warning was: #> ℹ In argument: `PEN = (function (..., minimum = 30, as_percent = FALSE, #>   only_all_tested = FALSE) ...`. #> ℹ In group 5: `order = \"Lactobacillales\"` and `genus = \"Enterococcus\"`. #> Caused by warning: #> ! Introducing NA: only 14 results available for PEN in group: order = #> \"Lactobacillales\", genus = \"Enterococcus\" (minimum = 30). #> ℹ Run `dplyr::last_dplyr_warnings()` to see the 72 remaining warnings. #> ℹ Columns selected for PCA: \"AMC\", \"CAZ\", \"CTX\", \"CXM\", \"GEN\", \"SXT\", #>   \"TMP\", and \"TOB\". Total observations available: 7. #> Groups (n=4, named as 'order'): #> [1] \"Caryophanales\"    \"Enterobacterales\" \"Lactobacillales\"  \"Pseudomonadales\"  #>    # }"},{"path":"https://msberends.github.io/AMR/reference/plot.html","id":null,"dir":"Reference","previous_headings":"","what":"Plotting for Classes sir, mic and disk — plot","title":"Plotting for Classes sir, mic and disk — plot","text":"Functions plot classes sir, mic disk, support base R ggplot2. Especially scale_*_mic() functions relevant wrappers plot MIC values ggplot2. allows custom MIC ranges plot intermediate log2 levels missing MIC values.","code":""},{"path":"https://msberends.github.io/AMR/reference/plot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plotting for Classes sir, mic and disk — plot","text":"","code":"scale_x_mic(keep_operators = \"edges\", mic_range = NULL, drop = FALSE, ...)  scale_y_mic(keep_operators = \"edges\", mic_range = NULL, drop = FALSE, ...)  scale_colour_mic(keep_operators = \"edges\", mic_range = NULL, drop = FALSE, ...)  scale_fill_mic(keep_operators = \"edges\", mic_range = NULL, drop = FALSE, ...)  # S3 method for class 'mic' plot(   x,   mo = NULL,   ab = NULL,   guideline = \"EUCAST\",   main = deparse(substitute(x)),   ylab = translate_AMR(\"Frequency\", language = language),   xlab = translate_AMR(\"Minimum Inhibitory Concentration (mg/L)\", language = language),   colours_SIR = c(\"#3CAEA3\", \"#F6D55C\", \"#ED553B\"),   language = get_AMR_locale(),   expand = TRUE,   include_PKPD = getOption(\"AMR_include_PKPD\", TRUE),   breakpoint_type = getOption(\"AMR_breakpoint_type\", \"human\"),   ... )  # S3 method for class 'mic' autoplot(   object,   mo = NULL,   ab = NULL,   guideline = \"EUCAST\",   title = deparse(substitute(object)),   ylab = translate_AMR(\"Frequency\", language = language),   xlab = translate_AMR(\"Minimum Inhibitory Concentration (mg/L)\", language = language),   colours_SIR = c(\"#3CAEA3\", \"#F6D55C\", \"#ED553B\"),   language = get_AMR_locale(),   expand = TRUE,   include_PKPD = getOption(\"AMR_include_PKPD\", TRUE),   breakpoint_type = getOption(\"AMR_breakpoint_type\", \"human\"),   ... )  # S3 method for class 'mic' fortify(object, ...)  # S3 method for class 'disk' plot(   x,   main = deparse(substitute(x)),   ylab = translate_AMR(\"Frequency\", language = language),   xlab = translate_AMR(\"Disk diffusion diameter (mm)\", language = language),   mo = NULL,   ab = NULL,   guideline = \"EUCAST\",   colours_SIR = c(\"#3CAEA3\", \"#F6D55C\", \"#ED553B\"),   language = get_AMR_locale(),   expand = TRUE,   include_PKPD = getOption(\"AMR_include_PKPD\", TRUE),   breakpoint_type = getOption(\"AMR_breakpoint_type\", \"human\"),   ... )  # S3 method for class 'disk' autoplot(   object,   mo = NULL,   ab = NULL,   title = deparse(substitute(object)),   ylab = translate_AMR(\"Frequency\", language = language),   xlab = translate_AMR(\"Disk diffusion diameter (mm)\", language = language),   guideline = \"EUCAST\",   colours_SIR = c(\"#3CAEA3\", \"#F6D55C\", \"#ED553B\"),   language = get_AMR_locale(),   expand = TRUE,   include_PKPD = getOption(\"AMR_include_PKPD\", TRUE),   breakpoint_type = getOption(\"AMR_breakpoint_type\", \"human\"),   ... )  # S3 method for class 'disk' fortify(object, ...)  # S3 method for class 'sir' plot(   x,   ylab = translate_AMR(\"Percentage\", language = language),   xlab = translate_AMR(\"Antimicrobial Interpretation\", language = language),   main = deparse(substitute(x)),   language = get_AMR_locale(),   ... )  # S3 method for class 'sir' autoplot(   object,   title = deparse(substitute(object)),   xlab = translate_AMR(\"Antimicrobial Interpretation\", language = language),   ylab = translate_AMR(\"Frequency\", language = language),   colours_SIR = c(\"#3CAEA3\", \"#F6D55C\", \"#ED553B\"),   language = get_AMR_locale(),   ... )  # S3 method for class 'sir' fortify(object, ...)"},{"path":"https://msberends.github.io/AMR/reference/plot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plotting for Classes sir, mic and disk — plot","text":"keep_operators character specifying handle operators (> <=) input. Accepts one three values: \"\" (TRUE) keep operators, \"none\" (FALSE) remove operators, \"edges\" keep operators ends range. mic_range manual range limit MIC values, e.g., mic_range = c(0.001, 32). Use NA set limit one side, e.g., mic_range = c(NA, 32). drop logical remove intermediate MIC values, defaults FALSE ... arguments passed methods x, object values created .mic(), .disk() .sir() (random_* variants, random_mic()) mo (vector ) text can coerced valid microorganism code .mo() ab (vector ) text can coerced valid antimicrobial drug code .ab() guideline interpretation guideline use - default latest included EUCAST guideline, see Details main, title title plot xlab, ylab axis title colours_SIR colours use filling bars, must vector three values (order S, R). default colours colour-blind friendly. language language used translate 'Susceptible', 'Increased exposure'/'Intermediate' 'Resistant' - default system language (see get_AMR_locale()) can overwritten setting package option AMR_locale, e.g. options(AMR_locale = \"de\"), see translate. Use language = NULL language = \"\" prevent translation. expand logical indicate whether range x axis expanded lowest highest value. MIC values, intermediate values factors 2 starting highest MIC value. disk diameters, whole diameter range filled. include_PKPD logical indicate PK/PD clinical breakpoints must applied last resort - default TRUE. Can also set package option AMR_include_PKPD. breakpoint_type type breakpoints use, either \"ECOFF\", \"animal\", \"human\". ECOFF stands Epidemiological Cut-values. default \"human\", can also set package option AMR_breakpoint_type. host set values veterinary species, automatically set \"animal\".","code":""},{"path":"https://msberends.github.io/AMR/reference/plot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plotting for Classes sir, mic and disk — plot","text":"autoplot() functions return ggplot model extendible ggplot2 function. fortify() functions return data.frame extension usage ggplot2::ggplot() function.","code":""},{"path":"https://msberends.github.io/AMR/reference/plot.