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DESCRIPTION

@ -1,6 +1,6 @@
Package: AMR
Version: 0.7.1.9105
Date: 2019-10-12
Version: 0.7.1.9106
Date: 2019-10-13
Title: Antimicrobial Resistance Analysis
Authors@R: c(
person(role = c("aut", "cre"),

4
NEWS.md

@ -1,5 +1,5 @@
# AMR 0.7.1.9105
<small>Last updated: 12-Oct-2019</small>
# AMR 0.7.1.9106
<small>Last updated: 13-Oct-2019</small>
### Breaking
* Determination of first isolates now **excludes** all 'unknown' microorganisms at default, i.e. microbial code `"UNKNOWN"`. They can be included with the new parameter `include_unknown`:

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cran-comments.md

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* A NOTE for having a data directory over 3 MB. This is needed to offer users reference data for the complete taxonomy of microorganisms - one of the most important features of this pacakge. Has been this way since version 0.3.0.
* This package writes lines to `[user library]/AMR/mo_history/mo_history.csv` when using the `as.mo()` function, in the exact same way (and borrowed from) the `extrafont` package on CRAN (version 0.17) writes to their user library package folder. Users are notified about this with a `message()` and staged install on R >= 3.6.0 still works. The CSV file is never newly created or deleted by this package, it only changes this file to improve speed and reliability of the `as.mo()` function. See the source code of `set_mo_history()` and `clear_mo_history()`.
* This package writes lines to `[library path]/AMR/mo_history/mo_history.csv` when using the `as.mo()` function, in the exact same way (and borrowed from) the `extrafont` package on CRAN (version 0.17) writes to the user library path. Users are notified about this with a `message()`, and staged install on R >= 3.6.0 still works. The CSV file is never newly created or deleted by this package, it only changes this file to improve speed and reliability of the `as.mo()` function. See the source code of functions `set_mo_history()` and `clear_mo_history()` in file `R/mo_history.R`.

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docs/404.html

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</button>
<span class="navbar-brand">
<a class="navbar-link" href="https://msberends.gitlab.io/AMR/index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9105</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9106</span>
</span>
</div>

2
docs/LICENSE-text.html

@ -84,7 +84,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9105</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9106</span>
</span>
</div>

580
docs/articles/AMR.html

@ -41,7 +41,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9105</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0</span>
</span>
</div>
@ -187,7 +187,7 @@
<h1>How to conduct AMR analysis</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">12 October 2019</h4>
<h4 class="date">13 October 2019</h4>
<div class="hidden name"><code>AMR.Rmd</code></div>
@ -196,7 +196,7 @@
<p><strong>Note:</strong> values on this page will change with every website update since they are based on randomly created values and the page was written in <a href="https://rmarkdown.rstudio.com/">R Markdown</a>. However, the methodology remains unchanged. This page was generated on 12 October 2019.</p>
<p><strong>Note:</strong> values on this page will change with every website update since they are based on randomly created values and the page was written in <a href="https://rmarkdown.rstudio.com/">R Markdown</a>. However, the methodology remains unchanged. This page was generated on 13 October 2019.</p>
<div id="introduction" class="section level1">
<h1 class="hasAnchor">
<a href="#introduction" class="anchor"></a>Introduction</h1>
@ -212,21 +212,21 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2019-10-12</td>
<td align="center">2019-10-13</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">2019-10-12</td>
<td align="center">2019-10-13</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">2019-10-12</td>
<td align="center">2019-10-13</td>
<td align="center">efgh</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
@ -321,68 +321,68 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2017-03-23</td>
<td align="center">O1</td>
<td align="center">2011-07-28</td>
<td align="center">N6</td>
<td align="center">Hospital C</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2012-08-16</td>
<td align="center">Q6</td>
<td align="center">Hospital C</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="odd">
<td align="center">2017-05-07</td>
<td align="center">G5</td>
<td align="center">Hospital A</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2016-10-13</td>
<td align="center">G10</td>
<td align="center">Hospital D</td>
<td align="center">Escherichia coli</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="odd">
<td align="center">2017-11-09</td>
<td align="center">M7</td>
<td align="center">Hospital D</td>
<td align="center">Escherichia coli</td>
<td align="center">I</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="even">
<td align="center">2016-03-31</td>
<td align="center">P9</td>
<td align="center">Hospital D</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="odd">
<td align="center">2015-07-16</td>
<td align="center">U2</td>
<td align="center">Hospital B</td>
<td align="center">Streptococcus pneumoniae</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2014-10-22</td>
<td align="center">B8</td>
<td align="center">Hospital B</td>
<td align="center">Staphylococcus aureus</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">M</td>
</tr>
<tr class="even">
<td align="center">2015-10-29</td>
<td align="center">V10</td>
<td align="center">Hospital D</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="odd">
<td align="center">2013-08-21</td>
<td align="center">U1</td>
<td align="center">Hospital A</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2017-06-24</td>
<td align="center">K6</td>
<td align="center">Hospital A</td>
<td align="center">Staphylococcus aureus</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
@ -407,8 +407,8 @@
#
# Item Count Percent Cum. Count Cum. Percent
# --- ----- ------- -------- ----------- -------------
# 1 M 10,324 51.62% 10,324 51.62%
# 2 F 9,676 48.38% 20,000 100.00%</code></pre>
# 1 M 10,399 52.00% 10,399 52.00%
# 2 F 9,601 48.01% 20,000 100.00%</code></pre>
<p>So, we can draw at least two conclusions immediately. From a data scientists perspective, the data looks clean: only values <code>M</code> and <code>F</code>. From a researchers perspective: there are slightly more men. Nothing we didn’t already know.</p>
<p>The data is already quite clean, but we still need to transform some variables. The <code>bacteria</code> column now consists of text, and we want to add more variables based on microbial IDs later on. So, we will transform this column to valid IDs. The <code><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate()</a></code> function of the <code>dplyr</code> package makes this really easy:</p>
<div class="sourceCode" id="cb13"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb13-1" data-line-number="1">data &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span></a>
@ -438,14 +438,14 @@
<a class="sourceLine" id="cb15-18" data-line-number="18"><span class="co"># Pasteurella multocida (no changes)</span></a>
<a class="sourceLine" id="cb15-19" data-line-number="19"><span class="co"># Staphylococcus (no changes)</span></a>
<a class="sourceLine" id="cb15-20" data-line-number="20"><span class="co"># Streptococcus groups A, B, C, G (no changes)</span></a>
<a class="sourceLine" id="cb15-21" data-line-number="21"><span class="co"># Streptococcus pneumoniae (1,451 values changed)</span></a>
<a class="sourceLine" id="cb15-21" data-line-number="21"><span class="co"># Streptococcus pneumoniae (1,461 values changed)</span></a>
<a class="sourceLine" id="cb15-22" data-line-number="22"><span class="co"># Viridans group streptococci (no changes)</span></a>
<a class="sourceLine" id="cb15-23" data-line-number="23"><span class="co"># </span></a>
<a class="sourceLine" id="cb15-24" data-line-number="24"><span class="co"># EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes (v3.1, 2016)</span></a>
<a class="sourceLine" id="cb15-25" data-line-number="25"><span class="co"># Table 01: Intrinsic resistance in Enterobacteriaceae (1,325 values changed)</span></a>
<a class="sourceLine" id="cb15-25" data-line-number="25"><span class="co"># Table 01: Intrinsic resistance in Enterobacteriaceae (1,290 values changed)</span></a>
<a class="sourceLine" id="cb15-26" data-line-number="26"><span class="co"># Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria (no changes)</span></a>
<a class="sourceLine" id="cb15-27" data-line-number="27"><span class="co"># Table 03: Intrinsic resistance in other Gram-negative bacteria (no changes)</span></a>
<a class="sourceLine" id="cb15-28" data-line-number="28"><span class="co"># Table 04: Intrinsic resistance in Gram-positive bacteria (2,722 values changed)</span></a>
<a class="sourceLine" id="cb15-28" data-line-number="28"><span class="co"># Table 04: Intrinsic resistance in Gram-positive bacteria (2,724 values changed)</span></a>
<a class="sourceLine" id="cb15-29" data-line-number="29"><span class="co"># Table 08: Interpretive rules for B-lactam agents and Gram-positive cocci (no changes)</span></a>
<a class="sourceLine" id="cb15-30" data-line-number="30"><span class="co"># Table 09: Interpretive rules for B-lactam agents and Gram-negative rods (no changes)</span></a>
<a class="sourceLine" id="cb15-31" data-line-number="31"><span class="co"># Table 11: Interpretive rules for macrolides, lincosamides, and streptogramins (no changes)</span></a>
@ -453,24 +453,24 @@
<a class="sourceLine" id="cb15-33" data-line-number="33"><span class="co"># Table 13: Interpretive rules for quinolones (no changes)</span></a>
<a class="sourceLine" id="cb15-34" data-line-number="34"><span class="co"># </span></a>
<a class="sourceLine" id="cb15-35" data-line-number="35"><span class="co"># Other rules</span></a>
<a class="sourceLine" id="cb15-36" data-line-number="36"><span class="co"># Non-EUCAST: amoxicillin/clav acid = S where ampicillin = S (2,240 values changed)</span></a>
<a class="sourceLine" id="cb15-37" data-line-number="37"><span class="co"># Non-EUCAST: ampicillin = R where amoxicillin/clav acid = R (134 values changed)</span></a>
<a class="sourceLine" id="cb15-36" data-line-number="36"><span class="co"># Non-EUCAST: amoxicillin/clav acid = S where ampicillin = S (2,293 values changed)</span></a>
<a class="sourceLine" id="cb15-37" data-line-number="37"><span class="co"># Non-EUCAST: ampicillin = R where amoxicillin/clav acid = R (126 values changed)</span></a>
<a class="sourceLine" id="cb15-38" data-line-number="38"><span class="co"># Non-EUCAST: piperacillin = R where piperacillin/tazobactam = R (no changes)</span></a>
<a class="sourceLine" id="cb15-39" data-line-number="39"><span class="co"># Non-EUCAST: piperacillin/tazobactam = S where piperacillin = S (no changes)</span></a>
<a class="sourceLine" id="cb15-40" data-line-number="40"><span class="co"># Non-EUCAST: trimethoprim = R where trimethoprim/sulfa = R (no changes)</span></a>
<a class="sourceLine" id="cb15-41" data-line-number="41"><span class="co"># Non-EUCAST: trimethoprim/sulfa = S where trimethoprim = S (no changes)</span></a>
<a class="sourceLine" id="cb15-42" data-line-number="42"><span class="co"># </span></a>
<a class="sourceLine" id="cb15-43" data-line-number="43"><span class="co"># --------------------------------------------------------------------------</span></a>
<a class="sourceLine" id="cb15-44" data-line-number="44"><span class="co"># EUCAST rules affected 6,530 out of 20,000 rows, making a total of 7,872 edits</span></a>
<a class="sourceLine" id="cb15-44" data-line-number="44"><span class="co"># EUCAST rules affected 6,534 out of 20,000 rows, making a total of 7,894 edits</span></a>
<a class="sourceLine" id="cb15-45" data-line-number="45"><span class="co"># =&gt; added 0 test results</span></a>
<a class="sourceLine" id="cb15-46" data-line-number="46"><span class="co"># </span></a>
<a class="sourceLine" id="cb15-47" data-line-number="47"><span class="co"># =&gt; changed 7,872 test results</span></a>
<a class="sourceLine" id="cb15-48" data-line-number="48"><span class="co"># - 104 test results changed from S to I</span></a>
<a class="sourceLine" id="cb15-49" data-line-number="49"><span class="co"># - 4,728 test results changed from S to R</span></a>
<a class="sourceLine" id="cb15-50" data-line-number="50"><span class="co"># - 1,044 test results changed from I to S</span></a>
<a class="sourceLine" id="cb15-51" data-line-number="51"><span class="co"># - 344 test results changed from I to R</span></a>
<a class="sourceLine" id="cb15-52" data-line-number="52"><span class="co"># - 1,620 test results changed from R to S</span></a>
<a class="sourceLine" id="cb15-53" data-line-number="53"><span class="co"># - 32 test results changed from R to I</span></a>
<a class="sourceLine" id="cb15-47" data-line-number="47"><span class="co"># =&gt; changed 7,894 test results</span></a>
<a class="sourceLine" id="cb15-48" data-line-number="48"><span class="co"># - 126 test results changed from S to I</span></a>
<a class="sourceLine" id="cb15-49" data-line-number="49"><span class="co"># - 4,707 test results changed from S to R</span></a>
<a class="sourceLine" id="cb15-50" data-line-number="50"><span class="co"># - 1,073 test results changed from I to S</span></a>
<a class="sourceLine" id="cb15-51" data-line-number="51"><span class="co"># - 317 test results changed from I to R</span></a>
<a class="sourceLine" id="cb15-52" data-line-number="52"><span class="co"># - 1,653 test results changed from R to S</span></a>
<a class="sourceLine" id="cb15-53" data-line-number="53"><span class="co"># - 18 test results changed from R to I</span></a>
<a class="sourceLine" id="cb15-54" data-line-number="54"><span class="co"># --------------------------------------------------------------------------</span></a>
<a class="sourceLine" id="cb15-55" data-line-number="55"><span class="co"># </span></a>
<a class="sourceLine" id="cb15-56" data-line-number="56"><span class="co"># Use eucast_rules(..., verbose = TRUE) (on your original data) to get a data.frame with all specified edits instead.</span></a></code></pre></div>
@ -498,7 +498,7 @@
<a class="sourceLine" id="cb17-3" data-line-number="3"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `bacteria` as input for `col_mo`.</span></a>
<a class="sourceLine" id="cb17-4" data-line-number="4"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `date` as input for `col_date`.</span></a>
<a class="sourceLine" id="cb17-5" data-line-number="5"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `patient_id` as input for `col_patient_id`.</span></a>
<a class="sourceLine" id="cb17-6" data-line-number="6"><span class="co"># =&gt; Found 5,669 first isolates (28.3% of total)</span></a></code></pre></div>
<a class="sourceLine" id="cb17-6" data-line-number="6"><span class="co"># =&gt; Found 5,663 first isolates (28.3% of total)</span></a></code></pre></div>
<p>So only 28.3% is suitable for resistance analysis! We can now filter on it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html">filter()</a></code> function, also from the <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb18"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb18-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb18-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(first <span class="op">==</span><span class="st"> </span><span class="ot">TRUE</span>)</a></code></pre></div>
@ -509,7 +509,7 @@
<div id="first-weighted-isolates" class="section level2">
<h2 class="hasAnchor">
<a href="#first-weighted-isolates" class="anchor"></a>First <em>weighted</em> isolates</h2>
<p>We made a slight twist to the CLSI algorithm, to take into account the antimicrobial susceptibility profile. Have a look at all isolates of patient H5, sorted on date:</p>
<p>We made a slight twist to the CLSI algorithm, to take into account the antimicrobial susceptibility profile. Have a look at all isolates of patient X9, sorted on date:</p>
<table class="table">
<thead><tr class="header">
<th align="center">isolate</th>
@ -525,10 +525,10 @@
<tbody>
<tr class="odd">
<td align="center">1</td>
<td align="center">2010-04-02</td>
<td align="center">H5</td>
<td align="center">2010-01-31</td>
<td align="center">X9</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
@ -536,10 +536,10 @@
</tr>
<tr class="even">
<td align="center">2</td>
<td align="center">2010-05-11</td>
<td align="center">H5</td>
<td align="center">2010-04-03</td>
<td align="center">X9</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
@ -547,21 +547,21 @@
</tr>
<tr class="odd">
<td align="center">3</td>
<td align="center">2010-08-11</td>
<td align="center">H5</td>
<td align="center">2010-05-12</td>
<td align="center">X9</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">4</td>
<td align="center">2010-08-26</td>
<td align="center">H5</td>
<td align="center">2010-08-29</td>
<td align="center">X9</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
@ -569,10 +569,10 @@
</tr>
<tr class="odd">
<td align="center">5</td>
<td align="center">2010-11-17</td>
<td align="center">H5</td>
<td align="center">2011-01-07</td>
<td align="center">X9</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
@ -580,30 +580,8 @@
</tr>
<tr class="even">
<td align="center">6</td>
<td align="center">2010-12-20</td>
<td align="center">H5</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="odd">
<td align="center">7</td>
<td align="center">2011-03-21</td>
<td align="center">H5</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">8</td>
<td align="center">2011-04-16</td>
<td align="center">H5</td>
<td align="center">2011-04-20</td>
<td align="center">X9</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -612,24 +590,46 @@
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">9</td>
<td align="center">2011-07-03</td>
<td align="center">H5</td>
<td align="center">7</td>
<td align="center">2011-06-24</td>
<td align="center">X9</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">8</td>
<td align="center">2011-07-10</td>
<td align="center">X9</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-07-07</td>
<td align="center">H5</td>
<tr class="odd">
<td align="center">9</td>
<td align="center">2011-11-07</td>
<td align="center">X9</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-12-20</td>
<td align="center">X9</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
@ -646,7 +646,7 @@
<a class="sourceLine" id="cb20-7" data-line-number="7"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `patient_id` as input for `col_patient_id`.</span></a>
<a class="sourceLine" id="cb20-8" data-line-number="8"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `keyab` as input for `col_keyantibiotics`. Use col_keyantibiotics = FALSE to prevent this.</span></a>
<a class="sourceLine" id="cb20-9" data-line-number="9"><span class="co"># [Criterion] Inclusion based on key antibiotics, ignoring I</span></a>
<a class="sourceLine" id="cb20-10" data-line-number="10"><span class="co"># =&gt; Found 15,117 first weighted isolates (75.6% of total)</span></a></code></pre></div>
<a class="sourceLine" id="cb20-10" data-line-number="10"><span class="co"># =&gt; Found 15,141 first weighted isolates (75.7% of total)</span></a></code></pre></div>
<table class="table">
<thead><tr class="header">
<th align="center">isolate</th>
@ -663,10 +663,10 @@
<tbody>
<tr class="odd">
<td align="center">1</td>
<td align="center">2010-04-02</td>
<td align="center">H5</td>
<td align="center">2010-01-31</td>
<td align="center">X9</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
@ -675,10 +675,10 @@
</tr>
<tr class="even">
<td align="center">2</td>
<td align="center">2010-05-11</td>
<td align="center">H5</td>
<td align="center">2010-04-03</td>
<td align="center">X9</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
@ -687,22 +687,22 @@
</tr>
<tr class="odd">
<td align="center">3</td>
<td align="center">2010-08-11</td>
<td align="center">H5</td>
<td align="center">2010-05-12</td>
<td align="center">X9</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">4</td>
<td align="center">2010-08-26</td>
<td align="center">H5</td>
<td align="center">2010-08-29</td>
<td align="center">X9</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
@ -711,10 +711,10 @@
</tr>
<tr class="odd">
<td align="center">5</td>
<td align="center">2010-11-17</td>
<td align="center">H5</td>
<td align="center">2011-01-07</td>
<td align="center">X9</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
@ -723,44 +723,56 @@
</tr>
<tr class="even">
<td align="center">6</td>
<td align="center">2010-12-20</td>
<td align="center">H5</td>
<td align="center">2011-04-20</td>
<td align="center">X9</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">7</td>
<td align="center">2011-03-21</td>
<td align="center">H5</td>
<td align="center">2011-06-24</td>
<td align="center">X9</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">8</td>
<td align="center">2011-04-16</td>
<td align="center">H5</td>
<td align="center">2011-07-10</td>
<td align="center">X9</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">TRUE</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">9</td>
<td align="center">2011-07-03</td>
<td align="center">H5</td>
<td align="center">2011-11-07</td>
<td align="center">X9</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-12-20</td>
<td align="center">X9</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
@ -769,25 +781,13 @@
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-07-07</td>
<td align="center">H5</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
</tbody>
</table>
<p>Instead of 2, now 8 isolates are flagged. In total, 75.6% of all isolates are marked ‘first weighted’ - 47.2% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.</p>
<p>Instead of 2, now 8 isolates are flagged. In total, 75.7% of all isolates are marked ‘first weighted’ - 47.4% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.</p>
<p>As with <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code>, there’s a shortcut for this new algorithm too:</p>
<div class="sourceCode" id="cb21"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb21-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb21-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/first_isolate.html">filter_first_weighted_isolate</a></span>()</a></code></pre></div>
<p>So we end up with 15,117 isolates for analysis.</p>
<p>So we end up with 15,141 isolates for analysis.</p>
<p>We can remove unneeded columns:</p>
<div class="sourceCode" id="cb22"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb22-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data_1st <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb22-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="op">-</span><span class="kw"><a href="https://rdrr.io/r/base/c.html">c</a></span>(first, keyab))</a></code></pre></div>
@ -811,88 +811,88 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2017-03-23</td>
<td align="center">O1</td>
<td align="center">2011-07-28</td>
<td align="center">N6</td>
<td align="center">Hospital C</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">2012-08-16</td>
<td align="center">Q6</td>
<td align="center">Hospital C</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">2017-05-07</td>
<td align="center">G5</td>
<td align="center">Hospital A</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">2016-10-13</td>
<td align="center">G10</td>
<td align="center">Hospital D</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">2017-11-09</td>
<td align="center">M7</td>
<td align="center">Hospital D</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">2016-03-31</td>
<td align="center">P9</td>
<td align="center">Hospital D</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">2015-07-16</td>
<td align="center">U2</td>
<td align="center">Hospital B</td>
<td align="center">B_STRPT_PNMN</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">F</td>
<td align="center">Gram-positive</td>
<td align="center">Streptococcus</td>
<td align="center">pneumoniae</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">2014-10-22</td>
<td align="center">B8</td>
<td align="center">Hospital B</td>
<td align="center">B_STPHY_AURS</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">M</td>
<td align="center">Gram-positive</td>
<td align="center">Staphylococcus</td>
<td align="center">aureus</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">2015-10-29</td>
<td align="center">V10</td>
<td align="center">Hospital D</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">2013-08-21</td>
<td align="center">U1</td>
<td align="center">Hospital A</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">2017-06-24</td>
<td align="center">K6</td>
<td align="center">Hospital A</td>
<td align="center">B_STPHY_AURS</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
<td align="center">Gram-positive</td>
@ -919,7 +919,7 @@
<div class="sourceCode" id="cb25"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb25-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/clean/man/freq.html">freq</a></span>(genus, species)</a></code></pre></div>
<p><strong>Frequency table</strong></p>
<p>Class: character<br>
Length: 15,117 (of which NA: 0 = 0%)<br>
Length: 15,141 (of which NA: 0 = 0%)<br>
Unique: 4</p>
<p>Shortest: 16<br>
Longest: 24</p>
@ -936,33 +936,33 @@ Longest: 24</p>
<tr class="odd">
<td align="left">1</td>
<td align="left">Escherichia coli</td>
<td align="right">7,403</td>
<td align="right">48.97%</td>
<td align="right">7,403</td>
<td align="right">48.97%</td>
<td align="right">7,470</td>
<td align="right">49.34%</td>
<td align="right">7,470</td>
<td align="right">49.34%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">Staphylococcus aureus</td>
<td align="right">3,757</td>
<td align="right">24.85%</td>
<td align="right">11,160</td>
<td align="right">73.82%</td>
<td align="right">3,803</td>
<td align="right">25.12%</td>
<td align="right">11,273</td>
<td align="right">74.45%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">Streptococcus pneumoniae</td>
<td align="right">2,307</td>
<td align="right">15.26%</td>
<td align="right">13,467</td>
<td align="right">89.09%</td>
<td align="right">2,290</td>
<td align="right">15.12%</td>
<td align="right">13,563</td>
<td align="right">89.58%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">Klebsiella pneumoniae</td>
<td align="right">1,650</td>
<td align="right">10.91%</td>
<td align="right">15,117</td>
<td align="right">1,578</td>
<td align="right">10.42%</td>
<td align="right">15,141</td>
<td align="right">100.00%</td>
</tr>
</tbody>
@ -973,7 +973,7 @@ Longest: 24</p>
<a href="#resistance-percentages" class="anchor"></a>Resistance percentages</h2>
<p>The functions <code><a href="../reference/portion.html">portion_S()</a></code>, <code><a href="../reference/portion.html">portion_SI()</a></code>, <code><a href="../reference/portion.html">portion_I()</a></code>, <code><a href="../reference/portion.html">portion_IR()</a></code> and <code><a href="../reference/portion.html">portion_R()</a></code> can be used to determine the portion of a specific antimicrobial outcome. As per the EUCAST guideline of 2019, we calculate resistance as the portion of R (<code><a href="../reference/portion.html">portion_R()</a></code>) and susceptibility as the portion of S and I (<code><a href="../reference/portion.html">portion_SI()</a></code>). These functions can be used on their own:</p>
<div class="sourceCode" id="cb26"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb26-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/portion.html">portion_R</a></span>(AMX)</a>
<a class="sourceLine" id="cb26-2" data-line-number="2"><span class="co"># [1] 0.470133</span></a></code></pre></div>
<a class="sourceLine" id="cb26-2" data-line-number="2"><span class="co"># [1] 0.4656231</span></a></code></pre></div>
<p>Or can be used in conjuction with <code><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/summarise.html">summarise()</a></code>, both from the <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb27"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb27-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb27-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital) <span class="op">%&gt;%</span><span class="st"> </span></a>
@ -986,19 +986,19 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Hospital A</td>
<td align="center">0.4604743</td>
<td align="center">0.4748959</td>
</tr>
<tr class="even">
<td align="center">Hospital B</td>
<td align="center">0.4653298</td>
<td align="center">0.4543224</td>
</tr>
<tr class="odd">
<td align="center">Hospital C</td>
<td align="center">0.4791855</td>
<td align="center">0.4659041</td>
</tr>
<tr class="even">
<td align="center">Hospital D</td>
<td align="center">0.4865761</td>
<td align="center">0.4712529</td>
</tr>
</tbody>
</table>
@ -1016,23 +1016,23 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Hospital A</td>
<td align="center">0.4604743</td>
<td align="center">4554</td>
<td align="center">0.4748959</td>
<td align="center">4561</td>
</tr>
<tr class="even">
<td align="center">Hospital B</td>
<td align="center">0.4653298</td>
<td align="center">5336</td>
<td align="center">0.4543224</td>
<td align="center">5298</td>
</tr>
<tr class="odd">
<td align="center">Hospital C</td>
<td align="center">0.4791855</td>
<td align="center">2210</td>
<td align="center">0.4659041</td>
<td align="center">2273</td>
</tr>
<tr class="even">
<td align="center">Hospital D</td>
<td align="center">0.4865761</td>
<td align="center">3017</td>
<td align="center">0.4712529</td>
<td align="center">3009</td>
</tr>
</tbody>
</table>
@ -1052,27 +1052,27 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Escherichia</td>
<td align="center">0.9227340</td>
<td align="center">0.8974740</td>
<td align="center">0.9940565</td>
<td align="center">0.9285141</td>
<td align="center">0.8966533</td>
<td align="center">0.9929050</td>
</tr>
<tr class="even">
<td align="center">Klebsiella</td>
<td align="center">0.8127273</td>
<td align="center">0.9024242</td>
<td align="center">0.9872727</td>
<td align="center">0.8225602</td>
<td align="center">0.9017744</td>
<td align="center">0.9866920</td>
</tr>
<tr class="odd">
<td align="center">Staphylococcus</td>
<td align="center">0.9291988</td>
<td align="center">0.9124301</td>
<td align="center">0.9933458</td>
<td align="center">0.9250592</td>
<td align="center">0.9261110</td>
<td align="center">0.9968446</td>
</tr>
<tr class="even">
<td align="center">Streptococcus</td>
<td align="center">0.6146511</td>
<td align="center">0.6200873</td>
<td align="center">0.0000000</td>
<td align="center">0.6146511</td>
<td align="center">0.6200873</td>
</tr>
</tbody>
</table>

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19
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<h1>How to apply EUCAST rules</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">13 August 2019</h4>
<h4 class="date">13 October 2019</h4>
<div class="hidden name"><code>EUCAST.Rmd</code></div>
@ -217,6 +219,7 @@
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@ -1,247 +0,0 @@
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<h1>How to use the <em>G</em>-test</h1>
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@ -187,7 +187,7 @@
<h1>How to determine multi-drug resistance (MDR)</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">30 September 2019</h4>
<h4 class="date">13 October 2019</h4>
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@ -230,18 +230,18 @@
<p>The data set looks like this now:</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" data-line-number="1"><span class="kw"><a href="https://rdrr.io/r/utils/head.html">head</a></span>(my_TB_data)</a>
<a class="sourceLine" id="cb3-2" data-line-number="2"><span class="co"># rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin</span></a>
<a class="sourceLine" id="cb3-3" data-line-number="3"><span class="co"># 1 R S R R S R</span></a>
<a class="sourceLine" id="cb3-4" data-line-number="4"><span class="co"># 2 I R S R R R</span></a>
<a class="sourceLine" id="cb3-5" data-line-number="5"><span class="co"># 3 R R R S R R</span></a>
<a class="sourceLine" id="cb3-6" data-line-number="6"><span class="co"># 4 R S I I R S</span></a>
<a class="sourceLine" id="cb3-7" data-line-number="7"><span class="co"># 5 S S I I R S</span></a>
<a class="sourceLine" id="cb3-8" data-line-number="8"><span class="co"># 6 S S S R S S</span></a>
<a class="sourceLine" id="cb3-3" data-line-number="3"><span class="co"># 1 R S S I S S</span></a>
<a class="sourceLine" id="cb3-4" data-line-number="4"><span class="co"># 2 I R S R S R</span></a>
<a class="sourceLine" id="cb3-5" data-line-number="5"><span class="co"># 3 S S R R R R</span></a>
<a class="sourceLine" id="cb3-6" data-line-number="6"><span class="co"># 4 S R R S S S</span></a>
<a class="sourceLine" id="cb3-7" data-line-number="7"><span class="co"># 5 S R R S R R</span></a>
<a class="sourceLine" id="cb3-8" data-line-number="8"><span class="co"># 6 R S S R R S</span></a>
<a class="sourceLine" id="cb3-9" data-line-number="9"><span class="co"># kanamycin</span></a>
<a class="sourceLine" id="cb3-10" data-line-number="10"><span class="co"># 1 R</span></a>
<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># 2 S</span></a>
<a class="sourceLine" id="cb3-12" data-line-number="12"><span class="co"># 3 S</span></a>
<a class="sourceLine" id="cb3-13" data-line-number="13"><span class="co"># 4 R</span></a>
<a class="sourceLine" id="cb3-14" data-line-number="14"><span class="co"># 5 R</span></a>
<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># 2 R</span></a>
<a class="sourceLine" id="cb3-12" data-line-number="12"><span class="co"># 3 I</span></a>
<a class="sourceLine" id="cb3-13" data-line-number="13"><span class="co"># 4 S</span></a>
<a class="sourceLine" id="cb3-14" data-line-number="14"><span class="co"># 5 S</span></a>
<a class="sourceLine" id="cb3-15" data-line-number="15"><span class="co"># 6 S</span></a></code></pre></div>
<p>We can now add the interpretation of MDR-TB to our data set:</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" data-line-number="1">my_TB_data<span class="op">$</span>mdr &lt;-<span class="st"> </span><span class="kw"><a href="../reference/mdro.html">mdr_tb</a></span>(my_TB_data)</a>
@ -251,7 +251,8 @@
<a class="sourceLine" id="cb4-5" data-line-number="5"><span class="co"># Version: WHO/HTM/TB/2014.11</span></a>
<a class="sourceLine" id="cb4-6" data-line-number="6"><span class="co"># Author: WHO (World Health Organization)</span></a>
<a class="sourceLine" id="cb4-7" data-line-number="7"><span class="co"># Source: https://www.who.int/tb/publications/pmdt_companionhandbook/en/</span></a>
<a class="sourceLine" id="cb4-8" data-line-number="8"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Reliability might be improved if these antimicrobial results would be available too: CAP (capreomycin), RIB (rifabutin), RFP (rifapentine)</span></a></code></pre></div>
<a class="sourceLine" id="cb4-8" data-line-number="8"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Auto-guessing columns suitable for analysis...</span></a>
<a class="sourceLine" id="cb4-9" data-line-number="9"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Reliability might be improved if these antimicrobial results would be available too: CAP (capreomycin), RIB (rifabutin), RFP (rifapentine)</span></a></code></pre></div>
<p>We also created a package dedicated to data cleaning and checking, called the <code>clean</code> package. It gets automatically installed with the <code>AMR</code> package, so we only have to load it:</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" data-line-number="1"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span>(clean)</a></code></pre></div>
<p>It contains the <code><a href="https://rdrr.io/pkg/clean/man/freq.html">freq()</a></code> function, to create a frequency table:</p>
@ -274,40 +275,40 @@ Unique: 5</p>
<tr class="odd">
<td align="left">1</td>
<td align="left">Mono-resistant</td>
<td align="right">3250</td>
<td align="right">65.00%</td>
<td align="right">3250</td>
<td align="right">65.00%</td>
<td align="right">3246</td>
<td align="right">64.92%</td>
<td align="right">3246</td>
<td align="right">64.92%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">Negative</td>
<td align="right">634</td>
<td align="right">12.68%</td>
<td align="right">3884</td>
<td align="right">77.68%</td>
<td align="right">681</td>
<td align="right">13.62%</td>
<td align="right">3927</td>
<td align="right">78.54%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">Multi-drug-resistant</td>
<td align="right">623</td>
<td align="right">12.46%</td>
<td align="right">4507</td>
<td align="right">90.14%</td>
<td align="right">593</td>
<td align="right">11.86%</td>
<td align="right">4520</td>
<td align="right">90.40%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">Poly-resistant</td>
<td align="right">282</td>
<td align="right">5.64%</td>
<td align="right">4789</td>
<td align="right">95.78%</td>
<td align="right">276</td>
<td align="right">5.52%</td>
<td align="right">4796</td>
<td align="right">95.92%</td>
</tr>
<tr class="odd">
<td align="left">5</td>
<td align="left">Extensive drug-resistant</td>
<td align="right">211</td>
<td align="right">4.22%</td>
<td align="right">204</td>
<td align="right">4.08%</td>
<td align="right">5000</td>
<td align="right">100.00%</td>
</tr>

