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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="">2.1.1.9138</small>
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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@@ -90,7 +90,7 @@
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 31 January 2025.</p>
generated on 01 February 2025.</p>
<div class="section level2">
<h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
</h2>
@@ -146,21 +146,21 @@ make the structure of your data generally look like this:</p>
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2025-01-31</td>
<td align="center">2025-02-01</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">2025-01-31</td>
<td align="center">2025-02-01</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">2025-01-31</td>
<td align="center">2025-02-01</td>
<td align="center">efgh</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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@@ -79,7 +79,7 @@
<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">31 January 2025</h4>
<h4 data-toc-skip class="date">01 February 2025</h4>
<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>
articles/index.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="">2.1.1.9138</small>
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articles/welcome_to_AMR.html
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authors.html
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<a class="navbar-brand me-2" href="index.html">AMR (for R)</a>
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index.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="">2.1.1.9138</small>
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news/index.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="">2.1.1.9138</small>
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@@ -48,18 +48,18 @@
</div>
<div class="section level2">
<h2 class="pkg-version" data-toc-text="2.1.1.9138" id="amr-2119138">AMR 2.1.1.9138<a class="anchor" aria-label="anchor" href="#amr-2119138"></a></h2>
<h2 class="pkg-version" data-toc-text="2.1.1.9139" id="amr-2119139">AMR 2.1.1.9139<a class="anchor" aria-label="anchor" href="#amr-2119139"></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-2-1-1-9138">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-2-1-1-9138"></a></h5>
<h5 id="a-new-milestone-amr-v30-with-one-health-support--human--veterinary--environmental-2-1-1-9139">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-2-1-1-9139"></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’s Atlantic Veterinary College</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-2-1-1-9138">Breaking<a class="anchor" aria-label="anchor" href="#breaking-2-1-1-9138"></a></h3>
<h3 id="breaking-2-1-1-9139">Breaking<a class="anchor" aria-label="anchor" href="#breaking-2-1-1-9139"></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 two years ago</li>
</ul></div>
<div class="section level3">
<h3 id="new-2-1-1-9138">New<a class="anchor" aria-label="anchor" href="#new-2-1-1-9138"></a></h3>
<h3 id="new-2-1-1-9139">New<a class="anchor" aria-label="anchor" href="#new-2-1-1-9139"></a></h3>
<ul><li>
<strong>One Health implementation</strong>
<ul><li>Function <code><a href="../reference/as.sir.html">as.sir()</a></code> now has extensive support for veterinary 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>
@@ -109,7 +109,7 @@
</ul></li>
</ul></div>
<div class="section level3">
<h3 id="changed-2-1-1-9138">Changed<a class="anchor" aria-label="anchor" href="#changed-2-1-1-9138"></a></h3>
<h3 id="changed-2-1-1-9139">Changed<a class="anchor" aria-label="anchor" href="#changed-2-1-1-9139"></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>
@@ -173,7 +173,7 @@
<li>Added console colours support of <code>sir</code> class for Positron</li>
</ul></div>
<div class="section level3">
<h3 id="other-2-1-1-9138">Other<a class="anchor" aria-label="anchor" href="#other-2-1-1-9138"></a></h3>
<h3 id="other-2-1-1-9139">Other<a class="anchor" aria-label="anchor" href="#other-2-1-1-9139"></a></h3>
<ul><li>Added Dr. Larisse Bolton as contributor for her fantastic implementation of WISCA in a mathematically solid way</li>
<li>Added Matthew Saab, Dr. Jordan Stull, and Prof. Javier Sanchez as contributors for their tremendous input on veterinary breakpoints and interpretations</li>
<li>Greatly improved <code>vctrs</code> integration, a Tidyverse package working in the background for many Tidyverse functions. For users, this means that functions such as <code>dplyr</code>’s <code><a href="https://dplyr.tidyverse.org/reference/bind_rows.html" class="external-link">bind_rows()</a></code>, <code><a href="https://dplyr.tidyverse.org/reference/rowwise.html" class="external-link">rowwise()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/c_across.html" class="external-link">c_across()</a></code> are now supported for e.g. columns of class <code>mic</code>. Despite this, this <code>AMR</code> package is still zero-dependent on any other package, including <code>dplyr</code> and <code>vctrs</code>.</li>
@@ -181,7 +181,7 @@
<li>Stopped support for SAS (<code>.xpt</code>) files, since their file structure and extremely inefficient and requires more disk space than GitHub allows in a single commit.</li>
</ul></div>
<div class="section level3">
<h3 id="older-versions-2-1-1-9138">Older Versions<a class="anchor" aria-label="anchor" href="#older-versions-2-1-1-9138"></a></h3>
<h3 id="older-versions-2-1-1-9139">Older Versions<a class="anchor" aria-label="anchor" href="#older-versions-2-1-1-9139"></a></h3>
<p>This changelog only contains changes from AMR v3.0 (February 2025) and later.</p>
