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<li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
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@ -195,7 +85,7 @@
<img src="../logo.svg" class="logo" alt=""><h1>How to conduct AMR data analysis</h1>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/AMR.Rmd" class="external-link"><code>vignettes/AMR.Rmd</code></a></small>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/AMR.Rmd" class="external-link"><code>vignettes/AMR.Rmd</code></a></small>
<div class="d-none name"><code>AMR.Rmd</code></div>
</div>
@ -205,7 +95,7 @@
website update since they are based on randomly created values and the
page was written in <a href="https://rmarkdown.rstudio.com/" class="external-link">R
Markdown</a>. However, the methodology remains unchanged. This page was
generated on 23 June 2024.</p>
generated on 16 July 2024.</p>
<div class="section level2">
<h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
</h2>
@ -261,21 +151,21 @@ make the structure of your data generally look like this:</p>
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2024-06-23</td>
<td align="center">2024-07-16</td>
<td align="center">abcd</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">S</td>
</tr>
<tr class="even">
<td align="center">2024-06-23</td>
<td align="center">2024-07-16</td>
<td align="center">abcd</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">R</td>
</tr>
<tr class="odd">
<td align="center">2024-06-23</td>
<td align="center">2024-07-16</td>
<td align="center">efgh</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
@ -318,9 +208,8 @@ have extracted from their laboratory systems:</p>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> M3 A 2015-10-25 E. coli R S S S </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> J3 A 2019-06-19 E. coli S S S S </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> G6 A 2015-04-27 S. aureus S S S S </span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,990 more rows</span></span></span></code></pre></div>
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,990 more rows</span></span></span>
<span></span>
<span><span class="co"># we will use 'our_data' as the data set name for this tutorial</span></span>
<span><span class="va">our_data</span> <span class="op">&lt;-</span> <span class="va">example_isolates_unclean</span></span></code></pre></div>
<p>For AMR data analysis, we would like the microorganism column to
@ -333,24 +222,21 @@ cleaned as SIR values as well.</p>
<p>With <code><a href="../reference/as.mo.html">as.mo()</a></code>, users can transform arbitrary
microorganism names or codes to current taxonomy. The <code>AMR</code>
package contains up-to-date taxonomic data. To be specific, currently
included data were retrieved on 11 Dec 2022.</p>
included data were retrieved on 24 Jun 2024.</p>
<p>The codes of the AMR packages that come from <code><a href="../reference/as.mo.html">as.mo()</a></code> are
short, but still human readable. More importantly, <code><a href="../reference/as.mo.html">as.mo()</a></code>
supports all kinds of input:</p>
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"Klebsiella pneumoniae"</span><span class="op">)</span></span>
<span><span class="co">#&gt; Class 'mo'</span></span>
<span><span class="co">#&gt; [1] B_KLBSL_PNMN</span></span></code></pre></div>
<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] B_KLBSL_PNMN</span></span>
<span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
<span><span class="co">#&gt; Class 'mo'</span></span>
<span><span class="co">#&gt; [1] B_KLBSL_PNMN</span></span></code></pre></div>
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"KLEPNE"</span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] B_KLBSL_PNMN</span></span>
<span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"KLEPNE"</span><span class="op">)</span></span>
<span><span class="co">#&gt; Class 'mo'</span></span>
<span><span class="co">#&gt; [1] B_KLBSL_PNMN</span></span></code></pre></div>
<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"KLPN"</span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] B_KLBSL_PNMN</span></span>
<span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"KLPN"</span><span class="op">)</span></span>
<span><span class="co">#&gt; Class 'mo'</span></span>
<span><span class="co">#&gt; [1] B_KLBSL_PNMN</span></span></code></pre></div>
<p>The first character in above codes denote their taxonomic kingdom,
@ -360,58 +246,53 @@ retrieve taxonomic properties, such as the name, genus, species, family,
order, and even Gram-stain. They all start with <code>mo_</code> and
they use <code><a href="../reference/as.mo.html">as.mo()</a></code> internally, so that still any arbitrary
user input can be used:</p>
<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/mo_property.html">mo_family</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] "Enterobacteriaceae"</span></span></code></pre></div>
<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] "Klebsiella"</span></span></code></pre></div>
<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/mo_property.html">mo_species</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] "pneumoniae"</span></span></code></pre></div>
<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; [1] "Enterobacteriaceae"</span></span>
<span><span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] "Klebsiella"</span></span>
<span><span class="fu"><a href="../reference/mo_property.html">mo_species</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] "pneumoniae"</span></span>
<span></span>
<span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="st">"Klebsiella pneumoniae"</span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] "Gram-negative"</span></span></code></pre></div>
<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; [1] "Gram-negative"</span></span>
<span></span>
<span><span class="fu"><a href="../reference/mo_property.html">mo_ref</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] "Trevisan, 1887"</span></span></code></pre></div>
<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; [1] "Trevisan, 1887"</span></span>
<span></span>
<span><span class="fu"><a href="../reference/mo_property.html">mo_snomed</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
<span><span class="co">#&gt; [[1]]</span></span>
<span><span class="co">#&gt; [1] "1098101000112102" "446870005" "1098201000112108" "409801009" </span></span>
<span><span class="co">#&gt; [5] "56415008" "714315002" "713926009"</span></span></code></pre></div>
<p>Now we can thus clean our data:</p>
<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">our_data</span><span class="op">$</span><span class="va">bacteria</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="va">our_data</span><span class="op">$</span><span class="va">bacteria</span>, info <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span>
<span><span class="co">#&gt; ℹ Microorganism translation was uncertain for four microorganisms. Run</span></span>
<span><span class="co">#&gt; mo_uncertainties() to review these uncertainties, or use</span></span>