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plotting for Classes sir, mic and disk — plot","text":"interpretation \"\" named \"Increased exposure\" EUCAST guidelines since 2019, named \"Intermediate\" cases. interpreting MIC values well disk diffusion diameters, supported guidelines used input guideline argument : \"EUCAST 2024\", \"EUCAST 2023\", \"EUCAST 2022\", \"EUCAST 2021\", \"EUCAST 2020\", \"EUCAST 2019\", \"EUCAST 2018\", \"EUCAST 2017\", \"EUCAST 2016\", \"EUCAST 2015\", \"EUCAST 2014\", \"EUCAST 2013\", \"EUCAST 2012\", \"EUCAST 2011\", \"CLSI 2024\", \"CLSI 2023\", \"CLSI 2022\", \"CLSI 2021\", \"CLSI 2020\", \"CLSI 2019\", \"CLSI 2018\", \"CLSI 2017\", \"CLSI 2016\", \"CLSI 2015\", \"CLSI 2014\", \"CLSI 2013\", \"CLSI 2012\", \"CLSI 2011\". Simply using \"CLSI\" \"EUCAST\" input automatically select latest version guideline.","code":""},{"path":"https://msberends.github.io/AMR/reference/plot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plotting for Classes sir, mic and disk — plot","text":"","code":"some_mic_values <- random_mic(size = 100) some_disk_values <- random_disk(size = 100, mo = \"Escherichia coli\", ab = \"cipro\") some_sir_values <- random_sir(50, prob_SIR = c(0.55, 0.05, 0.30))  plot(some_mic_values)  plot(some_disk_values)  plot(some_sir_values)   # when providing the microorganism and antibiotic, colours will show interpretations: plot(some_mic_values, mo = \"S. aureus\", ab = \"ampicillin\")  plot(some_disk_values, mo = \"Escherichia coli\", ab = \"cipro\")  plot(some_disk_values, mo = \"Escherichia coli\", ab = \"cipro\", language = \"nl\")    # Plotting using scale_x_mic() # \\donttest{ if (require(\"ggplot2\")) {   mic_plot <- ggplot(data.frame(mics = as.mic(c(0.125, \"<=4\", 4, 8, 32, \">=32\")),                                 counts = c(1, 1, 2, 2, 3, 3)),                      aes(mics, counts)) +     geom_col()   mic_plot +     labs(title = \"without scale_x_mic()\") }  if (require(\"ggplot2\")) {   mic_plot +     scale_x_mic() +     labs(title = \"with scale_x_mic()\") }  if (require(\"ggplot2\")) {   mic_plot +     scale_x_mic(keep_operators = \"all\") +     labs(title = \"with scale_x_mic() keeping all operators\") }  if (require(\"ggplot2\")) {   mic_plot +     scale_x_mic(mic_range = c(1, 128)) +     labs(title = \"with scale_x_mic() using a manual range\") }   if (require(\"ggplot2\")) {   autoplot(some_mic_values) }  if (require(\"ggplot2\")) {   autoplot(some_disk_values, mo = \"Escherichia coli\", ab = \"cipro\") }  if (require(\"ggplot2\")) {   autoplot(some_sir_values) }  # }"},{"path":"https://msberends.github.io/AMR/reference/proportion.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate Antimicrobial Resistance — proportion","title":"Calculate Antimicrobial Resistance — proportion","text":"functions can used calculate (co-)resistance susceptibility microbial isolates (.e. percentage S, SI, , IR R). functions support quasiquotation pipes, can used summarise() dplyr package also support grouped variables, see Examples. resistance() used calculate resistance, susceptibility() used calculate susceptibility.","code":""},{"path":"https://msberends.github.io/AMR/reference/proportion.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate Antimicrobial Resistance — proportion","text":"","code":"resistance(..., minimum = 30, as_percent = FALSE, only_all_tested = FALSE)  susceptibility(..., minimum = 30, as_percent = FALSE, only_all_tested = FALSE)  sir_confidence_interval(   ...,   ab_result = \"R\",   minimum = 30,   as_percent = FALSE,   only_all_tested = FALSE,   confidence_level = 0.95,   side = \"both\",   collapse = FALSE )  proportion_R(..., minimum = 30, as_percent = FALSE, only_all_tested = FALSE)  proportion_IR(..., minimum = 30, as_percent = FALSE, only_all_tested = FALSE)  proportion_I(..., minimum = 30, as_percent = FALSE, only_all_tested = FALSE)  proportion_SI(..., minimum = 30, as_percent = FALSE, only_all_tested = FALSE)  proportion_S(..., minimum = 30, as_percent = FALSE, only_all_tested = FALSE)  proportion_df(   data,   translate_ab = \"name\",   language = get_AMR_locale(),   minimum = 30,   as_percent = FALSE,   combine_SI = TRUE,   confidence_level = 0.95 )  sir_df(   data,   translate_ab = \"name\",   language = get_AMR_locale(),   minimum = 30,   as_percent = FALSE,   combine_SI = TRUE,   confidence_level = 0.95 )"},{"path":"https://msberends.github.io/AMR/reference/proportion.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Calculate Antimicrobial Resistance — proportion","text":"M39 Analysis Presentation Cumulative Antimicrobial Susceptibility Test Data, 5th Edition, 2022, Clinical Laboratory Standards Institute (CLSI). https://clsi.org/standards/products/microbiology/documents/m39/.","code":""},{"path":"https://msberends.github.io/AMR/reference/proportion.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate Antimicrobial Resistance — proportion","text":"... one vectors (columns) antibiotic interpretations. transformed internally .sir() needed. Use multiple columns calculate (lack ) co-resistance: probability one two drugs resistant susceptible result. See Examples. minimum minimum allowed number available (tested) isolates. isolate count lower minimum return NA warning. default number 30 isolates advised Clinical Laboratory Standards Institute (CLSI) best practice, see Source. as_percent logical indicate whether output must returned hundred fold % sign (character). value 0.123456 returned \"12.3%\". only_all_tested (combination therapies, .e. using one variable ...): logical indicate isolates must tested antibiotics, see section Combination Therapy ab_result antibiotic results test , must one values \"S\", \"\", \"R\" confidence_level confidence level returned confidence interval. calculation, number S SI isolates, R isolates compared total number available isolates R, S, using binom.test(), .e., Clopper-Pearson method. side side confidence interval return. default \"\" length 2 vector, can also (abbreviated ) \"min\"/\"left\"/\"lower\"/\"less\" \"max\"/\"right\"/\"higher\"/\"greater\". collapse logical indicate whether output values 'collapsed', .e. merged together one value, character value use collapsing data data.frame containing columns class sir (see .sir()) translate_ab column name antibiotics data set translate antibiotic abbreviations , using ab_property() language language returned text - default current system language (see get_AMR_locale()) can also set package option AMR_locale. Use language = NULL language = \"\" prevent translation. combine_SI logical indicate whether values S must merged one, output consists S+vs. R (susceptible vs. resistant) - default TRUE","code":""},{"path":"https://msberends.github.io/AMR/reference/proportion.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate Antimicrobial Resistance — proportion","text":"double , as_percent = TRUE, character.","code":""},{"path":"https://msberends.github.io/AMR/reference/proportion.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate Antimicrobial Resistance — proportion","text":"Remember filter data let contain first isolates! needed exclude duplicates reduce selection bias. Use first_isolate() determine data set one four available algorithms. function resistance() equal function proportion_R(). function susceptibility() equal function proportion_SI(). Since AMR v3.0, proportion_SI() proportion_I() include dose-dependent susceptibility ('SDD'). Use sir_confidence_interval() calculate confidence interval, relies binom.test(), .e., Clopper-Pearson method. function returns vector length 2 default antimicrobial resistance. Change side argument \"left\"/\"min\" \"right\"/\"max\" return single value, change ab_result argument e.g. c(\"S\", \"\") test antimicrobial susceptibility, see Examples. functions meant count isolates, calculate proportion resistance/susceptibility. Use count_*() functions count isolates. function susceptibility() essentially equal count_susceptible()/count_all(). Low counts can influence outcome - proportion_*() functions may camouflage , since return proportion (albeit dependent minimum argument). function proportion_df() takes variable data sir class (created .sir()) calculates proportions S, , R. also supports grouped variables. function sir_df() works