389
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@ -1,389 +0,0 @@
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<h1>How to predict antimicrobial resistance</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">09 February 2019</h4>
<div class="hidden name"><code>Predict.Rmd</code></div>
</div>
<div id="needed-r-packages" class="section level2">
<h2 class="hasAnchor">
<a href="#needed-r-packages" class="anchor"></a>Needed R packages</h2>
<p>As with many uses in R, we need some additional packages for AMR analysis. Our package works closely together with the <a href="https://www.tidyverse.org">tidyverse packages</a> <a href="https://dplyr.tidyverse.org/"><code>dplyr</code></a> and <a href="https://ggplot2.tidyverse.org"><code>ggplot2</code></a> by <a href="https://www.linkedin.com/in/hadleywickham/">Dr Hadley Wickham</a>. The tidyverse tremendously improves the way we conduct data science - it allows for a very natural way of writing syntaxes and creating beautiful plots in R.</p>
<p>Our <code>AMR</code> package depends on these packages and even extends their use and functions.</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(dplyr)</a>
<a class="sourceLine" id="cb1-2" data-line-number="2"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(ggplot2)</a>
<a class="sourceLine" id="cb1-3" data-line-number="3"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(AMR)</a>
<a class="sourceLine" id="cb1-4" data-line-number="4"></a>
<a class="sourceLine" id="cb1-5" data-line-number="5"><span class="co"># (if not yet installed, install with:)</span></a>
<a class="sourceLine" id="cb1-6" data-line-number="6"><span class="co"># install.packages(c("tidyverse", "AMR"))</span></a></code></pre></div>
</div>
<div id="prediction-analysis" class="section level2">
<h2 class="hasAnchor">
<a href="#prediction-analysis" class="anchor"></a>Prediction analysis</h2>
<p>Our package contains a function <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>, which takes the same input as functions for <a href="./articles/AMR.html">other AMR analysis</a>. Based on a date column, it calculates cases per year and uses a regression model to predict antimicrobial resistance.</p>
<p>It is basically as easy as:</p>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb2-1" data-line-number="1"><span class="co"># resistance prediction of piperacillin/tazobactam (pita):</span></a>
<a class="sourceLine" id="cb2-2" data-line-number="2"><span class="kw"><a href="../reference/resistance_predict.html">resistance_predict</a></span>(<span class="dt">tbl =</span> septic_patients, <span class="dt">col_date =</span> <span class="st">"date"</span>, <span class="dt">col_ab =</span> <span class="st">"pita"</span>)</a>
<a class="sourceLine" id="cb2-3" data-line-number="3"></a>
<a class="sourceLine" id="cb2-4" data-line-number="4"><span class="co"># or:</span></a>
<a class="sourceLine" id="cb2-5" data-line-number="5">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb2-6" data-line-number="6"><span class="st"> </span><span class="kw"><a href="../reference/resistance_predict.html">resistance_predict</a></span>(<span class="dt">col_ab =</span> <span class="st">"pita"</span>)</a>
<a class="sourceLine" id="cb2-7" data-line-number="7"></a>
<a class="sourceLine" id="cb2-8" data-line-number="8"><span class="co"># to bind it to object 'predict_pita' for example:</span></a>
<a class="sourceLine" id="cb2-9" data-line-number="9">predict_pita &lt;-<span class="st"> </span>septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb2-10" data-line-number="10"><span class="st"> </span><span class="kw"><a href="../reference/resistance_predict.html">resistance_predict</a></span>(<span class="dt">col_ab =</span> <span class="st">"pita"</span>)</a></code></pre></div>
<pre><code># NOTE: Using column `date` as input for `col_date`.
#
# Logistic regression model (logit) with binomial distribution
# ------------------------------------------------------------
#
# Call:
# glm(formula = df_matrix ~ year, family = binomial)
#
# Deviance Residuals:
# Min 1Q Median 3Q Max
# -2.9224 -1.3120 0.0170 0.7586 3.1932
#
# Coefficients:
# Estimate Std. Error z value Pr(&gt;|z|)
# (Intercept) -222.92857 45.93922 -4.853 1.22e-06 ***
# year 0.10994 0.02284 4.814 1.48e-06 ***
# ---
# Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#
# (Dispersion parameter for binomial family taken to be 1)
#
# Null deviance: 59.794 on 14 degrees of freedom
# Residual deviance: 35.191 on 13 degrees of freedom
# AIC: 93.464
#
# Number of Fisher Scoring iterations: 4</code></pre>
<p>The function will look for a data column itself if <code>col_date</code> is not set. The result is nothing more than a <code>data.frame</code>, containing the years, number of observations, actual observed resistance, the estimated resistance and the standard error below and above the estimation:</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" data-line-number="1">predict_pita</a>
<a class="sourceLine" id="cb4-2" data-line-number="2"><span class="co"># year value se_min se_max observations observed estimated</span></a>
<a class="sourceLine" id="cb4-3" data-line-number="3"><span class="co"># 1 2003 0.06250000 NA NA 32 0.06250000 0.06177594</span></a>
<a class="sourceLine" id="cb4-4" data-line-number="4"><span class="co"># 2 2004 0.08536585 NA NA 82 0.08536585 0.06846343</span></a>
<a class="sourceLine" id="cb4-5" data-line-number="5"><span class="co"># 3 2005 0.10000000 NA NA 60 0.10000000 0.07581637</span></a>
<a class="sourceLine" id="cb4-6" data-line-number="6"><span class="co"># 4 2006 0.05084746 NA NA 59 0.05084746 0.08388789</span></a>
<a class="sourceLine" id="cb4-7" data-line-number="7"><span class="co"># 5 2007 0.12121212 NA NA 66 0.12121212 0.09273250</span></a>
<a class="sourceLine" id="cb4-8" data-line-number="8"><span class="co"># 6 2008 0.04166667 NA NA 72 0.04166667 0.10240539</span></a>
<a class="sourceLine" id="cb4-9" data-line-number="9"><span class="co"># 7 2009 0.01639344 NA NA 61 0.01639344 0.11296163</span></a>
<a class="sourceLine" id="cb4-10" data-line-number="10"><span class="co"># 8 2010 0.09433962 NA NA 53 0.09433962 0.12445516</span></a>
<a class="sourceLine" id="cb4-11" data-line-number="11"><span class="co"># 9 2011 0.18279570 NA NA 93 0.18279570 0.13693759</span></a>
<a class="sourceLine" id="cb4-12" data-line-number="12"><span class="co"># 10 2012 0.30769231 NA NA 65 0.30769231 0.15045682</span></a>
<a class="sourceLine" id="cb4-13" data-line-number="13"><span class="co"># 11 2013 0.08620690 NA NA 58 0.08620690 0.16505550</span></a>
<a class="sourceLine" id="cb4-14" data-line-number="14"><span class="co"># 12 2014 0.15254237 NA NA 59 0.15254237 0.18076926</span></a>
<a class="sourceLine" id="cb4-15" data-line-number="15"><span class="co"># 13 2015 0.27272727 NA NA 55 0.27272727 0.19762493</span></a>
<a class="sourceLine" id="cb4-16" data-line-number="16"><span class="co"># 14 2016 0.25000000 NA NA 84 0.25000000 0.21563859</span></a>
<a class="sourceLine" id="cb4-17" data-line-number="17"><span class="co"># 15 2017 0.16279070 NA NA 86 0.16279070 0.23481370</span></a>
<a class="sourceLine" id="cb4-18" data-line-number="18"><span class="co"># 16 2018 0.25513926 0.2228376 0.2874409 NA NA 0.25513926</span></a>
<a class="sourceLine" id="cb4-19" data-line-number="19"><span class="co"># 17 2019 0.27658825 0.2386811 0.3144954 NA NA 0.27658825</span></a>
<a class="sourceLine" id="cb4-20" data-line-number="20"><span class="co"># 18 2020 0.29911630 0.2551715 0.3430611 NA NA 0.29911630</span></a>
<a class="sourceLine" id="cb4-21" data-line-number="21"><span class="co"># 19 2021 0.32266085 0.2723340 0.3729877 NA NA 0.32266085</span></a>
<a class="sourceLine" id="cb4-22" data-line-number="22"><span class="co"># 20 2022 0.34714076 0.2901847 0.4040968 NA NA 0.34714076</span></a>
<a class="sourceLine" id="cb4-23" data-line-number="23"><span class="co"># 21 2023 0.37245666 0.3087318 0.4361815 NA NA 0.37245666</span></a>
<a class="sourceLine" id="cb4-24" data-line-number="24"><span class="co"># 22 2024 0.39849187 0.3279750 0.4690088 NA NA 0.39849187</span></a>
<a class="sourceLine" id="cb4-25" data-line-number="25"><span class="co"># 23 2025 0.42511415 0.3479042 0.5023241 NA NA 0.42511415</span></a>
<a class="sourceLine" id="cb4-26" data-line-number="26"><span class="co"># 24 2026 0.45217796 0.3684992 0.5358568 NA NA 0.45217796</span></a>
<a class="sourceLine" id="cb4-27" data-line-number="27"><span class="co"># 25 2027 0.47952757 0.3897276 0.5693275 NA NA 0.47952757</span></a>
<a class="sourceLine" id="cb4-28" data-line-number="28"><span class="co"># 26 2028 0.50700045 0.4115444 0.6024565 NA NA 0.50700045</span></a>
<a class="sourceLine" id="cb4-29" data-line-number="29"><span class="co"># 27 2029 0.53443111 0.4338908 0.6349714 NA NA 0.53443111</span></a></code></pre></div>
<p>The function <code>plot</code> is available in base R, and can be extended by other packages to depend the output based on the type of input. We extended its function to cope with resistance predictions:</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/graphics/topics/plot">plot</a></span>(predict_pita)</a></code></pre></div>
<p><img src="Predict_files/figure-html/unnamed-chunk-4-1.png" width="720"></p>
<p>We also support the <code>ggplot2</code> package with the function <code><a href="../reference/resistance_predict.html">ggplot_rsi_predict()</a></code>:</p>
<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb6-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(ggplot2)</a>
<a class="sourceLine" id="cb6-2" data-line-number="2"><span class="kw"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span>(predict_pita)</a>
<a class="sourceLine" id="cb6-3" data-line-number="3"><span class="co"># Warning: Removed 15 rows containing missing values (geom_errorbar).</span></a></code></pre></div>
<p><img src="Predict_files/figure-html/unnamed-chunk-5-1.png" width="720"></p>
<div id="choosing-the-right-model" class="section level3">
<h3 class="hasAnchor">
<a href="#choosing-the-right-model" class="anchor"></a>Choosing the right model</h3>
<p>Resistance is not easily predicted; if we look at vancomycin resistance in Gram positives, the spread (i.e. standard error) is enormous:</p>
<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb7-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb7-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(mo) <span class="op">==</span><span class="st"> "Gram positive"</span>) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb7-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="../reference/resistance_predict.html">resistance_predict</a></span>(<span class="dt">col_ab =</span> <span class="st">"vanc"</span>, <span class="dt">year_min =</span> <span class="dv">2010</span>, <span class="dt">info =</span> <span class="ot">FALSE</span>) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb7-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/graphics/topics/plot">plot</a></span>()</a>
<a class="sourceLine" id="cb7-5" data-line-number="5"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `date` as input for `col_date`.</span></a></code></pre></div>
<p><img src="Predict_files/figure-html/unnamed-chunk-6-1.png" width="720"></p>
<p>Vancomycin resistance could be 100% in ten years, but might also stay around 0%.</p>
<p>You can define the model with the <code>model</code> parameter. The default model is a generalised linear regression model using a binomial distribution, assuming that a period of zero resistance was followed by a period of increasing resistance leading slowly to more and more resistance.</p>
<p>Valid values are:</p>
<table class="table">
<colgroup>
<col width="32%">
<col width="25%">
<col width="42%">
</colgroup>
<thead><tr class="header">
<th>Input values</th>
<th>Function used by R</th>
<th>Type of model</th>
</tr></thead>
<tbody>
<tr class="odd">
<td>
<code>"binomial"</code> or <code>"binom"</code> or <code>"logit"</code>
</td>
<td><code><a href="https://www.rdocumentation.org/packages/stats/topics/glm">glm(..., family = binomial)</a></code></td>
<td>Generalised linear model with binomial distribution</td>
</tr>
<tr class="even">
<td>
<code>"loglin"</code> or <code>"poisson"</code>
</td>
<td><code><a href="https://www.rdocumentation.org/packages/stats/topics/glm">glm(..., family = poisson)</a></code></td>
<td>Generalised linear model with poisson distribution</td>
</tr>
<tr class="odd">
<td>
<code>"lin"</code> or <code>"linear"</code>
</td>
<td><code><a href="https://www.rdocumentation.org/packages/stats/topics/lm">lm()</a></code></td>
<td>Linear model</td>
</tr>
</tbody>
</table>
<p>For the vancomycin resistance in Gram positive bacteria, a linear model might be more appropriate since no (left half of a) binomial distribution is to be expected based on observed years:</p>
<div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb8-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb8-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(mo) <span class="op">==</span><span class="st"> "Gram positive"</span>) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb8-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="../reference/resistance_predict.html">resistance_predict</a></span>(<span class="dt">col_ab =</span> <span class="st">"vanc"</span>, <span class="dt">year_min =</span> <span class="dv">2010</span>, <span class="dt">info =</span> <span class="ot">FALSE</span>, <span class="dt">model =</span> <span class="st">"linear"</span>) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb8-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/graphics/topics/plot">plot</a></span>()</a>
<a class="sourceLine" id="cb8-5" data-line-number="5"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `date` as input for `col_date`.</span></a></code></pre></div>
<p><img src="Predict_files/figure-html/unnamed-chunk-7-1.png" width="720"></p>
<p>This seems more likely, doesn’t it?</p>
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<h1>How to import data from SPSS / SAS / Stata</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">13 August 2019</h4>
<h4 class="date">13 October 2019</h4>
<div class="hidden name"><code>SPSS.Rmd</code></div>
@ -252,7 +254,7 @@
<a class="sourceLine" id="cb1-11" data-line-number="11"><span class="co"># [1] "Gram-negative"</span></a>
<a class="sourceLine" id="cb1-12" data-line-number="12"></a>
<a class="sourceLine" id="cb1-13" data-line-number="13"><span class="co"># Klebsiella is intrinsic resistant to amoxicllin, according to EUCAST:</span></a>
<a class="sourceLine" id="cb1-14" data-line-number="14">klebsiella_test &lt;-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/data.frame">data.frame</a></span>(<span class="dt">mo =</span> <span class="st">"klebsiella"</span>, </a>
<a class="sourceLine" id="cb1-14" data-line-number="14">klebsiella_test &lt;-<span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span>(<span class="dt">mo =</span> <span class="st">"klebsiella"</span>, </a>
<a class="sourceLine" id="cb1-15" data-line-number="15"> <span class="dt">amox =</span> <span class="st">"S"</span>,</a>
<a class="sourceLine" id="cb1-16" data-line-number="16"> <span class="dt">stringsAsFactors =</span> <span class="ot">FALSE</span>)</a>
<a class="sourceLine" id="cb1-17" data-line-number="17">klebsiella_test <span class="co"># (our original data)</span></a>
@ -324,9 +326,9 @@
<a href="#base-r" class="anchor"></a>Base R</h3>
<p>To import data from SPSS, SAS or Stata, you can use the <a href="https://haven.tidyverse.org/">great <code>haven</code> package</a> yourself:</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" data-line-number="1"><span class="co"># download and install the latest version:</span></a>
<a class="sourceLine" id="cb3-2" data-line-number="2"><span class="kw"><a href="https://www.rdocumentation.org/packages/utils/topics/install.packages">install.packages</a></span>(<span class="st">"haven"</span>)</a>
<a class="sourceLine" id="cb3-2" data-line-number="2"><span class="kw"><a href="https://rdrr.io/r/utils/install.packages.html">install.packages</a></span>(<span class="st">"haven"</span>)</a>
<a class="sourceLine" id="cb3-3" data-line-number="3"><span class="co"># load the package you just installed:</span></a>
<a class="sourceLine" id="cb3-4" data-line-number="4"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(haven) </a></code></pre></div>
<a class="sourceLine" id="cb3-4" data-line-number="4"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span>(haven) </a></code></pre></div>
<p>You can now import files as follows:</p>
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<p>Developed by <a href="https://www.rug.nl/staff/m.s.berends/">Matthijs S. Berends</a>, <a href="https://www.rug.nl/staff/c.f.luz/">Christian F. Luz</a>, <a href="https://www.rug.nl/staff/a.w.friedrich/">Alex W. Friedrich</a>, <a href="https://www.rug.nl/staff/b.sinha/">Bhanu N. M. Sinha</a>, <a href="https://www.rug.nl/staff/c.j.albers/">Casper J. Albers</a>, <a href="https://www.rug.nl/staff/c.glasner/">Corinna Glasner</a>.</p>
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<h1>How to work with WHONET data</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">13 August 2019</h4>
<h4 class="date">13 October 2019</h4>
<div class="hidden name"><code>WHONET.Rmd</code></div>
@ -199,7 +201,7 @@
<a href="#import-of-data" class="anchor"></a>Import of data</h1>
<p>This tutorial assumes you already imported the WHONET data with e.g. the <a href="https://readxl.tidyverse.org/"><code>readxl</code> package</a>. In RStudio, this can be done using the menu button ‘Import Dataset’ in the tab ‘Environment’. Choose the option ‘From Excel’ and select your exported file. Make sure date fields are imported correctly.</p>
<p>An example syntax could look like this:</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(readxl)</a>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span>(readxl)</a>
<a class="sourceLine" id="cb1-2" data-line-number="2">data &lt;-<span class="st"> </span><span class="kw"><a href="https://readxl.tidyverse.org/reference/read_excel.html">read_excel</a></span>(<span class="dt">path =</span> <span class="st">"path/to/your/file.xlsx"</span>)</a></code></pre></div>
<p>This package comes with an <a href="https://msberends.gitlab.io/AMR/reference/WHONET.html">example data set <code>WHONET</code></a>. We will use it for this analysis.</p>
</div>
@ -207,12 +209,12 @@
<h1 class="hasAnchor">
<a href="#preparation" class="anchor"></a>Preparation</h1>
<p>First, load the relevant packages if you did not yet did this. I use the tidyverse for all of my analyses. All of them. If you don’t know it yet, I suggest you read about it on their website: <a href="https://www.tidyverse.org/" class="uri">https://www.tidyverse.org/</a>.</p>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb2-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(dplyr) <span class="co"># part of tidyverse</span></a>
<a class="sourceLine" id="cb2-2" data-line-number="2"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(ggplot2) <span class="co"># part of tidyverse</span></a>
<a class="sourceLine" id="cb2-3" data-line-number="3"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(AMR) <span class="co"># this package</span></a></code></pre></div>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb2-1" data-line-number="1"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span>(dplyr) <span class="co"># part of tidyverse</span></a>
<a class="sourceLine" id="cb2-2" data-line-number="2"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span>(ggplot2) <span class="co"># part of tidyverse</span></a>
<a class="sourceLine" id="cb2-3" data-line-number="3"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span>(AMR) <span class="co"># this package</span></a></code></pre></div>
<p>We will have to transform some variables to simplify and automate the analysis:</p>
<ul>
<li>Microorganisms should be transformed to our own microorganism IDs (called an <code>mo</code>) using <a href="https://msberends.gitlab.io/AMR/reference/ITIS.html">the ITIS reference data set</a>, which contains all ~20,000 microorganisms from the taxonomic kingdoms Bacteria, Fungi and Protozoa. We do the tranformation with <code><a href="../reference/as.mo.html">as.mo()</a></code>. This function also recognises almost all WHONET abbreviations of microorganisms.</li>
<li>Microorganisms should be transformed to our own microorganism IDs (called an <code>mo</code>) using <a href="https://msberends.gitlab.io/AMR/reference/catalogue_of_life">our Catalogue of Life reference data set</a>, which contains all ~70,000 microorganisms from the taxonomic kingdoms Bacteria, Fungi and Protozoa. We do the tranformation with <code><a href="../reference/as.mo.html">as.mo()</a></code>. This function also recognises almost all WHONET abbreviations of microorganisms.</li>
<li>Antimicrobial results or interpretations have to be clean and valid. In other words, they should only contain values <code>"S"</code>, <code>"I"</code> or <code>"R"</code>. That is exactly where the <code><a href="../reference/as.rsi.html">as.rsi()</a></code> function is for.</li>
</ul>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" data-line-number="1"><span class="co"># transform variables</span></a>
@ -223,18 +225,19 @@
<a class="sourceLine" id="cb3-6" data-line-number="6"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html">mutate_at</a></span>(<span class="kw"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(AMP_ND10<span class="op">:</span>CIP_EE), as.rsi)</a></code></pre></div>
<p>No errors or warnings, so all values are transformed succesfully.</p>
<p>We created a package dedicated to data cleaning and checking, called the <code>clean</code> package. It gets automatically installed with the <code>AMR</code> package, so we only have to load it:</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(clean)</a></code></pre></div>
<p>It contains the <code><a href="https://www.rdocumentation.org/packages/clean/topics/freq">freq()</a></code> function, to create frequency tables.</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" data-line-number="1"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span>(clean)</a></code></pre></div>
<p>It contains the <code><a href="https://rdrr.io/pkg/clean/man/freq.html">freq()</a></code> function, to create frequency tables.</p>
<p>So let’s check our data, with a couple of frequency tables:</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" data-line-number="1"><span class="co"># our newly created `mo` variable</span></a>
<a class="sourceLine" id="cb5-2" data-line-number="2">data <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/clean/topics/freq">freq</a></span>(mo, <span class="dt">nmax =</span> <span class="dv">10</span>)</a></code></pre></div>
<a class="sourceLine" id="cb5-2" data-line-number="2">data <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/clean/man/freq.html">freq</a></span>(mo, <span class="dt">nmax =</span> <span class="dv">10</span>)</a></code></pre></div>
<p><strong>Frequency table</strong></p>
<p>Class: mo (character)<br>
Length: 500 (of which NA: 0 = 0.00%)<br>
Length: 500 (of which NA: 0 = 0%)<br>
Unique: 39</p>
<p>Families: 10<br>
Genera: 17<br>
Species: 39</p>
<p>Gram-negative: 281 (56.20%)<br>
Gram-positive: 219 (43.80%)<br>
Nr of genera: 17<br>
Nr of species: 39</p>
<table class="table">
<thead><tr class="header">
<th align="left"></th>
@ -247,7 +250,7 @@ Species: 39</p>
<tbody>
<tr class="odd">
<td align="left">1</td>
<td align="left">B_ESCHR_COL</td>
<td align="left">B_ESCHR_COLI</td>
<td align="right">245</td>
<td align="right">49.0%</td>
<td align="right">245</td>
@ -255,7 +258,7 @@ Species: 39</p>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">B_STPHY_CNS</td>
<td align="left">B_STPHY_CONS</td>
<td align="right">74</td>
<td align="right">14.8%</td>
<td align="right">319</td>
@ -263,7 +266,7 @@ Species: 39</p>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">B_STPHY_EPI</td>
<td align="left">B_STPHY_EPDR</td>
<td align="right">38</td>
<td align="right">7.6%</td>
<td align="right">357</td>
@ -271,7 +274,7 @@ Species: 39</p>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">B_STRPT_PNE</td>
<td align="left">B_STRPT_PNMN</td>
<td align="right">31</td>
<td align="right">6.2%</td>
<td align="right">388</td>
@ -279,7 +282,7 @@ Species: 39</p>
</tr>
<tr class="odd">
<td align="left">5</td>
<td align="left">B_STPHY_HOM</td>
<td align="left">B_STPHY_HMNS</td>
<td align="right">21</td>
<td align="right">4.2%</td>
<td align="right">409</td>
@ -287,7 +290,7 @@ Species: 39</p>
</tr>
<tr class="even">
<td align="left">6</td>
<td align="left">B_PROTS_MIR</td>
<td align="left">B_PROTS_MRBL</td>
<td align="right">9</td>
<td align="right">1.8%</td>
<td align="right">418</td>
@ -295,7 +298,7 @@ Species: 39</p>
</tr>
<tr class="odd">
<td align="left">7</td>
<td align="left">B_ENTRC_IUM</td>
<td align="left">B_ENTRC_FACM</td>
<td align="right">8</td>
<td align="right">1.6%</td>
<td align="right">426</td>
@ -303,7 +306,7 @@ Species: 39</p>
</tr>
<tr class="even">
<td align="left">8</td>
<td align="left">B_STPHY_CAP</td>
<td align="left">B_STPHY_CPTS</td>
<td align="right">8</td>
<td align="right">1.6%</td>
<td align="right">434</td>
@ -311,7 +314,7 @@ Species: 39</p>
</tr>
<tr class="odd">
<td align="left">9</td>
<td align="left">B_ENTRB_CLO</td>
<td align="left">B_ENTRB_CLOC</td>
<td align="right">5</td>
<td align="right">1.0%</td>
<td align="right">439</td>
@ -319,7 +322,7 @@ Species: 39</p>
</tr>
<tr class="even">
<td align="left">10</td>
<td align="left">B_ENTRC_COL</td>
<td align="left">B_ENTRC_CLMB</td>
<td align="right">4</td>
<td align="right">0.8%</td>
<td align="right">443</td>
@ -327,14 +330,14 @@ Species: 39</p>
</tr>
</tbody>
</table>
<p>(omitted 29 entries, n = 57 [11.4%])</p>
<p>(omitted 29 entries, n = 57 [11.40%])</p>
<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb6-1" data-line-number="1"></a>
<a class="sourceLine" id="cb6-2" data-line-number="2"><span class="co"># our transformed antibiotic columns</span></a>
<a class="sourceLine" id="cb6-3" data-line-number="3"><span class="co"># amoxicillin/clavulanic acid (J01CR02) as an example</span></a>
<a class="sourceLine" id="cb6-4" data-line-number="4">data <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/clean/topics/freq">freq</a></span>(AMC_ND2)</a></code></pre></div>
<a class="sourceLine" id="cb6-4" data-line-number="4">data <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/clean/man/freq.html">freq</a></span>(AMC_ND2)</a></code></pre></div>
<p><strong>Frequency table</strong></p>
<p>Class: factor &gt; ordered &gt; rsi (numeric)<br>
Length: 500 (of which NA: 19 = 3.80%)<br>
Length: 500 (of which NA: 19 = 3.8%)<br>
Levels: 3: S &lt; I &lt; R<br>
Unique: 3</p>
<p>%SI: 78.6%</p>
@ -352,25 +355,25 @@ Unique: 3</p>
<td align="left">1</td>
<td align="left">S</td>
<td align="right">356</td>
<td align="right">74.0%</td>
<td align="right">74.01%</td>
<td align="right">356</td>
<td align="right">74.0%</td>
<td align="right">74.01%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">R</td>
<td align="right">103</td>
<td align="right">21.4%</td>
<td align="right">21.41%</td>
<td align="right">459</td>
<td align="right">95.4%</td>
<td align="right">95.43%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">I</td>
<td align="right">22</td>
<td align="right">4.6%</td>
<td align="right">4.57%</td>
<td align="right">481</td>
<td align="right">100.0%</td>
<td align="right">100.00%</td>
</tr>
</tbody>
</table>
@ -383,6 +386,7 @@ Unique: 3</p>
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@ -397,13 +401,15 @@ Unique: 3</p>
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<p>Developed by <a href="https://www.rug.nl/staff/m.s.berends/">Matthijs S. Berends</a>, <a href="https://www.rug.nl/staff/c.f.luz/">Christian F. Luz</a>, <a href="https://www.rug.nl/staff/a.w.friedrich/">Alex W. Friedrich</a>, <a href="https://www.rug.nl/staff/b.sinha/">Bhanu N. M. Sinha</a>, <a href="https://www.rug.nl/staff/c.j.albers/">Casper J. Albers</a>, <a href="https://www.rug.nl/staff/c.glasner/">Corinna Glasner</a>.</p>
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<h1>How to get properties of an antibiotic</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">22 June 2019</h4>
<div class="hidden name"><code>ab_property.Rmd</code></div>
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<h1>How to get properties of an antibiotic</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">27 March 2019</h4>
<div class="hidden name"><code>atc_property.Rmd</code></div>
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<h1>Benchmarks</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">23 September 2019</h4>
<h4 class="date">13 October 2019</h4>
<div class="hidden name"><code>benchmarks.Rmd</code></div>
@ -237,45 +197,45 @@
<p><small>Source: <a href="https://gitlab.com/msberends/AMR/blob/master/vignettes/benchmarks.Rmd" class="uri">https://gitlab.com/msberends/AMR/blob/master/vignettes/benchmarks.Rmd</a></small></p>
<p>One of the most important features of this package is the complete microbial taxonomic database, supplied by the <a href="http://catalogueoflife.org">Catalogue of Life</a>. We created a function <code>as.mo()</code> that transforms any user input value to a valid microbial ID by using intelligent rules combined with the taxonomic tree of Catalogue of Life.</p>
<p>Using the <code>microbenchmark</code> package, we can review the calculation performance of this function. Its function <code>microbenchmark()</code> runs different input expressions independently of each other and measures their time-to-result.</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1"><span class="kw">library</span>(microbenchmark)</a>
<a class="sourceLine" id="cb1-2" data-line-number="2"><span class="kw">library</span>(AMR)</a></code></pre></div>
<p>One of the most important features of this package is the complete microbial taxonomic database, supplied by the <a href="http://catalogueoflife.org">Catalogue of Life</a>. We created a function <code><a href="../reference/as.mo.html">as.mo()</a></code> that transforms any user input value to a valid microbial ID by using intelligent rules combined with the taxonomic tree of Catalogue of Life.</p>
<p>Using the <code>microbenchmark</code> package, we can review the calculation performance of this function. Its function <code><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark()</a></code> runs different input expressions independently of each other and measures their time-to-result.</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span>(microbenchmark)</a>
<a class="sourceLine" id="cb1-2" data-line-number="2"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span>(AMR)</a></code></pre></div>
<p>In the next test, we try to ‘coerce’ different input values for <em>Staphylococcus aureus</em>. The actual result is the same every time: it returns its microorganism code <code>B_STPHY_AURS</code> (<em>B</em> stands for <em>Bacteria</em>, the taxonomic kingdom).</p>
<p>But the calculation time differs a lot:</p>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb2-1" data-line-number="1">S.aureus &lt;-<span class="st"> </span><span class="kw">microbenchmark</span>(</a>
<a class="sourceLine" id="cb2-2" data-line-number="2"> <span class="kw">as.mo</span>(<span class="st">&quot;sau&quot;</span>), <span class="co"># WHONET code</span></a>
<a class="sourceLine" id="cb2-3" data-line-number="3"> <span class="kw">as.mo</span>(<span class="st">&quot;stau&quot;</span>),</a>
<a class="sourceLine" id="cb2-4" data-line-number="4"> <span class="kw">as.mo</span>(<span class="st">&quot;STAU&quot;</span>),</a>
<a class="sourceLine" id="cb2-5" data-line-number="5"> <span class="kw">as.mo</span>(<span class="st">&quot;staaur&quot;</span>),</a>
<a class="sourceLine" id="cb2-6" data-line-number="6"> <span class="kw">as.mo</span>(<span class="st">&quot;STAAUR&quot;</span>),</a>
<a class="sourceLine" id="cb2-7" data-line-number="7"> <span class="kw">as.mo</span>(<span class="st">&quot;S. aureus&quot;</span>),</a>
<a class="sourceLine" id="cb2-8" data-line-number="8"> <span class="kw">as.mo</span>(<span class="st">&quot;S aureus&quot;</span>),</a>
<a class="sourceLine" id="cb2-9" data-line-number="9"> <span class="kw">as.mo</span>(<span class="st">&quot;Staphylococcus aureus&quot;</span>), <span class="co"># official taxonomic name</span></a>
<a class="sourceLine" id="cb2-10" data-line-number="10"> <span class="kw">as.mo</span>(<span class="st">&quot;Staphylococcus aureus (MRSA)&quot;</span>), <span class="co"># additional text</span></a>
<a class="sourceLine" id="cb2-11" data-line-number="11"> <span class="kw">as.mo</span>(<span class="st">&quot;Sthafilokkockus aaureuz&quot;</span>), <span class="co"># incorrect spelling</span></a>
<a class="sourceLine" id="cb2-12" data-line-number="12"> <span class="kw">as.mo</span>(<span class="st">&quot;MRSA&quot;</span>), <span class="co"># Methicillin Resistant S. aureus</span></a>
<a class="sourceLine" id="cb2-13" data-line-number="13"> <span class="kw">as.mo</span>(<span class="st">&quot;VISA&quot;</span>), <span class="co"># Vancomycin Intermediate S. aureus</span></a>
<a class="sourceLine" id="cb2-14" data-line-number="14"> <span class="kw">as.mo</span>(<span class="st">&quot;VRSA&quot;</span>), <span class="co"># Vancomycin Resistant S. aureus</span></a>
<a class="sourceLine" id="cb2-15" data-line-number="15"> <span class="kw">as.mo</span>(<span class="dv">22242419</span>), <span class="co"># Catalogue of Life ID</span></a>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb2-1" data-line-number="1">S.aureus &lt;-<span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span>(</a>
<a class="sourceLine" id="cb2-2" data-line-number="2"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"sau"</span>), <span class="co"># WHONET code</span></a>
<a class="sourceLine" id="cb2-3" data-line-number="3"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"stau"</span>),</a>
<a class="sourceLine" id="cb2-4" data-line-number="4"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"STAU"</span>),</a>
<a class="sourceLine" id="cb2-5" data-line-number="5"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"staaur"</span>),</a>
<a class="sourceLine" id="cb2-6" data-line-number="6"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"STAAUR"</span>),</a>
<a class="sourceLine" id="cb2-7" data-line-number="7"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"S. aureus"</span>),</a>
<a class="sourceLine" id="cb2-8" data-line-number="8"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"S aureus"</span>),</a>
<a class="sourceLine" id="cb2-9" data-line-number="9"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"Staphylococcus aureus"</span>), <span class="co"># official taxonomic name</span></a>
<a class="sourceLine" id="cb2-10" data-line-number="10"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"Staphylococcus aureus (MRSA)"</span>), <span class="co"># additional text</span></a>
<a class="sourceLine" id="cb2-11" data-line-number="11"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"Sthafilokkockus aaureuz"</span>), <span class="co"># incorrect spelling</span></a>
<a class="sourceLine" id="cb2-12" data-line-number="12"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"MRSA"</span>), <span class="co"># Methicillin Resistant S. aureus</span></a>
<a class="sourceLine" id="cb2-13" data-line-number="13"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"VISA"</span>), <span class="co"># Vancomycin Intermediate S. aureus</span></a>
<a class="sourceLine" id="cb2-14" data-line-number="14"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"VRSA"</span>), <span class="co"># Vancomycin Resistant S. aureus</span></a>
<a class="sourceLine" id="cb2-15" data-line-number="15"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="dv">22242419</span>), <span class="co"># Catalogue of Life ID</span></a>
<a class="sourceLine" id="cb2-16" data-line-number="16"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb2-17" data-line-number="17"><span class="kw">print</span>(S.aureus, <span class="dt">unit =</span> <span class="st">&quot;ms&quot;</span>, <span class="dt">signif =</span> <span class="dv">2</span>)</a>
<a class="sourceLine" id="cb2-17" data-line-number="17"><span class="kw"><a href="https://rdrr.io/r/base/print.html">print</a></span>(S.aureus, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">2</span>)</a>
<a class="sourceLine" id="cb2-18" data-line-number="18"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb2-19" data-line-number="19"><span class="co"># expr min lq mean median uq max</span></a>
<a class="sourceLine" id="cb2-20" data-line-number="20"><span class="co"># as.mo(&quot;sau&quot;) 9.1 9.1 12.0 9.5 10.0 35</span></a>
<a class="sourceLine" id="cb2-21" data-line-number="21"><span class="co"># as.mo(&quot;stau&quot;) 31.0 32.0 37.0 33.0 34.0 58</span></a>
<a class="sourceLine" id="cb2-22" data-line-number="22"><span class="co"># as.mo(&quot;STAU&quot;) 31.0 32.0 34.0 34.0 35.0 37</span></a>
<a class="sourceLine" id="cb2-23" data-line-number="23"><span class="co"># as.mo(&quot;staaur&quot;) 8.6 9.1 9.7 9.8 10.0 11</span></a>
<a class="sourceLine" id="cb2-24" data-line-number="24"><span class="co"># as.mo(&quot;STAAUR&quot;) 8.7 8.9 17.0 9.4 12.0 57</span></a>
<a class="sourceLine" id="cb2-25" data-line-number="25"><span class="co"># as.mo(&quot;S. aureus&quot;) 23.0 24.0 34.0 26.0 46.0 54</span></a>