<span><span class="co">#&gt; add_custom_microorganisms() to add custom entries.</span></span></code></pre></div>
<p>Apparently, there was some uncertainty about the translation to
taxonomic codes. Let’s check this:</p>
<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/as.mo.html">mo_uncertainties</a></span><span class="op">(</span><span class="op">)</span></span>
<span><span class="co">#&gt; Matching scores are based on the resemblance between the input and the full</span></span>
<span><span class="co">#&gt; taxonomic name, and the pathogenicity in humans. See ?mo_matching_score.</span></span>
<span><span class="co">#&gt; </span></span>
<span><span class="co">#&gt; --------------------------------------------------------------------------------</span></span>
<span><span class="co">#&gt; "E. coli" -&gt; Escherichia coli (B_ESCHR_COLI, 0.688)</span></span>
<span><span class="co">#&gt; Also matched: Enterobacter cowanii (0.600), Eubacterium combesii</span></span>
<span><span class="co">#&gt; Also matched: Escherichia coli coli (0.643), Escherichia coli</span></span>
<span><span class="co">#&gt; expressing (0.611), Enterobacter cowanii (0.600), Eubacterium combesii</span></span>
<span><span class="co">#&gt; (0.600), Eggerthia catenaformis (0.591), Eubacterium callanderi</span></span>
<span><span class="co">#&gt; (0.591), Enterocloster citroniae (0.587), Eubacterium cylindroides</span></span>
<span><span class="co">#&gt; (0.583), Enterococcus casseliflavus (0.577), Enterobacter cloacae</span></span>
<span><span class="co">#&gt; cloacae (0.571), Enterobacter cloacae complex (0.571), and Ehrlichia</span></span>
<span><span class="co">#&gt; canis (0.567)</span></span>
<span><span class="co">#&gt; (0.583), Enterococcus casseliflavus (0.577), and Enterobacter cloacae</span></span>
<span><span class="co">#&gt; cloacae (0.571)</span></span>
<span><span class="co">#&gt; --------------------------------------------------------------------------------</span></span>
<span><span class="co">#&gt; "K. pneumoniae" -&gt; Klebsiella pneumoniae (B_KLBSL_PNMN, 0.786)</span></span>
<span><span class="co">#&gt; Also matched: Klebsiella pneumoniae ozaenae (0.707), Klebsiella</span></span>
<span><span class="co">#&gt; pneumoniae pneumoniae (0.688), Klebsiella pneumoniae rhinoscleromatis</span></span>
<span><span class="co">#&gt; (0.658), Klebsiella pasteurii (0.500), Klebsiella planticola (0.500),</span></span>
<span><span class="co">#&gt; Kingella potus (0.400), Kosakonia pseudosacchari (0.361), Kaistella</span></span>
<span><span class="co">#&gt; palustris (0.333), Kocuria palustris (0.333), and Kocuria pelophila</span></span>
<span><span class="co">#&gt; (0.333)</span></span>
<span><span class="co">#&gt; Kingella potus (0.400), Kluyveromyces pseudotropicale (0.386),</span></span>
<span><span class="co">#&gt; Kluyveromyces pseudotropicalis (0.363), Kosakonia pseudosacchari</span></span>
<span><span class="co">#&gt; (0.361), and Kluyveromyces pseudotropicalis pseudotropicalis (0.361)</span></span>
<span><span class="co">#&gt; --------------------------------------------------------------------------------</span></span>
<span><span class="co">#&gt; "S. aureus" -&gt; Staphylococcus aureus (B_STPHY_AURS, 0.690)</span></span>
<span><span class="co">#&gt; Also matched: Staphylococcus aureus aureus (0.643), Staphylococcus</span></span>
@ -448,7 +329,7 @@ diffusion values, read more about that on the <code><a href="../reference/as.sir
page.</p>
<p>For now, we will just clean the SIR columns in our data using
dplyr:</p>
<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="co"># method 1, be explicit about the columns:</span></span>
<span><span class="va">our_data</span> <span class="op">&lt;-</span> <span class="va">our_data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_at</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html" class="external-link">vars</a></span><span class="op">(</span><span class="va">AMX</span><span class="op">:</span><span class="va">GEN</span><span class="op">)</span>, <span class="va">as.sir</span><span class="op">)</span></span>
@ -516,7 +397,7 @@ analysis, but the default phenotype-based method is in any case the
method to properly correct for most duplicate isolates. Read more about
the methods on the <code><a href="../reference/first_isolate.html">first_isolate()</a></code> page.</p>
<p>The outcome of the function can easily be added to our data:</p>
<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">our_data</span> <span class="op">&lt;-</span> <span class="va">our_data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>first <span class="op">=</span> <span class="fu"><a href="../reference/first_isolate.html">first_isolate</a></span><span class="op">(</span>info <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span><span class="op">)</span></span>
<span><span class="co">#&gt; ℹ Determining first isolates using an episode length of 365 days</span></span>
@ -530,16 +411,16 @@ the methods on the <code><a href="../reference/first_isolate.html">first_isolate
<p>So only 90% is suitable for resistance analysis! We can now filter on
it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter()</a></code> function, also from the
<code>dplyr</code> package:</p>
<div class="sourceCode" id="cb18"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">our_data_1st</span> <span class="op">&lt;-</span> <span class="va">our_data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">first</span> <span class="op">==</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div>
<p>For future use, the above two syntaxes can be shortened:</p>
<div class="sourceCode" id="cb19"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">our_data_1st</span> <span class="op">&lt;-</span> <span class="va">our_data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="../reference/first_isolate.html">filter_first_isolate</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
<p>So we end up with 2 712 isolates for analysis. Now our data looks
like:</p>
<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">our_data_1st</span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 2,712 × 9</span></span></span>
<span><span class="co">#&gt; patient_id hospital date bacteria AMX AMC CIP GEN first</span></span>
@ -564,7 +445,7 @@ like:</p>
<p>The base R <code><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary()</a></code> function gives a good first
impression, as it comes with support for the new <code>mo</code> and
<code>sir</code> classes that we now have in our data set:</p>
<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">our_data_1st</span><span class="op">)</span></span>
<span><span class="co">#&gt; patient_id hospital date </span></span>
<span><span class="co">#&gt; Length:2712 Length:2712 Min. :2011-01-01 </span></span>
@ -586,9 +467,8 @@ impression, as it comes with support for the new <code>mo</code> and
<span><span class="co">#&gt; %SDD : 0.0% (n=0) %SDD : 0.0% (n=0) </span></span>
<span><span class="co">#&gt; %I : 6.6% (n=178) %I : 3.1% (n=85) </span></span>
<span><span class="co">#&gt; %R :42.0% (n=1138) %R :37.3% (n=1011) </span></span>