<ul><li>For prior v2 versions, please see <a href="https://github.com/msberends/AMR/blob/v2.1.1/NEWS.md" class="external-link">our v2 archive</a>.</li>
<li>For prior v1 versions, please see <a href="https://github.com/msberends/AMR/blob/v1.8.2/NEWS.md" class="external-link">our v1 archive</a>.</li>
pkgdown.yml
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resistance_predict: resistance_predict.html
welcome_to_AMR: welcome_to_AMR.html
WHONET: WHONET.html
last_built: 2025-01-31T22:11Z
last_built: 2025-02-01T10:14Z
urls:
reference: https://msberends.github.io/AMR/reference
article: https://msberends.github.io/AMR/articles
reference/AMR-deprecated.html
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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reference/AMR.html
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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reference/ab_from_text.html
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reference/ab_property.html
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reference/add_custom_antimicrobials.html
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@@ -7,7 +7,7 @@
<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="">2.1.1.9138</small>
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@@ -111,16 +111,16 @@
<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 59 59.15616 34</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2 1980-03-01 44 44.92055 19</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3 1949-11-01 75 75.24932 50</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 4 1947-02-14 77 77.96164 52</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 5 1940-02-19 84 84.94795 59</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 6 1988-01-10 37 37.05753 11</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 7 1997-08-27 27 27.43014 2</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 8 1978-01-26 47 47.01370 21</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 9 1972-06-17 52 52.62466 27</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 10 1986-08-10 38 38.47671 13</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1 1965-12-05 59 59.15890 34</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2 1980-03-01 44 44.92329 19</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3 1949-11-01 75 75.25205 50</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 4 1947-02-14 77 77.96438 52</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 5 1940-02-19 84 84.95068 59</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 6 1988-01-10 37 37.06027 11</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 7 1997-08-27 27 27.43288 2</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 8 1978-01-26 47 47.01644 21</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 9 1972-06-17 52 52.62740 27</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 10 1986-08-10 38 38.47945 13</span>
</code></pre></div>
</div>
</main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
reference/age_groups.html
+1 -1
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@@ -7,7 +7,7 @@
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reference/antibiogram.html
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@@ -9,7 +9,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
<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="">2.1.1.9138</small>
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reference/antibiotics.html
+1 -1
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@@ -7,7 +7,7 @@
<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="">2.1.1.9138</small>
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reference/antimicrobial_class_selectors.html
+1 -1
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@@ -17,7 +17,7 @@ my_data_with_all_these_columns %&amp;gt;%
<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="">2.1.1.9138</small>
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reference/as.ab.html
+1 -1
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@@ -7,7 +7,7 @@
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reference/as.av.html
+1 -1
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@@ -7,7 +7,7 @@
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reference/as.disk.html
+1 -1
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@@ -7,7 +7,7 @@
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reference/as.mic.html
+1 -1
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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reference/as.mo.html
+1 -1
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@@ -7,7 +7,7 @@
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<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9138</small>
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reference/as.sir.html
+11 -11
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@@ -21,7 +21,7 @@ All breakpoints used for interpretation are available in our clinical_breakpoint
<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="">2.1.1.9138</small>