<a class="sourceLine" id="cb2-26" data-line-number="26"><span class="co"># as.mo(&quot;S aureus&quot;) 23.0 24.0 28.0 25.0 28.0 53</span></a>
<a class="sourceLine" id="cb2-27" data-line-number="27"><span class="co"># as.mo(&quot;Staphylococcus aureus&quot;) 29.0 29.0 31.0 30.0 32.0 34</span></a>
<a class="sourceLine" id="cb2-28" data-line-number="28"><span class="co"># as.mo(&quot;Staphylococcus aureus (MRSA)&quot;) 570.0 590.0 620.0 620.0 650.0 690</span></a>
<a class="sourceLine" id="cb2-29" data-line-number="29"><span class="co"># as.mo(&quot;Sthafilokkockus aaureuz&quot;) 310.0 320.0 350.0 330.0 340.0 480</span></a>
<a class="sourceLine" id="cb2-30" data-line-number="30"><span class="co"># as.mo(&quot;MRSA&quot;) 8.7 9.0 12.0 9.5 9.7 32</span></a>
<a class="sourceLine" id="cb2-31" data-line-number="31"><span class="co"># as.mo(&quot;VISA&quot;) 19.0 20.0 22.0 22.0 24.0 26</span></a>
<a class="sourceLine" id="cb2-32" data-line-number="32"><span class="co"># as.mo(&quot;VRSA&quot;) 19.0 20.0 28.0 22.0 43.0 48</span></a>
<a class="sourceLine" id="cb2-33" data-line-number="33"><span class="co"># as.mo(22242419) 18.0 19.0 25.0 22.0 23.0 41</span></a>
<a class="sourceLine" id="cb2-19" data-line-number="19"><span class="co"># expr min lq mean median uq max</span></a>
<a class="sourceLine" id="cb2-20" data-line-number="20"><span class="co"># as.mo("sau") 9.5 9.7 15 10 11 34</span></a>
<a class="sourceLine" id="cb2-21" data-line-number="21"><span class="co"># as.mo("stau") 31.0 32.0 38 33 34 62</span></a>
<a class="sourceLine" id="cb2-22" data-line-number="22"><span class="co"># as.mo("STAU") 31.0 32.0 39 35 39 56</span></a>
<a class="sourceLine" id="cb2-23" data-line-number="23"><span class="co"># as.mo("staaur") 9.6 10.0 17 11 31 31</span></a>
<a class="sourceLine" id="cb2-24" data-line-number="24"><span class="co"># as.mo("STAAUR") 9.6 9.8 13 10 10 34</span></a>
<a class="sourceLine" id="cb2-25" data-line-number="25"><span class="co"># as.mo("S. aureus") 24.0 25.0 27 25 28 33</span></a>
<a class="sourceLine" id="cb2-26" data-line-number="26"><span class="co"># as.mo("S aureus") 24.0 25.0 31 25 43 51</span></a>
<a class="sourceLine" id="cb2-27" data-line-number="27"><span class="co"># as.mo("Staphylococcus aureus") 29.0 30.0 32 31 34 39</span></a>
<a class="sourceLine" id="cb2-28" data-line-number="28"><span class="co"># as.mo("Staphylococcus aureus (MRSA)") 550.0 580.0 610 600 620 680</span></a>
<a class="sourceLine" id="cb2-29" data-line-number="29"><span class="co"># as.mo("Sthafilokkockus aaureuz") 290.0 310.0 360 340 380 530</span></a>
<a class="sourceLine" id="cb2-30" data-line-number="30"><span class="co"># as.mo("MRSA") 9.6 10.0 16 10 30 32</span></a>
<a class="sourceLine" id="cb2-31" data-line-number="31"><span class="co"># as.mo("VISA") 19.0 20.0 21 20 21 22</span></a>
<a class="sourceLine" id="cb2-32" data-line-number="32"><span class="co"># as.mo("VRSA") 20.0 20.0 26 21 24 46</span></a>
<a class="sourceLine" id="cb2-33" data-line-number="33"><span class="co"># as.mo(22242419) 18.0 18.0 19 19 19 22</span></a>
<a class="sourceLine" id="cb2-34" data-line-number="34"><span class="co"># neval</span></a>
<a class="sourceLine" id="cb2-35" data-line-number="35"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-36" data-line-number="36"><span class="co"># 10</span></a>
@ -291,158 +251,162 @@
<a class="sourceLine" id="cb2-46" data-line-number="46"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-47" data-line-number="47"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-48" data-line-number="48"><span class="co"># 10</span></a></code></pre></div>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-5-1.png" width="562.5" /></p>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-5-1.png" width="562.5"></p>
<p>In the table above, all measurements are shown in milliseconds (thousands of seconds). A value of 5 milliseconds means it can determine 200 input values per second. It case of 100 milliseconds, this is only 10 input values per second. The second input is the only one that has to be looked up thoroughly. All the others are known codes (the first one is a WHONET code) or common laboratory codes, or common full organism names like the last one. Full organism names are always preferred.</p>
<p>To achieve this speed, the <code>as.mo</code> function also takes into account the prevalence of human pathogenic microorganisms. The downside is of course that less prevalent microorganisms will be determined less fast. See this example for the ID of <em>Methanosarcina semesiae</em> (<code>B_MTHNSR_SEMS</code>), a bug probably never found before in humans:</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" data-line-number="1">M.semesiae &lt;-<span class="st"> </span><span class="kw">microbenchmark</span>(<span class="kw">as.mo</span>(<span class="st">&quot;metsem&quot;</span>),</a>
<a class="sourceLine" id="cb3-2" data-line-number="2"> <span class="kw">as.mo</span>(<span class="st">&quot;METSEM&quot;</span>),</a>
<a class="sourceLine" id="cb3-3" data-line-number="3"> <span class="kw">as.mo</span>(<span class="st">&quot;M. semesiae&quot;</span>),</a>
<a class="sourceLine" id="cb3-4" data-line-number="4"> <span class="kw">as.mo</span>(<span class="st">&quot;M. semesiae&quot;</span>),</a>
<a class="sourceLine" id="cb3-5" data-line-number="5"> <span class="kw">as.mo</span>(<span class="st">&quot;Methanosarcina semesiae&quot;</span>),</a>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" data-line-number="1">M.semesiae &lt;-<span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span>(<span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"metsem"</span>),</a>
<a class="sourceLine" id="cb3-2" data-line-number="2"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"METSEM"</span>),</a>
<a class="sourceLine" id="cb3-3" data-line-number="3"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"M. semesiae"</span>),</a>
<a class="sourceLine" id="cb3-4" data-line-number="4"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"M. semesiae"</span>),</a>
<a class="sourceLine" id="cb3-5" data-line-number="5"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"Methanosarcina semesiae"</span>),</a>
<a class="sourceLine" id="cb3-6" data-line-number="6"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb3-7" data-line-number="7"><span class="kw">print</span>(M.semesiae, <span class="dt">unit =</span> <span class="st">&quot;ms&quot;</span>, <span class="dt">signif =</span> <span class="dv">4</span>)</a>
<a class="sourceLine" id="cb3-7" data-line-number="7"><span class="kw"><a href="https://rdrr.io/r/base/print.html">print</a></span>(M.semesiae, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">4</span>)</a>
<a class="sourceLine" id="cb3-8" data-line-number="8"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb3-9" data-line-number="9"><span class="co"># expr min lq mean median uq</span></a>
<a class="sourceLine" id="cb3-10" data-line-number="10"><span class="co"># as.mo(&quot;metsem&quot;) 1343.00 1379.00 1415.00 1404.00 1424.00</span></a>
<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># as.mo(&quot;METSEM&quot;) 1335.00 1356.00 1418.00 1410.00 1451.00</span></a>
<a class="sourceLine" id="cb3-12" data-line-number="12"><span class="co"># as.mo(&quot;M. semesiae&quot;) 1852.00 2045.00 2081.00 2107.00 2154.00</span></a>
<a class="sourceLine" id="cb3-13" data-line-number="13"><span class="co"># as.mo(&quot;M. semesiae&quot;) 1961.00 2037.00 2095.00 2085.00 2123.00</span></a>
<a class="sourceLine" id="cb3-14" data-line-number="14"><span class="co"># as.mo(&quot;Methanosarcina semesiae&quot;) 30.55 31.13 34.35 32.63 33.33</span></a>
<a class="sourceLine" id="cb3-10" data-line-number="10"><span class="co"># as.mo("metsem") 1293.00 1304.00 1394.00 1316.00 1395.00</span></a>
<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># as.mo("METSEM") 1232.00 1278.00 1510.00 1309.00 1518.00</span></a>
<a class="sourceLine" id="cb3-12" data-line-number="12"><span class="co"># as.mo("M. semesiae") 1874.00 1928.00 2063.00 1961.00 2167.00</span></a>
<a class="sourceLine" id="cb3-13" data-line-number="13"><span class="co"># as.mo("M. semesiae") 1883.00 1926.00 2091.00 1978.00 2060.00</span></a>
<a class="sourceLine" id="cb3-14" data-line-number="14"><span class="co"># as.mo("Methanosarcina semesiae") 30.23 31.64 35.26 31.82 38.29</span></a>
<a class="sourceLine" id="cb3-15" data-line-number="15"><span class="co"># max neval</span></a>
<a class="sourceLine" id="cb3-16" data-line-number="16"><span class="co"># 1579.00 10</span></a>
<a class="sourceLine" id="cb3-17" data-line-number="17"><span class="co"># 1557.00 10</span></a>
<a class="sourceLine" id="cb3-18" data-line-number="18"><span class="co"># 2163.00 10</span></a>
<a class="sourceLine" id="cb3-19" data-line-number="19"><span class="co"># 2336.00 10</span></a>
<a class="sourceLine" id="cb3-20" data-line-number="20"><span class="co"># 54.12 10</span></a></code></pre></div>
<p>That takes 15.6 times as much time on average. A value of 100 milliseconds means it can only determine ~10 different input values per second. We can conclude that looking up arbitrary codes of less prevalent microorganisms is the worst way to go, in terms of calculation performance. Full names (like <em>Methanosarcina semesiae</em>) are almost fast - these are the most probable input from most data sets.</p>
<a class="sourceLine" id="cb3-16" data-line-number="16"><span class="co"># 1929.00 10</span></a>
<a class="sourceLine" id="cb3-17" data-line-number="17"><span class="co"># 2721.00 10</span></a>
<a class="sourceLine" id="cb3-18" data-line-number="18"><span class="co"># 2676.00 10</span></a>
<a class="sourceLine" id="cb3-19" data-line-number="19"><span class="co"># 2974.00 10</span></a>
<a class="sourceLine" id="cb3-20" data-line-number="20"><span class="co"># 52.65 10</span></a></code></pre></div>
<p>That takes 15.8 times as much time on average. A value of 100 milliseconds means it can only determine ~10 different input values per second. We can conclude that looking up arbitrary codes of less prevalent microorganisms is the worst way to go, in terms of calculation performance. Full names (like <em>Methanosarcina semesiae</em>) are almost fast - these are the most probable input from most data sets.</p>
<p>In the figure below, we compare <em>Escherichia coli</em> (which is very common) with <em>Prevotella brevis</em> (which is moderately common) and with <em>Methanosarcina semesiae</em> (which is uncommon):</p>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-9-1.png" width="562.5" /></p>
<p>In reality, the <code>as.mo()</code> functions <strong>learns from its own output to speed up determinations for next times</strong>. In above figure, this effect was disabled to show the difference with the boxplot below - when you would use <code>as.mo()</code> yourself:</p>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-11-1.png" width="562.5" /></p>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-9-1.png" width="562.5"></p>
<p>In reality, the <code><a href="../reference/as.mo.html">as.mo()</a></code> functions <strong>learns from its own output to speed up determinations for next times</strong>. In above figure, this effect was disabled to show the difference with the boxplot below - when you would use <code><a href="../reference/as.mo.html">as.mo()</a></code> yourself:</p>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-11-1.png" width="562.5"></p>
<p>The highest outliers are the first times. All next determinations were done in only thousands of seconds.</p>
<p>Uncommon microorganisms take a lot more time than common microorganisms. To relieve this pitfall and further improve performance, two important calculations take almost no time at all: <strong>repetitive results</strong> and <strong>already precalculated results</strong>.</p>
<div id="repetitive-results" class="section level3">
<h3>Repetitive results</h3>
<p>Repetitive results are unique values that are present more than once. Unique values will only be calculated once by <code>as.mo()</code>. We will use <code>mo_name()</code> for this test - a helper function that returns the full microbial name (genus, species and possibly subspecies) which uses <code>as.mo()</code> internally.</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" data-line-number="1"><span class="kw">library</span>(dplyr)</a>
<h3 class="hasAnchor">
<a href="#repetitive-results" class="anchor"></a>Repetitive results</h3>
<p>Repetitive results are unique values that are present more than once. Unique values will only be calculated once by <code><a href="../reference/as.mo.html">as.mo()</a></code>. We will use <code><a href="../reference/mo_property.html">mo_name()</a></code> for this test - a helper function that returns the full microbial name (genus, species and possibly subspecies) which uses <code><a href="../reference/as.mo.html">as.mo()</a></code> internally.</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" data-line-number="1"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span>(dplyr)</a>
<a class="sourceLine" id="cb4-2" data-line-number="2"><span class="co"># take all MO codes from the example_isolates data set</span></a>
<a class="sourceLine" id="cb4-3" data-line-number="3">x &lt;-<span class="st"> </span>example_isolates<span class="op">$</span>mo <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb4-4" data-line-number="4"><span class="st"> </span><span class="co"># keep only the unique ones</span></a>
<a class="sourceLine" id="cb4-5" data-line-number="5"><span class="st"> </span><span class="kw">unique</span>() <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb4-5" data-line-number="5"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/unique.html">unique</a></span>() <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb4-6" data-line-number="6"><span class="st"> </span><span class="co"># pick 50 of them at random</span></a>
<a class="sourceLine" id="cb4-7" data-line-number="7"><span class="st"> </span><span class="kw">sample</span>(<span class="dv">50</span>) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb4-7" data-line-number="7"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/sample.html">sample</a></span>(<span class="dv">50</span>) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb4-8" data-line-number="8"><span class="st"> </span><span class="co"># paste that 10,000 times</span></a>
<a class="sourceLine" id="cb4-9" data-line-number="9"><span class="st"> </span><span class="kw">rep</span>(<span class="dv">10000</span>) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb4-9" data-line-number="9"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/rep.html">rep</a></span>(<span class="dv">10000</span>) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb4-10" data-line-number="10"><span class="st"> </span><span class="co"># scramble it</span></a>
<a class="sourceLine" id="cb4-11" data-line-number="11"><span class="st"> </span><span class="kw">sample</span>()</a>
<a class="sourceLine" id="cb4-11" data-line-number="11"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/sample.html">sample</a></span>()</a>
<a class="sourceLine" id="cb4-12" data-line-number="12"> </a>
<a class="sourceLine" id="cb4-13" data-line-number="13"><span class="co"># got indeed 50 times 10,000 = half a million?</span></a>
<a class="sourceLine" id="cb4-14" data-line-number="14"><span class="kw">length</span>(x)</a>
<a class="sourceLine" id="cb4-14" data-line-number="14"><span class="kw"><a href="https://rdrr.io/r/base/length.html">length</a></span>(x)</a>
<a class="sourceLine" id="cb4-15" data-line-number="15"><span class="co"># [1] 500000</span></a>
<a class="sourceLine" id="cb4-16" data-line-number="16"></a>
<a class="sourceLine" id="cb4-17" data-line-number="17"><span class="co"># and how many unique values do we have?</span></a>
<a class="sourceLine" id="cb4-18" data-line-number="18"><span class="kw">n_distinct</span>(x)</a>
<a class="sourceLine" id="cb4-18" data-line-number="18"><span class="kw"><a href="https://dplyr.tidyverse.org/reference/n_distinct.html">n_distinct</a></span>(x)</a>
<a class="sourceLine" id="cb4-19" data-line-number="19"><span class="co"># [1] 50</span></a>
<a class="sourceLine" id="cb4-20" data-line-number="20"></a>
<a class="sourceLine" id="cb4-21" data-line-number="21"><span class="co"># now let&#39;s see:</span></a>
<a class="sourceLine" id="cb4-22" data-line-number="22">run_it &lt;-<span class="st"> </span><span class="kw">microbenchmark</span>(<span class="kw">mo_name</span>(x),</a>
<a class="sourceLine" id="cb4-21" data-line-number="21"><span class="co"># now let's see:</span></a>
<a class="sourceLine" id="cb4-22" data-line-number="22">run_it &lt;-<span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span>(<span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(x),</a>
<a class="sourceLine" id="cb4-23" data-line-number="23"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb4-24" data-line-number="24"><span class="kw">print</span>(run_it, <span class="dt">unit =</span> <span class="st">&quot;ms&quot;</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb4-24" data-line-number="24"><span class="kw"><a href="https://rdrr.io/r/base/print.html">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb4-25" data-line-number="25"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb4-26" data-line-number="26"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb4-27" data-line-number="27"><span class="co"># mo_name(x) 626 639 663 658 682 731 10</span></a></code></pre></div>
<p>So transforming 500,000 values (!!) of 50 unique values only takes 0.66 seconds (657 ms). You only lose time on your unique input values.</p>
<a class="sourceLine" id="cb4-27" data-line-number="27"><span class="co"># mo_name(x) 596 604 651 641 663 813 10</span></a></code></pre></div>
<p>So transforming 500,000 values (!!) of 50 unique values only takes 0.64 seconds (641 ms). You only lose time on your unique input values.</p>
</div>
<div id="precalculated-results" class="section level3">
<h3>Precalculated results</h3>
<p>What about precalculated results? If the input is an already precalculated result of a helper function like <code>mo_name()</code>, it almost doesn’t take any time at all (see ‘C’ below):</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" data-line-number="1">run_it &lt;-<span class="st"> </span><span class="kw">microbenchmark</span>(<span class="dt">A =</span> <span class="kw">mo_name</span>(<span class="st">&quot;B_STPHY_AURS&quot;</span>),</a>
<a class="sourceLine" id="cb5-2" data-line-number="2"> <span class="dt">B =</span> <span class="kw">mo_name</span>(<span class="st">&quot;S. aureus&quot;</span>),</a>
<a class="sourceLine" id="cb5-3" data-line-number="3"> <span class="dt">C =</span> <span class="kw">mo_name</span>(<span class="st">&quot;Staphylococcus aureus&quot;</span>),</a>
<h3 class="hasAnchor">
<a href="#precalculated-results" class="anchor"></a>Precalculated results</h3>
<p>What about precalculated results? If the input is an already precalculated result of a helper function like <code><a href="../reference/mo_property.html">mo_name()</a></code>, it almost doesn’t take any time at all (see ‘C’ below):</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" data-line-number="1">run_it &lt;-<span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span>(<span class="dt">A =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"B_STPHY_AURS"</span>),</a>
<a class="sourceLine" id="cb5-2" data-line-number="2"> <span class="dt">B =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"S. aureus"</span>),</a>
<a class="sourceLine" id="cb5-3" data-line-number="3"> <span class="dt">C =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"Staphylococcus aureus"</span>),</a>
<a class="sourceLine" id="cb5-4" data-line-number="4"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb5-5" data-line-number="5"><span class="kw">print</span>(run_it, <span class="dt">unit =</span> <span class="st">&quot;ms&quot;</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb5-5" data-line-number="5"><span class="kw"><a href="https://rdrr.io/r/base/print.html">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb5-6" data-line-number="6"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb5-7" data-line-number="7"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb5-8" data-line-number="8"><span class="co"># A 6.260 6.320 9.050 6.360 6.810 32.40 10</span></a>
<a class="sourceLine" id="cb5-9" data-line-number="9"><span class="co"># B 22.800 23.000 23.800 23.200 23.900 28.20 10</span></a>
<a class="sourceLine" id="cb5-10" data-line-number="10"><span class="co"># C 0.709 0.813 0.836 0.843 0.854 0.96 10</span></a></code></pre></div>
<p>So going from <code>mo_name(&quot;Staphylococcus aureus&quot;)</code> to <code>&quot;Staphylococcus aureus&quot;</code> takes 0.0008 seconds - it doesn’t even start calculating <em>if the result would be the same as the expected resulting value</em>. That goes for all helper functions:</p>
<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb6-1" data-line-number="1">run_it &lt;-<span class="st"> </span><span class="kw">microbenchmark</span>(<span class="dt">A =</span> <span class="kw">mo_species</span>(<span class="st">&quot;aureus&quot;</span>),</a>
<a class="sourceLine" id="cb6-2" data-line-number="2"> <span class="dt">B =</span> <span class="kw">mo_genus</span>(<span class="st">&quot;Staphylococcus&quot;</span>),</a>
<a class="sourceLine" id="cb6-3" data-line-number="3"> <span class="dt">C =</span> <span class="kw">mo_name</span>(<span class="st">&quot;Staphylococcus aureus&quot;</span>),</a>
<a class="sourceLine" id="cb6-4" data-line-number="4"> <span class="dt">D =</span> <span class="kw">mo_family</span>(<span class="st">&quot;Staphylococcaceae&quot;</span>),</a>
<a class="sourceLine" id="cb6-5" data-line-number="5"> <span class="dt">E =</span> <span class="kw">mo_order</span>(<span class="st">&quot;Bacillales&quot;</span>),</a>
<a class="sourceLine" id="cb6-6" data-line-number="6"> <span class="dt">F =</span> <span class="kw">mo_class</span>(<span class="st">&quot;Bacilli&quot;</span>),</a>
<a class="sourceLine" id="cb6-7" data-line-number="7"> <span class="dt">G =</span> <span class="kw">mo_phylum</span>(<span class="st">&quot;Firmicutes&quot;</span>),</a>
<a class="sourceLine" id="cb6-8" data-line-number="8"> <span class="dt">H =</span> <span class="kw">mo_kingdom</span>(<span class="st">&quot;Bacteria&quot;</span>),</a>
<a class="sourceLine" id="cb5-7" data-line-number="7"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb5-8" data-line-number="8"><span class="co"># A 6.300 6.460 6.79 6.500 6.810 8.32 10</span></a>
<a class="sourceLine" id="cb5-9" data-line-number="9"><span class="co"># B 24.600 24.700 28.70 25.600 26.600 51.30 10</span></a>
<a class="sourceLine" id="cb5-10" data-line-number="10"><span class="co"># C 0.778 0.828 0.93 0.854 0.872 1.63 10</span></a></code></pre></div>
<p>So going from <code><a href="../reference/mo_property.html">mo_name("Staphylococcus aureus")</a></code> to <code>"Staphylococcus aureus"</code> takes 0.0009 seconds - it doesn’t even start calculating <em>if the result would be the same as the expected resulting value</em>. That goes for all helper functions:</p>
<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb6-1" data-line-number="1">run_it &lt;-<span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span>(<span class="dt">A =</span> <span class="kw"><a href="../reference/mo_property.html">mo_species</a></span>(<span class="st">"aureus"</span>),</a>
<a class="sourceLine" id="cb6-2" data-line-number="2"> <span class="dt">B =</span> <span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(<span class="st">"Staphylococcus"</span>),</a>
<a class="sourceLine" id="cb6-3" data-line-number="3"> <span class="dt">C =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"Staphylococcus aureus"</span>),</a>
<a class="sourceLine" id="cb6-4" data-line-number="4"> <span class="dt">D =</span> <span class="kw"><a href="../reference/mo_property.html">mo_family</a></span>(<span class="st">"Staphylococcaceae"</span>),</a>
<a class="sourceLine" id="cb6-5" data-line-number="5"> <span class="dt">E =</span> <span class="kw"><a href="../reference/mo_property.html">mo_order</a></span>(<span class="st">"Bacillales"</span>),</a>
<a class="sourceLine" id="cb6-6" data-line-number="6"> <span class="dt">F =</span> <span class="kw"><a href="../reference/mo_property.html">mo_class</a></span>(<span class="st">"Bacilli"</span>),</a>
<a class="sourceLine" id="cb6-7" data-line-number="7"> <span class="dt">G =</span> <span class="kw"><a href="../reference/mo_property.html">mo_phylum</a></span>(<span class="st">"Firmicutes"</span>),</a>
<a class="sourceLine" id="cb6-8" data-line-number="8"> <span class="dt">H =</span> <span class="kw"><a href="../reference/mo_property.html">mo_kingdom</a></span>(<span class="st">"Bacteria"</span>),</a>
<a class="sourceLine" id="cb6-9" data-line-number="9"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb6-10" data-line-number="10"><span class="kw">print</span>(run_it, <span class="dt">unit =</span> <span class="st">&quot;ms&quot;</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb6-10" data-line-number="10"><span class="kw"><a href="https://rdrr.io/r/base/print.html">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb6-11" data-line-number="11"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb6-12" data-line-number="12"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb6-13" data-line-number="13"><span class="co"># A 0.466 0.466 0.495 0.475 0.510 0.622 10</span></a>
<a class="sourceLine" id="cb6-14" data-line-number="14"><span class="co"># B 0.497 0.511 0.558 0.517 0.575 0.844 10</span></a>
<a class="sourceLine" id="cb6-15" data-line-number="15"><span class="co"># C 0.709 0.783 0.876 0.857 0.956 1.110 10</span></a>
<a class="sourceLine" id="cb6-16" data-line-number="16"><span class="co"># D 0.477 0.486 0.547 0.514 0.639 0.669 10</span></a>
<a class="sourceLine" id="cb6-17" data-line-number="17"><span class="co"># E 0.468 0.476 0.504 0.481 0.520 0.630 10</span></a>
<a class="sourceLine" id="cb6-18" data-line-number="18"><span class="co"># F 0.454 0.461 0.509 0.475 0.522 0.687 10</span></a>
<a class="sourceLine" id="cb6-19" data-line-number="19"><span class="co"># G 0.459 0.465 0.522 0.475 0.587 0.637 10</span></a>
<a class="sourceLine" id="cb6-20" data-line-number="20"><span class="co"># H 0.432 0.460 0.502 0.469 0.535 0.623 10</span></a></code></pre></div>
<p>Of course, when running <code>mo_phylum(&quot;Firmicutes&quot;)</code> the function has zero knowledge about the actual microorganism, namely <em>S. aureus</em>. But since the result would be <code>&quot;Firmicutes&quot;</code> too, there is no point in calculating the result. And because this package ‘knows’ all phyla of all known bacteria (according to the Catalogue of Life), it can just return the initial value immediately.</p>
<a class="sourceLine" id="cb6-13" data-line-number="13"><span class="co"># A 0.457 0.463 0.477 0.476 0.483 0.511 10</span></a>
<a class="sourceLine" id="cb6-14" data-line-number="14"><span class="co"># B 0.486 0.496 0.508 0.499 0.512 0.569 10</span></a>
<a class="sourceLine" id="cb6-15" data-line-number="15"><span class="co"># C 0.781 0.803 0.825 0.829 0.847 0.854 10</span></a>
<a class="sourceLine" id="cb6-16" data-line-number="16"><span class="co"># D 0.479 0.495 0.528 0.510 0.517 0.749 10</span></a>
<a class="sourceLine" id="cb6-17" data-line-number="17"><span class="co"># E 0.457 0.464 0.484 0.475 0.498 0.547 10</span></a>
<a class="sourceLine" id="cb6-18" data-line-number="18"><span class="co"># F 0.458 0.464 0.472 0.468 0.477 0.496 10</span></a>
<a class="sourceLine" id="cb6-19" data-line-number="19"><span class="co"># G 0.446 0.453 0.462 0.459 0.467 0.499 10</span></a>
<a class="sourceLine" id="cb6-20" data-line-number="20"><span class="co"># H 0.426 0.458 0.467 0.467 0.472 0.507 10</span></a></code></pre></div>
<p>Of course, when running <code><a href="../reference/mo_property.html">mo_phylum("Firmicutes")</a></code> the function has zero knowledge about the actual microorganism, namely <em>S. aureus</em>. But since the result would be <code>"Firmicutes"</code> too, there is no point in calculating the result. And because this package ‘knows’ all phyla of all known bacteria (according to the Catalogue of Life), it can just return the initial value immediately.</p>
</div>
<div id="results-in-other-languages" class="section level3">
<h3>Results in other languages</h3>
<h3 class="hasAnchor">
<a href="#results-in-other-languages" class="anchor"></a>Results in other languages</h3>
<p>When the system language is non-English and supported by this <code>AMR</code> package, some functions will have a translated result. This almost does’t take extra time:</p>
<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb7-1" data-line-number="1"><span class="kw">mo_name</span>(<span class="st">&quot;CoNS&quot;</span>, <span class="dt">language =</span> <span class="st">&quot;en&quot;</span>) <span class="co"># or just mo_name(&quot;CoNS&quot;) on an English system</span></a>
<a class="sourceLine" id="cb7-2" data-line-number="2"><span class="co"># [1] &quot;Coagulase-negative Staphylococcus (CoNS)&quot;</span></a>
<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb7-1" data-line-number="1"><span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"en"</span>) <span class="co"># or just mo_name("CoNS") on an English system</span></a>
<a class="sourceLine" id="cb7-2" data-line-number="2"><span class="co"># [1] "Coagulase-negative Staphylococcus (CoNS)"</span></a>
<a class="sourceLine" id="cb7-3" data-line-number="3"></a>
<a class="sourceLine" id="cb7-4" data-line-number="4"><span class="kw">mo_name</span>(<span class="st">&quot;CoNS&quot;</span>, <span class="dt">language =</span> <span class="st">&quot;es&quot;</span>) <span class="co"># or just mo_name(&quot;CoNS&quot;) on a Spanish system</span></a>
<a class="sourceLine" id="cb7-5" data-line-number="5"><span class="co"># [1] &quot;Staphylococcus coagulasa negativo (SCN)&quot;</span></a>
<a class="sourceLine" id="cb7-4" data-line-number="4"><span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"es"</span>) <span class="co"># or just mo_name("CoNS") on a Spanish system</span></a>
<a class="sourceLine" id="cb7-5" data-line-number="5"><span class="co"># [1] "Staphylococcus coagulasa negativo (SCN)"</span></a>
<a class="sourceLine" id="cb7-6" data-line-number="6"></a>
<a class="sourceLine" id="cb7-7" data-line-number="7"><span class="kw">mo_name</span>(<span class="st">&quot;CoNS&quot;</span>, <span class="dt">language =</span> <span class="st">&quot;nl&quot;</span>) <span class="co"># or just mo_name(&quot;CoNS&quot;) on a Dutch system</span></a>
<a class="sourceLine" id="cb7-8" data-line-number="8"><span class="co"># [1] &quot;Coagulase-negatieve Staphylococcus (CNS)&quot;</span></a>
<a class="sourceLine" id="cb7-7" data-line-number="7"><span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"nl"</span>) <span class="co"># or just mo_name("CoNS") on a Dutch system</span></a>
<a class="sourceLine" id="cb7-8" data-line-number="8"><span class="co"># [1] "Coagulase-negatieve Staphylococcus (CNS)"</span></a>
<a class="sourceLine" id="cb7-9" data-line-number="9"></a>
<a class="sourceLine" id="cb7-10" data-line-number="10">run_it &lt;-<span class="st"> </span><span class="kw">microbenchmark</span>(<span class="dt">en =</span> <span class="kw">mo_name</span>(<span class="st">&quot;CoNS&quot;</span>, <span class="dt">language =</span> <span class="st">&quot;en&quot;</span>),</a>
<a class="sourceLine" id="cb7-11" data-line-number="11"> <span class="dt">de =</span> <span class="kw">mo_name</span>(<span class="st">&quot;CoNS&quot;</span>, <span class="dt">language =</span> <span class="st">&quot;de&quot;</span>),</a>
<a class="sourceLine" id="cb7-12" data-line-number="12"> <span class="dt">nl =</span> <span class="kw">mo_name</span>(<span class="st">&quot;CoNS&quot;</span>, <span class="dt">language =</span> <span class="st">&quot;nl&quot;</span>),</a>
<a class="sourceLine" id="cb7-13" data-line-number="13"> <span class="dt">es =</span> <span class="kw">mo_name</span>(<span class="st">&quot;CoNS&quot;</span>, <span class="dt">language =</span> <span class="st">&quot;es&quot;</span>),</a>
<a class="sourceLine" id="cb7-14" data-line-number="14"> <span class="dt">it =</span> <span class="kw">mo_name</span>(<span class="st">&quot;CoNS&quot;</span>, <span class="dt">language =</span> <span class="st">&quot;it&quot;</span>),</a>
<a class="sourceLine" id="cb7-15" data-line-number="15"> <span class="dt">fr =</span> <span class="kw">mo_name</span>(<span class="st">&quot;CoNS&quot;</span>, <span class="dt">language =</span> <span class="st">&quot;fr&quot;</span>),</a>
<a class="sourceLine" id="cb7-16" data-line-number="16"> <span class="dt">pt =</span> <span class="kw">mo_name</span>(<span class="st">&quot;CoNS&quot;</span>, <span class="dt">language =</span> <span class="st">&quot;pt&quot;</span>),</a>
<a class="sourceLine" id="cb7-10" data-line-number="10">run_it &lt;-<span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span>(<span class="dt">en =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"en"</span>),</a>
<a class="sourceLine" id="cb7-11" data-line-number="11"> <span class="dt">de =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"de"</span>),</a>
<a class="sourceLine" id="cb7-12" data-line-number="12"> <span class="dt">nl =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"nl"</span>),</a>
<a class="sourceLine" id="cb7-13" data-line-number="13"> <span class="dt">es =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"es"</span>),</a>
<a class="sourceLine" id="cb7-14" data-line-number="14"> <span class="dt">it =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"it"</span>),</a>
<a class="sourceLine" id="cb7-15" data-line-number="15"> <span class="dt">fr =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"fr"</span>),</a>
<a class="sourceLine" id="cb7-16" data-line-number="16"> <span class="dt">pt =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"pt"</span>),</a>
<a class="sourceLine" id="cb7-17" data-line-number="17"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb7-18" data-line-number="18"><span class="kw">print</span>(run_it, <span class="dt">unit =</span> <span class="st">&quot;ms&quot;</span>, <span class="dt">signif =</span> <span class="dv">4</span>)</a>
<a class="sourceLine" id="cb7-18" data-line-number="18"><span class="kw"><a href="https://rdrr.io/r/base/print.html">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">4</span>)</a>
<a class="sourceLine" id="cb7-19" data-line-number="19"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb7-20" data-line-number="20"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb7-21" data-line-number="21"><span class="co"># en 18.35 18.55 21.13 18.70 18.79 43.22 10</span></a>
<a class="sourceLine" id="cb7-22" data-line-number="22"><span class="co"># de 19.69 19.94 20.81 20.24 20.74 25.64 10</span></a>
<a class="sourceLine" id="cb7-23" data-line-number="23"><span class="co"># nl 25.28 25.42 28.05 25.55 26.59 48.83 10</span></a>
<a class="sourceLine" id="cb7-24" data-line-number="24"><span class="co"># es 19.77 19.95 22.83 20.29 20.76 46.03 10</span></a>
<a class="sourceLine" id="cb7-25" data-line-number="25"><span class="co"># it 19.81 19.88 20.19 20.13 20.55 20.85 10</span></a>
<a class="sourceLine" id="cb7-26" data-line-number="26"><span class="co"># fr 19.62 20.02 22.79 20.26 21.23 44.33 10</span></a>
<a class="sourceLine" id="cb7-27" data-line-number="27"><span class="co"># pt 20.05 20.37 23.19 20.67 21.46 44.96 10</span></a></code></pre></div>
<a class="sourceLine" id="cb7-21" data-line-number="21"><span class="co"># en 19.99 20.17 25.15 20.21 22.19 43.86 10</span></a>
<a class="sourceLine" id="cb7-22" data-line-number="22"><span class="co"># de 21.17 21.47 26.00 21.51 21.85 44.12 10</span></a>
<a class="sourceLine" id="cb7-23" data-line-number="23"><span class="co"># nl 26.69 26.71 27.24 27.10 27.80 28.04 10</span></a>
<a class="sourceLine" id="cb7-24" data-line-number="24"><span class="co"># es 21.20 21.36 24.26 21.51 21.85 43.76 10</span></a>
<a class="sourceLine" id="cb7-25" data-line-number="25"><span class="co"># it 21.09 21.24 26.27 21.59 22.46 46.14 10</span></a>
<a class="sourceLine" id="cb7-26" data-line-number="26"><span class="co"># fr 21.16 21.35 23.98 21.51 22.11 44.93 10</span></a>
<a class="sourceLine" id="cb7-27" data-line-number="27"><span class="co"># pt 21.10 21.13 21.35 21.28 21.37 22.24 10</span></a></code></pre></div>
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<h1>How to create frequency tables</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">10 July 2019</h4>
<div class="hidden name"><code>freq.Rmd</code></div>
</div>
<div id="introduction" class="section level2">
<h2 class="hasAnchor">
<a href="#introduction" class="anchor"></a>Introduction</h2>
<p>Frequency tables (or frequency distributions) are summaries of the distribution of values in a sample. With the <code><a href="../reference/freq.html">freq()</a></code> function, you can create univariate frequency tables. Multiple variables will be pasted into one variable, so it forces a univariate distribution. We take the <code>septic_patients</code> dataset (included in this AMR package) as example.</p>
</div>
<div id="frequencies-of-one-variable" class="section level2">