<span><span class="co">#&gt; %NI : 0.0% (n=0) %NI : 0.0% (n=0)</span></span></code></pre></div>
<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; %NI : 0.0% (n=0) %NI : 0.0% (n=0)</span></span>
<span></span>
<span><span class="fu"><a href="https://pillar.r-lib.org/reference/glimpse.html" class="external-link">glimpse</a></span><span class="op">(</span><span class="va">our_data_1st</span><span class="op">)</span></span>
<span><span class="co">#&gt; Rows: 2,712</span></span>
<span><span class="co">#&gt; Columns: 9</span></span>
@ -600,9 +480,8 @@ impression, as it comes with support for the new <code>mo</code> and
<span><span class="co">#&gt; $ AMC <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> I, I, I, S, S, S, S, S, S, S, S, S, I, S, S, S, S, R, S, S,…</span></span>
<span><span class="co">#&gt; $ CIP <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> S, S, S, S, R, S, S, S, S, S, S, S, S, S, S, S, S, S, S, S,…</span></span>
<span><span class="co">#&gt; $ GEN <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> S, S, S, S, S, S, S, S, S, S, R, S, S, S, S, S, S, S, S, S,…</span></span>
<span><span class="co">#&gt; $ first <span style="color: #949494; font-style: italic;">&lt;lgl&gt;</span> TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,…</span></span></code></pre></div>
<div class="sourceCode" id="cb23"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; $ first <span style="color: #949494; font-style: italic;">&lt;lgl&gt;</span> TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,…</span></span>
<span></span>
<span><span class="co"># number of unique values per column:</span></span>
<span><span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">sapply</a></span><span class="op">(</span><span class="va">our_data_1st</span>, <span class="va">n_distinct</span><span class="op">)</span></span>
<span><span class="co">#&gt; patient_id hospital date bacteria AMX AMC CIP </span></span>
@ -615,7 +494,7 @@ impression, as it comes with support for the new <code>mo</code> and
<p>To just get an idea how the species are distributed, create a
frequency table with <code><a href="../reference/count.html">count()</a></code> based on the name of the
microorganisms:</p>
<div class="sourceCode" id="cb24"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">our_data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="../reference/count.html">count</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">bacteria</span><span class="op">)</span>, sort <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 4 × 2</span></span></span>
@ -624,9 +503,8 @@ microorganisms:</p>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> Escherichia coli <span style="text-decoration: underline;">1</span>518</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> Staphylococcus aureus 730</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> Streptococcus pneumoniae 426</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> Klebsiella pneumoniae 326</span></span></code></pre></div>
<div class="sourceCode" id="cb25"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> Klebsiella pneumoniae 326</span></span>
<span></span>
<span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="../reference/count.html">count</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">bacteria</span><span class="op">)</span>, sort <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 4 × 2</span></span></span>
@ -643,7 +521,7 @@ microorganisms:</p>
<p>Using so-called antibiotic class selectors, you can select or filter
columns based on the antibiotic class that your antibiotic results are
in:</p>
<div class="sourceCode" id="cb26"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">date</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span></span>
<span><span class="co">#&gt; ℹ For aminoglycosides() using column 'GEN' (gentamicin)</span></span>
@ -660,9 +538,8 @@ in:</p>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> 2015-04-27 S </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> 2011-06-21 S </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> 2014-09-05 S </span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,702 more rows</span></span></span></code></pre></div>
<div class="sourceCode" id="cb27"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,702 more rows</span></span></span>
<span></span>
<span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">bacteria</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">betalactams</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span></span>
<span><span class="co">#&gt; ℹ For betalactams() using columns 'AMX' (amoxicillin) and 'AMC'</span></span>
@ -680,9 +557,8 @@ in:</p>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> B_STPHY_AURS S S </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> B_ESCHR_COLI S S </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> B_ESCHR_COLI S S </span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,702 more rows</span></span></span></code></pre></div>
<div class="sourceCode" id="cb28"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,702 more rows</span></span></span>
<span></span>
<span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">bacteria</span>, <span class="fu"><a href="https://tidyselect.r-lib.org/reference/where.html" class="external-link">where</a></span><span class="op">(</span><span class="va">is.sir</span><span class="op">)</span><span class="op">)</span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 2,712 × 5</span></span></span>
@ -698,9 +574,8 @@ in:</p>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> B_STPHY_AURS S S S S </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> B_ESCHR_COLI S S S S </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> B_ESCHR_COLI S S S S </span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,702 more rows</span></span></span></code></pre></div>
<div class="sourceCode" id="cb29"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,702 more rows</span></span></span>
<span></span>
<span><span class="co"># filtering using AB selectors is also possible:</span></span>
<span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/any.html" class="external-link">any</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span><span class="op">)</span></span>
@ -718,9 +593,8 @@ in:</p>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> P5 A 2019-03-09 B_STPHY_AURS S S S R TRUE </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> Q8 A 2019-08-10 B_STPHY_AURS S S S R TRUE </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> K5 A 2013-03-15 B_STRPT_PNMN S S S R TRUE </span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 1,001 more rows</span></span></span></code></pre></div>
<div class="sourceCode" id="cb30"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 1,001 more rows</span></span></span>
<span></span>
<span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/all.html" class="external-link">all</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">betalactams</a></span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span><span class="op">)</span></span>