exactly like proportion_df(), adds number isolates.","code":""},{"path":"https://msberends.github.io/AMR/reference/proportion.html","id":"combination-therapy","dir":"Reference","previous_headings":"","what":"Combination Therapy","title":"Calculate Antimicrobial Resistance — proportion","text":"using one variable ... (= combination therapy), use only_all_tested count isolates tested antibiotics/variables test . See example two antibiotics, Drug Drug B, susceptibility() works calculate %SI:   Please note , combination therapies, only_all_tested = TRUE applies :   , combination therapies, only_all_tested = FALSE applies :   Using only_all_tested impact using one antibiotic input.","code":"--------------------------------------------------------------------                     only_all_tested = FALSE  only_all_tested = TRUE                     -----------------------  -----------------------  Drug A    Drug B   include as  include as   include as  include as                     numerator   denominator  numerator   denominator --------  --------  ----------  -----------  ----------  -----------  S or I    S or I       X            X            X            X    R       S or I       X            X            X            X   <NA>     S or I       X            X            -            -  S or I      R          X            X            X            X    R         R          -            X            -            X   <NA>       R          -            -            -            -  S or I     <NA>        X            X            -            -    R        <NA>        -            -            -            -   <NA>      <NA>        -            -            -            - -------------------------------------------------------------------- count_S()    +   count_I()    +   count_R()    = count_all()   proportion_S() + proportion_I() + proportion_R() = 1 count_S()    +   count_I()    +   count_R()    >= count_all()   proportion_S() + proportion_I() + proportion_R() >= 1"},{"path":"https://msberends.github.io/AMR/reference/proportion.html","id":"interpretation-of-sir","dir":"Reference","previous_headings":"","what":"Interpretation of SIR","title":"Calculate Antimicrobial Resistance — proportion","text":"2019, European Committee Antimicrobial Susceptibility Testing (EUCAST) decided change definitions susceptibility testing categories S, , R shown (https://www.eucast.org/newsiandr): S - Susceptible, standard dosing regimen microorganism categorised \"Susceptible, standard dosing regimen\", high likelihood therapeutic success using standard dosing regimen agent. - Susceptible, increased exposure  microorganism categorised \"Susceptible, Increased exposure\" high likelihood therapeutic success exposure agent increased adjusting dosing regimen concentration site infection. R = Resistant microorganism categorised \"Resistant\" high likelihood therapeutic failure even increased exposure. Exposure function mode administration, dose, dosing interval, infusion time, well distribution excretion antimicrobial agent influence infecting organism site infection. AMR package honours insight. Use susceptibility() (equal proportion_SI()) determine antimicrobial susceptibility count_susceptible() (equal count_SI()) count susceptible isolates.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/proportion.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate Antimicrobial Resistance — proportion","text":"","code":"# example_isolates is a data set available in the AMR package. # run ?example_isolates for more info. example_isolates #> # A tibble: 2,000 × 46 #>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX   #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir> #>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  2 2002-01-03 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA    #>  3 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  4 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  5 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  6 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #>  7 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  8 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R     #>  9 2002-01-16 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA    #> 10 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R     NA    S     NA    #> # ℹ 1,990 more rows #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> #   CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> #   TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> #   FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>, #> #   TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>, AZM <sir>, #> #   IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>, MUP <sir>, …   # base R ------------------------------------------------------------ # determines %R resistance(example_isolates$AMX) #> [1] 0.5955556 sir_confidence_interval(example_isolates$AMX) #> [1] 0.5688204 0.6218738 sir_confidence_interval(example_isolates$AMX,   confidence_level = 0.975 ) #> [1] 0.5650148 0.6255670 sir_confidence_interval(example_isolates$AMX,   confidence_level = 0.975,   collapse = \", \" ) #> [1] \"0.565, 0.626\"  # determines %S+I: susceptibility(example_isolates$AMX) #> [1] 0.4044444 sir_confidence_interval(example_isolates$AMX,   ab_result = c(\"S\", \"I\") ) #> [1] 0.3781262 0.4311796  # be more specific proportion_S(example_isolates$AMX) #> [1] 0.4022222 proportion_SI(example_isolates$AMX) #> Note that proportion_SI() will also include dose-dependent #> susceptibility, 'SDD'. This note will be shown once for this session. #> [1] 0.4044444 proportion_I(example_isolates$AMX) #> Note that proportion_I() will also include dose-dependent susceptibility, #> 'SDD'. This note will be shown once for this session. #> [1] 0.002222222 proportion_IR(example_isolates$AMX) #> Note that proportion_IR() will also include dose-dependent #> susceptibility, 'SDD'. This note will be shown once for this session. #> [1] 0.5977778 proportion_R(example_isolates$AMX) #> [1] 0.5955556  # dplyr ------------------------------------------------------------- # \\donttest{ if (require(\"dplyr\")) {   example_isolates %>%     group_by(ward) %>%     summarise(       r = resistance(CIP),       n = n_sir(CIP)     ) # n_sir works like n_distinct in dplyr, see ?n_sir } #> # A tibble: 3 × 3 #>   ward           r     n #>   <chr>      <dbl> <int> #> 1 Clinical   0.147   869 #> 2 ICU        0.190   447 #> 3 Outpatient 0.161    93 if (require(\"dplyr\")) {   example_isolates %>%     group_by(ward) %>%     summarise(       cipro_R = resistance(CIP),       ci_min = sir_confidence_interval(CIP, side = \"min\"),       ci_max = sir_confidence_interval(CIP, side = \"max\"),     ) } #> # A tibble: 3 × 4 #>   ward       cipro_R ci_min ci_max #>   <chr>        <dbl>  <dbl>  <dbl> #> 1 Clinical     0.147 0.124   0.173 #> 2 ICU          0.190 0.155   0.230 #> 3 Outpatient   0.161 0.0932  0.252 if (require(\"dplyr\")) {   # scoped dplyr verbs with antibiotic selectors   # (you could also use across() of course)   example_isolates %>%     group_by(ward) %>%     summarise_at(       c(aminoglycosides(), carbapenems()),       resistance     ) } #> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' #>   (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin) #> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem) #> Warning: There was 1 warning in `summarise()`. #> ℹ In argument: `KAN = (function (..., minimum = 30, as_percent = FALSE, #>   only_all_tested = FALSE) ...