<h2 class="hasAnchor">
<a href="#frequencies-of-one-variable" class="anchor"></a>Frequencies of one variable</h2>
<p>To only show and quickly review the content of one variable, you can just select this variable in various ways. Let’s say we want to get the frequencies of the <code>gender</code> variable of the <code>septic_patients</code> dataset:</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1"><span class="co"># Any of these will work:</span></a>
<a class="sourceLine" id="cb1-2" data-line-number="2"><span class="co"># freq(septic_patients$gender)</span></a>
<a class="sourceLine" id="cb1-3" data-line-number="3"><span class="co"># freq(septic_patients[, "gender"])</span></a>
<a class="sourceLine" id="cb1-4" data-line-number="4"></a>
<a class="sourceLine" id="cb1-5" data-line-number="5"><span class="co"># Using tidyverse:</span></a>
<a class="sourceLine" id="cb1-6" data-line-number="6"><span class="co"># septic_patients$gender %&gt;% freq()</span></a>
<a class="sourceLine" id="cb1-7" data-line-number="7"><span class="co"># septic_patients[, "gender"] %&gt;% freq()</span></a>
<a class="sourceLine" id="cb1-8" data-line-number="8"><span class="co"># septic_patients %&gt;% freq("gender")</span></a>
<a class="sourceLine" id="cb1-9" data-line-number="9"></a>
<a class="sourceLine" id="cb1-10" data-line-number="10"><span class="co"># Probably the fastest and easiest:</span></a>
<a class="sourceLine" id="cb1-11" data-line-number="11">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(gender) </a></code></pre></div>
<p><strong>Frequency table of <code>gender</code> from <code>septic_patients</code> (2,000 x 49)</strong></p>
<p>Class: character<br>
Length: 2,000 (of which NA: 0 = 0.00%)<br>
Unique: 2</p>
<p>Shortest: 1<br>
Longest: 1</p>
<table class="table">
<thead><tr class="header">
<th align="left"></th>
<th align="left">Item</th>
<th align="right">Count</th>
<th align="right">Percent</th>
<th align="right">Cum. Count</th>
<th align="right">Cum. Percent</th>
</tr></thead>
<tbody>
<tr class="odd">
<td align="left">1</td>
<td align="left">M</td>
<td align="right">1,031</td>
<td align="right">51.6%</td>
<td align="right">1,031</td>
<td align="right">51.6%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">F</td>
<td align="right">969</td>
<td align="right">48.4%</td>
<td align="right">2,000</td>
<td align="right">100.0%</td>
</tr>
</tbody>
</table>
<p>This immediately shows the class of the variable, its length and availability (i.e. the amount of <code>NA</code>), the amount of unique values and (most importantly) that among septic patients men are more prevalent than women.</p>
</div>
<div id="frequencies-of-more-than-one-variable" class="section level2">
<h2 class="hasAnchor">
<a href="#frequencies-of-more-than-one-variable" class="anchor"></a>Frequencies of more than one variable</h2>
<p>Multiple variables will be pasted into one variable to review individual cases, keeping a univariate frequency table.</p>
<p>For illustration, we could add some more variables to the <code>septic_patients</code> dataset to learn about bacterial properties:</p>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb2-1" data-line-number="1">my_patients &lt;-<span class="st"> </span>septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/join.html">left_join_microorganisms</a></span>()</a>
<a class="sourceLine" id="cb2-2" data-line-number="2"><span class="co"># Joining, by = "mo"</span></a></code></pre></div>
<p>Now all variables of the <code>microorganisms</code> dataset have been joined to the <code>septic_patients</code> dataset. The <code>microorganisms</code> dataset consists of the following variables:</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/colnames">colnames</a></span>(microorganisms)</a>
<a class="sourceLine" id="cb3-2" data-line-number="2"><span class="co"># [1] "mo" "col_id" "fullname" "kingdom" "phylum" </span></a>
<a class="sourceLine" id="cb3-3" data-line-number="3"><span class="co"># [6] "class" "order" "family" "genus" "species" </span></a>
<a class="sourceLine" id="cb3-4" data-line-number="4"><span class="co"># [11] "subspecies" "rank" "ref" "species_id" "source" </span></a>
<a class="sourceLine" id="cb3-5" data-line-number="5"><span class="co"># [16] "prevalence"</span></a></code></pre></div>
<p>If we compare the dimensions between the old and new dataset, we can see that these 15 variables were added:</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/dim">dim</a></span>(septic_patients)</a>
<a class="sourceLine" id="cb4-2" data-line-number="2"><span class="co"># [1] 2000 49</span></a>
<a class="sourceLine" id="cb4-3" data-line-number="3"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/dim">dim</a></span>(my_patients)</a>
<a class="sourceLine" id="cb4-4" data-line-number="4"><span class="co"># [1] 2000 64</span></a></code></pre></div>
<p>So now the <code>genus</code> and <code>species</code> variables are available. A frequency table of these combined variables can be created like this:</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" data-line-number="1">my_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb5-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(genus, species, <span class="dt">nmax =</span> <span class="dv">15</span>)</a></code></pre></div>
<p><strong>Frequency table of <code>genus</code> and <code>species</code> from <code>my_patients</code> (2,000 x 64)</strong></p>
<p>Columns: 2<br>
Length: 2,000 (of which NA: 0 = 0.00%)<br>
Unique: 95</p>
<p>Shortest: 8<br>
Longest: 34</p>
<table class="table">
<thead><tr class="header">
<th align="left"></th>
<th align="left">Item</th>
<th align="right">Count</th>
<th align="right">Percent</th>
<th align="right">Cum. Count</th>
<th align="right">Cum. Percent</th>
</tr></thead>
<tbody>
<tr class="odd">
<td align="left">1</td>
<td align="left">Escherichia coli</td>
<td align="right">467</td>
<td align="right">23.4%</td>
<td align="right">467</td>
<td align="right">23.4%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">Staphylococcus coagulase-negative</td>
<td align="right">313</td>
<td align="right">15.6%</td>
<td align="right">780</td>
<td align="right">39.0%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">Staphylococcus aureus</td>
<td align="right">235</td>
<td align="right">11.7%</td>
<td align="right">1,015</td>
<td align="right">50.7%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">Staphylococcus epidermidis</td>
<td align="right">174</td>
<td align="right">8.7%</td>
<td align="right">1,189</td>
<td align="right">59.4%</td>
</tr>
<tr class="odd">
<td align="left">5</td>
<td align="left">Streptococcus pneumoniae</td>
<td align="right">117</td>
<td align="right">5.8%</td>
<td align="right">1,306</td>
<td align="right">65.3%</td>
</tr>
<tr class="even">
<td align="left">6</td>
<td align="left">Staphylococcus hominis</td>
<td align="right">81</td>
<td align="right">4.0%</td>
<td align="right">1,387</td>
<td align="right">69.4%</td>
</tr>
<tr class="odd">
<td align="left">7</td>
<td align="left">Klebsiella pneumoniae</td>
<td align="right">58</td>
<td align="right">2.9%</td>
<td align="right">1,445</td>
<td align="right">72.2%</td>
</tr>
<tr class="even">
<td align="left">8</td>
<td align="left">Enterococcus faecalis</td>
<td align="right">39</td>
<td align="right">2.0%</td>
<td align="right">1,484</td>
<td align="right">74.2%</td>
</tr>
<tr class="odd">
<td align="left">9</td>
<td align="left">Proteus mirabilis</td>
<td align="right">36</td>
<td align="right">1.8%</td>
<td align="right">1,520</td>
<td align="right">76.0%</td>
</tr>
<tr class="even">
<td align="left">10</td>
<td align="left">Pseudomonas aeruginosa</td>
<td align="right">30</td>
<td align="right">1.5%</td>
<td align="right">1,550</td>
<td align="right">77.5%</td>
</tr>
<tr class="odd">
<td align="left">11</td>
<td align="left">Serratia marcescens</td>
<td align="right">25</td>
<td align="right">1.2%</td>
<td align="right">1,575</td>
<td align="right">78.8%</td>
</tr>
<tr class="even">
<td align="left">12</td>
<td align="left">Enterobacter cloacae</td>
<td align="right">23</td>
<td align="right">1.2%</td>
<td align="right">1,598</td>
<td align="right">79.9%</td>
</tr>
<tr class="odd">
<td align="left">13</td>
<td align="left">Enterococcus faecium</td>
<td align="right">21</td>
<td align="right">1.0%</td>
<td align="right">1,619</td>
<td align="right">81.0%</td>
</tr>
<tr class="even">
<td align="left">14</td>
<td align="left">Staphylococcus capitis</td>
<td align="right">21</td>
<td align="right">1.0%</td>
<td align="right">1,640</td>
<td align="right">82.0%</td>
</tr>
<tr class="odd">
<td align="left">15</td>
<td align="left">Bacteroides fragilis</td>
<td align="right">20</td>
<td align="right">1.0%</td>
<td align="right">1,660</td>
<td align="right">83.0%</td>
</tr>
</tbody>
</table>
<p>(omitted 80 entries, n = 340 [17.0%])</p>
</div>
<div id="frequencies-of-numeric-values" class="section level2">
<h2 class="hasAnchor">
<a href="#frequencies-of-numeric-values" class="anchor"></a>Frequencies of numeric values</h2>
<p>Frequency tables can be created of any input.</p>
<p>In case of numeric values (like integers, doubles, etc.) additional descriptive statistics will be calculated and shown into the header:</p>
<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb6-1" data-line-number="1"><span class="co"># # get age distribution of unique patients</span></a>
<a class="sourceLine" id="cb6-2" data-line-number="2">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb6-3" data-line-number="3"><span class="st"> </span><span class="kw">distinct</span>(patient_id, <span class="dt">.keep_all =</span> <span class="ot">TRUE</span>) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb6-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(age, <span class="dt">nmax =</span> <span class="dv">5</span>, <span class="dt">header =</span> <span class="ot">TRUE</span>)</a></code></pre></div>
<p><strong>Frequency table of <code>age</code> from a <code>data.frame</code> (981 x 49)</strong></p>
<p>Class: numeric<br>
Length: 981 (of which NA: 0 = 0.00%)<br>
Unique: 73</p>
<p>Mean: 71.08<br>
SD: 14.05 (CV: 0.20, MAD: 13.34)<br>
Five-Num: 14 | 63 | 74 | 82 | 97 (IQR: 19, CQV: 0.13)<br>
Outliers: 15 (unique count: 12)</p>
<table class="table">
<thead><tr class="header">
<th align="left"></th>
<th align="right">Item</th>
<th align="right">Count</th>
<th align="right">Percent</th>
<th align="right">Cum. Count</th>
<th align="right">Cum. Percent</th>
</tr></thead>
<tbody>
<tr class="odd">
<td align="left">1</td>
<td align="right">83</td>
<td align="right">44</td>
<td align="right">4.5%</td>
<td align="right">44</td>
<td align="right">4.5%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="right">76</td>
<td align="right">43</td>
<td align="right">4.4%</td>
<td align="right">87</td>
<td align="right">8.9%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="right">75</td>
<td align="right">37</td>
<td align="right">3.8%</td>
<td align="right">124</td>
<td align="right">12.6%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="right">82</td>
<td align="right">33</td>
<td align="right">3.4%</td>
<td align="right">157</td>
<td align="right">16.0%</td>
</tr>
<tr class="odd">
<td align="left">5</td>
<td align="right">78</td>
<td align="right">32</td>
<td align="right">3.3%</td>
<td align="right">189</td>
<td align="right">19.3%</td>
</tr>
</tbody>
</table>
<p>(omitted 68 entries, n = 792 [80.7%])</p>
<p>So the following properties are determined, where <code>NA</code> values are always ignored:</p>
<ul>
<li><p><strong>Mean</strong></p></li>
<li><p><strong>Standard deviation</strong></p></li>
<li><p><strong>Coefficient of variation</strong> (CV), the standard deviation divided by the mean</p></li>
<li><p><strong>Mean absolute deviation</strong> (MAD), the median of the absolute deviations from the median - a more robust statistic than the standard deviation</p></li>
<li><p><strong>Five numbers of Tukey</strong>, namely: the minimum, Q1, median, Q3 and maximum</p></li>
<li><p><strong>Interquartile range</strong> (IQR), the distance between Q1 and Q3</p></li>
<li><p><strong>Coefficient of quartile variation</strong> (CQV, sometimes called <em>coefficient of dispersion</em>), calculated as (Q3 - Q1) / (Q3 + Q1) using <code><a href="https://www.rdocumentation.org/packages/stats/topics/quantile">quantile()</a></code> with <code>type = 6</code> as quantile algorithm to comply with SPSS standards</p></li>
<li><p><strong>Outliers</strong> (total count and unique count)</p></li>
</ul>
<p>So for example, the above frequency table quickly shows the median age of patients being 74.</p>
</div>
<div id="frequencies-of-factors" class="section level2">
<h2 class="hasAnchor">
<a href="#frequencies-of-factors" class="anchor"></a>Frequencies of factors</h2>
<p>To sort frequencies of factors on their levels instead of item count, use the <code>sort.count</code> parameter.</p>
<p><code>sort.count</code> is <code>TRUE</code> by default. Compare this default behaviour…</p>
<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb7-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb7-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(hospital_id)</a></code></pre></div>
<p><strong>Frequency table of <code>hospital_id</code> from <code>septic_patients</code> (2,000 x 49)</strong></p>
<p>Class: factor (numeric)<br>
Length: 2,000 (of which NA: 0 = 0.00%)<br>
Levels: 4: A, B, C, D<br>
Unique: 4</p>
<table class="table">
<thead><tr class="header">
<th align="left"></th>
<th align="left">Item</th>
<th align="right">Count</th>
<th align="right">Percent</th>
<th align="right">Cum. Count</th>
<th align="right">Cum. Percent</th>
</tr></thead>
<tbody>
<tr class="odd">
<td align="left">1</td>
<td align="left">D</td>
<td align="right">762</td>
<td align="right">38.1%</td>
<td align="right">762</td>
<td align="right">38.1%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">B</td>
<td align="right">663</td>
<td align="right">33.2%</td>
<td align="right">1,425</td>
<td align="right">71.2%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">A</td>
<td align="right">321</td>
<td align="right">16.0%</td>
<td align="right">1,746</td>
<td align="right">87.3%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">C</td>
<td align="right">254</td>
<td align="right">12.7%</td>
<td align="right">2,000</td>
<td align="right">100.0%</td>
</tr>
</tbody>
</table>
<p>… to this, where items are now sorted on factor levels:</p>
<div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb8-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb8-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(hospital_id, <span class="dt">sort.count =</span> <span class="ot">FALSE</span>)</a></code></pre></div>
<p><strong>Frequency table of <code>hospital_id</code> from <code>septic_patients</code> (2,000 x 49)</strong></p>
<p>Class: factor (numeric)<br>
Length: 2,000 (of which NA: 0 = 0.00%)<br>
Levels: 4: A, B, C, D<br>
Unique: 4</p>
<table class="table">
<thead><tr class="header">
<th align="left"></th>
<th align="left">Item</th>
<th align="right">Count</th>
<th align="right">Percent</th>
<th align="right">Cum. Count</th>
<th align="right">Cum. Percent</th>
</tr></thead>
<tbody>
<tr class="odd">
<td align="left">1</td>
<td align="left">A</td>
<td align="right">321</td>
<td align="right">16.0%</td>
<td align="right">321</td>
<td align="right">16.0%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">B</td>
<td align="right">663</td>
<td align="right">33.2%</td>
<td align="right">984</td>
<td align="right">49.2%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">C</td>
<td align="right">254</td>
<td align="right">12.7%</td>
<td align="right">1,238</td>
<td align="right">61.9%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">D</td>
<td align="right">762</td>
<td align="right">38.1%</td>
<td align="right">2,000</td>
<td align="right">100.0%</td>
</tr>
</tbody>
</table>
<p>All classes will be printed into the header. Variables with the new <code>rsi</code> class of this AMR package are actually ordered factors and have three classes (look at <code>Class</code> in the header):</p>
<div class="sourceCode" id="cb9"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb9-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb9-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(AMX, <span class="dt">header =</span> <span class="ot">TRUE</span>)</a></code></pre></div>
<p><strong>Frequency table of <code>AMX</code> from <code>septic_patients</code> (2,000 x 49)</strong></p>
<p>Class: factor &gt; ordered &gt; rsi (numeric)<br>
Length: 2,000 (of which NA: 771 = 38.55%)<br>
Levels: 3: S &lt; I &lt; R<br>
Unique: 3</p>
<p>Drug: Amoxicillin (AMX, J01CA04)<br>
Group: Beta-lactams/penicillins<br>
%SI: 44.43%</p>
<table class="table">
<thead><tr class="header">
<th align="left"></th>
<th align="left">Item</th>
<th align="right">Count</th>
<th align="right">Percent</th>
<th align="right">Cum. Count</th>
<th align="right">Cum. Percent</th>
</tr></thead>
<tbody>
<tr class="odd">
<td align="left">1</td>
<td align="left">R</td>
<td align="right">683</td>
<td align="right">55.6%</td>
<td align="right">683</td>
<td align="right">55.6%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">S</td>
<td align="right">543</td>
<td align="right">44.2%</td>
<td align="right">1,226</td>
<td align="right">99.8%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">I</td>
<td align="right">3</td>
<td align="right">0.2%</td>
<td align="right">1,229</td>
<td align="right">100.0%</td>
</tr>
</tbody>
</table>
</div>
<div id="frequencies-of-dates" class="section level2">
<h2 class="hasAnchor">
<a href="#frequencies-of-dates" class="anchor"></a>Frequencies of dates</h2>
<p>Frequencies of dates will show the oldest and newest date in the data, and the amount of days between them:</p>
<div class="sourceCode" id="cb10"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb10-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb10-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(date, <span class="dt">nmax =</span> <span class="dv">5</span>, <span class="dt">header =</span> <span class="ot">TRUE</span>)</a></code></pre></div>
<p><strong>Frequency table of <code>date</code> from <code>septic_patients</code> (2,000 x 49)</strong></p>
<p>Class: Date (numeric)<br>
Length: 2,000 (of which NA: 0 = 0.00%)<br>
Unique: 1,140</p>
<p>Oldest: 2 January 2002<br>
Newest: 28 December 2017 (+5,839)<br>
Median: 31 July 2009 (47.39%)</p>
<table class="table">
<thead><tr class="header">
<th align="left"></th>
<th align="left">Item</th>
<th align="right">Count</th>
<th align="right">Percent</th>
<th align="right">Cum. Count</th>
<th align="right">Cum. Percent</th>
</tr></thead>
<tbody>
<tr class="odd">
<td align="left">1</td>
<td align="left">2016-05-21</td>
<td align="right">10</td>
<td align="right">0.5%</td>
<td align="right">10</td>
<td align="right">0.5%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">2004-11-15</td>
<td align="right">8</td>
<td align="right">0.4%</td>
<td align="right">18</td>
<td align="right">0.9%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">2013-07-29</td>
<td align="right">8</td>
<td align="right">0.4%</td>
<td align="right">26</td>
<td align="right">1.3%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">2017-06-12</td>
<td align="right">8</td>
<td align="right">0.4%</td>
<td align="right">34</td>
<td align="right">1.7%</td>
</tr>
<tr class="odd">
<td align="left">5</td>
<td align="left">2015-11-19</td>
<td align="right">7</td>
<td align="right">0.4%</td>
<td align="right">41</td>
<td align="right">2.0%</td>
</tr>
</tbody>
</table>
<p>(omitted 1,135 entries, n = 1,959 [98.0%])</p>
</div>
<div id="assigning-a-frequency-table-to-an-object" class="section level2">
<h2 class="hasAnchor">
<a href="#assigning-a-frequency-table-to-an-object" class="anchor"></a>Assigning a frequency table to an object</h2>
<p>A frequency table is actually a regular <code>data.frame</code>, with the exception that it contains an additional class.</p>
<div class="sourceCode" id="cb11"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb11-1" data-line-number="1">my_df &lt;-<span class="st"> </span>septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(age)</a>
<a class="sourceLine" id="cb11-2" data-line-number="2"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/class">class</a></span>(my_df)</a></code></pre></div>
<p>[1] “freq” “data.frame”</p>
<p>Because of this additional class, a frequency table prints like the examples above. But the object itself contains the complete table without a row limitation:</p>
<div class="sourceCode" id="cb12"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb12-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/dim">dim</a></span>(my_df)</a></code></pre></div>
<p>[1] 74 5</p>
</div>
<div id="additional-parameters" class="section level2">
<h2 class="hasAnchor">
<a href="#additional-parameters" class="anchor"></a>Additional parameters</h2>
<div id="parameter-na-rm" class="section level3">
<h3 class="hasAnchor">
<a href="#parameter-na-rm" class="anchor"></a>Parameter <code>na.rm</code>
</h3>
<p>With the <code>na.rm</code> parameter you can remove <code>NA</code> values from the frequency table (defaults to <code>TRUE</code>, but the number of <code>NA</code> values will always be shown into the header):</p>
<div class="sourceCode" id="cb13"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb13-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb13-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(AMX, <span class="dt">na.rm =</span> <span class="ot">FALSE</span>)</a></code></pre></div>
<p><strong>Frequency table of <code>AMX</code> from <code>septic_patients</code> (2,000 x 49)</strong></p>
<p>Class: factor &gt; ordered &gt; rsi (numeric)<br>
Length: 2,000 (of which NA: 771 = 38.55%)<br>
Levels: 3: S &lt; I &lt; R<br>
Unique: 4</p>
<p>Drug: Amoxicillin (AMX, J01CA04)<br>
Group: Beta-lactams/penicillins<br>
%SI: 44.43%</p>
<table class="table">
<thead><tr class="header">
<th align="left"></th>
<th align="left">Item</th>
<th align="right">Count</th>
<th align="right">Percent</th>
<th align="right">Cum. Count</th>
<th align="right">Cum. Percent</th>
</tr></thead>
<tbody>
<tr class="odd">
<td align="left">1</td>
<td align="left">(NA)</td>
<td align="right">771</td>
<td align="right">38.6%</td>
<td align="right">771</td>
<td align="right">38.6%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">R</td>
<td align="right">683</td>
<td align="right">34.2%</td>
<td align="right">1,454</td>
<td align="right">72.7%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">S</td>
<td align="right">543</td>
<td align="right">27.2%</td>
<td align="right">1,997</td>
<td align="right">99.8%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">I</td>
<td align="right">3</td>
<td align="right">0.2%</td>
<td align="right">2,000</td>
<td align="right">100.0%</td>
</tr>
</tbody>
</table>
</div>
<div id="parameter-row-names" class="section level3">
<h3 class="hasAnchor">
<a href="#parameter-row-names" class="anchor"></a>Parameter <code>row.names</code>
</h3>
<p>A frequency table shows row indices. To remove them, use <code>row.names = FALSE</code>:</p>
<div class="sourceCode" id="cb14"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb14-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb14-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(hospital_id, <span class="dt">row.names =</span> <span class="ot">FALSE</span>)</a></code></pre></div>
<p><strong>Frequency table of <code>hospital_id</code> from <code>septic_patients</code> (2,000 x 49)</strong></p>
<p>Class: factor (numeric)<br>
Length: 2,000 (of which NA: 0 = 0.00%)<br>
Levels: 4: A, B, C, D<br>
Unique: 4</p>
<table class="table">
<thead><tr class="header">
<th align="left">Item</th>
<th align="right">Count</th>
<th align="right">Percent</th>
<th align="right">Cum. Count</th>
<th align="right">Cum. Percent</th>
</tr></thead>
<tbody>
<tr class="odd">
<td align="left">D</td>
<td align="right">762</td>
<td align="right">38.1%</td>
<td align="right">762</td>
<td align="right">38.1%</td>
</tr>
<tr class="even">
<td align="left">B</td>
<td align="right">663</td>
<td align="right">33.2%</td>
<td align="right">1,425</td>
<td align="right">71.2%</td>
</tr>
<tr class="odd">
<td align="left">A</td>
<td align="right">321</td>
<td align="right">16.0%</td>
<td align="right">1,746</td>
<td align="right">87.3%</td>
</tr>
<tr class="even">
<td align="left">C</td>
<td align="right">254</td>
<td align="right">12.7%</td>
<td align="right">2,000</td>
<td align="right">100.0%</td>
</tr>
</tbody>
</table>
</div>
<div id="parameter-markdown" class="section level3">
<h3 class="hasAnchor">
<a href="#parameter-markdown" class="anchor"></a>Parameter <code>markdown</code>
</h3>
<p>The <code>markdown</code> parameter is <code>TRUE</code> at default in non-interactive sessions, like in reports created with R Markdown. This will always print all rows, unless <code>nmax</code> is set. Without markdown (like in regular R), a frequency table would print like:</p>
<div class="sourceCode" id="cb15"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb15-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb15-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(hospital_id, <span class="dt">markdown =</span> <span class="ot">FALSE</span>)</a>
<a class="sourceLine" id="cb15-3" data-line-number="3"><span class="co"># Frequency table of `hospital_id` from `septic_patients` (2,000 x 49) </span></a>
<a class="sourceLine" id="cb15-4" data-line-number="4"><span class="co"># </span></a>
<a class="sourceLine" id="cb15-5" data-line-number="5"><span class="co"># Class: factor (numeric)</span></a>
<a class="sourceLine" id="cb15-6" data-line-number="6"><span class="co"># Length: 2,000 (of which NA: 0 = 0.00%)</span></a>
<a class="sourceLine" id="cb15-7" data-line-number="7"><span class="co"># Levels: 4: A, B, C, D</span></a>
<a class="sourceLine" id="cb15-8" data-line-number="8"><span class="co"># Unique: 4</span></a>
<a class="sourceLine" id="cb15-9" data-line-number="9"><span class="co"># </span></a>
<a class="sourceLine" id="cb15-10" data-line-number="10"><span class="co"># Item Count Percent Cum. Count Cum. Percent</span></a>
<a class="sourceLine" id="cb15-11" data-line-number="11"><span class="co"># --- ----- ------ -------- ----------- -------------</span></a>
<a class="sourceLine" id="cb15-12" data-line-number="12"><span class="co"># 1 D 762 38.1% 762 38.1%</span></a>
<a class="sourceLine" id="cb15-13" data-line-number="13"><span class="co"># 2 B 663 33.2% 1,425 71.2%</span></a>
<a class="sourceLine" id="cb15-14" data-line-number="14"><span class="co"># 3 A 321 16.0% 1,746 87.3%</span></a>
<a class="sourceLine" id="cb15-15" data-line-number="15"><span class="co"># 4 C 254 12.7% 2,000 100.0%</span></a></code></pre></div>
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<h1>How to get properties of a microorganism</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">07 June 2019</h4>
<div class="hidden name"><code>mo_property.Rmd</code></div>
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<h1>How to predict antimicrobial resistance</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">28 August 2019</h4>
<h4 class="date">13 October 2019</h4>
<div class="hidden name"><code>resistance_predict.Rmd</code></div>
@ -199,9 +201,9 @@
<a href="#needed-r-packages" class="anchor"></a>Needed R packages</h2>
<p>As with many uses in R, we need some additional packages for AMR analysis. Our package works closely together with the <a href="https://www.tidyverse.org">tidyverse packages</a> <a href="https://dplyr.tidyverse.org/"><code>dplyr</code></a> and <a href="https://ggplot2.tidyverse.org"><code>ggplot2</code></a> by Dr Hadley Wickham. The tidyverse tremendously improves the way we conduct data science - it allows for a very natural way of writing syntaxes and creating beautiful plots in R.</p>
<p>Our <code>AMR</code> package depends on these packages and even extends their use and functions.</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(dplyr)</a>
<a class="sourceLine" id="cb1-2" data-line-number="2"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(ggplot2)</a>
<a class="sourceLine" id="cb1-3" data-line-number="3"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(AMR)</a>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span>(dplyr)</a>
<a class="sourceLine" id="cb1-2" data-line-number="2"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span>(ggplot2)</a>
<a class="sourceLine" id="cb1-3" data-line-number="3"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span>(AMR)</a>
<a class="sourceLine" id="cb1-4" data-line-number="4"></a>
<a class="sourceLine" id="cb1-5" data-line-number="5"><span class="co"># (if not yet installed, install with:)</span></a>
<a class="sourceLine" id="cb1-6" data-line-number="6"><span class="co"># install.packages(c("tidyverse", "AMR"))</span></a></code></pre></div>
@ -282,7 +284,7 @@
<a class="sourceLine" id="cb4-28" data-line-number="28"><span class="co"># 26 2028 0.47970658 0.3804212 0.5789920 NA NA 0.47970658</span></a>
<a class="sourceLine" id="cb4-29" data-line-number="29"><span class="co"># 27 2029 0.50734745 0.4021241 0.6125708 NA NA 0.50734745</span></a></code></pre></div>
<p>The function <code>plot</code> is available in base R, and can be extended by other packages to depend the output based on the type of input. We extended its function to cope with resistance predictions:</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/graphics/topics/plot">plot</a></span>(predict_TZP)</a></code></pre></div>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" data-line-number="1"><span class="kw"><a href="https://rdrr.io/r/graphics/plot.html">plot</a></span>(predict_TZP)</a></code></pre></div>
<p><img src="resistance_predict_files/figure-html/unnamed-chunk-4-1.png" width="720"></p>
<p>This is the fastest way to plot the result. It automatically adds the right axes, error bars, titles, number of available observations and type of model.</p>
<p>We also support the <code>ggplot2</code> package with our custom function <code><a href="../reference/resistance_predict.html">ggplot_rsi_predict()</a></code> to create more appealing plots:</p>
@ -321,21 +323,21 @@
<td>
<code>"binomial"</code> or <code>"binom"</code> or <code>"logit"</code>
</td>
<td><code><a href="https://www.rdocumentation.org/packages/stats/topics/glm">glm(..., family = binomial)</a></code></td>
<td><code><a href="https://rdrr.io/r/stats/glm.html">glm(..., family = binomial)</a></code></td>
<td>Generalised linear model with binomial distribution</td>
</tr>
<tr class="even">
<td>
<code>"loglin"</code> or <code>"poisson"</code>
</td>
<td><code><a href="https://www.rdocumentation.org/packages/stats/topics/glm">glm(..., family = poisson)</a></code></td>
<td><code><a href="https://rdrr.io/r/stats/glm.html">glm(..., family = poisson)</a></code></td>
<td>Generalised linear model with poisson distribution</td>
</tr>
<tr class="odd">
<td>
<code>"lin"</code> or <code>"linear"</code>
</td>
<td><code><a href="https://www.rdocumentation.org/packages/stats/topics/lm">lm()</a></code></td>
<td><code><a href="https://rdrr.io/r/stats/lm.html">lm()</a></code></td>
<td>Linear model</td>
</tr>
</tbody>
@ -349,14 +351,14 @@
<p><img src="resistance_predict_files/figure-html/unnamed-chunk-7-1.png" width="720"></p>
<p>This seems more likely, doesn’t it?</p>
<p>The model itself is also available from the object, as an <code>attribute</code>:</p>
<div class="sourceCode" id="cb10"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb10-1" data-line-number="1">model &lt;-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/attributes">attributes</a></span>(predict_TZP)<span class="op">$</span>model</a>
<div class="sourceCode" id="cb10"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb10-1" data-line-number="1">model &lt;-<span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/attributes.html">attributes</a></span>(predict_TZP)<span class="op">$</span>model</a>
<a class="sourceLine" id="cb10-2" data-line-number="2"></a>
<a class="sourceLine" id="cb10-3" data-line-number="3"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/summary">summary</a></span>(model)<span class="op">$</span>family</a>
<a class="sourceLine" id="cb10-3" data-line-number="3"><span class="kw"><a href="https://rdrr.io/r/base/summary.html">summary</a></span>(model)<span class="op">$</span>family</a>
<a class="sourceLine" id="cb10-4" data-line-number="4"><span class="co"># </span></a>
<a class="sourceLine" id="cb10-5" data-line-number="5"><span class="co"># Family: binomial </span></a>
<a class="sourceLine" id="cb10-6" data-line-number="6"><span class="co"># Link function: logit</span></a>
<a class="sourceLine" id="cb10-7" data-line-number="7"></a>
<a class="sourceLine" id="cb10-8" data-line-number="8"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/summary">summary</a></span>(model)<span class="op">$</span>coefficients</a>
<a class="sourceLine" id="cb10-8" data-line-number="8"><span class="kw"><a href="https://rdrr.io/r/base/summary.html">summary</a></span>(model)<span class="op">$</span>coefficients</a>
<a class="sourceLine" id="cb10-9" data-line-number="9"><span class="co"># Estimate Std. Error z value Pr(&gt;|z|)</span></a>
<a class="sourceLine" id="cb10-10" data-line-number="10"><span class="co"># (Intercept) -224.3987194 48.0335384 -4.671709 2.987038e-06</span></a>
<a class="sourceLine" id="cb10-11" data-line-number="11"><span class="co"># year 0.1106102 0.0238753 4.632831 3.606990e-06</span></a></code></pre></div>
@ -365,6 +367,7 @@
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@ -231,11 +231,11 @@
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<h1 class="page-header">
<a href="#amr-0-7-1-9105" class="anchor"></a>AMR 0.7.1.9105<small> Unreleased </small>
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</h1>
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<p><small>Last updated: 13-Oct-2019</small></p>
<div id="breaking" class="section level3">
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<p>These functions are so-called '<a href='https://www.rdocumentation.org/packages/base/topics/Deprecated'>Deprecated</a>'. They will be removed in a future release. Using the functions will give a warning with the name of the function it has been replaced by (if there is one).</p>
<p>These functions are so-called '<a href='https://rdrr.io/r/base/Deprecated.html'>Deprecated</a>'. They will be removed in a future release. Using the functions will give a warning with the name of the function it has been replaced by (if there is one).</p>
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<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9055</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0</span>
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@ -189,7 +194,6 @@
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@ -207,7 +211,7 @@
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@ -229,12 +234,11 @@
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<div class="ref-description">
<p>Welcome to the <code>AMR</code> package.</p>
</div>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p><code>AMR</code> is a free and open-source R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. It supports any table format, including WHONET/EARS-Net data.</p>
@ -253,23 +257,24 @@
<li><p>Applying EUCAST expert rules</p></li>
<li><p>Descriptive statistics: frequency tables, kurtosis and skewness</p></li>
</ul>
<h2 class="hasAnchor" id="authors"><a class="anchor" href="#authors"></a>Authors</h2>
<p>Matthijs S. Berends[1,2] Christian F. Luz[1], Erwin E.A. Hassing[2], Corinna Glasner[1], Alex W. Friedrich[1], Bhanu N.M. Sinha[1] <br /></p>
<p>Matthijs S. Berends[1,2] Christian F. Luz[1], Erwin E.A. Hassing[2], Corinna Glasner[1], Alex W. Friedrich[1], Bhanu N.M. Sinha[1] <br /></p>
<p>[1] Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands - <a href='https://www.rug.nl'>https://www.rug.nl</a> <a href='https://www.umcg.nl'>https://www.umcg.nl</a> <br />
[2] Certe Medical Diagnostics &amp; Advice, Groningen, the Netherlands - <a href='https://www.certe.nl'>https://www.certe.nl</a></p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="contact-us"><a class="anchor" href="#contact-us"></a>Contact us</h2>
<p>For suggestions, comments or questions, please contact us at:</p>
<p>For suggestions, comments or questions, please contact us at:</p>
<p>Matthijs S. Berends <br />
m.s.berends [at] umcg [dot] nl <br />
Department of Medical Microbiology, University of Groningen <br />
@ -278,33 +283,30 @@ Post Office Box 30001 <br />
9700 RB Groningen</p>
<p>If you have found a bug, please file a new issue at: <br />
<a href='https://gitlab.com/msberends/AMR/issues'>https://gitlab.com/msberends/AMR/issues</a></p>
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<p>Developed by <a href='https://www.rug.nl/staff/m.s.berends/'>Matthijs S. Berends</a>, <a href='https://www.rug.nl/staff/c.f.luz/'>Christian F. Luz</a>, <a href='https://www.rug.nl/staff/a.w.friedrich/'>Alex W. Friedrich</a>, <a href='https://www.rug.nl/staff/b.sinha/'>Bhanu N. M. Sinha</a>, <a href='https://www.rug.nl/staff/c.j.albers/'>Casper J. Albers</a>, <a href='https://www.rug.nl/staff/c.glasner/'>Corinna Glasner</a>.</p>
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@ -327,6 +329,8 @@ Post Office Box 30001 <br />
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51
docs/reference/WHOCC.html

