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@@ -31,7 +31,7 @@
<a class="navbar-brand me-2" href="https://amr-for-r.org/index.html">AMR (for R)</a> <a class="navbar-brand me-2" href="https://amr-for-r.org/index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
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@@ -30,7 +30,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -91,7 +91,7 @@
website update since they are based on randomly created values and the 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 page was written in <a href="https://rmarkdown.rstudio.com/" class="external-link">R
Markdown</a>. However, the methodology remains unchanged. This page was Markdown</a>. However, the methodology remains unchanged. This page was
generated on 15 December 2025.</p> generated on 22 December 2025.</p>
<div class="section level2"> <div class="section level2">
<h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a> <h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
</h2> </h2>
@@ -147,21 +147,21 @@ make the structure of your data generally look like this:</p>
</tr></thead> </tr></thead>
<tbody> <tbody>
<tr class="odd"> <tr class="odd">
<td align="center">2025-12-15</td> <td align="center">2025-12-22</td>
<td align="center">abcd</td> <td align="center">abcd</td>
<td align="center">Escherichia coli</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>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">2025-12-15</td> <td align="center">2025-12-22</td>
<td align="center">abcd</td> <td align="center">abcd</td>
<td align="center">Escherichia coli</td> <td align="center">Escherichia coli</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">R</td> <td align="center">R</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="center">2025-12-15</td> <td align="center">2025-12-22</td>
<td align="center">efgh</td> <td align="center">efgh</td>
<td align="center">Escherichia coli</td> <td align="center">Escherichia coli</td>
<td align="center">R</td> <td align="center">R</td>
@@ -1254,7 +1254,7 @@ function on a grouped <code>tibble</code>, i.e., using
provides an extension to that function:</p> provides an extension to that function:</p>
<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb22"><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">combined_ab</span><span class="op">)</span></span></code></pre></div> <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">combined_ab</span><span class="op">)</span></span></code></pre></div>
<p><img src="AMR_files/figure-html/unnamed-chunk-10-1.png" class="r-plt" width="720"></p> <p><img src="AMR_files/figure-html/unnamed-chunk-10-1.png" class="r-plt" alt="" width="720"></p>
<p>To calculate antimicrobial resistance in a more sensible way, also by <p>To calculate antimicrobial resistance in a more sensible way, also by
correcting for too few results, we use the <code><a href="../reference/proportion.html">resistance()</a></code> and correcting for too few results, we use the <code><a href="../reference/proportion.html">resistance()</a></code> and
<code><a href="../reference/proportion.html">susceptibility()</a></code> functions.</p> <code><a href="../reference/proportion.html">susceptibility()</a></code> functions.</p>
@@ -1348,7 +1348,7 @@ categories.</p>
<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">"MIC Distribution and SIR Interpretation"</span>,</span> <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">"MIC Distribution and SIR Interpretation"</span>,</span>
<span> x <span class="op">=</span> <span class="st">"Sample Groups"</span>,</span> <span> x <span class="op">=</span> <span class="st">"Sample Groups"</span>,</span>
<span> y <span class="op">=</span> <span class="st">"MIC (mg/L)"</span><span class="op">)</span></span></code></pre></div> <span> y <span class="op">=</span> <span class="st">"MIC (mg/L)"</span><span class="op">)</span></span></code></pre></div>
<p><img src="AMR_files/figure-html/mic_plot-1.png" class="r-plt" width="720"></p> <p><img src="AMR_files/figure-html/mic_plot-1.png" class="r-plt" alt="" width="720"></p>
<p>This plot provides an intuitive way to assess susceptibility patterns <p>This plot provides an intuitive way to assess susceptibility patterns
across different groups while incorporating clinical breakpoints.</p> across different groups while incorporating clinical breakpoints.</p>
<p>For a more straightforward and less manual approach, <p>For a more straightforward and less manual approach,
@@ -1357,12 +1357,12 @@ extended by this package to directly plot MIC and disk diffusion
values:</p> values:</p>