<span><span class="co">#&gt; ℹ For betalactams() using columns 'AMX' (amoxicillin) and 'AMC'</span></span>
@ -738,9 +612,8 @@ in:</p>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> Q2 A 2019-09-22 B_ESCHR_COLI R R S S TRUE </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> X7 A 2011-03-20 B_ESCHR_COLI R R S R TRUE </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> V1 A 2018-08-07 B_STPHY_AURS R R S S TRUE </span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 473 more rows</span></span></span></code></pre></div>
<div class="sourceCode" id="cb31"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 473 more rows</span></span></span>
<span></span>
<span><span class="co"># even works in base R (since R 3.0):</span></span>
<span><span class="va">our_data_1st</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/all.html" class="external-link">all</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">betalactams</a></span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span>, <span class="op">]</span></span>
<span><span class="co">#&gt; ℹ For betalactams() using columns 'AMX' (amoxicillin) and 'AMC'</span></span>
@ -793,7 +666,7 @@ failure</li>
function to create any of the above antibiogram types. For starters,
this is what the included <code>example_isolates</code> data set looks
like:</p>
<div class="sourceCode" id="cb32"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">example_isolates</span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 2,000 × 46</span></span></span>
<span><span class="co">#&gt; date patient age gender ward mo PEN OXA FLC AMX </span></span>
@ -822,7 +695,7 @@ like:</p>
should be used. The <code>antibiotics</code> argument in the
<code><a href="../reference/antibiogram.html">antibiogram()</a></code> function supports any (combination) of the
previously mentioned antibiotic class selectors:</p>
<div class="sourceCode" id="cb33"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/antibiogram.html">antibiogram</a></span><span class="op">(</span><span class="va">example_isolates</span>,</span>
<span> antibiotics <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span>
<span><span class="co">#&gt; ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB'</span></span>
@ -949,7 +822,7 @@ Chinese, Czech, Danish, Dutch, Finnish, French, German, Greek, Italian,
Japanese, Norwegian, Polish, Portuguese, Romanian, Russian, Spanish,
Swedish, Turkish, or Ukrainian. In this next example, we force the
language to be Spanish using the <code>language</code> argument:</p>
<div class="sourceCode" id="cb34"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/antibiogram.html">antibiogram</a></span><span class="op">(</span><span class="va">example_isolates</span>,</span>
<span> mo_transform <span class="op">=</span> <span class="st">"gramstain"</span>,</span>
<span> antibiotics <span class="op">=</span> <span class="fu"><a href="../reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>,</span>
@ -995,7 +868,7 @@ language to be Spanish using the <code>language</code> argument:</p>
</h4>
<p>To create a combined antibiogram, use antibiotic codes or names with
a plus <code>+</code> character like this:</p>
<div class="sourceCode" id="cb35"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb18"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/antibiogram.html">antibiogram</a></span><span class="op">(</span><span class="va">example_isolates</span>,</span>
<span> antibiotics <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"TZP"</span>, <span class="st">"TZP+TOB"</span>, <span class="st">"TZP+GEN"</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
<table class="table">
@ -1077,7 +950,7 @@ a plus <code>+</code> character like this:</p>
<p>To create a syndromic antibiogram, the <code>syndromic_group</code>
argument must be used. This can be any column in the data, or e.g. an
<code><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse()</a></code> with calculations based on certain columns:</p>
<div class="sourceCode" id="cb36"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb19"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/antibiogram.html">antibiogram</a></span><span class="op">(</span><span class="va">example_isolates</span>,</span>
<span> antibiotics <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span>,</span>
<span> syndromic_group <span class="op">=</span> <span class="st">"ward"</span><span class="op">)</span></span>
@ -1271,7 +1144,7 @@ Antibiogram) in which cases are predefined based on clinical or
demographic characteristics (e.g., endocarditis in 75+ females). This
next example is a simplification without clinical characteristics, but
just gives an idea of how a WISCA can be created:</p>
<div class="sourceCode" id="cb37"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">wisca</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/antibiogram.html">antibiogram</a></span><span class="op">(</span><span class="va">example_isolates</span>,</span>
<span> antibiotics <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"AMC"</span>, <span class="st">"AMC+CIP"</span>, <span class="st">"TZP"</span>, <span class="st">"TZP+TOB"</span><span class="op">)</span>,</span>
<span> mo_transform <span class="op">=</span> <span class="st">"gramstain"</span>,</span>
@ -1339,7 +1212,7 @@ just gives an idea of how a WISCA can be created:</p>
<p>Antibiograms can be plotted using <code><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot()</a></code> from the
<code>ggplot2</code> packages, since this <code>AMR</code> package
provides an extension to that function:</p>
<div class="sourceCode" id="cb38"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span><span class="va">wisca</span><span class="op">)</span></span></code></pre></div>
<p><img src="AMR_files/figure-html/unnamed-chunk-10-1.png" width="720"></p>
<p>To calculate antimicrobial resistance in a more sensible way, also by
@ -1368,12 +1241,12 @@ proportion of R (<code><a href="../reference/proportion.html">proportion_R()</a>
I (<code><a href="../reference/proportion.html">proportion_SI()</a></code>, equal to
<code><a href="../reference/proportion.html">susceptibility()</a></code>). These functions can be used on their
own:</p>
<div class="sourceCode" id="cb39"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="../reference/proportion.html">resistance</a></span><span class="op">(</span><span class="va">AMX</span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] 0.4288348</span></span></code></pre></div>
<p>Or can be used in conjunction with <code><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by()</a></code> and
<code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise()</a></code>, both from the <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb40"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb23"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span>amoxicillin <span class="op">=</span> <span class="fu"><a href="../reference/proportion.html">resistance</a></span><span class="op">(</span><span class="va">AMX</span><span class="op">)</span><span class="op">)</span></span>