@ -15,21 +15,25 @@
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<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." />
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<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9055</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0</span>
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@ -189,7 +194,6 @@
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@ -207,7 +211,7 @@
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@ -218,6 +222,7 @@
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@ -229,57 +234,53 @@
</div>
<div class="ref-description">
<p>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.</p>
</div>
<h2 class="hasAnchor" id="whocc"><a class="anchor" href="#whocc"></a>WHOCC</h2>
<p><img src='figures/logo_who.png' height=60px style=margin-bottom:5px /> <br />
<p><img src='figures/logo_who.png' height=60px style=margin-bottom:5px /> <br />
This package contains <strong>all ~450 antimicrobial 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://www.whocc.no'>https://www.whocc.no</a>) and the Pharmaceuticals Community Register of the European Commission (<a href='http://ec.europa.eu/health/documents/community-register/html/atc.htm'>http://ec.europa.eu/health/documents/community-register/html/atc.htm</a>).</p>
<p>These have become the gold standard for international drug utilisation monitoring and research.</p>
<p>The WHOCC is located in Oslo at the Norwegian Institute of Public Health and funded by the Norwegian government. The European Commission is the executive of the European Union and promotes its general interest.</p>
<p><strong>NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package. See <a href='https://www.whocc.no/copyright_disclaimer/'>https://www.whocc.no/copyright_disclaimer/</a>.</strong></p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<span class='fu'><a href='as.ab.html'>as.ab</a></span>(<span class='st'>"meropenem"</span>)
<pre class="examples"><span class='fu'><a href='as.ab.html'>as.ab</a></span>(<span class='st'>"meropenem"</span>)
<span class='fu'><a href='ab_property.html'>ab_name</a></span>(<span class='st'>"J01DH02"</span>)
<span class='fu'><a href='ab_property.html'>ab_tradenames</a></span>(<span class='st'>"flucloxacillin"</span>)
<span class='co'># }</span></pre>
<span class='fu'><a href='ab_property.html'>ab_tradenames</a></span>(<span class='st'>"flucloxacillin"</span>)</pre>
</div>
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<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked">
<li><a href="#whocc">WHOCC</a></li>
<li><a href="#read-more-on-our-website-">Read more on our website!</a></li>
<li><a href="#examples">Examples</a></li>
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<p>Developed by <a href='https://www.rug.nl/staff/m.s.berends/'>Matthijs S. Berends</a>, <a href='https://www.rug.nl/staff/c.f.luz/'>Christian F. Luz</a>, <a href='https://www.rug.nl/staff/a.w.friedrich/'>Alex W. Friedrich</a>, <a href='https://www.rug.nl/staff/b.sinha/'>Bhanu N. M. Sinha</a>, <a href='https://www.rug.nl/staff/c.glasner/'>Corinna Glasner</a>.</p>
<p>Developed by <a href='https://www.rug.nl/staff/m.s.berends/'>Matthijs S. Berends</a>, <a href='https://www.rug.nl/staff/c.f.luz/'>Christian F. Luz</a>, <a href='https://www.rug.nl/staff/a.w.friedrich/'>Alex W. Friedrich</a>, <a href='https://www.rug.nl/staff/b.sinha/'>Bhanu N. M. Sinha</a>, <a href='https://www.rug.nl/staff/c.j.albers/'>Casper J. Albers</a>, <a href='https://www.rug.nl/staff/c.glasner/'>Corinna Glasner</a>.</p>
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@ -302,6 +303,8 @@ This package contains <strong>all ~450 antimicrobial drugs</strong> and their An
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9067</span>
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<p>This example data set has the exact same structure as an export file from WHONET. Such files can be used with this package, as this example data set shows. The data itself was based on our <code><a href='example_isolates.html'>example_isolates</a></code> data set.</p>
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<pre class="usage"><span class='no'>WHONET</span></pre>
<h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
<p>A <code><a href='https://www.rdocumentation.org/packages/base/topics/data.frame'>data.frame</a></code> with 500 observations and 53 variables:</p><dl class='dl-horizontal'>
<p>A <code><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a></code> with 500 observations and 53 variables:</p><dl class='dl-horizontal'>
<dt><code>Identification number</code></dt><dd><p>ID of the sample</p></dd>
<dt><code>Specimen number</code></dt><dd><p>ID of the specimen</p></dd>
<dt><code>Organism</code></dt><dd><p>Name of the microorganism. Before analysis, you should transform this to a valid microbial class, using <code><a href='as.mo.html'>as.mo</a></code>.</p></dd>
@ -265,35 +269,35 @@
<dt><code>Comment</code></dt><dd><p>Other comments</p></dd>
<dt><code>Date of data entry</code></dt><dd><p>Date this data was entered in WHONET</p></dd>
<dt><code>AMP_ND10:CIP_EE</code></dt><dd><p>27 different antibiotics. You can lookup the abbreviatons in the <code><a href='antibiotics.html'>antibiotics</a></code> data set, or use e.g. <code><a href='ab_property.html'>ab_name</a>("AMP")</code> to get the official name immediately. Before analysis, you should transform this to a valid antibiotic class, using <code><a href='as.rsi.html'>as.rsi</a></code>.</p></dd>
</dl>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
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<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." />
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9055</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0</span>
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@ -189,7 +194,6 @@
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@ -207,7 +211,7 @@
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@ -229,9 +234,7 @@
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<div class="ref-description">
<p>Use these functions to return a specific property of an antibiotic from the <code><a href='antibiotics.html'>antibiotics</a></code> data set. All input values will be evaluated internally with <code><a href='as.ab.html'>as.ab</a></code>.</p>
</div>
<pre class="usage"><span class='fu'>ab_name</span>(<span class='no'>x</span>, <span class='kw'>language</span> <span class='kw'>=</span> <span class='fu'><a href='translate.html'>get_locale</a></span>(), <span class='kw'>tolower</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='no'>...</span>)
@ -255,7 +258,7 @@
<span class='fu'>ab_info</span>(<span class='no'>x</span>, <span class='kw'>language</span> <span class='kw'>=</span> <span class='fu'><a href='translate.html'>get_locale</a></span>(), <span class='no'>...</span>)
<span class='fu'>ab_property</span>(<span class='no'>x</span>, <span class='kw'>property</span> <span class='kw'>=</span> <span class='st'>"name"</span>, <span class='kw'>language</span> <span class='kw'>=</span> <span class='fu'><a href='translate.html'>get_locale</a></span>(), <span class='no'>...</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
@ -265,7 +268,7 @@
</tr>
<tr>
<th>language</th>
<td><p>language of the returned text, defaults to system language (see <code><a href='translate.html'>get_locale</a></code>) and can also be set with <code><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a>("AMR_locale")</code>. Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></td>
<td><p>language of the returned text, defaults to system language (see <code><a href='translate.html'>get_locale</a></code>) and can also be set with <code><a href='https://rdrr.io/r/base/options.html'>getOption</a>("AMR_locale")</code>. Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></td>
</tr>
<tr>
<th>tolower</th>
@ -288,7 +291,7 @@
<td><p>one of the column names of one of the <code><a href='antibiotics.html'>antibiotics</a></code> data set</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
@ -299,31 +302,27 @@
<li><p>A <code>character</code> in all other cases</p></li>
</ul>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>All output will be <a href='translate.html'>translate</a>d where possible.</p>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<p>World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: <a href='https://www.whocc.no/atc_ddd_index/'>https://www.whocc.no/atc_ddd_index/</a></p>
<p>World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: <a href='https://www.whocc.no/atc_ddd_index/'>https://www.whocc.no/atc_ddd_index/</a></p>
<p>WHONET 2019 software: <a href='http://www.whonet.org/software.html'>http://www.whonet.org/software.html</a></p>
<p>European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: <a href='http://ec.europa.eu/health/documents/community-register/html/atc.htm'>http://ec.europa.eu/health/documents/community-register/html/atc.htm</a></p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='antibiotics.html'>antibiotics</a></code></p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<span class='co'># all properties:</span>
<pre class="examples"><span class='co'># all properties:</span>
<span class='fu'>ab_name</span>(<span class='st'>"AMX"</span>) <span class='co'># "Amoxicillin"</span>
<span class='fu'>ab_atc</span>(<span class='st'>"AMX"</span>) <span class='co'># J01CA04 (ATC code from the WHO)</span>
<span class='fu'>ab_cid</span>(<span class='st'>"AMX"</span>) <span class='co'># 33613 (Compound ID from PubChem)</span>
@ -335,8 +334,8 @@
<span class='fu'>ab_atc_group1</span>(<span class='st'>"AMX"</span>) <span class='co'># "Beta-lactam antibacterials, penicillins"</span>
<span class='fu'>ab_atc_group2</span>(<span class='st'>"AMX"</span>) <span class='co'># "Penicillins with extended spectrum"</span>
<span class='fu'>ab_name</span>(<span class='kw'>x</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"AMC"</span>, <span class='st'>"PLB"</span>)) <span class='co'># "Amoxicillin/clavulanic acid" "Polymyxin B"</span>
<span class='fu'>ab_name</span>(<span class='kw'>x</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"AMC"</span>, <span class='st'>"PLB"</span>),
<span class='fu'>ab_name</span>(<span class='kw'>x</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"AMC"</span>, <span class='st'>"PLB"</span>)) <span class='co'># "Amoxicillin/clavulanic acid" "Polymyxin B"</span>
<span class='fu'>ab_name</span>(<span class='kw'>x</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"AMC"</span>, <span class='st'>"PLB"</span>),
<span class='kw'>tolower</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) <span class='co'># "amoxicillin/clavulanic acid" "polymyxin B"</span>
<span class='fu'>ab_ddd</span>(<span class='st'>"AMX"</span>, <span class='st'>"oral"</span>) <span class='co'># 1</span>
@ -351,38 +350,33 @@
<span class='fu'>ab_name</span>(<span class='st'>"fluklox"</span>) <span class='co'># "Flucloxacillin"</span>
<span class='fu'>ab_name</span>(<span class='st'>"floxapen"</span>) <span class='co'># "Flucloxacillin"</span>
<span class='fu'>ab_name</span>(<span class='fl'>21319</span>) <span class='co'># "Flucloxacillin" (using CID)</span>
<span class='fu'>ab_name</span>(<span class='st'>"J01CF05"</span>) <span class='co'># "Flucloxacillin" (using ATC)</span>
<span class='co'># }</span></pre>
<span class='fu'>ab_name</span>(<span class='st'>"J01CF05"</span>) <span class='co'># "Flucloxacillin" (using ATC)</span></pre>
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<li><a href="#arguments">Arguments</a></li>
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<li><a href="#read-more-on-our-website-">Read more on our website!</a></li>
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<p>Developed by <a href='https://www.rug.nl/staff/m.s.berends/'>Matthijs S. Berends</a>, <a href='https://www.rug.nl/staff/c.f.luz/'>Christian F. Luz</a>, <a href='https://www.rug.nl/staff/a.w.friedrich/'>Alex W. Friedrich</a>, <a href='https://www.rug.nl/staff/b.sinha/'>Bhanu N. M. Sinha</a>, <a href='https://www.rug.nl/staff/c.j.albers/'>Casper J. Albers</a>, <a href='https://www.rug.nl/staff/c.glasner/'>Corinna Glasner</a>.</p>
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<h1>Name of an antibiotic</h1>
<div class="hidden name"><code>abname.Rd</code></div>
</div>
<div class="ref-description">
<p>Convert antibiotic codes to a (trivial) antibiotic name or ATC code, or vice versa. This uses the data from <code><a href='antibiotics.html'>antibiotics</a></code>.</p>
</div>
<pre class="usage"><span class='fu'>abname</span>(<span class='no'>abcode</span>, <span class='kw'>from</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"guess"</span>, <span class='st'>"atc"</span>, <span class='st'>"certe"</span>, <span class='st'>"umcg"</span>),
<span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"official"</span>, <span class='kw'>textbetween</span> <span class='kw'>=</span> <span class='st'>" + "</span>, <span class='kw'>tolower</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>abcode</th>
<td><p>a code or name, like <code>"AMOX"</code>, <code>"AMCL"</code> or <code>"J01CA04"</code></p></td>
</tr>
<tr>
<th>from, to</th>
<td><p>type to transform from and to. See <code><a href='antibiotics.html'>antibiotics</a></code> for its column names. WIth <code>from = "guess"</code> the from will be guessed from <code>"atc"</code>, <code>"certe"</code> and <code>"umcg"</code>. When using <code>to = "atc"</code>, the ATC code will be searched using <code><a href='as.atc.html'>as.atc</a></code>.</p></td>
</tr>
<tr>
<th>textbetween</th>
<td><p>text to put between multiple returned texts</p></td>
</tr>
<tr>
<th>tolower</th>
<td><p>return output as lower case with function <code><a href='https://www.rdocumentation.org/packages/base/topics/chartr'>tolower</a></code>.</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<p><code><a href='antibiotics.html'>antibiotics</a></code></p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p><strong>The <code><a href='AMR-deprecated.html'>ab_property</a></code> functions are faster and more concise</strong>, but do not support concatenated strings, like <code>abname("AMCL+GENT"</code>.</p>
<h2 class="hasAnchor" id="whocc"><a class="anchor" href="#whocc"></a>WHOCC</h2>
<p><img src='figures/logo_who.png' height=60px style=margin-bottom:5px /> <br />
This package contains <strong>all ~500 antimicrobial 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://www.whocc.no'>https://www.whocc.no</a>) and the Pharmaceuticals Community Register of the European Commission (<a href='http://ec.europa.eu/health/documents/community-register/html/atc.htm'>http://ec.europa.eu/health/documents/community-register/html/atc.htm</a>).</p>
<p>These have become the gold standard for international drug utilisation monitoring and research.</p>
<p>The WHOCC is located in Oslo at the Norwegian Institute of Public Health and funded by the Norwegian government. The European Commission is the executive of the European Union and promotes its general interest.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a comprehensive tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<span class='fu'>abname</span>(<span class='st'>"AMCL"</span>)
<span class='co'># "Amoxicillin and beta-lactamase inhibitor"</span>
<span class='co'># It is quite flexible at default (having `from = "guess"`)</span>
<span class='fu'>abname</span>(<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"amox"</span>, <span class='st'>"J01CA04"</span>, <span class='st'>"Trimox"</span>, <span class='st'>"dispermox"</span>, <span class='st'>"Amoxil"</span>))
<span class='co'># "Amoxicillin" "Amoxicillin" "Amoxicillin" "Amoxicillin" "Amoxicillin"</span>
<span class='co'># Multiple antibiotics can be combined with "+".</span>
<span class='co'># The second antibiotic will be set to lower case when `tolower` was not set:</span>
<span class='fu'>abname</span>(<span class='st'>"AMCL+GENT"</span>, <span class='kw'>textbetween</span> <span class='kw'>=</span> <span class='st'>"/"</span>)
<span class='co'># "amoxicillin and enzyme inhibitor/gentamicin"</span>
<span class='fu'>abname</span>(<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"AMCL"</span>, <span class='st'>"GENT"</span>))
<span class='co'># "Amoxicillin and beta-lactamase inhibitor" "Gentamicin"</span>
<span class='fu'>abname</span>(<span class='st'>"AMCL"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"trivial_nl"</span>)
<span class='co'># "Amoxicilline/clavulaanzuur"</span>
<span class='fu'>abname</span>(<span class='st'>"AMCL"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"atc"</span>)
<span class='co'># "J01CR02"</span>
<span class='co'># specific codes for University Medical Center Groningen (UMCG):</span>
<span class='fu'>abname</span>(<span class='st'>"J01CR02"</span>, <span class='kw'>from</span> <span class='kw'>=</span> <span class='st'>"atc"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"umcg"</span>)
<span class='co'># "AMCL"</span>
<span class='co'># specific codes for Certe:</span>
<span class='fu'>abname</span>(<span class='st'>"J01CR02"</span>, <span class='kw'>from</span> <span class='kw'>=</span> <span class='st'>"atc"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"certe"</span>)
<span class='co'># "amcl"</span>
<span class='co'># }</span></pre>
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<h2>Contents</h2>
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<li><a href="#arguments">Arguments</a></li>
<li><a href="#source">Source</a></li>
<li><a href="#details">Details</a></li>
<li><a href="#whocc">WHOCC</a></li>
<li><a href="#read-more-on-our-website-">Read more on our website!</a></li>
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<meta property="og:description" content="Calculates age in years based on a reference date, which is the sytem date at default." />
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<div class="ref-description">
<p>Calculates age in years based on a reference date, which is the sytem date at default.</p>
</div>
<pre class="usage"><span class='fu'>age</span>(<span class='no'>x</span>, <span class='kw'>reference</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/Sys.time'>Sys.Date</a></span>(), <span class='kw'>exact</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</pre>
<pre class="usage"><span class='fu'>age</span>(<span class='no'>x</span>, <span class='kw'>reference</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/Sys.time.html'>Sys.Date</a></span>(), <span class='kw'>exact</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>x</th>
<td><p>date(s), will be coerced with <code><a href='https://www.rdocumentation.org/packages/base/topics/as.POSIXlt'>as.POSIXlt</a></code></p></td>
<td><p>date(s), will be coerced with <code><a href='https://rdrr.io/r/base/as.POSIXlt.html'>as.POSIXlt</a></code></p></td>
</tr>
<tr>
<th>reference</th>
<td><p>reference date(s) (defaults to today), will be coerced with <code><a href='https://www.rdocumentation.org/packages/base/topics/as.POSIXlt'>as.POSIXlt</a></code> and cannot be lower than <code>x</code></p></td>
<td><p>reference date(s) (defaults to today), will be coerced with <code><a href='https://rdrr.io/r/base/as.POSIXlt.html'>as.POSIXlt</a></code> and cannot be lower than <code>x</code></p></td>
</tr>
<tr>
<th>exact</th>
@ -256,58 +259,52 @@
<td><p>a logical to indicate whether missing values should be removed</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>An integer (no decimals) if <code>exact = FALSE</code>, a double (with decimals) otherwise</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p>To split ages into groups, use the <code><a href='age_groups.html'>age_groups</a></code> function.</p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<span class='co'># 10 random birth dates</span>
<span class='no'>df</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/data.frame'>data.frame</a></span>(<span class='kw'>birth_date</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/Sys.time'>Sys.Date</a></span>() - <span class='fu'><a href='https://www.rdocumentation.org/packages/stats/topics/Uniform'>runif</a></span>(<span class='fl'>10</span>) * <span class='fl'>25000</span>)
<pre class="examples"><span class='co'># 10 random birth dates</span>
<span class='no'>df</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a></span>(<span class='kw'>birth_date</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/Sys.time.html'>Sys.Date</a></span>() - <span class='fu'><a href='https://rdrr.io/r/stats/Uniform.html'>runif</a></span>(<span class='fl'>10</span>) * <span class='fl'>25000</span>)
<span class='co'># add ages</span>
<span class='no'>df</span>$<span class='no'>age</span> <span class='kw'>&lt;-</span> <span class='fu'>age</span>(<span class='no'>df</span>$<span class='no'>birth_date</span>)
<span class='co'># add exact ages</span>
<span class='no'>df</span>$<span class='no'>age_exact</span> <span class='kw'>&lt;-</span> <span class='fu'>age</span>(<span class='no'>df</span>$<span class='no'>birth_date</span>, <span class='kw'>exact</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
<span class='no'>df</span>
<span class='co'># }</span></pre>
<span class='no'>df</span></pre>
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<p>Split ages into age groups defined by the <code>split</code> parameter. This allows for easier demographic (antimicrobial resistance) analysis.</p>
</div>
<pre class="usage"><span class='fu'>age_groups</span>(<span class='no'>x</span>, <span class='kw'>split_at</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='fl'>12</span>, <span class='fl'>25</span>, <span class='fl'>55</span>, <span class='fl'>75</span>), <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</pre>
<pre class="usage"><span class='fu'>age_groups</span>(<span class='no'>x</span>, <span class='kw'>split_at</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='fl'>12</span>, <span class='fl'>25</span>, <span class='fl'>55</span>, <span class='fl'>75</span>), <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
@ -252,43 +255,40 @@
<td><p>a logical to indicate whether missing values should be removed</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>Ordered <code><a href='https://www.rdocumentation.org/packages/base/topics/factor'>factor</a></code></p>
<p>Ordered <code><a href='https://rdrr.io/r/base/factor.html'>factor</a></code></p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>To split ages, the input can be:</p><ul>
<li><p>A numeric vector. A vector of e.g. <code><a href='https://www.rdocumentation.org/packages/base/topics/c'>c(10, 20)</a></code> will split on 0-9, 10-19 and 20+. A value of only <code>50</code> will split on 0-49 and 50+.
<li><p>A numeric vector. A vector of e.g. <code><a href='https://rdrr.io/r/base/c.html'>c(10, 20)</a></code> will split on 0-9, 10-19 and 20+. A value of only <code>50</code> will split on 0-49 and 50+.
The default is to split on young children (0-11), youth (12-24), young adults (25-54), middle-aged adults (55-74) and elderly (75+).</p></li>
<li><p>A character:</p><ul>
<li><p><code>"children"</code> or <code>"kids"</code>, equivalent of: <code><a href='https://www.rdocumentation.org/packages/base/topics/c'>c(0, 1, 2, 4, 6, 13, 18)</a></code>. This will split on 0, 1, 2-3, 4-5, 6-12, 13-17 and 18+.</p></li>
<li><p><code>"elderly"</code> or <code>"seniors"</code>, equivalent of: <code><a href='https://www.rdocumentation.org/packages/base/topics/c'>c(65, 75, 85)</a></code>. This will split on 0-64, 65-74, 75-84, 85+.</p></li>
<li><p><code>"children"</code> or <code>"kids"</code>, equivalent of: <code><a href='https://rdrr.io/r/base/c.html'>c(0, 1, 2, 4, 6, 13, 18)</a></code>. This will split on 0, 1, 2-3, 4-5, 6-12, 13-17 and 18+.</p></li>
<li><p><code>"elderly"</code> or <code>"seniors"</code>, equivalent of: <code><a href='https://rdrr.io/r/base/c.html'>c(65, 75, 85)</a></code>. This will split on 0-64, 65-74, 75-84, 85+.</p></li>
<li><p><code>"fives"</code>, equivalent of: <code>1:20 * 5</code>. This will split on 0-4, 5-9, 10-14, ..., 90-94, 95-99, 100+.</p></li>
<li><p><code>"tens"</code>, equivalent of: <code>1:10 * 10</code>. This will split on 0-9, 10-19, 20-29, ... 80-89, 90-99, 100+.</p></li>
</ul></li>
</ul>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p>To determine ages, based on one or more reference dates, use the <code><a href='age.html'>age</a></code> function.</p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<span class='no'>ages</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='fl'>3</span>, <span class='fl'>8</span>, <span class='fl'>16</span>, <span class='fl'>54</span>, <span class='fl'>31</span>, <span class='fl'>76</span>, <span class='fl'>101</span>, <span class='fl'>43</span>, <span class='fl'>21</span>)
<pre class="examples"><span class='no'>ages</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='fl'>3</span>, <span class='fl'>8</span>, <span class='fl'>16</span>, <span class='fl'>54</span>, <span class='fl'>31</span>, <span class='fl'>76</span>, <span class='fl'>101</span>, <span class='fl'>43</span>, <span class='fl'>21</span>)
<span class='co'># split into 0-49 and 50+</span>
<span class='fu'>age_groups</span>(<span class='no'>ages</span>, <span class='fl'>50</span>)
<span class='co'># split into 0-19, 20-49 and 50+</span>
<span class='fu'>age_groups</span>(<span class='no'>ages</span>, <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='fl'>20</span>, <span class='fl'>50</span>))
<span class='fu'>age_groups</span>(<span class='no'>ages</span>, <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='fl'>20</span>, <span class='fl'>50</span>))
<span class='co'># split into groups of ten years</span>
<span class='fu'>age_groups</span>(<span class='no'>ages</span>, <span class='fl'>1</span>:<span class='fl'>10</span> * <span class='fl'>10</span>)
@ -301,45 +301,41 @@
<span class='co'># split specifically for children</span>
<span class='fu'>age_groups</span>(<span class='no'>ages</span>, <span class='st'>"children"</span>)
<span class='co'># same:</span>
<span class='fu'>age_groups</span>(<span class='no'>ages</span>, <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='fl'>1</span>, <span class='fl'>2</span>, <span class='fl'>4</span>, <span class='fl'>6</span>, <span class='fl'>13</span>, <span class='fl'>17</span>))
<span class='fu'>age_groups</span>(<span class='no'>ages</span>, <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='fl'>1</span>, <span class='fl'>2</span>, <span class='fl'>4</span>, <span class='fl'>6</span>, <span class='fl'>13</span>, <span class='fl'>17</span>))
<span class='co'># resistance of ciprofloxacine per age group</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>dplyr</span>)
<span class='no'>example_isolates</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='first_isolate.html'>filter_first_isolate</a></span>() <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>mo</span> <span class='kw'>==</span> <span class='fu'><a href='as.mo.html'>as.mo</a></span>(<span class='st'>"E. coli"</span>)) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='kw'>age_group</span> <span class='kw'>=</span> <span class='fu'>age_groups</span>(<span class='no'>age</span>)) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>age_group</span>, <span class='no'>CIP</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='ggplot_rsi.html'>ggplot_rsi</a></span>(<span class='kw'>x</span> <span class='kw'>=</span> <span class='st'>"age_group"</span>)
<span class='co'># }</span></pre>
<span class='fu'><a href='ggplot_rsi.html'>ggplot_rsi</a></span>(<span class='kw'>x</span> <span class='kw'>=</span> <span class='st'>"age_group"</span>)</pre>
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<meta property="og:description" content="A data set containing all antibiotics. Use as.ab or one of the ab_property functions to retrieve values from this 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." />
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<div class="ref-description">
<p>A data set containing all antibiotics. Use <code><a href='as.ab.html'>as.ab</a></code> or one of the <code><a href='ab_property.html'>ab_property</a></code> functions to retrieve values from this data set. Three identifiers are included in this data set: an antibiotic ID (<code>ab</code>, primarily used in this package) as defined by WHONET/EARS-Net, an ATC code (<code>atc</code>) as defined by the WHO, and a Compound ID (<code>cid</code>) as found in PubChem. Other properties in this data set are derived from one or more of these codes.</p>
</div>
<pre class="usage"><span class='no'>antibiotics</span></pre>
<h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
<p>A <code><a href='https://www.rdocumentation.org/packages/base/topics/data.frame'>data.frame</a></code> with 453 observations and 13 variables:</p><dl class='dl-horizontal'>
<p>A <code><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a></code> with 453 observations and 13 variables:</p><dl class='dl-horizontal'>
<dt><code>ab</code></dt><dd><p>Antibiotic ID as used in this package (like <code>AMC</code>), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available</p></dd>
<dt><code>atc</code></dt><dd><p>ATC code (Anatomical Therapeutic Chemical) as defined by the WHOCC, like <code>J01CR02</code></p></dd>
<dt><code>cid</code></dt><dd><p>Compound ID as found in PubChem</p></dd>
@ -252,67 +256,60 @@
<dt><code>oral_units</code></dt><dd><p>Units of <code>ddd_units</code></p></dd>
<dt><code>iv_ddd</code></dt><dd><p>Defined Daily Dose (DDD), parenteral treatment</p></dd>
<dt><code>iv_units</code></dt><dd><p>Units of <code>iv_ddd</code></p></dd>
</dl>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<p>World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology (WHOCC): <a href='https://www.whocc.no/atc_ddd_index/'>https://www.whocc.no/atc_ddd_index/</a></p>
<p>WHONET 2019 software: <a href='http://www.whonet.org/software.html'>http://www.whonet.org/software.html</a></p>
<p>European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: <a href='http://ec.europa.eu/health/documents/community-register/html/atc.htm'>http://ec.europa.eu/health/documents/community-register/html/atc.htm</a></p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>Properties that are based on an ATC code are only available when an ATC is available. These properties are: <code>atc_group1</code>, <code>atc_group2</code>, <code>oral_ddd</code>, <code>oral_units</code>, <code>iv_ddd</code> and <code>iv_units</code></p>
<p>Synonyms (i.e. trade names) are derived from the Compound ID (<code>cid</code>) and consequently only available where a CID is available.</p>
<h2 class="hasAnchor" id="whocc"><a class="anchor" href="#whocc"></a>WHOCC</h2>
<p><img src='figures/logo_who.png' height=60px style=margin-bottom:5px /> <br />
<p><img src='figures/logo_who.png' height=60px style=margin-bottom:5px /> <br />
This package contains <strong>all ~450 antimicrobial 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://www.whocc.no'>https://www.whocc.no</a>) and the Pharmaceuticals Community Register of the European Commission (<a href='http://ec.europa.eu/health/documents/community-register/html/atc.htm'>http://ec.europa.eu/health/documents/community-register/html/atc.htm</a>).</p>
<p>These have become the gold standard for international drug utilisation monitoring and research.</p>
<p>The WHOCC is located in Oslo at the Norwegian Institute of Public Health and funded by the Norwegian government. The European Commission is the executive of the European Union and promotes its general interest.</p>
<p><strong>NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package. See <a href='https://www.whocc.no/copyright_disclaimer/'>https://www.whocc.no/copyright_disclaimer/</a>.</strong></p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='microorganisms.html'>microorganisms</a></code></p></div>
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<h2>Contents</h2>
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<li><a href="#format">Format</a></li>
<li><a href="#source">Source</a></li>
<li><a href="#details">Details</a></li>
<li><a href="#whocc">WHOCC</a></li>
<li><a href="#read-more-on-our-website-">Read more on our website!</a></li>
<li><a href="#see-also">See also</a></li>
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<p>Developed by <a href='https://www.rug.nl/staff/m.s.berends/'>Matthijs S. Berends</a>, <a href='https://www.rug.nl/staff/c.f.luz/'>Christian F. Luz</a>, <a href='https://www.rug.nl/staff/a.w.friedrich/'>Alex W. Friedrich</a>, <a href='https://www.rug.nl/staff/b.sinha/'>Bhanu N. M. Sinha</a>, <a href='https://www.rug.nl/staff/c.j.albers/'>Casper J. Albers</a>, <a href='https://www.rug.nl/staff/c.glasner/'>Corinna Glasner</a>.</p>
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<h1>Transform to ATC code</h1>
<div class="hidden name"><code>as.atc.Rd</code></div>
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<div class="ref-description">
<p>Use this function to determine the ATC code of one or more antibiotics. The data set <code><a href='antibiotics.html'>antibiotics</a></code> will be searched for abbreviations, official names and trade names.</p>
</div>
<pre class="usage"><span class='fu'>as.atc</span>(<span class='no'>x</span>)
<span class='fu'>is.atc</span>(<span class='no'>x</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
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<th>x</th>
<td><p>character vector to determine <code>ATC</code> code</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>Character (vector) with class <code>"atc"</code>. Unknown values will return <code>NA</code>.</p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>Use the <code><a href='ab_property.html'>ab_property</a></code> functions to get properties based on the returned ATC code, see Examples.</p>
<p>In the ATC classification system, the active substances are classified in a hierarchy with five different levels. The system has fourteen main anatomical/pharmacological groups or 1st levels. Each ATC main group is divided into 2nd levels which could be either pharmacological or therapeutic groups. The 3rd and 4th levels are chemical, pharmacological or therapeutic subgroups and the 5th level is the chemical substance. The 2nd, 3rd and 4th levels are often used to identify pharmacological subgroups when that is considered more appropriate than therapeutic or chemical subgroups.
Source: <a href='https://www.whocc.no/atc/structure_and_principles/'>https://www.whocc.no/atc/structure_and_principles/</a></p>
<h2 class="hasAnchor" id="whocc"><a class="anchor" href="#whocc"></a>WHOCC</h2>
<p><img src='figures/logo_who.png' height=60px style=margin-bottom:5px /> <br />
This package contains <strong>all ~450 antimicrobial 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://www.whocc.no'>https://www.whocc.no</a>) and the Pharmaceuticals Community Register of the European Commission (<a href='http://ec.europa.eu/health/documents/community-register/html/atc.htm'>http://ec.europa.eu/health/documents/community-register/html/atc.htm</a>).</p>
<p>These have become the gold standard for international drug utilisation monitoring and research.</p>
<p>The WHOCC is located in Oslo at the Norwegian Institute of Public Health and funded by the Norwegian government. The European Commission is the executive of the European Union and promotes its general interest.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='antibiotics.html'>antibiotics</a></code> for the dataframe that is being used to determine ATCs.</p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<span class='co'># These examples all return "J01FA01", the ATC code of Erythromycin:</span>
<span class='fu'>as.atc</span>(<span class='st'>"J01FA01"</span>)
<span class='fu'>as.atc</span>(<span class='st'>"Erythromycin"</span>)
<span class='fu'>as.atc</span>(<span class='st'>"eryt"</span>)
<span class='fu'>as.atc</span>(<span class='st'>" eryt 123"</span>)
<span class='fu'>as.atc</span>(<span class='st'>"ERYT"</span>)
<span class='fu'>as.atc</span>(<span class='st'>"ERY"</span>)
<span class='co'># }</span></pre>
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<li><a href="#read-more-on-our-website-">Read more on our website!</a></li>
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<meta property="og:description" content="This transforms a vector to a new class disk, which is a growth zone size (around an antibiotic disk) in millimeters between 6 and 99." />
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9055</span>
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<p>This transforms a vector to a new class <code>disk</code>, which is a growth zone size (around an antibiotic disk) in millimeters between 6 and 99.</p>
</div>
<pre class="usage"><span class='fu'>as.disk</span>(<span class='no'>x</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='fu'>is.disk</span>(<span class='no'>x</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
@ -250,28 +253,24 @@
<td><p>a logical indicating whether missing values should be removed</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>Ordered integer factor with new class <code>disk</code></p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>Interpret disk values as RSI values with <code><a href='as.rsi.html'>as.rsi</a></code>. It supports guidelines from EUCAST and CLSI.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='as.rsi.html'>as.rsi</a></code></p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<span class='co'># interpret disk values</span>
<pre class="examples"><span class='co'># interpret disk values</span>
<span class='fu'><a href='as.rsi.html'>as.rsi</a></span>(<span class='kw'>x</span> <span class='kw'>=</span> <span class='fl'>12</span>,
<span class='kw'>mo</span> <span class='kw'>=</span> <span class='fu'><a href='as.mo.html'>as.mo</a></span>(<span class='st'>"S. pneumoniae"</span>),
<span class='kw'>ab</span> <span class='kw'>=</span> <span class='st'>"AMX"</span>,
@ -279,36 +278,32 @@
<span class='fu'><a href='as.rsi.html'>as.rsi</a></span>(<span class='kw'>x</span> <span class='kw'>=</span> <span class='fl'>12</span>,
<span class='kw'>mo</span> <span class='kw'>=</span> <span class='fu'><a href='as.mo.html'>as.mo</a></span>(<span class='st'>"S. pneumoniae"</span>),
<span class='kw'>ab</span> <span class='kw'>=</span> <span class='st'>"AMX"</span>,
<span class='kw'>guideline</span> <span class='kw'>=</span> <span class='st'>"CLSI"</span>)
<span class='co'># }</span></pre>
<span class='kw'>guideline</span> <span class='kw'>=</span> <span class='st'>"CLSI"</span>)</pre>
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<meta property="og:title" content="Class 'mic' — as.mic" />
<meta property="og:description" content="This transforms a vector to a new class mic, which is an ordered factor with valid MIC values as levels. Invalid MIC values will be translated as NA with a warning." />
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9055</span>
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@ -189,7 +194,6 @@
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@ -229,15 +234,13 @@
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<div class="ref-description">
<p>This transforms a vector to a new class <code>mic</code>, which is an ordered factor with valid MIC values as levels. Invalid MIC values will be translated as <code>NA</code> with a warning.</p>
</div>
<pre class="usage"><span class='fu'>as.mic</span>(<span class='no'>x</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='fu'>is.mic</span>(<span class='no'>x</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
@ -250,28 +253,24 @@
<td><p>a logical indicating whether missing values should be removed</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>Ordered factor with new class <code>mic</code></p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>Interpret MIC values as RSI values with <code><a href='as.rsi.html'>as.rsi</a></code>. It supports guidelines from EUCAST and CLSI.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='as.rsi.html'>as.rsi</a></code></p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<span class='no'>mic_data</span> <span class='kw'>&lt;-</span> <span class='fu'>as.mic</span>(<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"&gt;=32"</span>, <span class='st'>"1.0"</span>, <span class='st'>"1"</span>, <span class='st'>"1.00"</span>, <span class='fl'>8</span>, <span class='st'>"&lt;=0.128"</span>, <span class='st'>"8"</span>, <span class='st'>"16"</span>, <span class='st'>"16"</span>))
<pre class="examples"><span class='no'>mic_data</span> <span class='kw'>&lt;-</span> <span class='fu'>as.mic</span>(<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"&gt;=32"</span>, <span class='st'>"1.0"</span>, <span class='st'>"1"</span>, <span class='st'>"1.00"</span>, <span class='fl'>8</span>, <span class='st'>"&lt;=0.128"</span>, <span class='st'>"8"</span>, <span class='st'>"16"</span>, <span class='st'>"16"</span>))
<span class='fu'>is.mic</span>(<span class='no'>mic_data</span>)
<span class='co'># this can also coerce combined MIC/RSI values:</span>
@ -287,40 +286,36 @@
<span class='kw'>ab</span> <span class='kw'>=</span> <span class='st'>"AMX"</span>,
<span class='kw'>guideline</span> <span class='kw'>=</span> <span class='st'>"EUCAST"</span>)
<span class='fu'><a href='https://www.rdocumentation.org/packages/graphics/topics/plot'>plot</a></span>(<span class='no'>mic_data</span>)
<span class='fu'><a href='https://www.rdocumentation.org/packages/graphics/topics/barplot'>barplot</a></span>(<span class='no'>mic_data</span>)
<span class='fu'><a href='https://rdrr.io/r/graphics/plot.html'>plot</a></span>(<span class='no'>mic_data</span>)
<span class='fu'><a href='https://rdrr.io/r/graphics/barplot.html'>barplot</a></span>(<span class='no'>mic_data</span>)
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>clean</span>)
<span class='fu'><a href='https://www.rdocumentation.org/packages/clean/topics/freq'>freq</a></span>(<span class='no'>mic_data</span>)
<span class='co'># }</span></pre>
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>clean</span>)
<span class='fu'><a href='https://rdrr.io/pkg/clean/man/freq.html'>freq</a></span>(<span class='no'>mic_data</span>)</pre>
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<meta property="og:title" content="Transform to microorganism ID — as.mo" />
<meta property="og:description" content="Use this function to determine a valid microorganism ID (mo). Determination is done using intelligent rules and the complete taxonomic kingdoms Bacteria, Chromista, Protozoa, Archaea and most microbial species from the kingdom Fungi (see Source). The input can be almost anything: a full name (like &quot;Staphylococcus aureus&quot;), an abbreviated name (like &quot;S. aureus&quot;), an abbreviation known in the field (like &quot;MRSA&quot;), or just a genus. Please see Examples." />
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<div class="ref-description">
<p>Use this function to determine a valid microorganism ID (<code>mo</code>). Determination is done using intelligent rules and the complete taxonomic kingdoms Bacteria, Chromista, Protozoa, Archaea and most microbial species from the kingdom Fungi (see Source). The input can be almost anything: a full name (like <code>"Staphylococcus aureus"</code>), an abbreviated name (like <code>"S. aureus"</code>), an abbreviation known in the field (like <code>"MRSA"</code>), or just a genus. Please see Examples.</p>
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<pre class="usage"><span class='fu'>as.mo</span>(<span class='no'>x</span>, <span class='kw'>Becker</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>Lancefield</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>allow_uncertain</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
@ -246,7 +249,7 @@
<span class='fu'>mo_renamed</span>()
<span class='fu'>clear_mo_history</span>(<span class='no'>...</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
@ -277,11 +280,10 @@
<td><p>other parameters passed on to functions</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>Character (vector) with class <code>"mo"</code></p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p><strong>General info</strong> <br />
@ -299,7 +301,8 @@ A microorganism ID from this package (class: <code>mo</code>) typically looks li
----&gt; taxonomic kingdom: A (Archaea), AN (Animalia), B (Bacteria),
C (Chromista), F (Fungi), P (Protozoa)
</pre>
<p>Values that cannot be coered will be considered 'unknown' and will get the MO code <code>UNKNOWN</code>.</p>
<p>Values that cannot be coered will be considered 'unknown' and will get the MO code <code>UNKNOWN</code>.</p>
<p>Use the <code><a href='mo_property.html'>mo_property</a>_*</code> functions to get properties based on the returned code, see Examples.</p>
<p>The algorithm uses data from the Catalogue of Life (see below) and from one other source (see <code><a href='microorganisms.html'>microorganisms</a></code>).</p>
<p><strong>Self-learning algoritm</strong> <br />
@ -312,20 +315,23 @@ The <code>as.mo()</code> function uses several coercion rules for fast and logic
<li><p>Taxonomic kingdom: the function starts with determining Bacteria, then Fungi, then Protozoa, then others;</p></li>
<li><p>Breakdown of input values to identify possible matches.</p></li>
</ul>
<p>This will lead to the effect that e.g. <code>"E. coli"</code> (a highly prevalent microorganism found in humans) will return the microbial ID of <em>Escherichia coli</em> and not <em>Entamoeba coli</em> (a less prevalent microorganism in humans), although the latter would alphabetically come first. In addition, the <code>as.mo()</code> function can differentiate four levels of uncertainty to guess valid results:</p>
<p>This will lead to the effect that e.g. <code>"E. coli"</code> (a highly prevalent microorganism found in humans) will return the microbial ID of <em>Escherichia coli</em> and not <em>Entamoeba coli</em> (a less prevalent microorganism in humans), although the latter would alphabetically come first. In addition, the <code>as.mo()</code> function can differentiate four levels of uncertainty to guess valid results:</p>
<ul>
<li><p>Uncertainty level 0: no additional rules are applied;</p></li>
<li><p>Uncertainty level 1: allow previously accepted (but now invalid) taxonomic names and minor spelling errors;</p></li>
<li><p>Uncertainty level 2: allow all of level 1, strip values between brackets, inverse the words of the input, strip off text elements from the end keeping at least two elements;</p></li>
<li><p>Uncertainty level 3: allow all of level 1 and 2, strip off text elements from the end, allow any part of a taxonomic name.</p></li>
</ul>
<p>This leads to e.g.:</p>
<p>This leads to e.g.:</p>
<ul>
<li><p><code>"Streptococcus group B (known as S. agalactiae)"</code>. The text between brackets will be removed and a warning will be thrown that the result <em>Streptococcus group B</em> (<code>B_STRPT_GRPB</code>) needs review.</p></li>
<li><p><code>"S. aureus - please mind: MRSA"</code>. The last word will be stripped, after which the function will try to find a match. If it does not, the second last word will be stripped, etc. Again, a warning will be thrown that the result <em>Staphylococcus aureus</em> (<code>B_STPHY_AURS</code>) needs review.</p></li>
<li><p><code>"Fluoroquinolone-resistant Neisseria gonorrhoeae"</code>. The first word will be stripped, after which the function will try to find a match. A warning will be thrown that the result <em>Neisseria gonorrhoeae</em> (<code>B_NESSR_GNRR</code>) needs review.</p></li>
</ul>
<p>The level of uncertainty can be set using the argument <code>allow_uncertain</code>. The default is <code>allow_uncertain = TRUE</code>, which is equal to uncertainty level 2. Using <code>allow_uncertain = FALSE</code> is equal to uncertainty level 0 and will skip all rules. You can also use e.g. <code>as.mo(..., allow_uncertain = 1)</code> to only allow up to level 1 uncertainty.</p>
<p>The level of uncertainty can be set using the argument <code>allow_uncertain</code>. The default is <code>allow_uncertain = TRUE</code>, which is equal to uncertainty level 2. Using <code>allow_uncertain = FALSE</code> is equal to uncertainty level 0 and will skip all rules. You can also use e.g. <code>as.mo(..., allow_uncertain = 1)</code> to only allow up to level 1 uncertainty.</p>
<p>Use <code>mo_failures()</code> to get a vector with all values that could not be coerced to a valid value. <br />
Use <code>mo_uncertainties()</code> to get a <code>data.frame</code> with all values that were coerced to a valid value, but with uncertainty. <br />
Use <code>mo_renamed()</code> to get a <code>data.frame</code> with all values that could be coerced based on an old, previously accepted taxonomic name.</p>
@ -334,35 +340,33 @@ The intelligent rules consider the prevalence of microorganisms in humans groupe
<p>Group 1 (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is <em>Enterococcus</em>, <em>Staphylococcus</em> or <em>Streptococcus</em>. This group consequently contains all common Gram-negative bacteria, such as <em>Pseudomonas</em> and <em>Legionella</em> and all species within the order Enterobacteriales.</p>
<p>Group 2 consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is <em>Aspergillus</em>, <em>Bacteroides</em>, <em>Candida</em>, <em>Capnocytophaga</em>, <em>Chryseobacterium</em>, <em>Cryptococcus</em>, <em>Elisabethkingia</em>, <em>Flavobacterium</em>, <em>Fusobacterium</em>, <em>Giardia</em>, <em>Leptotrichia</em>, <em>Mycoplasma</em>, <em>Prevotella</em>, <em>Rhodotorula</em>, <em>Treponema</em>, <em>Trichophyton</em> or <em>Ureaplasma</em>.</p>
<p>Group 3 (least prevalent microorganisms) consists of all other microorganisms.</p>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<p>[1] Becker K <em>et al.</em> <strong>Coagulase-Negative Staphylococci</strong>. 2014. Clin Microbiol Rev. 27(4): 870–926. <a href='https://dx.doi.org/10.1128/CMR.00109-13'>https://dx.doi.org/10.1128/CMR.00109-13</a></p>
<p>[1] Becker K <em>et al.</em> <strong>Coagulase-Negative Staphylococci</strong>. 2014. Clin Microbiol Rev. 27(4): 870–926. <a href='https://dx.doi.org/10.1128/CMR.00109-13'>https://dx.doi.org/10.1128/CMR.00109-13</a></p>
<p>[2] Becker K <em>et al.</em> <strong>Implications of identifying the recently defined members of the <em>S. aureus</em> complex, <em>S. argenteus</em> and <em>S. schweitzeri</em>: A position paper of members of the ESCMID Study Group for staphylococci and Staphylococcal Diseases (ESGS).</strong> 2019. Clin Microbiol Infect. <a href='https://doi.org/10.1016/j.cmi.2019.02.028'>https://doi.org/10.1016/j.cmi.2019.02.028</a></p>
<p>[3] Lancefield RC <strong>A serological differentiation of human and other groups of hemolytic streptococci</strong>. 1933. J Exp Med. 57(4): 571–95. <a href='https://dx.doi.org/10.1084/jem.57.4.571'>https://dx.doi.org/10.1084/jem.57.4.571</a></p>
<p>[4] Catalogue of Life: Annual Checklist (public online taxonomic database), <a href='http://www.catalogueoflife.org'>http://www.catalogueoflife.org</a> (check included annual version with <code><a href='catalogue_of_life_version.html'>catalogue_of_life_version</a>()</code>).</p>
<h2 class="hasAnchor" id="catalogue-of-life"><a class="anchor" href="#catalogue-of-life"></a>Catalogue of Life</h2>
<p><img src='figures/logo_col.png' height=40px style=margin-bottom:5px /> <br />
<p><img src='figures/logo_col.png' height=40px style=margin-bottom:5px /> <br />
This package contains the complete taxonomic tree of almost all microorganisms (~70,000 species) from the authoritative and comprehensive Catalogue of Life (<a href='http://www.catalogueoflife.org'>http://www.catalogueoflife.org</a>). The Catalogue of Life is the most comprehensive and authoritative global index of species currently available.</p>
<p><a href='catalogue_of_life.html'>Click here</a> for more information about the included taxa. Check which version of the Catalogue of Life was included in this package with <code><a href='catalogue_of_life_version.html'>catalogue_of_life_version</a>()</code>.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='microorganisms.html'>microorganisms</a></code> for the <code>data.frame</code> that is being used to determine ID's. <br />
The <code><a href='mo_property.html'>mo_property</a></code> functions (like <code><a href='mo_property.html'>mo_genus</a></code>, <code><a href='mo_property.html'>mo_gramstain</a></code>) to get properties based on the returned code.</p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<pre class="examples"><span class='co'># \donttest{</span>
<span class='co'># These examples all return "B_STPHY_AURS", the ID of S. aureus:</span>
<span class='fu'>as.mo</span>(<span class='st'>"sau"</span>) <span class='co'># WHONET code</span>
<span class='fu'>as.mo</span>(<span class='st'>"stau"</span>)
@ -398,11 +402,12 @@ The <code><a href='mo_property.html'>mo_property</a></code> functions (like <cod
<span class='fu'><a href='mo_property.html'>mo_genus</a></span>(<span class='st'>"E. coli"</span>) <span class='co'># returns "Escherichia"</span>
<span class='fu'><a href='mo_property.html'>mo_gramstain</a></span>(<span class='st'>"E. coli"</span>) <span class='co'># returns "Gram negative"</span>
<span class='co'># }</span><span class='co'># NOT RUN {</span>
<span class='co'># }</span>
<span class='kw'>if</span> (<span class='fl'>FALSE</span>) {
<span class='no'>df</span>$<span class='no'>mo</span> <span class='kw'>&lt;-</span> <span class='fu'>as.mo</span>(<span class='no'>df</span>$<span class='no'>microorganism_name</span>)
<span class='co'># the select function of tidyverse is also supported:</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>dplyr</span>)
<span class='no'>df</span>$<span class='no'>mo</span> <span class='kw'>&lt;-</span> <span class='no'>df</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>microorganism_name</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>as.mo</span>()
@ -413,40 +418,35 @@ The <code><a href='mo_property.html'>mo_property</a></code> functions (like <cod
<span class='fu'>as.mo</span>()
<span class='co'># although this works easier and does the same:</span>
<span class='no'>df</span> <span class='kw'>&lt;-</span> <span class='no'>df</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='kw'>mo</span> <span class='kw'>=</span> <span class='fu'>as.mo</span>(<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/paste'>paste</a></span>(<span class='no'>genus</span>, <span class='no'>species</span>)))
<span class='co'># }</span></pre>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='kw'>mo</span> <span class='kw'>=</span> <span class='fu'>as.mo</span>(<span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste</a></span>(<span class='no'>genus</span>, <span class='no'>species</span>)))
}</pre>
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<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked">
<li><a href="#arguments">Arguments</a></li>
<li><a href="#value">Value</a></li>
<li><a href="#details">Details</a></li>
<li><a href="#source">Source</a></li>
<li><a href="#catalogue-of-life">Catalogue of Life</a></li>
<li><a href="#read-more-on-our-website-">Read more on our website!</a></li>
<li><a href="#see-also">See also</a></li>
<li><a href="#examples">Examples</a></li>
</ul>
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@ -45,15 +49,15 @@
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<meta property="og:title" content="Class 'rsi' — as.rsi" />
<meta property="og:description" content="Interpret MIC values according to EUCAST or CLSI, or clean up existing RSI values. This transforms the input to a new class rsi, which is an ordered factor with levels S &amp;lt; I &amp;lt; R. Invalid antimicrobial interpretations will be translated as NA with a warning." />
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@ -80,7 +85,7 @@
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<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9067</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0</span>
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@ -189,7 +194,6 @@
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<ul class="nav navbar-nav navbar-right">
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<a href="https://gitlab.com/msberends/AMR">
@ -207,7 +211,7 @@
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@ -218,6 +222,7 @@
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@ -229,9 +234,7 @@
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<div class="ref-description">
<p>Interpret MIC values according to EUCAST or CLSI, or clean up existing RSI values. This transforms the input to a new class <code>rsi</code>, which is an ordered factor with levels <code>S &lt; I &lt; R</code>. Invalid antimicrobial interpretations will be translated as <code>NA</code> with a warning.</p>
</div>
<pre class="usage"><span class='fu'>as.rsi</span>(<span class='no'>x</span>, <span class='no'>...</span>)
@ -249,7 +252,7 @@
<span class='fu'>is.rsi</span>(<span class='no'>x</span>)
<span class='fu'>is.rsi.eligible</span>(<span class='no'>x</span>, <span class='kw'>threshold</span> <span class='kw'>=</span> <span class='fl'>0.05</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
@ -271,7 +274,7 @@
</tr>
<tr>
<th>guideline</th>
<td><p>defaults to the latest included EUCAST guideline, run <code><a href='https://www.rdocumentation.org/packages/base/topics/unique'>unique(AMR::rsi_translation$guideline)</a></code> for all options</p></td>
<td><p>defaults to the latest included EUCAST guideline, run <code><a href='https://rdrr.io/r/base/unique.html'>unique(AMR::rsi_translation$guideline)</a></code> for all options</p></td>
</tr>
<tr>
<th>col_mo</th>
@ -282,43 +285,40 @@
<td><p>maximum fraction of invalid antimicrobial interpretations of <code>x</code>, see Examples</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>Ordered factor with new class <code>rsi</code></p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>Run <code><a href='https://www.rdocumentation.org/packages/base/topics/unique'>unique(AMR::rsi_translation$guideline)</a></code> for a list of all supported guidelines.</p>
<p>Run <code><a href='https://rdrr.io/r/base/unique.html'>unique(AMR::rsi_translation$guideline)</a></code> for a list of all supported guidelines.</p>
<p>After using <code>as.rsi</code>, you can use <code><a href='eucast_rules.html'>eucast_rules</a></code> to (1) apply inferred susceptibility and resistance based on results of other antimicrobials and (2) apply intrinsic resistance based on taxonomic properties of a microorganism.</p>
<p>The function <code>is.rsi.eligible</code> returns <code>TRUE</code> when a columns contains at most 5% invalid antimicrobial interpretations (not S and/or I and/or R), and <code>FALSE</code> otherwise. The threshold of 5% can be set with the <code>threshold</code> parameter.</p>
<h2 class="hasAnchor" id="interpretation-of-s-i-and-r"><a class="anchor" href="#interpretation-of-s-i-and-r"></a>Interpretation of S, I and R</h2>
<p>In 2019, EUCAST has decided to change the definitions of susceptibility testing categories S, I and R as shown below (<a href='http://www.eucast.org/newsiandr/'>http://www.eucast.org/newsiandr/</a>). Results of several consultations on the new definitions are available on the EUCAST website under "Consultations".</p>
<p>In 2019, EUCAST has decided to change the definitions of susceptibility testing categories S, I and R as shown below (<a href='http://www.eucast.org/newsiandr/'>http://www.eucast.org/newsiandr/</a>). Results of several consultations on the new definitions are available on the EUCAST website under "Consultations".</p>
<ul>
<li><p><strong>S</strong> - Susceptible, standard dosing regimen: 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>
<li><p><strong>I</strong> - Susceptible, increased exposure: A microorganism is categorised as "Susceptible, Increased exposure" when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.</p></li>
<li><p><strong>R</strong> - Resistant: A microorganism is categorised as "Resistant" when there is a high likelihood of therapeutic failure even when there is increased exposure.</p></li>
</ul>
<p>Exposure is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.</p>
<p>Exposure is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.</p>
<p>This AMR package honours this new insight. Use <code><a href='portion.html'>portion_SI</a></code> to determine antimicrobial susceptibility and <code><a href='count.html'>count_SI</a></code> to count susceptible isolates.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='as.mic.html'>as.mic</a></code></p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<span class='no'>rsi_data</span> <span class='kw'>&lt;-</span> <span class='fu'>as.rsi</span>(<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/rep'>rep</a></span>(<span class='st'>"S"</span>, <span class='fl'>474</span>), <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/rep'>rep</a></span>(<span class='st'>"I"</span>, <span class='fl'>36</span>), <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/rep'>rep</a></span>(<span class='st'>"R"</span>, <span class='fl'>370</span>)))
<span class='no'>rsi_data</span> <span class='kw'>&lt;-</span> <span class='fu'>as.rsi</span>(<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/rep'>rep</a></span>(<span class='st'>"S"</span>, <span class='fl'>474</span>), <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/rep'>rep</a></span>(<span class='st'>"I"</span>, <span class='fl'>36</span>), <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/rep'>rep</a></span>(<span class='st'>"R"</span>, <span class='fl'>370</span>), <span class='st'>"A"</span>, <span class='st'>"B"</span>, <span class='st'>"C"</span>))
<pre class="examples"><span class='no'>rsi_data</span> <span class='kw'>&lt;-</span> <span class='fu'>as.rsi</span>(<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/rep.html'>rep</a></span>(<span class='st'>"S"</span>, <span class='fl'>474</span>), <span class='fu'><a href='https://rdrr.io/r/base/rep.html'>rep</a></span>(<span class='st'>"I"</span>, <span class='fl'>36</span>), <span class='fu'><a href='https://rdrr.io/r/base/rep.html'>rep</a></span>(<span class='st'>"R"</span>, <span class='fl'>370</span>)))
<span class='no'>rsi_data</span> <span class='kw'>&lt;-</span> <span class='fu'>as.rsi</span>(<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/rep.html'>rep</a></span>(<span class='st'>"S"</span>, <span class='fl'>474</span>), <span class='fu'><a href='https://rdrr.io/r/base/rep.html'>rep</a></span>(<span class='st'>"I"</span>, <span class='fl'>36</span>), <span class='fu'><a href='https://rdrr.io/r/base/rep.html'>rep</a></span>(<span class='st'>"R"</span>, <span class='fl'>370</span>), <span class='st'>"A"</span>, <span class='st'>"B"</span>, <span class='st'>"C"</span>))
<span class='fu'>is.rsi</span>(<span class='no'>rsi_data</span>)
<span class='co'># this can also coerce combined MIC/RSI values:</span>
@ -334,14 +334,14 @@
<span class='kw'>ab</span> <span class='kw'>=</span> <span class='st'>"AMX"</span>,
<span class='kw'>guideline</span> <span class='kw'>=</span> <span class='st'>"EUCAST"</span>)
<span class='fu'><a href='https://www.rdocumentation.org/packages/graphics/topics/plot'>plot</a></span>(<span class='no'>rsi_data</span>) <span class='co'># for percentages</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/graphics/topics/barplot'>barplot</a></span>(<span class='no'>rsi_data</span>) <span class='co'># for frequencies</span>
<span class='fu'><a href='https://rdrr.io/r/graphics/plot.html'>plot</a></span>(<span class='no'>rsi_data</span>) <span class='co'># for percentages</span>
<span class='fu'><a href='https://rdrr.io/r/graphics/barplot.html'>barplot</a></span>(<span class='no'>rsi_data</span>) <span class='co'># for frequencies</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>clean</span>)
<span class='fu'><a href='https://www.rdocumentation.org/packages/clean/topics/freq'>freq</a></span>(<span class='no'>rsi_data</span>) <span class='co'># frequency table with informative header</span>
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>clean</span>)
<span class='fu'><a href='https://rdrr.io/pkg/clean/man/freq.html'>freq</a></span>(<span class='no'>rsi_data</span>) <span class='co'># frequency table with informative header</span>
<span class='co'># using dplyr's mutate</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>dplyr</span>)
<span class='no'>example_isolates</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate_all.html'>mutate_at</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>PEN</span>:<span class='no'>RIF</span>), <span class='no'>as.rsi</span>)
@ -353,38 +353,33 @@
<span class='co'># default threshold of `is.rsi.eligible` is 5%.</span>
<span class='fu'>is.rsi.eligible</span>(<span class='no'>WHONET</span>$<span class='no'>`First name`</span>) <span class='co'># fails, &gt;80% is invalid</span>
<span class='fu'>is.rsi.eligible</span>(<span class='no'>WHONET</span>$<span class='no'>`First name`</span>, <span class='kw'>threshold</span> <span class='kw'>=</span> <span class='fl'>0.99</span>) <span class='co'># succeeds</span>
<span class='co'># }</span></pre>
<span class='fu'>is.rsi.eligible</span>(<span class='no'>WHONET</span>$<span class='no'>`First name`</span>, <span class='kw'>threshold</span> <span class='kw'>=</span> <span class='fl'>0.99</span>) <span class='co'># succeeds</span></pre>
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<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked">
<li><a href="#arguments">Arguments</a></li>
<li><a href="#value">Value</a></li>
<li><a href="#details">Details</a></li>
<li><a href="#interpretation-of-s-i-and-r">Interpretation of S, I and R</a></li>
<li><a href="#read-more-on-our-website-">Read more on our website!</a></li>
<li><a href="#see-also">See also</a></li>
<li><a href="#examples">Examples</a></li>
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<p>Developed by <a href='https://www.rug.nl/staff/m.s.berends/'>Matthijs S. Berends</a>, <a href='https://www.rug.nl/staff/c.f.luz/'>Christian F. Luz</a>, <a href='https://www.rug.nl/staff/a.w.friedrich/'>Alex W. Friedrich</a>, <a href='https://www.rug.nl/staff/b.sinha/'>Bhanu N. M. Sinha</a>, <a href='https://www.rug.nl/staff/c.j.albers/'>Casper J. Albers</a>, <a href='https://www.rug.nl/staff/c.glasner/'>Corinna Glasner</a>.</p>
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51
docs/reference/atc_online.html