`. #> ℹ In group 3: `ward = \"Outpatient\"`. #> Caused by warning: #> ! Introducing NA: only 23 results available for KAN in group: ward = #> \"Outpatient\" (minimum = 30). #> # A tibble: 3 × 7 #>   ward         GEN   TOB   AMK   KAN    IPM    MEM #>   <chr>      <dbl> <dbl> <dbl> <dbl>  <dbl>  <dbl> #> 1 Clinical   0.229 0.315 0.626     1 0.0498 0.0458 #> 2 ICU        0.290 0.400 0.662     1 0.0862 0.0894 #> 3 Outpatient 0.2   0.368 0.605    NA 0.0541 0.0541 if (require(\"dplyr\")) {   example_isolates %>%     group_by(ward) %>%     summarise(       R = resistance(CIP, as_percent = TRUE),       SI = susceptibility(CIP, as_percent = TRUE),       n1 = count_all(CIP), # the actual total; sum of all three       n2 = n_sir(CIP), # same - analogous to n_distinct       total = n()     ) # NOT the number of tested isolates!    # Calculate co-resistance between amoxicillin/clav acid and gentamicin,   # so we can see that combination therapy does a lot more than mono therapy:   example_isolates %>% susceptibility(AMC) # %SI = 76.3%   example_isolates %>% count_all(AMC) #   n = 1879    example_isolates %>% susceptibility(GEN) # %SI = 75.4%   example_isolates %>% count_all(GEN) #   n = 1855    example_isolates %>% susceptibility(AMC, GEN) # %SI = 94.1%   example_isolates %>% count_all(AMC, GEN) #   n = 1939     # See Details on how `only_all_tested` works. Example:   example_isolates %>%     summarise(       numerator = count_susceptible(AMC, GEN),       denominator = count_all(AMC, GEN),       proportion = susceptibility(AMC, GEN)     )    example_isolates %>%     summarise(       numerator = count_susceptible(AMC, GEN, only_all_tested = TRUE),       denominator = count_all(AMC, GEN, only_all_tested = TRUE),       proportion = susceptibility(AMC, GEN, only_all_tested = TRUE)     )     example_isolates %>%     group_by(ward) %>%     summarise(       cipro_p = susceptibility(CIP, as_percent = TRUE),       cipro_n = count_all(CIP),       genta_p = susceptibility(GEN, as_percent = TRUE),       genta_n = count_all(GEN),       combination_p = susceptibility(CIP, GEN, as_percent = TRUE),       combination_n = count_all(CIP, GEN)     )    # Get proportions S/I/R immediately of all sir columns   example_isolates %>%     select(AMX, CIP) %>%     proportion_df(translate = FALSE)    # It also supports grouping variables   # (use sir_df to also include the count)   example_isolates %>%     select(ward, AMX, CIP) %>%     group_by(ward) %>%     sir_df(translate = FALSE) } #> # A tibble: 12 × 7 #>    ward       antibiotic interpretation value ci_min ci_max isolates #>  * <chr>      <chr>      <ord>          <dbl>  <dbl>  <dbl>    <int> #>  1 Clinical   AMX        SI             0.423 0.389   0.457      357 #>  2 Clinical   AMX        R              0.577 0.543   0.611      487 #>  3 Clinical   CIP        SI             0.853 0.827   0.876      741 #>  4 Clinical   CIP        R              0.147 0.124   0.173      128 #>  5 ICU        AMX        SI             0.369 0.323   0.417      158 #>  6 ICU        AMX        R              0.631 0.583   0.677      270 #>  7 ICU        CIP        SI             0.810 0.770   0.845      362 #>  8 ICU        CIP        R              0.190 0.155   0.230       85 #>  9 Outpatient AMX        SI             0.397 0.288   0.515       31 #> 10 Outpatient AMX        R              0.603 0.485   0.712       47 #> 11 Outpatient CIP        SI             0.839 0.748   0.907       78 #> 12 Outpatient CIP        R              0.161 0.0932  0.252       15 # }"},{"path":"https://msberends.github.io/AMR/reference/random.html","id":null,"dir":"Reference","previous_headings":"","what":"Random MIC Values/Disk Zones/SIR Generation — random","title":"Random MIC Values/Disk Zones/SIR Generation — random","text":"functions can used generating random MIC values disk diffusion diameters, AMR data analysis practice. providing microorganism antimicrobial drug, generated results reflect reality much possible.","code":""},{"path":"https://msberends.github.io/AMR/reference/random.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Random MIC Values/Disk Zones/SIR Generation — random","text":"","code":"random_mic(size = NULL, mo = NULL, ab = NULL, ...)  random_disk(size = NULL, mo = NULL, ab = NULL, ...)  random_sir(size = NULL, prob_SIR = c(0.33, 0.33, 0.33), ...)"},{"path":"https://msberends.github.io/AMR/reference/random.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Random MIC Values/Disk Zones/SIR Generation — random","text":"size desired size returned vector. used data.frame call dplyr verb, get current (group) size left blank. mo character can coerced valid microorganism code .mo() ab character can coerced valid antimicrobial drug code .ab() ... ignored, place allow future extensions prob_SIR vector length 3: probabilities \"S\" (1st value), \"\" (2nd value) \"R\" (3rd value)","code":""},{"path":"https://msberends.github.io/AMR/reference/random.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Random MIC Values/Disk Zones/SIR Generation — random","text":"class mic random_mic() (see .mic()) class disk random_disk() (see .disk())","code":""},{"path":"https://msberends.github.io/AMR/reference/random.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Random MIC Values/Disk Zones/SIR Generation — random","text":"base R function sample() used generating values. Generated values based EUCAST 2024 guideline implemented clinical_breakpoints data set. create specific generated values per bug drug, set mo /ab argument.","code":""},{"path":"https://msberends.github.io/AMR/reference/random.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Random MIC Values/Disk Zones/SIR Generation — random","text":"","code":"random_mic(25) #> Class 'mic' #>  [1] 16     64     256    0.002  1      0.001  64     0.25   1      16     #> [11] 0.5    8      8      0.0625 1      0.5    0.025  256    256    1      #> [21] 0.01   1      64     32     4      random_disk(25) #> Class 'disk' #>  [1] 49 47 14 33 49 43 41 41 43 31 20 43 42 11 18 42  8 42 16 25 42  8 15 30 29 random_sir(25) #> Class 'sir' #>  [1] I S S I S I I S R S S I I S S I I S I R S S R I S  # \\donttest{ # make the random generation more realistic by setting a bug and/or drug: random_mic(25, \"Klebsiella pneumoniae\") # range 0.0625-64 #> Class 'mic' #>  [1] 64     0.025  2      0.25   32     64     0.002  32     0.01   0.001  #> [11] 0.25   0.125  0.0625 64     128    0.002  128    128    1      0.002  #> [21] 1      0.005  0.001  4      0.001  random_mic(25, \"Klebsiella pneumoniae\", \"meropenem\") # range 0.0625-16 #> Class 'mic' #>  [1] 1    2    1    >=16 8    1    >=16 >=16 2    1    2    1    1    8    4    #> [16] 1    1    4    2    >=16 >=16 2    4    2    1    random_mic(25, \"Streptococcus pneumoniae\", \"meropenem\") # range 0.0625-4 #> Class 'mic' #>  [1] 2     0.25  >=8   >=8   0.5   1     1     0.125 0.25  1     2     1     #> [13] 0.25  >=8   0.25  2     1     1     >=8   0.125 0.5   >=8   0.125 0.25  #> [25] 0.25   random_disk(25, \"Klebsiella pneumoniae\") # range 8-50 #> Class 'disk' #>  [1] 45 49 24 46 23 18 15 17 17 28 40 20 21 43 39  9 33 17  8 20 30 21 44 48 41 random_disk(25, \"Klebsiella pneumoniae\", \"ampicillin\") # range 11-17 #> Class 'disk' #>  [1] 13 15 11 14 16 16 11 15 11 17 14 15 17 17 16 16 16 12 14 12 15 13 13 13 16 random_disk(25, \"Streptococcus pneumoniae\", \"ampicillin\") # range 12-27 #> Class 'disk' #>  [1] 22 23 19 19 23 15 23 18 21 24 22 25 19 19 16 17 17 16 27 21 27 25 15 21 27 # }"},{"path":"https://msberends.github.io/AMR/reference/resistance_predict.html","id":null,"dir":"Reference","previous_headings":"","what":"Predict Antimicrobial Resistance — resistance_predict","title":"Predict Antimicrobial Resistance — resistance_predict","text":"Create prediction model predict antimicrobial resistance next years statistical solid ground. Standard errors (SE) returned columns se_min se_max. See Examples real live example.","code":""},{"path":"https://msberends.github.io/AMR/reference/resistance_predict.