@ -1387,7 +1260,7 @@ own:</p>
<p><em>Author: Dr. Matthijs Berends, 26th Feb 2023</em></p>
</div>
</div>
</main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
</main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
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@ -1404,9 +1277,9 @@ own:</p>
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Changelog
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@ -195,7 +85,7 @@
<img src="../logo.svg" class="logo" alt=""><h1>How to apply EUCAST rules</h1>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/EUCAST.Rmd" class="external-link"><code>vignettes/EUCAST.Rmd</code></a></small>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/EUCAST.Rmd" class="external-link"><code>vignettes/EUCAST.Rmd</code></a></small>
<div class="d-none name"><code>EUCAST.Rmd</code></div>
</div>
@ -248,9 +138,8 @@ be applied using <code><a href="../reference/eucast_rules.html">eucast_rules()</
<span><span class="va">oops</span></span>
<span><span class="co">#&gt; mo ampicillin</span></span>
<span><span class="co">#&gt; 1 Klebsiella S</span></span>
<span><span class="co">#&gt; 2 Escherichia S</span></span></code></pre></div>
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; 2 Escherichia S</span></span>
<span></span>
<span><span class="fu"><a href="../reference/eucast_rules.html">eucast_rules</a></span><span class="op">(</span><span class="va">oops</span>, info <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span>
<span><span class="co">#&gt; mo ampicillin</span></span>
<span><span class="co">#&gt; 1 Klebsiella R</span></span>
@ -259,14 +148,13 @@ be applied using <code><a href="../reference/eucast_rules.html">eucast_rules()</
<code><a href="../reference/mo_property.html">mo_is_intrinsic_resistant()</a></code> that uses the same guideline,
but allows to check for one or more specific microorganisms or
antibiotics:</p>
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span></span>
<span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Klebsiella"</span>, <span class="st">"Escherichia"</span><span class="op">)</span>,</span>
<span> <span class="st">"ampicillin"</span></span>
<span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] TRUE FALSE</span></span></code></pre></div>
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; [1] TRUE FALSE</span></span>
<span></span>
<span><span class="fu"><a href="../reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span></span>
<span> <span class="st">"Klebsiella"</span>,</span>
<span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"ampicillin"</span>, <span class="st">"kanamycin"</span><span class="op">)</span></span>
@ -277,7 +165,7 @@ used for filling in known resistance and susceptibility based on results
of other antimicrobials drugs. This process is called <em>interpretive
reading</em>, is basically a form of imputation, and is part of the
<code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function as well:</p>
<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span></span>
<span> mo <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span></span>
<span> <span class="st">"Staphylococcus aureus"</span>,</span>
@ -295,7 +183,7 @@ reading</em>, is basically a form of imputation, and is part of the
<span> FOX <span class="op">=</span> <span class="st">"S"</span>, <span class="co"># Cefoxitin</span></span>
<span> stringsAsFactors <span class="op">=</span> <span class="cn">FALSE</span></span>
<span><span class="op">)</span></span></code></pre></div>
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">data</span></span></code></pre></div>
<table class="table">
<thead><tr class="header">
@ -361,7 +249,7 @@ reading</em>, is basically a form of imputation, and is part of the
</tr>
</tbody>
</table>
<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/eucast_rules.html">eucast_rules</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
<table class="table">
<thead><tr class="header">
@ -428,7 +316,7 @@ reading</em>, is basically a form of imputation, and is part of the
</tbody>
</table>
</div>
</main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
</main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
</nav></aside>
</div>
@ -445,9 +333,9 @@ reading</em>, is basically a form of imputation, and is part of the
</footer>
</div>
</body>
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190
articles/MDR.html
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@ -5,7 +5,6 @@
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@ -49,141 +39,41 @@
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Conduct AMR Analysis
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Generate Antibiogram (Trad./Syndromic/WISCA)
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Predict Antimicrobial Resistance
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Download Data Sets for Own Use
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Set User- Or Team-specific Package Settings
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Conduct Principal Component Analysis for AMR
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Determine Multi-Drug Resistance (MDR)
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Work with WHONET Data
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<li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
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@ -195,7 +85,7 @@
<img src="../logo.svg" class="logo" alt=""><h1>How to determine multi-drug resistance (MDR)</h1>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/MDR.Rmd" class="external-link"><code>vignettes/MDR.Rmd</code></a></small>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/MDR.Rmd" class="external-link"><code>vignettes/MDR.Rmd</code></a></small>
<div class="d-none name"><code>MDR.Rmd</code></div>
</div>
@ -495,7 +385,7 @@ Unique: 5</p>
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@ -512,9 +402,9 @@ Unique: 5</p>
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@ -5,7 +5,6 @@
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<title>How to conduct principal component analysis (PCA) for AMR • AMR (for R)</title>
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@ -195,7 +85,7 @@
<img src="../logo.svg" class="logo" alt=""><h1>How to conduct principal component analysis (PCA) for AMR</h1>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/PCA.Rmd" class="external-link"><code>vignettes/PCA.Rmd</code></a></small>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/PCA.Rmd" class="external-link"><code>vignettes/PCA.Rmd</code></a></small>
<div class="d-none name"><code>PCA.Rmd</code></div>
</div>
@ -337,7 +227,7 @@ automatically adds the right labels and even groups:</p>
<span> <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span>title <span class="op">=</span> <span class="st">"An AMR/PCA biplot!"</span><span class="op">)</span></span></code></pre></div>
<p><img src="PCA_files/figure-html/unnamed-chunk-7-1.png" width="750"></p>
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Conduct AMR Analysis
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Generate Antibiogram (Trad./Syndromic/WISCA)