@ -15,21 +15,25 @@
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@ -45,15 +49,15 @@
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<meta property="og:title" content="Get ATC properties from WHOCC website — atc_online_property" />
<meta property="og:description" content="Gets data from the WHO to determine properties of an ATC (e.g. an antibiotic) like name, defined daily dose (DDD) or standard unit. This function requires an internet connection." />
<meta property="og:image" content="https://msberends.gitlab.io/AMR/logo.png" />
<meta name="twitter:card" content="summary" />
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@ -64,6 +68,7 @@
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@ -80,7 +85,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9055</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0</span>
</span>
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@ -189,7 +194,6 @@
</a>
</li>
</ul>
<ul class="nav navbar-nav navbar-right">
<li>
<a href="https://gitlab.com/msberends/AMR">
@ -207,7 +211,7 @@
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</ul>
<form class="navbar-form navbar-right" role="search">
<form class="navbar-form navbar-right hidden-xs hidden-sm" role="search">
<div class="form-group">
<input type="search" class="form-control" name="search-input" id="search-input" placeholder="Search..." aria-label="Search for..." autocomplete="off">
</div>
@ -218,6 +222,7 @@
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<div class="row">
@ -229,9 +234,7 @@
</div>
<div class="ref-description">
<p>Gets data from the WHO to determine properties of an ATC (e.g. an antibiotic) like name, defined daily dose (DDD) or standard unit. <br /> <strong>This function requires an internet connection.</strong></p>
</div>
<pre class="usage"><span class='fu'>atc_online_property</span>(<span class='no'>atc_code</span>, <span class='no'>property</span>, <span class='kw'>administration</span> <span class='kw'>=</span> <span class='st'>"O"</span>,
@ -240,7 +243,7 @@
<span class='fu'>atc_online_groups</span>(<span class='no'>atc_code</span>, <span class='no'>...</span>)
<span class='fu'>atc_online_ddd</span>(<span class='no'>atc_code</span>, <span class='no'>...</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
@ -265,11 +268,10 @@
<td><p>parameters to pass on to <code>atc_property</code></p></td>
</tr>
</table>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<p><a href='https://www.whocc.no/atc_ddd_alterations__cumulative/ddd_alterations/abbrevations/'>https://www.whocc.no/atc_ddd_alterations__cumulative/ddd_alterations/abbrevations/</a></p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>Options for parameter <code>administration</code>:</p><ul>
@ -284,7 +286,8 @@
<li><p><code>"TD"</code> = transdermal</p></li>
<li><p><code>"V"</code> = vaginal</p></li>
</ul>
<p>Abbreviations of return values when using <code>property = "U"</code> (unit):</p><ul>
<p>Abbreviations of return values when using <code>property = "U"</code> (unit):</p><ul>
<li><p><code>"g"</code> = gram</p></li>
<li><p><code>"mg"</code> = milligram</p></li>
<li><p><code>"mcg"</code> = microgram</p></li>
@ -294,15 +297,15 @@
<li><p><code>"mmol"</code> = millimole</p></li>
<li><p><code>"ml"</code> = milliliter (e.g. eyedrops)</p></li>
</ul>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<pre class="examples"><span class='co'># \donttest{</span>
<span class='co'># oral DDD (Defined Daily Dose) of amoxicillin</span>
<span class='fu'>atc_online_property</span>(<span class='st'>"J01CA04"</span>, <span class='st'>"DDD"</span>, <span class='st'>"O"</span>)
<span class='co'># parenteral DDD (Defined Daily Dose) of amoxicillin</span>
@ -319,27 +322,25 @@
<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked">
<li><a href="#arguments">Arguments</a></li>
<li><a href="#source">Source</a></li>
<li><a href="#details">Details</a></li>
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<h1>Property of an antibiotic</h1>
<div class="hidden name"><code>atc_property.Rd</code></div>
</div>
<div class="ref-description">
<p>Use these functions to return a specific property of an antibiotic from the <code><a href='antibiotics.html'>antibiotics</a></code> data set, based on their ATC code. Get such a code with <code><a href='as.atc.html'>as.atc</a></code>.</p>
</div>
<pre class="usage"><span class='fu'>atc_property</span>(<span class='no'>x</span>, <span class='kw'>property</span> <span class='kw'>=</span> <span class='st'>"official"</span>)
<span class='fu'>atc_official</span>(<span class='no'>x</span>, <span class='kw'>language</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)
<span class='fu'>atc_name</span>(<span class='no'>x</span>, <span class='kw'>language</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)
<span class='fu'>atc_trivial_nl</span>(<span class='no'>x</span>)
<span class='fu'>atc_certe</span>(<span class='no'>x</span>)
<span class='fu'>atc_umcg</span>(<span class='no'>x</span>)
<span class='fu'>atc_tradenames</span>(<span class='no'>x</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>x</th>
<td><p>a (vector of a) valid <code><a href='as.atc.html'>atc</a></code> code or any text that can be coerced to a valid atc with <code><a href='as.atc.html'>as.atc</a></code></p></td>
</tr>
<tr>
<th>property</th>
<td><p>one of the column names of one of the <code><a href='antibiotics.html'>antibiotics</a></code> data set, like <code>"atc"</code> and <code>"official"</code></p></td>
</tr>
<tr>
<th>language</th>
<td><p>language of the returned text, defaults to English (<code>"en"</code>) and can be set with <code><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a>("AMR_locale")</code>. Either one of <code>"en"</code> (English) or <code>"nl"</code> (Dutch).</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>A vector of values. In case of <code>atc_tradenames</code>, if <code>x</code> is of length one, a vector will be returned. Otherwise a <code><a href='https://www.rdocumentation.org/packages/base/topics/list'>list</a></code>, with <code>x</code> as names.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a comprehensive tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='antibiotics.html'>antibiotics</a></code></p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<span class='fu'><a href='as.atc.html'>as.atc</a></span>(<span class='st'>"amcl"</span>) <span class='co'># J01CR02</span>
<span class='fu'>atc_name</span>(<span class='st'>"amcl"</span>) <span class='co'># Amoxicillin and beta-lactamase inhibitor</span>
<span class='fu'>atc_name</span>(<span class='st'>"amcl"</span>, <span class='st'>"nl"</span>) <span class='co'># Amoxicilline met enzymremmer</span>
<span class='fu'>atc_trivial_nl</span>(<span class='st'>"amcl"</span>) <span class='co'># Amoxicilline/clavulaanzuur</span>
<span class='fu'>atc_certe</span>(<span class='st'>"amcl"</span>) <span class='co'># amcl</span>
<span class='fu'>atc_umcg</span>(<span class='st'>"amcl"</span>) <span class='co'># AMCL</span>
<span class='co'># }</span></pre>
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</ul>
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<li>
<a href="https://gitlab.com/msberends/AMR">
@ -207,7 +211,7 @@
</li>
</ul>
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<form class="navbar-form navbar-right hidden-xs hidden-sm" role="search">
<div class="form-group">
<input type="search" class="form-control" name="search-input" id="search-input" placeholder="Search..." aria-label="Search for..." autocomplete="off">
</div>
@ -218,6 +222,7 @@
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</header>
<div class="row">
@ -229,13 +234,11 @@
</div>
<div class="ref-description">
<p>Easy check for availability of columns in a data set. This makes it easy to get an idea of which antimicrobial combination can be used for calculation with e.g. <code><a href='portion.html'>portion_R</a></code>.</p>
</div>
<pre class="usage"><span class='fu'>availability</span>(<span class='no'>tbl</span>, <span class='kw'>width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
@ -248,26 +251,23 @@
<td><p>number of characters to present the visual availability, defaults to filling the width of the console</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p><code>data.frame</code> with column names of <code>tbl</code> as row names</p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>The function returns a <code>data.frame</code> with columns <code>"resistant"</code> and <code>"visual_resistance"</code>. The values in that columns are calculated with <code><a href='portion.html'>portion_R</a></code>.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<span class='fu'>availability</span>(<span class='no'>example_isolates</span>)
<pre class="examples"><span class='fu'>availability</span>(<span class='no'>example_isolates</span>)
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>dplyr</span>)
<span class='no'>example_isolates</span> <span class='kw'>%&gt;%</span> <span class='fu'>availability</span>()
<span class='no'>example_isolates</span> <span class='kw'>%&gt;%</span>
@ -277,34 +277,31 @@
<span class='no'>example_isolates</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>mo</span> <span class='kw'>==</span> <span class='fu'><a href='as.mo.html'>as.mo</a></span>(<span class='st'>"E. coli"</span>)) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select_all.html'>select_if</a></span>(<span class='no'>is.rsi</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>availability</span>()
<span class='co'># }</span></pre>
<span class='fu'>availability</span>()</pre>
</div>
<div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked">
<li><a href="#arguments">Arguments</a></li>
<li><a href="#value">Value</a></li>
<li><a href="#details">Details</a></li>
<li><a href="#read-more-on-our-website-">Read more on our website!</a></li>
<li><a href="#examples">Examples</a></li>
</ul>
</div>
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<p>Developed by <a href='https://www.rug.nl/staff/m.s.berends/'>Matthijs S. Berends</a>, <a href='https://www.rug.nl/staff/c.f.luz/'>Christian F. Luz</a>, <a href='https://www.rug.nl/staff/a.w.friedrich/'>Alex W. Friedrich</a>, <a href='https://www.rug.nl/staff/b.sinha/'>Bhanu N. M. Sinha</a>, <a href='https://www.rug.nl/staff/c.j.albers/'>Casper J. Albers</a>, <a href='https://www.rug.nl/staff/c.glasner/'>Corinna Glasner</a>.</p>
</div>
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<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.3.0.</p>
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@ -327,6 +324,8 @@
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2
docs/reference/bug_drug_combinations.html