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Predict Antimicrobial Resistance — resistance_predict","text":"","code":"resistance_predict(   x,   col_ab,   col_date = NULL,   year_min = NULL,   year_max = NULL,   year_every = 1,   minimum = 30,   model = NULL,   I_as_S = TRUE,   preserve_measurements = TRUE,   info = interactive(),   ... )  sir_predict(   x,   col_ab,   col_date = NULL,   year_min = NULL,   year_max = NULL,   year_every = 1,   minimum = 30,   model = NULL,   I_as_S = TRUE,   preserve_measurements = TRUE,   info = interactive(),   ... )  # S3 method for class 'resistance_predict' plot(x, main = paste(\"Resistance Prediction of\", x_name), ...)  ggplot_sir_predict(   x,   main = paste(\"Resistance Prediction of\", x_name),   ribbon = TRUE,   ... )  # S3 method for class 'resistance_predict' autoplot(   object,   main = paste(\"Resistance Prediction of\", x_name),   ribbon = TRUE,   ... )"},{"path":"https://msberends.github.io/AMR/reference/resistance_predict.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Predict Antimicrobial Resistance — resistance_predict","text":"x data.frame containing isolates. Can left blank automatic determination, see Examples. col_ab column name x containing antimicrobial interpretations (\"R\", \"\" \"S\") col_date column name date, used calculate years column consist years already - default first column date class year_min lowest year use prediction model, dafaults lowest year col_date year_max highest year use prediction model - default 10 years today year_every unit sequence lowest year found data year_max minimum minimal amount available isolates per year include. Years containing less observations estimated model. model statistical model choice. generalised linear regression model binomial distribution (.e. using glm(..., family = binomial), assuming period zero resistance followed period increasing resistance leading slowly resistance. See Details valid options. I_as_S logical indicate whether values \"\" treated \"S\" (otherwise treated \"R\"). default, TRUE, follows redefinition EUCAST interpretation (increased exposure) 2019, see section Interpretation S, R . preserve_measurements logical indicate whether predictions years actually available data overwritten original data. standard errors years NA. info logical indicate whether textual analysis printed name summary() statistical model. ... arguments passed functions main title plot ribbon logical indicate whether ribbon shown (default) error bars object model data plotted","code":""},{"path":"https://msberends.github.io/AMR/reference/resistance_predict.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Predict Antimicrobial Resistance — resistance_predict","text":"data.frame extra class resistance_predict columns: year value, estimated preserve_measurements = FALSE, combination observed estimated otherwise se_min, lower bound standard error minimum 0 (standard error never go 0%) se_max upper bound standard error maximum 1 (standard error never go 100%) observations, total number available observations year, .e. \\(S + + R\\) observed, original observed resistant percentages estimated, estimated resistant percentages, calculated model Furthermore, model available attribute: attributes(x)$model, see Examples.","code":""},{"path":"https://msberends.github.io/AMR/reference/resistance_predict.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Predict Antimicrobial Resistance — resistance_predict","text":"Valid options statistical model (argument model) : \"binomial\" \"binom\" \"logit\": generalised linear regression model binomial distribution \"loglin\" \"poisson\": generalised log-linear regression model poisson distribution \"lin\" \"linear\": linear regression model","code":""},{"path":"https://msberends.github.io/AMR/reference/resistance_predict.html","id":"interpretation-of-sir","dir":"Reference","previous_headings":"","what":"Interpretation of SIR","title":"Predict Antimicrobial Resistance — resistance_predict","text":"2019, European Committee Antimicrobial Susceptibility Testing (EUCAST) decided change definitions susceptibility testing categories S, , R shown (https://www.eucast.org/newsiandr): S - Susceptible, standard dosing regimen microorganism categorised \"Susceptible, standard dosing regimen\", high likelihood therapeutic success using standard dosing regimen agent. - Susceptible, increased exposure  microorganism categorised \"Susceptible, Increased exposure\" high likelihood therapeutic success exposure agent increased adjusting dosing regimen concentration site infection. R = Resistant microorganism categorised \"Resistant\" high likelihood therapeutic failure even increased exposure. Exposure function mode administration, dose, dosing interval, infusion time, well distribution excretion antimicrobial agent influence infecting organism site infection. AMR package honours insight. Use susceptibility() (equal proportion_SI()) determine antimicrobial susceptibility count_susceptible() (equal count_SI()) count susceptible isolates.","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/resistance_predict.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Predict Antimicrobial Resistance — resistance_predict","text":"","code":"x <- resistance_predict(example_isolates,   col_ab = \"AMX\",   year_min = 2010,   model = \"binomial\" ) plot(x)  # \\donttest{ if (require(\"ggplot2\")) {   ggplot_sir_predict(x) }   # using dplyr: if (require(\"dplyr\")) {   x <- example_isolates %>%     filter_first_isolate() %>%     filter(mo_genus(mo) == \"Staphylococcus\") %>%     resistance_predict(\"PEN\", model = \"binomial\")   print(plot(x))    # get the model from the object   mymodel <- attributes(x)$model   summary(mymodel) }  #> NULL #>  #> Call: #> glm(formula = df_matrix ~ year, family = binomial) #>  #> Coefficients: #>             Estimate Std. Error z value Pr(>|z|) #> (Intercept) 27.05312   72.24652   0.374    0.708 #> year        -0.01286    0.03601  -0.357    0.721 #>  #> (Dispersion parameter for binomial family taken to be 1) #>  #>     Null deviance: 5.7883  on 11  degrees of freedom #> Residual deviance: 5.6608  on 10  degrees of freedom #> AIC: 50.745 #>  #> Number of Fisher Scoring iterations: 4 #>   # create nice plots with ggplot2 yourself if (require(\"dplyr\") && require(\"ggplot2\")) {   data <- example_isolates %>%     filter(mo == as.mo(\"E. coli\")) %>%     resistance_predict(       col_ab = \"AMX\",       col_date = \"date\",       model = \"binomial\",       info = FALSE,       minimum = 15     )   head(data)   autoplot(data) }  # }"},{"path":"https://msberends.github.io/AMR/reference/skewness.html","id":null,"dir":"Reference","previous_headings":"","what":"Skewness of the Sample — skewness","title":"Skewness of the Sample — skewness","text":"Skewness measure asymmetry probability distribution real-valued random variable mean. negative ('left-skewed'): left tail longer; mass distribution concentrated right histogram. positive ('right-skewed'): right tail longer; mass distribution concentrated left histogram. normal distribution skewness 0.","code":""},{"path":"https://msberends.github.io/AMR/reference/skewness.