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Predict Antimicrobial Resistance
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Download Data Sets for Own Use
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Set User- Or Team-specific Package Settings
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<a class="dropdown-item" href="../articles/PCA.html">
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Conduct Principal Component Analysis for AMR
</a>
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Determine Multi-Drug Resistance (MDR)
</a>
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Work with WHONET Data
</a>
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Apply Eucast Rules
</a>
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Get Taxonomy of a Microorganism
</a>
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<span class="fa fa-capsules"></span>
Get Properties of an Antibiotic Drug
</a>
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Get Properties of an Antiviral Drug
</a>
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<li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
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@ -195,7 +85,7 @@
<img src="../logo.svg" class="logo" alt=""><h1>How to work with WHONET data</h1>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/WHONET.Rmd" class="external-link"><code>vignettes/WHONET.Rmd</code></a></small>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/WHONET.Rmd" class="external-link"><code>vignettes/WHONET.Rmd</code></a></small>
<div class="d-none name"><code>WHONET.Rmd</code></div>
</div>
@ -427,7 +317,7 @@ using the included <code><a href="../reference/ggplot_sir.html">ggplot_sir()</a>
<span> <span class="fu"><a href="../reference/ggplot_sir.html">ggplot_sir</a></span><span class="op">(</span>translate_ab <span class="op">=</span> <span class="st">"ab"</span>, facet <span class="op">=</span> <span class="st">"Country"</span>, datalabels <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div>
<p><img src="WHONET_files/figure-html/unnamed-chunk-7-1.png" width="720"></p>
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AMR &amp; tidymodels
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@ -194,9 +84,9 @@
<main id="main" class="col-md-9"><div class="page-header">
<img src="../logo.svg" class="logo" alt=""><h1>Data sets for download / own use</h1>
<h4 data-toc-skip class="date">23 June 2024</h4>
<h4 data-toc-skip class="date">16 July 2024</h4>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/datasets.Rmd" class="external-link"><code>vignettes/datasets.Rmd</code></a></small>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/datasets.Rmd" class="external-link"><code>vignettes/datasets.Rmd</code></a></small>
<div class="d-none name"><code>datasets.Rmd</code></div>
</div>
@ -215,43 +105,44 @@ of the data sets look like.</p>
<h2 id="microorganisms-full-microbial-taxonomy">
<code>microorganisms</code>: Full Microbial Taxonomy<a class="anchor" aria-label="anchor" href="#microorganisms-full-microbial-taxonomy"></a>
</h2>
<p>A data set with 52 171 rows and 23 columns, containing the following
<p>A data set with 70 547 rows and 26 columns, containing the following
column names:<br><em>mo</em>, <em>fullname</em>, <em>status</em>, <em>kingdom</em>,
<em>phylum</em>, <em>class</em>, <em>order</em>, <em>family</em>,
<em>genus</em>, <em>species</em>, <em>subspecies</em>, <em>rank</em>,
<em>ref</em>, <em>oxygen_tolerance</em>, <em>source</em>, <em>lpsn</em>,
<em>lpsn_parent</em>, <em>lpsn_renamed_to</em>, <em>gbif</em>,
<em>lpsn_parent</em>, <em>lpsn_renamed_to</em>, <em>mycobank</em>,
<em>mycobank_parent</em>, <em>mycobank_renamed_to</em>, <em>gbif</em>,
<em>gbif_parent</em>, <em>gbif_renamed_to</em>, <em>prevalence</em>, and
<em>snomed</em>.</p>
<p>This data set is in R available as <code>microorganisms</code>, after
you load the <code>AMR</code> package.</p>
<p>It was last updated on 14 July 2023 08:49:06 UTC. Find more info
<p>It was last updated on 16 July 2024 12:51:57 UTC. Find more info
about the structure of this data set <a href="https://msberends.github.io/AMR/reference/microorganisms.html">here</a>.</p>
<p><strong>Direct download links:</strong></p>
<ul>
<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.rds" class="external-link">original
R Data Structure (RDS) file</a> (1.2 MB)<br>
R Data Structure (RDS) file</a> (1.6 MB)<br>
</li>
<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.txt" class="external-link">tab-separated
text file</a> (11.7 MB)<br>
text file</a> (15.9 MB)<br>
</li>
<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.xlsx" class="external-link">Microsoft
Excel workbook</a> (5.2 MB)<br>
Excel workbook</a> (7.8 MB)<br>
</li>
<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.feather" class="external-link">Apache
Feather file</a> (5.5 MB)<br>
Feather file</a> (19 MB)<br>
</li>
<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.parquet" class="external-link">Apache
Parquet file</a> (2.6 MB)<br>
Parquet file</a> (0 kB)<br>
</li>
<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.xpt" class="external-link">SAS
transport (XPT) file</a> (48.6 MB)<br>
transport (XPT) file</a> (69.5 MB)<br>
</li>
<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.sav" class="external-link">IBM
SPSS Statistics data file</a> (17.8 MB)<br>
SPSS Statistics data file</a> (24.5 MB)<br>
</li>
<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.dta" class="external-link">Stata
DTA file</a> (48.6 MB)</li>
DTA file</a> (69.5 MB)</li>
</ul>
<p><strong>NOTE: The exported files for SAS, SPSS and Stata contain only
the first 50 SNOMED codes per record, as their file size would otherwise
@ -263,16 +154,16 @@ all SNOMED codes as comma separated values.</p>
<div class="section level3">
<h3 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a>
</h3>
<p>This data set contains the full microbial taxonomy of five kingdoms
<p>This data set contains the full microbial taxonomy of six kingdoms
from the List of Prokaryotic names with Standing in Nomenclature (LPSN)
and the Global Biodiversity Information Facility (GBIF):</p>
<ul>
<li>Parte, AC <em>et al.</em> (2020). <strong>List of Prokaryotic names
with Standing in Nomenclature (LPSN) moves to the DSMZ.</strong>
International Journal of Systematic and Evolutionary Microbiology, 70,
5607-5612; . Accessed from <a href="https://lpsn.dsmz.de" class="external-link uri">https://lpsn.dsmz.de</a> on December 11th, 2022.</li>
5607-5612; . Accessed from <a href="https://lpsn.dsmz.de" class="external-link uri">https://lpsn.dsmz.de</a> on June 24th, 2024.</li>
<li>GBIF Secretariat (2023). GBIF Backbone Taxonomy. Checklist dataset .
Accessed from <a href="https://www.gbif.org" class="external-link uri">https://www.gbif.org</a> on January 8th, 2024.</li>
Accessed from <a href="https://www.gbif.org" class="external-link uri">https://www.gbif.org</a> on June 24th, 2024.</li>
<li>Public Health Information Network Vocabulary Access and Distribution
System (PHIN VADS). US Edition of SNOMED CT from 1 September 2020. Value