@ -85,7 +85,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9104</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0</span>
</span>
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59
docs/reference/catalogue_of_life.html

@ -15,21 +15,25 @@
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@ -45,15 +49,15 @@
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<meta property="og:title" content="The Catalogue of Life — catalogue_of_life" />
<meta property="og:description" content="This package contains the complete taxonomic tree of almost all microorganisms from the authoritative and comprehensive Catalogue of Life." />
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@ -64,6 +68,7 @@
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<body>
@ -80,7 +85,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9055</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0</span>
</span>
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@ -189,7 +194,6 @@
</a>
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@ -207,7 +211,7 @@
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</div>
@ -218,6 +222,7 @@
</div><!--/.navbar -->
</header>
<div class="row">
@ -229,23 +234,23 @@
</div>
<div class="ref-description">
<p>This package contains the complete taxonomic tree of almost all microorganisms from the authoritative and comprehensive Catalogue of Life.</p>
</div>
<h2 class="hasAnchor" id="catalogue-of-life"><a class="anchor" href="#catalogue-of-life"></a>Catalogue of Life</h2>
<p><img src='figures/logo_col.png' height=40px style=margin-bottom:5px /> <br />
<p><img src='figures/logo_col.png' height=40px style=margin-bottom:5px /> <br />
This package contains the complete taxonomic tree of almost all microorganisms (~70,000 species) from the authoritative and comprehensive Catalogue of Life (<a href='http://www.catalogueoflife.org'>http://www.catalogueoflife.org</a>). The Catalogue of Life is the most comprehensive and authoritative global index of species currently available.</p>
<p>Click here for more information about the included taxa. Check which version of the Catalogue of Life was included in this package with <code><a href='catalogue_of_life_version.html'>catalogue_of_life_version</a>()</code>.</p>
<h2 class="hasAnchor" id="included-taxa"><a class="anchor" href="#included-taxa"></a>Included taxa</h2>
<p>Included are:</p><ul>
<p>Included are:</p><ul>
<li><p>All ~61,000 (sub)species from the kingdoms of Archaea, Bacteria, Chromista and Protozoa</p></li>
<li><p>All ~8,500 (sub)species from these orders of the kingdom of Fungi: Eurotiales, Microascales, Mucorales, Onygenales, Pneumocystales, Saccharomycetales, Schizosaccharomycetales and Tremellales. 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 and including everything would tremendously slow down our algorithms too. By only including the aforementioned taxonomic orders, the most relevant fungi are covered (like all species of <em>Aspergillus</em>, <em>Candida</em>, <em>Cryptococcus</em>, <em>Histplasma</em>, <em>Pneumocystis</em>, <em>Saccharomyces</em> and <em>Trichophyton</em>).</p></li>
<li><p>All ~150 (sub)species from ~100 other relevant genera from the kingdom of Animalia (like <em>Strongyloides</em> and <em>Taenia</em>)</p></li>
@ -253,23 +258,21 @@ This package contains the complete taxonomic tree of almost all microorganisms (
<li><p>The complete taxonomic tree of all included (sub)species: from kingdom to subspecies</p></li>
<li><p>The responsible author(s) and year of scientific publication</p></li>
</ul>
<p>The Catalogue of Life (<a href='http://www.catalogueoflife.org'>http://www.catalogueoflife.org</a>) is the most comprehensive and authoritative global index of species currently available. It holds essential information on the names, relationships and distributions of over 1.9 million species. The Catalogue of Life is used to support the major biodiversity and conservation information services such as the Global Biodiversity Information Facility (GBIF), Encyclopedia of Life (EoL) and the International Union for Conservation of Nature Red List. It is recognised by the Convention on Biological Diversity as a significant component of the Global Taxonomy Initiative and a contribution to Target 1 of the Global Strategy for Plant Conservation.</p>
<p>The Catalogue of Life (<a href='http://www.catalogueoflife.org'>http://www.catalogueoflife.org</a>) is the most comprehensive and authoritative global index of species currently available. It holds essential information on the names, relationships and distributions of over 1.9 million species. The Catalogue of Life is used to support the major biodiversity and conservation information services such as the Global Biodiversity Information Facility (GBIF), Encyclopedia of Life (EoL) and the International Union for Conservation of Nature Red List. It is recognised by the Convention on Biological Diversity as a significant component of the Global Taxonomy Initiative and a contribution to Target 1 of the Global Strategy for Plant Conservation.</p>
<p>The syntax used to transform the original data to a cleansed R format, can be found here: <a href='https://gitlab.com/msberends/AMR/blob/master/data-raw/reproduction_of_microorganisms.R'>https://gitlab.com/msberends/AMR/blob/master/data-raw/reproduction_of_microorganisms.R</a>.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p>Data set <code><a href='microorganisms.html'>microorganisms</a></code> for the actual data. <br />
Function <code><a href='as.mo.html'>as.mo</a>()</code> to use the data for intelligent determination of microorganisms.</p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<span class='co'># Get version info of included data set</span>
<pre class="examples"><span class='co'># Get version info of included data set</span>
<span class='fu'><a href='catalogue_of_life_version.html'>catalogue_of_life_version</a></span>()
@ -296,35 +299,31 @@ Function <code><a href='as.mo.html'>as.mo</a>()</code> to use the data for intel
<span class='fu'><a href='mo_property.html'>mo_kingdom</a></span>(<span class='st'>"C. elegans"</span>)
<span class='co'># [1] "Bacteria" # Bacteria?!</span>
<span class='fu'><a href='mo_property.html'>mo_name</a></span>(<span class='st'>"C. elegans"</span>)
<span class='co'># [1] "Chroococcus limneticus elegans" # Because a microorganism was found</span>
<span class='co'># }</span></pre>
<span class='co'># [1] "Chroococcus limneticus elegans" # Because a microorganism was found</span></pre>
</div>
<div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked">
<li><a href="#catalogue-of-life">Catalogue of Life</a></li>
<li><a href="#included-taxa">Included taxa</a></li>
<li><a href="#read-more-on-our-website-">Read more on our website!</a></li>
<li><a href="#see-also">See also</a></li>
<li><a href="#examples">Examples</a></li>
</ul>
</div>
</div>
<footer>
<div class="copyright">
<p>Developed by <a href='https://www.rug.nl/staff/m.s.berends/'>Matthijs S. Berends</a>, <a href='https://www.rug.nl/staff/c.f.luz/'>Christian F. Luz</a>, <a href='https://www.rug.nl/staff/a.w.friedrich/'>Alex W. Friedrich</a>, <a href='https://www.rug.nl/staff/b.sinha/'>Bhanu N. M. Sinha</a>, <a href='https://www.rug.nl/staff/c.j.albers/'>Casper J. Albers</a>, <a href='https://www.rug.nl/staff/c.glasner/'>Corinna Glasner</a>.</p>
</div>
<div class="pkgdown">
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.3.0.</p>
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@ -347,6 +346,8 @@ Function <code><a href='as.mo.html'>as.mo</a>()</code> to use the data for intel
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59
docs/reference/catalogue_of_life_version.html