<div class="sourceCode" id="cb27"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb27"><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">mic_values</span><span class="op">)</span></span></code></pre></div> <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">mic_values</span><span class="op">)</span></span></code></pre></div>
<p><img src="AMR_files/figure-html/autoplot-1.png" class="r-plt" width="720"></p> <p><img src="AMR_files/figure-html/autoplot-1.png" class="r-plt" alt="" width="720"></p>
<div class="sourceCode" id="cb28"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb28"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span> <code class="sourceCode R"><span></span>
<span><span class="co"># by providing `mo` and `ab`, colours will indicate the SIR interpretation:</span></span> <span><span class="co"># by providing `mo` and `ab`, colours will indicate the SIR interpretation:</span></span>
<span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span><span class="va">mic_values</span>, mo <span class="op">=</span> <span class="st">"K. pneumoniae"</span>, ab <span class="op">=</span> <span class="st">"cipro"</span>, guideline <span class="op">=</span> <span class="st">"EUCAST 2024"</span><span class="op">)</span></span></code></pre></div> <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">mic_values</span>, mo <span class="op">=</span> <span class="st">"K. pneumoniae"</span>, ab <span class="op">=</span> <span class="st">"cipro"</span>, guideline <span class="op">=</span> <span class="st">"EUCAST 2024"</span><span class="op">)</span></span></code></pre></div>
<p><img src="AMR_files/figure-html/autoplot-2.png" class="r-plt" width="720"></p> <p><img src="AMR_files/figure-html/autoplot-2.png" class="r-plt" alt="" width="720"></p>
<hr> <hr>
<p><em>Author: Dr. Matthijs Berends, 23rd Feb 2025</em></p> <p><em>Author: Dr. Matthijs Berends, 23rd Feb 2025</em></p>
</div> </div>

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@@ -3,7 +3,7 @@
**Note:** values on this page will change with every website update **Note:** values on this page will change with every website update
since they are based on randomly created values and the page was written since they are based on randomly created values and the page was written
in [R Markdown](https://rmarkdown.rstudio.com/). However, the in [R Markdown](https://rmarkdown.rstudio.com/). However, the
methodology remains unchanged. This page was generated on 15 December methodology remains unchanged. This page was generated on 22 December
2025. 2025.
## Introduction ## Introduction
@@ -52,9 +52,9 @@ structure of your data generally look like this:
| date | patient_id | mo | AMX | CIP | | date | patient_id | mo | AMX | CIP |
|:----------:|:----------:|:----------------:|:---:|:---:| |:----------:|:----------:|:----------------:|:---:|:---:|
| 2025-12-15 | abcd | Escherichia coli | S | S | | 2025-12-22 | abcd | Escherichia coli | S | S |
| 2025-12-15 | abcd | Escherichia coli | S | R | | 2025-12-22 | abcd | Escherichia coli | S | R |
| 2025-12-15 | efgh | Escherichia coli | R | S | | 2025-12-22 | efgh | Escherichia coli | R | S |
### Needed R packages ### Needed R packages

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@@ -30,7 +30,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

305
articles/AMR_with_tidymodels.html
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@@ -30,7 +30,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -88,7 +88,7 @@
<blockquote> <blockquote>
<p>This page was entirely written by our <a href="https://chat.amr-for-r.org" class="external-link">AMR for R Assistant</a>, a ChatGPT <p>This page was almost entirely written by our <a href="https://chat.amr-for-r.org" class="external-link">AMR for R Assistant</a>, a ChatGPT
manually-trained model able to answer any question about the manually-trained model able to answer any question about the
<code>AMR</code> package.</p> <code>AMR</code> package.</p>
</blockquote> </blockquote>
@@ -413,7 +413,7 @@ ROC curve looks like this:</p>
<code class="sourceCode R"><span><span class="va">predictions</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span> <code class="sourceCode R"><span><span class="va">predictions</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu">roc_curve</span><span class="op">(</span><span class="va">mo</span>, <span class="va">`.pred_Gram-negative`</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">roc_curve</span><span class="op">(</span><span class="va">mo</span>, <span class="va">`.pred_Gram-negative`</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://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> <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="op">)</span></span></code></pre></div>