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Skewness of the Sample — skewness","text":"","code":"skewness(x, na.rm = FALSE)  # Default S3 method skewness(x, na.rm = FALSE)  # S3 method for class 'matrix' skewness(x, na.rm = FALSE)  # S3 method for class 'data.frame' skewness(x, na.rm = FALSE)"},{"path":"https://msberends.github.io/AMR/reference/skewness.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Skewness of the Sample — skewness","text":"x vector values, matrix data.frame na.rm logical value indicating whether NA values stripped computation proceeds","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/reference/skewness.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Skewness of the Sample — skewness","text":"","code":"skewness(runif(1000)) #> [1] -0.03310027"},{"path":"https://msberends.github.io/AMR/reference/translate.html","id":null,"dir":"Reference","previous_headings":"","what":"Translate Strings from the AMR Package — translate","title":"Translate Strings from the AMR Package — translate","text":"language-dependent output AMR functions, mo_name(), mo_gramstain(), mo_type() ab_name().","code":""},{"path":"https://msberends.github.io/AMR/reference/translate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Translate Strings from the AMR Package — translate","text":"","code":"get_AMR_locale()  set_AMR_locale(language)  reset_AMR_locale()  translate_AMR(x, language = get_AMR_locale())"},{"path":"https://msberends.github.io/AMR/reference/translate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Translate Strings from the AMR Package — translate","text":"language language choose. Use one supported language names ISO-639-1 codes: English (en), Chinese (zh), Czech (cs), Danish (da), Dutch (nl), Finnish (fi), French (fr), German (de), Greek (el), Italian (), Japanese (ja), Norwegian (), Polish (pl), Portuguese (pt), Romanian (ro), Russian (ru), Spanish (es), Swedish (sv), Turkish (tr), Ukrainian (uk). x text translate","code":""},{"path":"https://msberends.github.io/AMR/reference/translate.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Translate Strings from the AMR Package — translate","text":"currently 20 supported languages English (en), Chinese (zh), Czech (cs), Danish (da), Dutch (nl), Finnish (fi), French (fr), German (de), Greek (el), Italian (), Japanese (ja), Norwegian (), Polish (pl), Portuguese (pt), Romanian (ro), Russian (ru), Spanish (es), Swedish (sv), Turkish (tr), Ukrainian (uk). languages translations available antimicrobial drugs colloquial microorganism names. permanently silence -per-session language note non-English operating system, can set package option AMR_locale .Rprofile file like :   save file. Please read adding updating language Wiki.","code":"# Open .Rprofile file utils::file.edit(\"~/.Rprofile\")  # Then add e.g. Italian support to that file using: options(AMR_locale = \"Italian\")"},{"path":"https://msberends.github.io/AMR/reference/translate.html","id":"changing-the-default-language","dir":"Reference","previous_headings":"","what":"Changing the Default Language","title":"Translate Strings from the AMR Package — translate","text":"system language used default (returned Sys.getenv(\"LANG\") , LANG set, Sys.getlocale(\"LC_COLLATE\")), language supported. language used can overwritten two ways checked order: Setting package option AMR_locale, either using e.g. set_AMR_locale(\"German\") running e.g. options(AMR_locale = \"German\"). Note setting R option works session. Save command options(AMR_locale = \"(language)\") .Rprofile file apply every session. Run utils::file.edit(\"~/.Rprofile\") edit .Rprofile file. Setting system variable LANGUAGE LANG, e.g. adding LANGUAGE=\"de_DE.utf8\" .Renviron file home directory. Thus, package option AMR_locale set, system variables LANGUAGE LANG ignored.","code":""},{"path":"https://msberends.github.io/AMR/reference/translate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Translate Strings from the AMR Package — translate","text":"","code":"# Current settings (based on system language) ab_name(\"Ciprofloxacin\") #> [1] \"Ciprofloxacin\" mo_name(\"Coagulase-negative Staphylococcus (CoNS)\") #> [1] \"Coagulase-negative Staphylococcus (CoNS)\"  # setting another language set_AMR_locale(\"Dutch\") #> ℹ Using Dutch (Nederlands) for the AMR package for this session. ab_name(\"Ciprofloxacin\") #> [1] \"Ciprofloxacine\" mo_name(\"Coagulase-negative Staphylococcus (CoNS)\") #> [1] \"Coagulase-negatieve Staphylococcus (CNS)\"  # setting yet another language set_AMR_locale(\"German\") #> ℹ Using German (Deutsch) for the AMR package for this session. ab_name(\"Ciprofloxacin\") #> [1] \"Ciprofloxacin\" mo_name(\"Coagulase-negative Staphylococcus (CoNS)\") #> [1] \"Koagulase-negative Staphylococcus (KNS)\"  # set_AMR_locale() understands endonyms, English exonyms, and ISO-639-1: set_AMR_locale(\"Deutsch\") #> ℹ Using German (Deutsch) for the AMR package for this session. set_AMR_locale(\"German\") #> ℹ Using German (Deutsch) for the AMR package for this session. set_AMR_locale(\"de\") #> ℹ Using German (Deutsch) for the AMR package for this session. ab_name(\"amox/clav\") #> ℹ More than one result was found for item 1: amoxicillin and clavulansäure #> [1] \"Amoxicillin/Clavulansäure\"  # reset to system default reset_AMR_locale() #> ℹ Using the English language (English) for the AMR package for this #>   session. ab_name(\"amox/clav\") #> [1] \"Amoxicillin/clavulanic acid\""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"amr-2119063","dir":"Changelog","previous_headings":"","what":"AMR 2.1.1.9063","title":"AMR 2.1.1.9063","text":"(beta version eventually become v3.0. ’re happy reach new major milestone soon, new One Health support! Install beta using instructions .)","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"a-new-milestone-amr-v30-with-one-health-support--human--veterinary--environmental-2-1-1-9063","dir":"Changelog","previous_headings":"","what":"A New Milestone: AMR v3.0 with One Health Support (= Human + Veterinary + Environmental)","title":"AMR 2.1.1.9063","text":"package now supports tools AMR data analysis clinical settings, also veterinary environmental microbiology. made possible collaboration University Prince Edward Island, Canada. celebrate great improvement package, also updated package logo reflect change.","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"breaking-2-1-1-9063","dir":"Changelog","previous_headings":"","what":"Breaking","title":"AMR 2.1.1.9063","text":"Removed functions references used deprecated rsi class, replaced sir equivalents year ago","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"new-2-1-1-9063","dir":"Changelog","previous_headings":"","what":"New","title":"AMR 2.1.1.9063","text":"Function .sir() now extensive support animal breakpoints CLSI. Use breakpoint_type = \"animal\" set host argument variable contains animal species names. clinical_breakpoints data set contains breakpoints, can downloaded download page. antibiotics data set contains veterinary antibiotics, pradofloxacin enrofloxacin. WHOCC codes veterinary use added well. ab_atc() now supports ATC codes veterinary antibiotics (start “Q”) ab_url() now supports retrieving WHOCC url ATCvet pages EUCAST 2024 CLSI 2024 now supported, adding 4,000 new clinical breakpoints clinical_breakpoints data set usage .sir(). EUCAST 2024 now new default guideline MIC disks diffusion