@ -15,21 +15,25 @@
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@ -45,15 +49,15 @@
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<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9055</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0</span>
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<input type="search" class="form-control" name="search-input" id="search-input" placeholder="Search..." aria-label="Search for..." autocomplete="off">
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@ -218,6 +222,7 @@
</div><!--/.navbar -->
</header>
<div class="row">
@ -229,74 +234,64 @@
</div>
<div class="ref-description">
<p>This function returns information about the included data from the Catalogue of Life.</p>
</div>
<pre class="usage"><span class='fu'>catalogue_of_life_version</span>()</pre>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>a <code>list</code>, which prints in pretty format</p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>For DSMZ, see <code><a href='microorganisms.html'>?microorganisms</a></code>.</p>
<h2 class="hasAnchor" id="catalogue-of-life"><a class="anchor" href="#catalogue-of-life"></a>Catalogue of Life</h2>
<p><img src='figures/logo_col.png' height=40px style=margin-bottom:5px /> <br />
<p><img src='figures/logo_col.png' height=40px style=margin-bottom:5px /> <br />
This package contains the complete taxonomic tree of almost all microorganisms (~70,000 species) from the authoritative and comprehensive Catalogue of Life (<a href='http://www.catalogueoflife.org'>http://www.catalogueoflife.org</a>). The Catalogue of Life is the most comprehensive and authoritative global index of species currently available.</p>
<p><a href='catalogue_of_life.html'>Click here</a> for more information about the included taxa. Check which version of the Catalogue of Life was included in this package with <code>catalogue_of_life_version()</code>.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='microorganisms.html'>microorganisms</a></code></p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>clean</span>)
<span class='no'>microorganisms</span> <span class='kw'>%&gt;%</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/clean/topics/freq'>freq</a></span>(<span class='no'>kingdom</span>)
<span class='no'>microorganisms</span> <span class='kw'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>kingdom</span>) <span class='kw'>%&gt;%</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/clean/topics/freq'>freq</a></span>(<span class='no'>phylum</span>, <span class='kw'>nmax</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)
<span class='co'># }</span></pre>
<pre class="examples"><span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>dplyr</span>)
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>clean</span>)
<span class='no'>microorganisms</span> <span class='kw'>%&gt;%</span> <span class='fu'><a href='https://rdrr.io/pkg/clean/man/freq.html'>freq</a></span>(<span class='no'>kingdom</span>)
<span class='no'>microorganisms</span> <span class='kw'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>kingdom</span>) <span class='kw'>%&gt;%</span> <span class='fu'><a href='https://rdrr.io/pkg/clean/man/freq.html'>freq</a></span>(<span class='no'>phylum</span>, <span class='kw'>nmax</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)</pre>
</div>
<div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked">
<li><a href="#value">Value</a></li>
<li><a href="#details">Details</a></li>
<li><a href="#catalogue-of-life">Catalogue of Life</a></li>
<li><a href="#read-more-on-our-website-">Read more on our website!</a></li>
<li><a href="#see-also">See also</a></li>
<li><a href="#examples">Examples</a></li>
</ul>
</div>
</div>
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<p>Developed by <a href='https://www.rug.nl/staff/m.s.berends/'>Matthijs S. Berends</a>, <a href='https://www.rug.nl/staff/c.f.luz/'>Christian F. Luz</a>, <a href='https://www.rug.nl/staff/a.w.friedrich/'>Alex W. Friedrich</a>, <a href='https://www.rug.nl/staff/b.sinha/'>Bhanu N. M. Sinha</a>, <a href='https://www.rug.nl/staff/c.j.albers/'>Casper J. Albers</a>, <a href='https://www.rug.nl/staff/c.glasner/'>Corinna Glasner</a>.</p>
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@ -319,6 +314,8 @@ This package contains the complete taxonomic tree of almost all microorganisms (
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@ -15,21 +15,25 @@
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@ -45,16 +49,16 @@
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<meta property="og:title" content="Count isolates — count" />
<meta property="og:title" content="Count 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 dplyrs summarise and support grouped variables, see Examples.
count_R and count_IR can be used to count resistant isolates, count_S and count_SI can be used to count susceptible isolates." />
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@ -65,6 +69,7 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
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@ -81,7 +86,7 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
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<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9067</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0</span>
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@ -190,7 +195,6 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
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@ -208,7 +212,7 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
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@ -219,6 +223,7 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
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@ -230,10 +235,8 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
</div>
<div class="ref-description">
<p>These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in <code>dplyr</code>s <code><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></code> and support grouped variables, see <em>Examples</em>.</p>
<p><code>count_R</code> and <code>count_IR</code> can be used to count resistant isolates, <code>count_S</code> and <code>count_SI</code> can be used to count susceptible isolates.<br /></p>
</div>
<pre class="usage"><span class='fu'>count_R</span>(<span class='no'>...</span>, <span class='kw'>only_all_tested</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
@ -252,7 +255,7 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
<span class='fu'>count_df</span>(<span class='no'>data</span>, <span class='kw'>translate_ab</span> <span class='kw'>=</span> <span class='st'>"name"</span>, <span class='kw'>language</span> <span class='kw'>=</span> <span class='fu'><a href='translate.html'>get_locale</a></span>(),
<span class='kw'>combine_SI</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>combine_IR</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
@ -274,7 +277,7 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
</tr>
<tr>
<th>language</th>
<td><p>language of the returned text, defaults to system language (see <code><a href='translate.html'>get_locale</a></code>) and can also be set with <code><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a>("AMR_locale")</code>. Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></td>
<td><p>language of the returned text, defaults to system language (see <code><a href='translate.html'>get_locale</a></code>) and can also be set with <code><a href='https://rdrr.io/r/base/options.html'>getOption</a>("AMR_locale")</code>. Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></td>
</tr>
<tr>
<th>combine_SI</th>
@ -285,38 +288,37 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
<td><p>a logical to indicate whether all values of I and R must be merged into one, so the output only consists of S vs. I+R (susceptible vs. non-susceptible). This is outdated, see parameter <code>combine_SI</code>.</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<p>Wickham H. <strong>Tidy Data.</strong> The Journal of Statistical Software, vol. 59, 2014. <a href='http://vita.had.co.nz/papers/tidy-data.html'>http://vita.had.co.nz/papers/tidy-data.html</a></p>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>Integer</p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>These functions are meant to count isolates. Use the <code><a href='portion.html'>portion</a>_*</code> functions to calculate microbial resistance.</p>
<p>The function <code>n_rsi</code> is an alias of <code>count_all</code>. They can be used to count all available isolates, i.e. where all input antibiotics have an available result (S, I or R). Their use is equal to <code><a href='https://dplyr.tidyverse.org/reference/n_distinct.html'>n_distinct</a></code>. Their function is equal to <code>count_S(...) + count_IR(...)</code>.</p>
<p>The function <code>count_df</code> takes any variable from <code>data</code> that has an <code>"rsi"</code> class (created with <code><a href='as.rsi.html'>as.rsi</a></code>) and counts the amounts of S, I and R. The resulting <em>tidy data</em> (see Source) <code>data.frame</code> will have three rows (S/I/R) and a column for each variable with class <code>"rsi"</code>.</p>
<p>The function <code>rsi_df</code> works exactly like <code>count_df</code>, but adds the percentage of S, I and R.</p>
<h2 class="hasAnchor" id="interpretation-of-s-i-and-r"><a class="anchor" href="#interpretation-of-s-i-and-r"></a>Interpretation of S, I and R</h2>
<p>In 2019, EUCAST has decided to change the definitions of susceptibility testing categories S, I and R as shown below (<a href='http://www.eucast.org/newsiandr/'>http://www.eucast.org/newsiandr/</a>). Results of several consultations on the new definitions are available on the EUCAST website under "Consultations".</p>
<p>In 2019, EUCAST has decided to change the definitions of susceptibility testing categories S, I and R as shown below (<a href='http://www.eucast.org/newsiandr/'>http://www.eucast.org/newsiandr/</a>). Results of several consultations on the new definitions are available on the EUCAST website under "Consultations".</p>
<ul>
<li><p><strong>S</strong> - Susceptible, standard dosing regimen: 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>
<li><p><strong>I</strong> - Susceptible, increased exposure: A microorganism is categorised as "Susceptible, Increased exposure" when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.</p></li>
<li><p><strong>R</strong> - Resistant: A microorganism is categorised as "Resistant" when there is a high likelihood of therapeutic failure even when there is increased exposure.</p></li>
</ul>
<p>Exposure is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.</p>
<p>Exposure is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.</p>
<p>This AMR package honours this new insight. Use <code><a href='portion.html'>portion_SI</a></code> to determine antimicrobial susceptibility and <code>count_SI</code> to count susceptible isolates.</p>
<h2 class="hasAnchor" id="combination-therapy"><a class="anchor" href="#combination-therapy"></a>Combination therapy</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, Antibiotic A and Antibiotic B, about how <code>portion_SI</code> works to calculate the %SI:</p>
<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, Antibiotic A and Antibiotic B, about how <code>portion_SI</code> works to calculate the %SI:</p>
<pre>
--------------------------------------------------------------------
only_all_tested = FALSE only_all_tested = TRUE
@ -335,28 +337,27 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
&lt;NA&gt; &lt;NA&gt; - - - -
--------------------------------------------------------------------
</pre>
<p>Please note that, in combination therapies, for <code>only_all_tested = TRUE</code> applies that:</p><pre>
<p>Please note that, in combination therapies, for <code>only_all_tested = TRUE</code> applies that:</p><pre>
count_S() + count_I() + count_R() == count_all()
portion_S() + portion_I() + portion_R() == 1
</pre><p>and that, in combination therapies, for <code>only_all_tested = FALSE</code> applies that:</p><pre>
count_S() + count_I() + count_R() &gt;= count_all()
portion_S() + portion_I() + portion_R() &gt;= 1
</pre>
<p>Using <code>only_all_tested</code> has no impact when only using one antibiotic as input.</p>
<p>Using <code>only_all_tested</code> has no impact when only using one antibiotic as input.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='portion.html'>portion</a>_*</code> to calculate microbial resistance and susceptibility.</p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<span class='co'># example_isolates is a data set available in the AMR package.</span>
<pre class="examples"><span class='co'># example_isolates is a data set available in the AMR package.</span>
?<span class='no'>example_isolates</span>
<span class='co'># Count resistant isolates</span>
@ -377,7 +378,7 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
<span class='fu'>count_SI</span>(<span class='no'>example_isolates</span>$<span class='no'>AMX</span>)
<span class='fu'><a href='portion.html'>portion_SI</a></span>(<span class='no'>example_isolates</span>$<span class='no'>AMX</span>) * <span class='fu'>n_rsi</span>(<span class='no'>example_isolates</span>$<span class='no'>AMX</span>)
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>dplyr</span>)
<span class='no'>example_isolates</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></span>(<span class='kw'>R</span> <span class='kw'>=</span> <span class='fu'>count_R</span>(<span class='no'>CIP</span>),
@ -396,9 +397,9 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
<span class='fu'>count_SI</span>(<span class='no'>example_isolates</span>$<span class='no'>GEN</span>) <span class='co'># 1399</span>
<span class='fu'>count_all</span>(<span class='no'>example_isolates</span>$<span class='no'>GEN</span>) <span class='co'># 1855</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/with'>with</a></span>(<span class='no'>example_isolates</span>,
<span class='fu'><a href='https://rdrr.io/r/base/with.html'>with</a></span>(<span class='no'>example_isolates</span>,
<span class='fu'>count_SI</span>(<span class='no'>AMC</span>, <span class='no'>GEN</span>)) <span class='co'># 1764</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/with'>with</a></span>(<span class='no'>example_isolates</span>,
<span class='fu'><a href='https://rdrr.io/r/base/with.html'>with</a></span>(<span class='no'>example_isolates</span>,
<span class='fu'>n_rsi</span>(<span class='no'>AMC</span>, <span class='no'>GEN</span>)) <span class='co'># 1936</span>
<span class='co'># Get portions S/I/R immediately of all rsi columns</span>
@ -410,43 +411,35 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
<span class='no'>example_isolates</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>hospital_id</span>, <span class='no'>AMX</span>, <span class='no'>CIP</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>count_df</span>(<span class='kw'>translate</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='co'># }</span></pre>
<span class='fu'>count_df</span>(<span class='kw'>translate</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</pre>
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<li><a href="#arguments">Arguments</a></li>
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<li><a href="#value">Value</a></li>
<li><a href="#details">Details</a></li>
<li><a href="#interpretation-of-s-i-and-r">Interpretation of S, I and R</a></li>
<li><a href="#combination-therapy">Combination therapy</a></li>
<li><a href="#read-more-on-our-website-">Read more on our website!</a></li>
<li><a href="#see-also">See also</a></li>
<li><a href="#examples">Examples</a></li>
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<p>Developed by <a href='https://www.rug.nl/staff/m.s.berends/'>Matthijs S. Berends</a>, <a href='https://www.rug.nl/staff/c.f.luz/'>Christian F. Luz</a>, <a href='https://www.rug.nl/staff/a.w.friedrich/'>Alex W. Friedrich</a>, <a href='https://www.rug.nl/staff/b.sinha/'>Bhanu N. M. Sinha</a>, <a href='https://www.rug.nl/staff/c.j.albers/'>Casper J. Albers</a>, <a href='https://www.rug.nl/staff/c.glasner/'>Corinna Glasner</a>.</p>
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@ -469,6 +462,8 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
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2
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@ -85,7 +85,7 @@
</button>
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<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9100</span>
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</span>
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44
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@ -15,21 +15,25 @@
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@ -45,15 +49,15 @@
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<meta property="og:title" content="Data set with 2,000 blood culture isolates — example_isolates" />
<meta property="og:description" content="An anonymised data set containing 2,000 microbial blood culture isolates with their full antibiograms found 4 different hospitals in the Netherlands, between 2001 and 2017. This data.frame can be used to practice AMR analysis. For examples, please read the tutorial on our website." />
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@ -189,7 +194,6 @@
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@ -207,7 +211,7 @@
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@ -218,6 +222,7 @@
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@ -229,16 +234,15 @@
</div>
<div class="ref-description">
<p>An anonymised data set containing 2,000 microbial blood culture isolates with their full antibiograms found 4 different hospitals in the Netherlands, between 2001 and 2017. This <code>data.frame</code> can be used to practice AMR analysis. For examples, please read <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>the tutorial on our website</a>.</p>
</div>
<pre class="usage"><span class='no'>example_isolates</span></pre>
<h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
<p>A <code><a href='https://www.rdocumentation.org/packages/base/topics/data.frame'>data.frame</a></code> with 2,000 observations and 49 variables:</p><dl class='dl-horizontal'>
<p>A <code><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a></code> with 2,000 observations and 49 variables:</p><dl class='dl-horizontal'>
<dt><code>date</code></dt><dd><p>date of receipt at the laboratory</p></dd>
<dt><code>hospital_id</code></dt><dd><p>ID of the hospital, from A to D</p></dd>
<dt><code>ward_icu</code></dt><dd><p>logical to determine if ward is an intensive care unit</p></dd>
@ -249,35 +253,35 @@
<dt><code>patient_id</code></dt><dd><p>ID of the patient, first 10 characters of an SHA hash containing irretrievable information</p></dd>
<dt><code>mo</code></dt><dd><p>ID of microorganism created with <code><a href='as.mo.html'>as.mo</a></code>, see also <code><a href='microorganisms.html'>microorganisms</a></code></p></dd>
<dt><code>PEN:RIF</code></dt><dd><p>40 different antibiotics with class <code>rsi</code> (see <code><a href='as.rsi.html'>as.rsi</a></code>); these column names occur in <code><a href='antibiotics.html'>antibiotics</a></code> data set and can be translated with <code><a href='ab_property.html'>ab_name</a></code></p></dd>
</dl>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9059</span>
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@ -189,7 +194,6 @@
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@ -218,6 +222,7 @@
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@ -229,40 +234,40 @@
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<p>These functions are extensions of functions in other packages.</p>
</div>
<pre class="usage"><span class='fu'>scale_type.mo</span>(<span class='no'>x</span>)
<span class='fu'>scale_type.ab</span>(<span class='no'>x</span>)</pre>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
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<meta property="og:title" content="Filter isolates on result in antibiotic class — filter_ab_class" />
<meta property="og:description" content="Filter isolates on results in specific antibiotic variables based on their class (ATC groups). This makes it easy to get a list of isolates that were tested for e.g. any aminoglycoside." />
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<div class="ref-description">
<p>Filter isolates on results in specific antibiotic variables based on their class (ATC groups). This makes it easy to get a list of isolates that were tested for e.g. any aminoglycoside.</p>
</div>
<pre class="usage"><span class='fu'>filter_ab_class</span>(<span class='no'>x</span>, <span class='no'>ab_class</span>, <span class='kw'>result</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>scope</span> <span class='kw'>=</span> <span class='st'>"any"</span>, <span class='no'>...</span>)
@ -259,7 +262,7 @@
<span class='fu'>filter_macrolides</span>(<span class='no'>x</span>, <span class='kw'>result</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>scope</span> <span class='kw'>=</span> <span class='st'>"any"</span>, <span class='no'>...</span>)
<span class='fu'>filter_tetracyclines</span>(<span class='no'>x</span>, <span class='kw'>result</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>scope</span> <span class='kw'>=</span> <span class='st'>"any"</span>, <span class='no'>...</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
@ -284,23 +287,21 @@
<td><p>parameters passed on to <code>filter_at</code> from the <code>dplyr</code> package</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>The <code>group</code> column in <code><a href='antibiotics.html'>antibiotics</a></code> data set will be searched for <code>ab_class</code> (case-insensitive). If no results are found, the <code>atc_group1</code> and <code>atc_group2</code> columns will be searched. Next, <code>x</code> will be checked for column names with a value in any abbreviations, codes or official names found in the <code>antibiotics</code> data set.</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
<pre class="examples"><span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>dplyr</span>)
<span class='co'># filter on isolates that have any result for any aminoglycoside</span>
<span class='no'>example_isolates</span> <span class='kw'>%&gt;%</span> <span class='fu'>filter_aminoglycosides</span>()
<span class='co'># this is essentially the same as (but without determination of column names):</span>
<span class='no'>example_isolates</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter_all.html'>filter_at</a></span>(<span class='kw'>.vars</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"GEN"</span>, <span class='st'>"TOB"</span>, <span class='st'>"AMK"</span>, <span class='st'>"KAN"</span>)),
<span class='kw'>.vars_predicate</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/all_vars.html'>any_vars</a></span>(<span class='no'>.</span> <span class='kw'>%in%</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"S"</span>, <span class='st'>"I"</span>, <span class='st'>"R"</span>)))
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter_all.html'>filter_at</a></span>(<span class='kw'>.vars</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"GEN"</span>, <span class='st'>"TOB"</span>, <span class='st'>"AMK"</span>, <span class='st'>"KAN"</span>)),
<span class='kw'>.vars_predicate</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/all_vars.html'>any_vars</a></span>(<span class='no'>.</span> <span class='kw'>%in%</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"S"</span>, <span class='st'>"I"</span>, <span class='st'>"R"</span>)))
<span class='co'># filter on isolates that show resistance to ANY aminoglycoside</span>
@ -319,30 +320,29 @@
<span class='co'># all aminoglycosides and all fluoroquinolones</span>
<span class='no'>example_isolates</span> <span class='kw'>%&gt;%</span>
<span class='fu'>filter_aminoglycosides</span>(<span class='st'>"R"</span>, <span class='st'>"all"</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>filter_fluoroquinolones</span>(<span class='st'>"R"</span>, <span class='st'>"all"</span>)
<span class='co'># }</span></pre>
<span class='fu'>filter_fluoroquinolones</span>(<span class='st'>"R"</span>, <span class='st'>"all"</span>)</pre>
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<meta property="og:description" content="Create a frequency table of a vector with items or a data.frame. Supports quasiquotation and markdown for reports. Best practice is: data %&amp;gt;% freq(var).
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<h1>Frequency table</h1>
<div class="hidden name"><code>freq.Rd</code></div>
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<div class="ref-description">
<p>Create a frequency table of a vector with items or a <code>data.frame</code>. Supports quasiquotation and markdown for reports. Best practice is: <code>data %&gt;% freq(var)</code>.<br />
<code>top_freq</code> can be used to get the top/bottom <em>n</em> items of a frequency table, with counts as names.</p>
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<pre class="usage"><span class='fu'>freq</span>(<span class='no'>x</span>, <span class='no'>...</span>, <span class='kw'>sort.count</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>nmax</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a></span>(<span class='st'>"max.print.freq"</span>),
<span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>row.names</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>markdown</span> <span class='kw'>=</span> !<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/interactive'>interactive</a></span>(),
<span class='kw'>digits</span> <span class='kw'>=</span> <span class='fl'>2</span>, <span class='kw'>quote</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>header</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>title</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
<span class='kw'>na</span> <span class='kw'>=</span> <span class='st'>"&lt;NA&gt;"</span>, <span class='kw'>droplevels</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>sep</span> <span class='kw'>=</span> <span class='st'>" "</span>,
<span class='kw'>decimal.mark</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a></span>(<span class='st'>"OutDec"</span>), <span class='kw'>big.mark</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/ifelse'>ifelse</a></span>(<span class='no'>decimal.mark</span> <span class='kw'>!=</span>
<span class='st'>","</span>, <span class='st'>","</span>, <span class='st'>"."</span>))
<span class='fu'>frequency_tbl</span>(<span class='no'>x</span>, <span class='no'>...</span>, <span class='kw'>sort.count</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
<span class='kw'>nmax</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a></span>(<span class='st'>"max.print.freq"</span>), <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>row.names</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
<span class='kw'>markdown</span> <span class='kw'>=</span> !<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/interactive'>interactive</a></span>(), <span class='kw'>digits</span> <span class='kw'>=</span> <span class='fl'>2</span>, <span class='kw'>quote</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
<span class='kw'>header</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>title</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>na</span> <span class='kw'>=</span> <span class='st'>"&lt;NA&gt;"</span>, <span class='kw'>droplevels</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
<span class='kw'>sep</span> <span class='kw'>=</span> <span class='st'>" "</span>, <span class='kw'>decimal.mark</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a></span>(<span class='st'>"OutDec"</span>),
<span class='kw'>big.mark</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/ifelse'>ifelse</a></span>(<span class='no'>decimal.mark</span> <span class='kw'>!=</span> <span class='st'>","</span>, <span class='st'>","</span>, <span class='st'>"."</span>))
<span class='fu'>top_freq</span>(<span class='no'>f</span>, <span class='no'>n</span>)
<span class='fu'>header</span>(<span class='no'>f</span>, <span class='kw'>property</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)
<span class='co'># S3 method for freq</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/print'>print</a></span>(<span class='no'>x</span>, <span class='kw'>nmax</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a></span>(<span class='st'>"max.print.freq"</span>, <span class='kw'>default</span> <span class='kw'>=</span> <span class='fl'>15</span>),
<span class='kw'>markdown</span> <span class='kw'>=</span> !<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/interactive'>interactive</a></span>(), <span class='kw'>header</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
<span class='kw'>decimal.mark</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a></span>(<span class='st'>"OutDec"</span>), <span class='kw'>big.mark</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/ifelse'>ifelse</a></span>(<span class='no'>decimal.mark</span> <span class='kw'>!=</span>
<span class='st'>","</span>, <span class='st'>","</span>, <span class='st'>"."</span>), <span class='no'>...</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>x</th>
<td><p>vector of any class or a <code><a href='https://www.rdocumentation.org/packages/base/topics/data.frame'>data.frame</a></code>, <code>tibble</code> (may contain a grouping variable) or <code><a href='https://www.rdocumentation.org/packages/base/topics/table'>table</a></code></p></td>
</tr>
<tr>
<th>...</th>
<td><p>up to nine different columns of <code>x</code> when <code>x</code> is a <code>data.frame</code> or <code>tibble</code>, to calculate frequencies from - see Examples. Also supports quasiquotion.</p></td>
</tr>
<tr>
<th>sort.count</th>
<td><p>sort on count, i.e. frequencies. This will be <code>TRUE</code> at default for everything except when using grouping variables.</p></td>
</tr>
<tr>
<th>nmax</th>
<td><p>number of row to print. The default, <code>15</code>, uses <code><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a>("max.print.freq")</code>. Use <code>nmax = 0</code>, <code>nmax = Inf</code>, <code>nmax = NULL</code> or <code>nmax = NA</code> to print all rows.</p></td>
</tr>
<tr>
<th>na.rm</th>
<td><p>a logical value indicating whether <code>NA</code> values should be removed from the frequency table. The header (if set) will always print the amount of <code>NA</code>s.</p></td>
</tr>
<tr>
<th>row.names</th>
<td><p>a logical value indicating whether row indices should be printed as <code>1:nrow(x)</code></p></td>
</tr>
<tr>
<th>markdown</th>
<td><p>a logical value indicating whether the frequency table should be printed in markdown format. This will print all rows (except when <code>nmax</code> is defined) and is default behaviour in non-interactive R sessions (like when knitting RMarkdown files).</p></td>
</tr>
<tr>
<th>digits</th>
<td><p>how many significant digits are to be used for numeric values in the header (not for the items themselves, that depends on <code><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a>("digits")</code>)</p></td>
</tr>
<tr>
<th>quote</th>
<td><p>a logical value indicating whether or not strings should be printed with surrounding quotes. Default is to print them only around characters that are actually numeric values.</p></td>
</tr>
<tr>
<th>header</th>
<td><p>a logical value indicating whether an informative header should be printed</p></td>
</tr>
<tr>
<th>title</th>
<td><p>text to show above frequency table, at default to tries to coerce from the variables passed to <code>x</code></p></td>
</tr>
<tr>
<th>na</th>
<td><p>a character string that should be used to show empty (<code>NA</code>) values (only useful when <code>na.rm = FALSE</code>)</p></td>
</tr>
<tr>
<th>droplevels</th>
<td><p>a logical value indicating whether in factors empty levels should be dropped</p></td>
</tr>
<tr>
<th>sep</th>
<td><p>a character string to separate the terms when selecting multiple columns</p></td>
</tr>
<tr>
<th>decimal.mark</th>
<td><p><!-- % -->
used for prettying (longish) numerical and complex sequences.
Passed to <code><a href='https://www.rdocumentation.org/packages/base/topics/formatc'>prettyNum</a></code>: that help page explains the details.</p></td>
</tr>
<tr>
<th>big.mark</th>
<td><p><!-- % -->
used for prettying (longish) numerical and complex sequences.
Passed to <code><a href='https://www.rdocumentation.org/packages/base/topics/formatc'>prettyNum</a></code>: that help page explains the details.</p></td>
</tr>
<tr>
<th>f</th>
<td><p>a frequency table</p></td>
</tr>
<tr>
<th>n</th>
<td><p>number of top <em>n</em> items to return, use -n for the bottom <em>n</em> items. It will include more than <code>n</code> rows if there are ties.</p></td>
</tr>
<tr>
<th>property</th>
<td><p>property in header to return this value directly</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>A <code>data.frame</code> (with an additional class <code>"freq"</code>) with five columns: <code>item</code>, <code>count</code>, <code>percent</code>, <code>cum_count</code> and <code>cum_percent</code>.</p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>Frequency tables (or frequency distributions) are summaries of the distribution of values in a sample. With the `freq` function, you can create univariate frequency tables. Multiple variables will be pasted into one variable, so it forces a univariate distribution. This package also has a vignette available to explain the use of this function further, run <code><a href='https://www.rdocumentation.org/packages/utils/topics/browseVignettes'>browseVignettes("AMR")</a></code> to read it.</p>
<p>For numeric values of any class, these additional values will all be calculated with <code>na.rm = TRUE</code> and shown into the header:</p><ul>
<li><p>Mean, using <code><a href='https://www.rdocumentation.org/packages/base/topics/mean'>mean</a></code></p></li>
<li><p>Standard Deviation, using <code><a href='https://www.rdocumentation.org/packages/stats/topics/sd'>sd</a></code></p></li>
<li><p>Coefficient of Variation (CV), the standard deviation divided by the mean</p></li>
<li><p>Mean Absolute Deviation (MAD), using <code><a href='https://www.rdocumentation.org/packages/stats/topics/mad'>mad</a></code></p></li>
<li><p>Tukey Five-Number Summaries (minimum, Q1, median, Q3, maximum), using <code><a href='https://www.rdocumentation.org/packages/stats/topics/fivenum'>fivenum</a></code></p></li>
<li><p>Interquartile Range (IQR) calculated as <code>Q3 - Q1</code> using the Tukey Five-Number Summaries, i.e. <strong>not</strong> using the <code><a href='https://www.rdocumentation.org/packages/stats/topics/quantile'>quantile</a></code> function</p></li>
<li><p>Coefficient of Quartile Variation (CQV, sometimes called coefficient of dispersion), calculated as <code>(Q3 - Q1) / (Q3 + Q1)</code> using the Tukey Five-Number Summaries</p></li>
<li><p>Outliers (total count and unique count), using <code><a href='https://www.rdocumentation.org/packages/grDevices/topics/boxplot.stats'>boxplot.stats</a></code></p></li>
</ul>
<p>For dates and times of any class, these additional values will be calculated with <code>na.rm = TRUE</code> and shown into the header:</p><ul>
<li><p>Oldest, using <code><a href='https://www.rdocumentation.org/packages/base/topics/Extremes'>min</a></code></p></li>
<li><p>Newest, using <code><a href='https://www.rdocumentation.org/packages/base/topics/Extremes'>max</a></code>, with difference between newest and oldest</p></li>
<li><p>Median, using <code><a href='https://www.rdocumentation.org/packages/stats/topics/median'>median</a></code>, with percentage since oldest</p></li>
</ul>
<p>In factors, all factor levels that are not existing in the input data will be dropped.</p>
<p>The function <code>top_freq</code> uses <code><a href='https://dplyr.tidyverse.org/reference/top_n.html'>top_n</a></code> internally and will include more than <code>n</code> rows if there are ties.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
<span class='co'># this all gives the same result:</span>
<span class='fu'>freq</span>(<span class='no'>septic_patients</span>$<span class='no'>hospital_id</span>)
<span class='fu'>freq</span>(<span class='no'>septic_patients</span>[, <span class='st'>"hospital_id"</span>])
<span class='no'>septic_patients</span>$<span class='no'>hospital_id</span> <span class='kw'>%&gt;%</span> <span class='fu'>freq</span>()
<span class='no'>septic_patients</span>[, <span class='st'>"hospital_id"</span>] <span class='kw'>%&gt;%</span> <span class='fu'>freq</span>()
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span> <span class='fu'>freq</span>(<span class='st'>"hospital_id"</span>)
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span> <span class='fu'>freq</span>(<span class='no'>hospital_id</span>) <span class='co'>#&lt;- easiest to remember (tidyverse)</span>
<span class='co'># you could also use `select` or `pull` to get your variables</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>hospital_id</span> <span class='kw'>==</span> <span class='st'>"A"</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>mo</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>()
<span class='co'># multiple selected variables will be pasted together</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='no'>left_join_microorganisms</span> <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>genus</span>, <span class='no'>species</span>)
<span class='co'># functions as quasiquotation are also supported</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='fu'><a href='mo_property.html'>mo_genus</a></span>(<span class='no'>mo</span>), <span class='fu'><a href='mo_property.html'>mo_species</a></span>(<span class='no'>mo</span>))
<span class='co'># group a variable and analyse another</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>gender</span>)
<span class='co'># get top 10 bugs of hospital A as a vector</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>hospital_id</span> <span class='kw'>==</span> <span class='st'>"A"</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>mo</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>top_freq</span>(<span class='fl'>10</span>)
<span class='co'># save frequency table to an object</span>
<span class='no'>years</span> <span class='kw'>&lt;-</span> <span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='kw'>year</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/format'>format</a></span>(<span class='no'>date</span>, <span class='st'>"%Y"</span>)) <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>year</span>)
<span class='co'># show only the top 5</span>
<span class='no'>years</span> <span class='kw'>%&gt;%</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/print'>print</a></span>(<span class='kw'>nmax</span> <span class='kw'>=</span> <span class='fl'>5</span>)
<span class='co'># save to an object with formatted percentages</span>
<span class='no'>years</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/format'>format</a></span>(<span class='no'>years</span>)
<span class='co'># print a histogram of numeric values</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>age</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/graphics/topics/hist'>hist</a></span>()
<span class='co'># or a boxplot of numeric values</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>age</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/graphics/topics/boxplot'>boxplot</a></span>()
<span class='co'># or even a boxplot per group</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>age</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/graphics/topics/boxplot'>boxplot</a></span>()
<span class='co'># or print all points to a regular plot</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>age</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/graphics/topics/plot'>plot</a></span>()
<span class='co'># transform to a data.frame or tibble</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>age</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/as.data.frame'>as.data.frame</a></span>()
<span class='co'># or transform (back) to a vector</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>age</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/vector'>as.vector</a></span>()
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/identical'>identical</a></span>(<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>age</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/vector'>as.vector</a></span>() <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/sort'>sort</a></span>(),
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/sort'>sort</a></span>(<span class='no'>septic_patients</span>$<span class='no'>age</span>)) <span class='co'># TRUE</span>
<span class='co'># it also supports `table` objects</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/table'>table</a></span>(<span class='no'>septic_patients</span>$<span class='no'>gender</span>,
<span class='no'>septic_patients</span>$<span class='no'>age</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='kw'>sep</span> <span class='kw'>=</span> <span class='st'>" **sep** "</span>)
<span class='co'># only get selected columns</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>item</span>, <span class='no'>percent</span>)
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>count</span>, -<span class='no'>cum_count</span>)
<span class='co'># check differences between frequency tables</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/diff'>diff</a></span>(<span class='fu'>freq</span>(<span class='no'>septic_patients</span>$<span class='no'>TMP</span>),
<span class='fu'>freq</span>(<span class='no'>septic_patients</span>$<span class='no'>SXT</span>))
<span class='co'># }</span></pre>
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<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked">
<li><a href="#arguments">Arguments</a></li>
<li><a href="#value">Value</a></li>
<li><a href="#details">Details</a></li>
<li><a href="#read-more-on-our-website-">Read more on our website!</a></li>
<li><a href="#examples">Examples</a></li>
</ul>
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