Set Name ‘Microorganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: <a href="https://phinvads.cdc.gov" class="external-link uri">https://phinvads.cdc.gov</a>
@ -295,52 +186,55 @@ Set Name ‘Microorganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: <a hre
</tr>
<tr class="even">
<td align="center">Animalia</td>
<td align="center">1 379</td>
<td align="center">1 713</td>
</tr>
<tr class="odd">
<td align="center">Archaea</td>
<td align="center">1 314</td>
<td align="center">1 418</td>
</tr>
<tr class="even">
<td align="center">Bacteria</td>
<td align="center">36 501</td>
<td align="center">39 238</td>
</tr>
<tr class="odd">
<td align="center">Fungi</td>
<td align="center">7 905</td>
<td align="center">Chromista</td>
<td align="center">164</td>
</tr>
<tr class="even">
<td align="center">Protozoa</td>
<td align="center">5 071</td>
<td align="center">Fungi</td>
<td align="center">19 878</td>
</tr>
</tbody>
</table>
<p>Example rows when filtering on genus <em>Escherichia</em>:</p>
<table class="table">
<table style="width:100%;" class="table">
<colgroup>
<col width="3%">
<col width="7%">
<col width="2%">
<col width="2%">
<col width="4%">
<col width="5%">
<col width="4%">
<col width="5%">
<col width="3%">
<col width="4%">
<col width="3%">
<col width="2%">
<col width="6%">
<col width="7%">
<col width="2%">
<col width="2%">
<col width="3%">
<col width="4%">
<col width="4%">
<col width="4%">
<col width="2%">
<col width="3%">
<col width="2%">
<col width="2%">
<col width="5%">
<col width="6%">
<col width="1%">
<col width="1%">
<col width="2%">
<col width="3%">
<col width="2%">
<col width="3%">
<col width="4%">
<col width="2%">
<col width="2%">
<col width="3%">
<col width="11%">
<col width="2%">
<col width="10%">
</colgroup>
<thead><tr class="header">
<th align="center">mo</th>
@ -361,6 +255,9 @@ Set Name ‘Microorganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: <a hre
<th align="center">lpsn</th>
<th align="center">lpsn_parent</th>
<th align="center">lpsn_renamed_to</th>
<th align="center">mycobank</th>
<th align="center">mycobank_parent</th>
<th align="center">mycobank_renamed_to</th>
<th align="center">gbif</th>
<th align="center">gbif_parent</th>
<th align="center">gbif_renamed_to</th>
@ -387,7 +284,10 @@ Set Name ‘Microorganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: <a hre
<td align="center">515602</td>
<td align="center">482</td>
<td align="center"></td>
<td align="center">3221780</td>
<td align="center"></td>
<td align="center"></td>
<td align="center"></td>
<td align="center"></td>
<td align="center">11158430</td>
<td align="center"></td>
<td align="center">1.0</td>
@ -407,7 +307,7 @@ Set Name ‘Microorganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: <a hre
<td align="center"></td>
<td align="center">species</td>
<td align="center">Leclerc, 1962</td>
<td align="center">aerobe</td>
<td align="center">likely facultative anaerobe</td>
<td align="center">LPSN</td>
<td align="center">776052</td>
<td align="center">515602</td>
@ -415,6 +315,9 @@ Set Name ‘Microorganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: <a hre
<td align="center"></td>
<td align="center"></td>
<td align="center"></td>
<td align="center"></td>
<td align="center"></td>
<td align="center"></td>
<td align="center">1.0</td>
<td align="center"></td>
</tr>
@ -432,13 +335,16 @@ Set Name ‘Microorganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: <a hre
<td align="center"></td>
<td align="center">species</td>
<td align="center">Huys et al., 2003</td>
<td align="center">aerobe</td>
<td align="center">facultative anaerobe</td>
<td align="center">LPSN</td>
<td align="center">776053</td>
<td align="center">515602</td>
<td align="center"></td>
<td align="center"></td>
<td align="center"></td>
<td align="center"></td>
<td align="center">5427575</td>
<td align="center">3221780</td>
<td align="center"></td>
<td align="center"></td>
<td align="center">1.0</td>
<td align="center">419388003</td>
@ -465,6 +371,9 @@ Set Name ‘Microorganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: <a hre
<td align="center"></td>
<td align="center"></td>
<td align="center"></td>
<td align="center"></td>
<td align="center"></td>
<td align="center"></td>
<td align="center">1.5</td>
<td align="center"></td>
</tr>
@ -487,15 +396,18 @@ Set Name ‘Microorganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: <a hre
<td align="center">776057</td>
<td align="center">515602</td>
<td align="center"></td>
<td align="center"></td>
<td align="center"></td>
<td align="center"></td>
<td align="center">11286021</td>
<td align="center">3221780</td>
<td align="center"></td>
<td align="center"></td>
<td align="center">1.0</td>
<td align="center">1095001000112106, 715307006, 737528008, …</td>
</tr>
<tr class="even">
<td align="center">B_ESCHR_DYSN</td>
<td align="center">Escherichia dysenteriae</td>
<td align="center">B_ESCHR_COLI_COLI</td>
<td align="center">Escherichia coli coli</td>
<td align="center">accepted</td>
<td align="center">Bacteria</td>
<td align="center">Pseudomonadota</td>
@ -503,19 +415,22 @@ Set Name ‘Microorganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: <a hre
<td align="center">Enterobacterales</td>
<td align="center">Enterobacteriaceae</td>
<td align="center">Escherichia</td>
<td align="center">dysenteriae</td>
<td align="center">coli</td>
<td align="center">coli</td>
<td align="center">subspecies</td>
<td align="center"></td>
<td align="center">species</td>
<td align="center"></td>
<td align="center">likely facultative anaerobe</td>
<td align="center">GBIF</td>
<td align="center"></td>
<td align="center"></td>
<td align="center"></td>
<td align="center">10862979</td>
<td align="center">3221780</td>
<td align="center"></td>
<td align="center">1.5</td>
<td align="center"></td>
<td align="center"></td>
<td align="center">12233256</td>
<td align="center"></td>
<td align="center"></td>
<td align="center">1.0</td>
<td align="center"></td>
</tr>
</tbody>
@ -912,7 +827,7 @@ column names:<br><em>guideline</em>, <em>type</em>, <em>host</em>, <em>method</e
<em>breakpoint_R</em>, <em>uti</em>, and <em>is_SDD</em>.</p>
<p>This data set is in R available as <code>clinical_breakpoints</code>,
after you load the <code>AMR</code> package.</p>
<p>It was last updated on 19 June 2024 13:08:23 UTC. Find more info
<p>It was last updated on 16 July 2024 12:51:57 UTC. Find more info
about the structure of this data set <a href="https://msberends.github.io/AMR/reference/clinical_breakpoints.html">here</a>.</p>
<p><strong>Direct download links:</strong></p>
<ul>
@ -923,7 +838,7 @@ R Data Structure (RDS) file</a> (70 kB)<br>
text file</a> (3.1 MB)<br>
</li>
<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/clinical_breakpoints.xlsx" class="external-link">Microsoft
Excel workbook</a> (1.7 MB)<br>
Excel workbook</a> (2 MB)<br>
</li>
<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/clinical_breakpoints.feather" class="external-link">Apache
Feather file</a> (4.9 MB)<br>
@ -1125,37 +1040,37 @@ use.</p>
<code>intrinsic_resistant</code>: Intrinsic Bacterial
Resistance<a class="anchor" aria-label="anchor" href="#intrinsic_resistant-intrinsic-bacterial-resistance"></a>
</h2>
<p>A data set with 134 634 rows and 2 columns, containing the following