interpretations. .sir() now brings additional factor levels: “NI” non-interpretable “SDD” susceptible dose-dependent. Currently, clinical_breakpoints data set contains 24 breakpoints can return value “SDD” instead “”. New function group scale_*_mic(), namely: scale_x_mic(), scale_y_mic(), scale_colour_mic() scale_fill_mic(). advanced ggplot2 extensions allow easy plotting MIC values. allow manual range definition plotting missing intermediate log2 levels. New function rescale_mic(), allows rescale MIC values manually set range. powerhouse behind scale_*_mic() functions, can used users directly e.g. compare equality MIC distributions rescaling range first. microorganisms data set now contains additional columns mycobank, mycobank_parent, mycobank_renamed_to New function mo_mycobank() get MycoBank record number, analogous existing functions mo_lpsn() mo_gbif() ’ve welcomed 2,000 records 2023, 900 2024, many thousands new fungi New function mo_group_members() retrieve member microorganisms microorganism group. example, mo_group_members(\"Strep group C\") returns vector microorganisms group.","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"changed-2-1-1-9063","dir":"Changelog","previous_headings":"","what":"Changed","title":"AMR 2.1.1.9063","text":"now possible use column names argument ab, mo, uti: .sir(..., ab = \"column1\", mo = \"column2\", uti = \"column3\"). greatly improves flexibility users. Users can now set criteria (using regular expressions) considered S, , R, SDD, NI. get quantitative values, .double() sir object return 1 S, 2 SDD/, 3 R (NI become NA). functions using sir classes (e.g., summary()) updated reflect change contain NI SDD. Added “clindamycin inducible screening” CLI1. Since clindamycin lincosamide, antibiotic selector lincosamides() now contains argument only_treatable = TRUE (similar antibiotic selectors contain non-treatable drugs) Added Amorolfine (AMO, D01AE16), now also part antifungals() selector Added selectors nitrofurans() rifamycins() using antibiotic selectors aminoglycosides() exclude non-treatable drugs like gentamicin-high, function now always returns warning can included using only_treatable = FALSE Added valid levels: 4096, 6 powers 0.0625, 5 powers 192 (192, 384, 576, 768, 960) Added new argument keep_operators .mic(). can \"\" (default), \"none\", \"edges\". argument also available new rescale_mic() scale_*_mic() functions. Comparisons MIC values now strict. example, >32 higher (never equal ) 32. Thus, .mic(\">32\") == .mic(32) now returns FALSE, .mic(\">32\") > .mic(32) now returns TRUE. Sorting MIC values (using sort()) fixed manner; <0.001 now gets sorted 0.001, >0.001 gets sorted 0.001. Updated italicise_taxonomy() support HTML output custom_eucast_rules() now supports multiple antibiotics antibiotic groups affected single rule mo_info() now contains extra element group_members, contents new mo_group_members() function Greatly improved vctrs integration, Tidyverse package working background many Tidyverse functions. users, means functions dplyr’s bind_rows(), rowwise() c_across() now supported e.g. columns class mic. Despite , AMR package still zero-dependent package, including dplyr vctrs. Updated ATC codes WHOCC Updated antibiotic DDDs WHOCC Fix using manual value mo_transform antibiogram() Fix mapping ‘high level’ antibiotics .ab() (amphotericin B-high, gentamicin-high, kanamycin-high, streptomycin-high, tobramycin-high) Improved overall algorithm .ab() better performance accuracy Improved overall algorithm .mo() better performance accuracy. Specifically, weight given genus species combinations cases subspecies miswritten, result correct genus species. Intermediate log2 levels used MIC plotting now common values instead following strict dilution range Fixed bug antibiogram() returns empty data set","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"other-2-1-1-9063","dir":"Changelog","previous_headings":"","what":"Other","title":"AMR 2.1.1.9063","text":"Added Jordan Stull, Matthew Saab, Javier Sanchez contributors, thank valuable input","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"amr-211","dir":"Changelog","previous_headings":"","what":"AMR 2.1.1","title":"AMR 2.1.1","text":"CRAN release: 2023-10-21 included many isolates patients altering antibiograms within bacterial species See info issue #122 Added 1,366 LOINC codes antibiotics data set updated latest version (LOINC v2.76) MICs can now used complex number calculations allow scientific number format input (e.g., .mic(\"1.28e-2\")) Fix rounding MICs latest R beta (‘R-devel’) Removed unneeded note used language option AMR_locale set Fixed non-ASCII characters documentation, according CRAN maintainers","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"amr-210","dir":"Changelog","previous_headings":"","what":"AMR 2.1.0","title":"AMR 2.1.0","text":"CRAN release: 2023-07-16","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"new-2-1-0","dir":"Changelog","previous_headings":"","what":"New","title":"AMR 2.1.0","text":"Clinical breakpoints intrinsic resistance EUCAST 2023 CLSI 2023 added clinical_breakpoints data set usage .sir(). EUCAST 2023 (v13.0) now new default guideline MIC disks diffusion interpretations EUCAST dosage guideline v13.0 added dosage data set clinical_breakpoints data set now also contains epidemiological cut-(ECOFF) values CLSI animal breakpoints. two new breakpoint types can used MIC/disk interpretation using .sir(..., breakpoint_type = \"ECOFF\") oras.sir(..., breakpoint_type = \"animal\"), important new addition veterinary microbiology. Added support 30 species groups / complexes. gathered new data set microorganisms.groups used clinical breakpoint interpretation. example, CLSI 2023 contains breakpoints RGM group (Rapidly Growing Mycobacterium, containing 80 species) now supported package. Added mo_oxygen_tolerance() retrieve values Added mo_is_anaerobic() determine genera/species obligate anaerobic bacteria Added LPSN GBIF identifiers, oxygen tolerance mo_info() Added SAS Transport files (file extension .xpt) download page use SAS software Added microbial codes Gram-negative/positive anaerobic bacteria","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"changed-2-1-0","dir":"Changelog","previous_headings":"","what":"Changed","title":"AMR 2.1.0","text":"Updated algorithm .mo() giving weight fungi Fixed clinical breakpoints errors introduced source import rules mo_rank() now returns NA ‘unknown’ microorganisms (B_ANAER, B_ANAER-NEG, B_ANAER-POS, B_GRAMN, B_GRAMP, F_FUNGUS, F_YEAST, UNKNOWN) printing microorganism antibiotic codes tibble, mouse-hover now shows full name code Now settable arguments breakpoint type PK/PD, like .sir() now contain name guideline table subtitle plot Fixed formatting sir_interpretation_history() Fixed WHONET codes microorganisms consequently couple entries clinical_breakpoints Fixed bug .mo() led coercion NA values using custom microorganism codes Fixed usage icu_exclude first_isolates() Now allows searching species names Fix using keep_synonyms argument using MO codes input Fix using minimum_matching_score argument Updated code table microorganisms.codes Fixed endless loop using reference_df .mo() Fixed bug indicating UTIs .sir() Greatly improved speed .sir()","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"amr-200","dir":"Changelog","previous_headings":"","what":"AMR 2.0.0","title":"AMR 2.0.0","text":"CRAN release: 2023-03-12 new major release AMR package, great new additions also breaking changes current users. listed . TL;DR functions arguments ‘rsi’ replaced ‘sir’, interpretation MIC values (now .sir() instead .rsi()) - old functions still work now Many new interesting functions, antibiogram() (generating traditional/combined/syndromic/WISCA antibiograms), sir_confidence_interval() mean_amr_distance(), add_custom_microorganisms() add custom microorganisms package Clinical breakpoints added EUCAST 2022 CLSI 2022 Microbiological taxonomy (microorganisms data set) updated 2022 now based LPSN GBIF Much increased algorithms translate user input valid taxonomy, e.g. using recent scientific work per-species human pathogenicity 20 new antibiotics added updated DDDs ATC codes Extended support antiviral agents (antivirals data set), many new functions Now available 20 languages Many small bug fixes","code":""},{"path":[]},{"path":"https://msberends.github.io/AMR/news/index.html","id":"sir-vs-rsi-2-0-0","dir":"Changelog","previous_headings":"New","what":"SIR vs. RSI","title":"AMR 2.0.0","text":"milestone version, replaced mentions RSI SIR, comply actually commonly used field clinical microbiology comes tri-form regarding AMR. existing functions .rsi(), rsi_df() ggplot_rsi() still work, replacements .sir(), sir_df(), ggplot_sir() now current functions AMR data analysis. warning thrown session remind users . data set rsi_translation now called clinical_breakpoints better reflect content. ‘RSI functions’ removed future version, late 2023 / early 2024.","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"new-antibiogram-function-2-0-0","dir":"Changelog","previous_headings":"New","what":"New antibiogram function","title":"AMR 2.0.0","text":"new antibiogram() function, users can now generate traditional, combined, syndromic, even weighted-incidence syndromic combination antibiograms (WISCA). , follow logic previously described work Klinker et al. (2021, DOI 10.1177/20499361211011373) Barbieri et al. (2021, DOI 10.1186/s13756-021-00939-2). help page antibiogram() extensively elaborates use cases, antibiogram() also supports printing R Markdown Quarto, support 20 languages. Furthermore, different plotting methods implemented allow graphical visualisations well.","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"interpretation-of-mic-and-disk-diffusion-values-2-0-0","dir":"Changelog","previous_headings":"New","what":"Interpretation of MIC and disk diffusion values","title":"AMR 2.0.0","text":"clinical breakpoints intrinsic resistance EUCAST 2022 CLSI 2022 added .sir(). EUCAST 2022 (v12.0) now new default guideline MIC disks diffusion interpretations, eucast_rules() apply EUCAST Expert Rules. default guideline (EUCAST) can now changed new AMR_guideline option, : options(AMR_guideline = \"CLSI 2020\"). new arguments include_PKPD (default: TRUE) include_screening (default: FALSE), users can now specify whether breakpoints screening PK/PD table included interpreting MICs disks diffusion values. options can set globally, can read new manual. Interpretation guidelines older 10 years removed, oldest now included guidelines EUCAST CLSI 2013.","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"supported-languages-2-0-0","dir":"Changelog","previous_headings":"New","what":"Supported languages","title":"AMR 2.0.0","text":"added support following ten languages: Chinese (simplified), Czech, Finnish, Greek, Japanese, Norwegian (bokmål), Polish, Romanian, Turkish Ukrainian. antibiotic names now available languages, AMR package automatically determine supported language based user’s system language. grateful valuable input colleagues countries. AMR package now available 20 languages total, according download stats used almost countries world!","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"outbreak-management-2-0-0","dir":"Changelog","previous_headings":"New","what":"Outbreak management","title":"AMR 2.0.0","text":"analysis outbreak management, updated get_episode() is_new_episode() functions: now contain argument case_free_days. argument can used quantify duration case-free days (inter-epidemic interval), new episode start. common requirement outbreak management, e.g. determining number norovirus outbreaks hospital. case-free period 14 28 days, new norovirus cases time considered different (new) episode.","code":""},{"path":"https://msberends.github.io/AMR/news/index.html","id":"microbiological-taxonomy-2-0-0","dir":"Changelog","previous_headings":"New","what":"Microbiological taxonomy","title":"AMR 2.0.0","text":"microorganisms data set longer relies Catalogue Life, List Prokaryotic names Standing Nomenclature (LPSN) supplemented ‘backbone taxonomy’ Global Biodiversity Information Facility (GBIF). structure data set changed include separate LPSN GBIF identifiers. Almost previous MO codes retained. contains 1,400 taxonomic names 2022. previously relied experience categorise species pathogenic groups, happy encounter recent work Bartlett et al. (2022, DOI 10.1099/mic.0.001269) extensively studied medical-scientific literature categorise bacterial species groups. See mo_matching_score() work incorporated prevalence column microorganisms data set. Using results, .mo() mo_*() functions now much better capable converting user input valid taxonomic records. new function add_custom_microorganisms() allows users add custom microorganisms AMR package. also made following changes regarding included taxonomy microorganisms functions: Updated full microbiological taxonomy according latest daily LPSN data set (December 2022) latest yearly GBIF taxonomy backbone (November 2022) Added function mo_current() get currently valid taxonomic name microorganism Support 1,516 city-like serovars Salmonella, Salmonella Goldcoast. Formally, serovars belonging S. enterica species, reported name genus city. reason, serovars subspecies column microorganisms data set “enterica” species column, full name contain species name (enterica). new argument keep_synonyms allows correct updated taxonomy, favour now deleted argument allow_uncertain increased tremendously speed returns generally consequent results Sequential coercion now extremely fast results stored package environment, although coercion unknown values must run per session. Previous results can reset/removed new mo_reset_session() function. 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Support data.frame-enhancing R packages, specifically: data.table::data.table, janitor::tabyl, tibble::tibble, tsibble::tsibble. AMR package functions data set output (sir_df() bug_drug_combinations()), now return data type input. data sets package now tibble, instead base R data.frames. Older R versions still supported, even support tibbles. data sets now also continually exported Apache Feather Apache Parquet formats. can find info article website. Fixed certain EUCAST breakpoints MIC values Allow NA values (e.g. .sir(.disk(NA), ...)) Fix bug-drug combinations multiple breakpoints different body sites Interpretation MIC disk zones now informative availability breakpoints robust Removed .integer() method MIC values, since MIC integer values running table() MIC values consequently failed able retrieve level position (’s normally .integer() factors work) Fixed determination Gram stains (mo_gramstain()), since taxonomic phyla Actinobacteria, Chloroflexi, Firmicutes, Tenericutes renamed respectively Actinomycetota, Chloroflexota, Bacillota, Mycoplasmatota 2021 droplevels() MIC now return common factor default lose mic class. Use droplevels(..., .mic = TRUE) keep mic class. 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