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@@ -782,16 +782,16 @@ 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: 57 × 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> 2025-01-31 <span style="color: #949494;">22:12:00</span> 4 genta Escheri… cattle GEN <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 2025-01-31 <span style="color: #949494;">22:12:00</span> 3 tobra Escheri… horses TOB <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> 2025-01-31 <span style="color: #949494;">22:12:01</span> 2 nitrofu… E. coli human NIT <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 2025-01-31 <span style="color: #949494;">22:12:01</span> 2 nitrofu… E. coli human NIT <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 2025-01-31 <span style="color: #949494;">22:12:00</span> 1 tobra bacteria human TOB <span style="color: #949494;">B_</span>[KNG]<span style="color: #949494;">_</span>BACTERIA</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 2025-01-31 <span style="color: #949494;">22:12:00</span> 1 genta bacteria human GEN <span style="color: #949494;">B_</span>[KNG]<span style="color: #949494;">_</span>BACTERIA</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> 2025-01-31 <span style="color: #949494;">22:12:01</span> 1 nitrofu… E. coli human NIT <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> 2025-01-31 <span style="color: #949494;">22:12:01</span> 1 nitrofu… E. coli human NIT <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 2025-01-31 <span style="color: #949494;">22:12:01</span> 1 tobra E. coli human TOB <span style="color: #949494;">B_</span>[ORD]<span style="color: #949494;">_</span>ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 2025-01-31 <span style="color: #949494;">22:12:01</span> 1 genta E. coli human GEN <span style="color: #949494;">B_</span>[ORD]<span style="color: #949494;">_</span>ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 2025-02-01 <span style="color: #949494;">10:15:34</span> 4 AMX B_STRPT… human AMX <span style="color: #949494;">B_</span>STRPT<span style="color: #949494;">_</span>PNMN </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 2025-02-01 <span style="color: #949494;">10:15:41</span> 4 genta Escheri… human GEN <span style="color: #949494;">B_</span>[ORD]<span style="color: #949494;">_</span>ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> 2025-02-01 <span style="color: #949494;">10:15:41</span> 4 genta Escheri… human GEN <span style="color: #949494;">B_</span>[ORD]<span style="color: #949494;">_</span>ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 2025-02-01 <span style="color: #949494;">10:15:42</span> 4 genta Escheri… cattle GEN <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 2025-02-01 <span style="color: #949494;">10:15:42</span> 4 genta Escheri… cattle GEN <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 2025-02-01 <span style="color: #949494;">10:15:34</span> 3 AMX B_STRPT… human AMX <span style="color: #949494;">B_</span>STRPT<span style="color: #949494;">_</span>PNMN </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> 2025-02-01 <span style="color: #949494;">10:15:41</span> 3 tobra Escheri… human TOB <span style="color: #949494;">B_</span>[ORD]<span style="color: #949494;">_</span>ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> 2025-02-01 <span style="color: #949494;">10:15:41</span> 3 tobra Escheri… human TOB <span style="color: #949494;">B_</span>[ORD]<span style="color: #949494;">_</span>ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 2025-02-01 <span style="color: #949494;">10:15:42</span> 3 tobra Escheri… horses TOB <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 2025-02-01 <span style="color: #949494;">10:15:42</span> 3 tobra Escheri… horses TOB <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 47 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>
reference/atc_online.html
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@@ -7,7 +7,7 @@
<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="">2.1.1.9138</small>
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reference/av_from_text.html
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@@ -7,7 +7,7 @@
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reference/av_property.html
+1 -1
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@@ -7,7 +7,7 @@
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reference/availability.html
+1 -1
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@@ -7,7 +7,7 @@
<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="">2.1.1.9138</small>
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reference/bug_drug_combinations.html
+1 -1
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@@ -7,7 +7,7 @@
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reference/clinical_breakpoints.html
+1 -1
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@@ -21,7 +21,7 @@ Use as.sir() to transform MICs or disks measurements to SIR values."><meta prope
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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reference/count.html
+1 -1
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@@ -9,7 +9,7 @@ count_resistant() should be used to count resistant isolates, count_susceptible(
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reference/custom_eucast_rules.html
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@@ -7,7 +7,7 @@
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reference/dosage.html
+1 -1
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@@ -7,7 +7,7 @@
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reference/eucast_rules.html
+1 -1
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@@ -9,7 +9,7 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
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reference/example_isolates.html
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@@ -7,7 +7,7 @@
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[{"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\") #> ClLine truncated
[{"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\") #> ClLine truncated