<p>A data set with 340 804 rows and 2 columns, containing the following
column names:<br><em>mo</em> and <em>ab</em>.</p>
<p>This data set is in R available as <code>intrinsic_resistant</code>,
after you load the <code>AMR</code> package.</p>
<p>It was last updated on 16 December 2022 15:10:43 UTC. Find more info
<p>It was last updated on 16 July 2024 12:51:57 UTC. Find more info
about the structure of this data set <a href="https://msberends.github.io/AMR/reference/intrinsic_resistant.html">here</a>.</p>
<p><strong>Direct download links:</strong></p>
<ul>
<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.rds" class="external-link">original
R Data Structure (RDS) file</a> (78 kB)<br>
R Data Structure (RDS) file</a> (0.1 MB)<br>
</li>
<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.txt" class="external-link">tab-separated
text file</a> (5.1 MB)<br>
text file</a> (12.4 MB)<br>
</li>
<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.xlsx" class="external-link">Microsoft
Excel workbook</a> (1.3 MB)<br>
Excel workbook</a> (3.4 MB)<br>
</li>
<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.feather" class="external-link">Apache
Feather file</a> (1.2 MB)<br>
Feather file</a> (13.1 MB)<br>
</li>
<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.parquet" class="external-link">Apache
Parquet file</a> (0.2 MB)<br>
Parquet file</a> (0 kB)<br>
</li>
<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.xpt" class="external-link">SAS
transport (XPT) file</a> (9.5 MB)<br>
transport (XPT) file</a> (28.3 MB)<br>
</li>
<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.sav" class="external-link">IBM
SPSS Statistics data file</a> (7.4 MB)<br>
SPSS Statistics data file</a> (18.4 MB)<br>
</li>
<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.dta" class="external-link">Stata
DTA file</a> (9.5 MB)</li>
DTA file</a> (28.3 MB)</li>
</ul>
<div class="section level3">
<h3 id="source-4">Source<a class="anchor" aria-label="anchor" href="#source-4"></a>
@ -2188,7 +2103,7 @@ which are used in the <code>clinical_breakpoints</code> data set.</p>
column names:<br><em>code</em> and <em>mo</em>.</p>
<p>This data set is in R available as <code>microorganisms.codes</code>,
after you load the <code>AMR</code> package.</p>
<p>It was last updated on 16 June 2024 09:28:56 UTC. Find more info
<p>It was last updated on 16 July 2024 12:51:57 UTC. Find more info
about the structure of this data set <a href="https://msberends.github.io/AMR/reference/microorganisms.codes.html">here</a>.</p>
<p><strong>Direct download links:</strong></p>
<ul>
@ -2199,7 +2114,7 @@ R Data Structure (RDS) file</a> (22 kB)<br>
text file</a> (0.1 MB)<br>
</li>
<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.codes.xlsx" class="external-link">Microsoft
Excel workbook</a> (91 kB)<br>
Excel workbook</a> (82 kB)<br>
</li>
<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.codes.feather" class="external-link">Apache
Feather file</a> (0.1 MB)<br>
@ -2259,7 +2174,7 @@ laboratory systems and <a href="https://whonet.org" class="external-link">WHONET
</table>
</div>
</div>
</main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
</main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
</nav></aside>
</div>
@ -2276,9 +2191,9 @@ laboratory systems and <a href="https://whonet.org" class="external-link">WHONET
</footer>
</div>
</body>
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@ -1,155 +1,49 @@
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@ -195,7 +85,7 @@
<img src="../logo.svg" class="logo" alt=""><h1>Using AMR with other packages: AMR &amp; dplyr/tidyverse</h1>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/other_pkg.Rmd" class="external-link"><code>vignettes/other_pkg.Rmd</code></a></small>
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@ -220,9 +110,9 @@ used to working in <code>dplyr</code> or other tidyverse packages.</p>
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@ -195,7 +85,7 @@
<img src="../logo.svg" class="logo" alt=""><h1>How to predict antimicrobial resistance</h1>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/resistance_predict.Rmd" class="external-link"><code>vignettes/resistance_predict.Rmd</code></a></small>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/resistance_predict.Rmd" class="external-link"><code>vignettes/resistance_predict.Rmd</code></a></small>
<div class="d-none name"><code>resistance_predict.Rmd</code></div>
</div>
@ -362,16 +252,15 @@ model might be more appropriate:</p>
<span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">model</span><span class="op">)</span><span class="op">$</span><span class="va">family</span></span>
<span><span class="co">#&gt; </span></span>
<span><span class="co">#&gt; Family: binomial </span></span>
<span><span class="co">#&gt; Link function: logit</span></span></code></pre></div>
<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; Link function: logit</span></span>
<span></span>
<span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">model</span><span class="op">)</span><span class="op">$</span><span class="va">coefficients</span></span>
<span><span class="co">#&gt; Estimate Std. Error z value Pr(&gt;|z|)</span></span>
<span><span class="co">#&gt; (Intercept) -200.67944891 46.17315349 -4.346237 1.384932e-05</span></span>
<span><span class="co">#&gt; year 0.09883005 0.02295317 4.305725 1.664395e-05</span></span></code></pre></div>
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@ -388,9 +277,9 @@ model might be more appropriate:</p>
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9061</small>
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AMR &amp; data.table
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<li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
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@ -195,7 +85,7 @@
<img src="../logo.svg" class="logo" alt=""><h1>Welcome to the `AMR` package</h1>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/welcome_to_AMR.Rmd" class="external-link"><code>vignettes/welcome_to_AMR.Rmd</code></a></small>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/welcome_to_AMR.Rmd" class="external-link"><code>vignettes/welcome_to_AMR.Rmd</code></a></small>
<div class="d-none name"><code>welcome_to_AMR.Rmd</code></div>
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@ -222,7 +112,7 @@ this a successful and durable project!</p>
10.18637/jss.v104.i03</a>) and formed the basis of two PhD theses (<a href="https://doi.org/10.33612/diss.177417131" class="external-link">DOI
10.33612/diss.177417131</a> and <a href="https://doi.org/10.33612/diss.192486375" class="external-link">DOI
10.33612/diss.192486375</a>).</p>
<p>After installing this package, R knows ~52 000 distinct microbial
<p>After installing this package, R knows ~71 000 distinct microbial
species and all ~600 antibiotic, antimycotic and antiviral drugs by name
and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED
CT), and knows all about valid SIR and MIC values. The integral
@ -313,9 +203,9 @@ included with the package. </small></p>
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