<p><img src="AMR_with_tidymodels_files/figure-html/unnamed-chunk-8-1.png" class="r-plt" width="720"></p> <p><img src="AMR_with_tidymodels_files/figure-html/unnamed-chunk-8-1.png" class="r-plt" alt="" width="720"></p>
</div> </div>
<div class="section level3"> <div class="section level3">
<h3 id="conclusion"> <h3 id="conclusion">
@@ -438,21 +438,258 @@ and reproducibly.</p>
<code>&lt;mic&gt;</code> columns directly in <code>tidymodels</code> <code>&lt;mic&gt;</code> columns directly in <code>tidymodels</code>
workflows using AMR-specific recipe steps. This includes a workflows using AMR-specific recipe steps. This includes a
transformation to <code>log2</code> scale using transformation to <code>log2</code> scale using
<code>step_mic_log2()</code>, which prepares MIC values for use in <code><a href="../reference/amr-tidymodels.html">step_mic_log2()</a></code>, which prepares MIC values for use in
classification models.</p> classification models.</p>
<p>This approach and idea formed the basis for the publication <a href="https://doi.org/10.3389/fmicb.2025.1582703" class="external-link">DOI: <p>This approach and idea formed the basis for the publication <a href="https://doi.org/10.3389/fmicb.2025.1582703" class="external-link">DOI:
10.3389/fmicb.2025.1582703</a> to model the presence of 10.3389/fmicb.2025.1582703</a> to model the presence of
extended-spectrum beta-lactamases (ESBL).</p> extended-spectrum beta-lactamases (ESBL) based on MIC values.</p>
<blockquote> <div class="section level3">
<p>NOTE: THIS EXAMPLE WILL BE AVAILABLE IN A NEXT VERSION (#TODO)</p> <h3 id="objective-1">
<p>The new AMR package version will contain new tidymodels selectors <strong>Objective</strong><a class="anchor" aria-label="anchor" href="#objective-1"></a>
such as <code>step_mic_log2()</code>.</p> </h3>
</blockquote> <p>Our goal is to:</p>
<!-- TODO for AMR v3.1.0: add info from here: https://github.com/msberends/AMR/blob/2461631bcefa78ebdb37bdfad359be74cdd9165a/vignettes/AMR_with_tidymodels.Rmd#L212-L291 --> <ol style="list-style-type: decimal">
<li>Use raw MIC values to predict whether a bacterial isolate produces
ESBL.</li>
<li>Apply AMR-aware preprocessing in a <code>tidymodels</code>
recipe.</li>
<li>Train a classification model and evaluate its predictive
performance.</li>
</ol>
</div>
<div class="section level3">
<h3 id="data-preparation-1">
<strong>Data Preparation</strong><a class="anchor" aria-label="anchor" href="#data-preparation-1"></a>
</h3>
<p>We use the <code>esbl_isolates</code> dataset that comes with the AMR
package.</p>
<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="co"># Load required libraries</span></span>
<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://amr-for-r.org">AMR</a></span><span class="op">)</span></span>
<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://tidymodels.tidymodels.org" class="external-link">tidymodels</a></span><span class="op">)</span></span>
<span></span>
<span><span class="co"># View the esbl_isolates data set</span></span>
<span><span class="va">esbl_isolates</span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 500 × 19</span></span></span>
<span><span class="co">#&gt; esbl genus AMC AMP TZP CXM FOX CTX CAZ GEN TOB TMP SXT</span></span>
<span><span class="co">#&gt; <span style="color: #949494; font-style: italic;">&lt;lgl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span></span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 1</span> FALSE Esch… 32 32 4 64 64 8<span style="color: #555555;">.00</span> 8<span style="color: #555555;">.00</span> 1 1 16<span style="color: #555555;">.0</span> 20</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 2</span> FALSE Esch… 32 32 4 64 64 4<span style="color: #555555;">.00</span> 8<span style="color: #555555;">.00</span> 1 1 16<span style="color: #555555;">.0</span> 320</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 3</span> FALSE Esch… 4 2 64 8 4 8<span style="color: #555555;">.00</span> 0.12 16 16 0.5 20</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 4</span> FALSE Kleb… 32 32 16 64 64 8<span style="color: #555555;">.00</span> 8<span style="color: #555555;">.00</span> 1 1 0.5 20</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 5</span> FALSE Esch… 32 32 4 4 4 0.25 2<span style="color: #555555;">.00</span> 1 1 16<span style="color: #555555;">.0</span> 320</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 6</span> FALSE Citr… 32 32 16 64 64 64<span style="color: #555555;">.00</span> 32<span style="color: #555555;">.00</span> 1 1 0.5 20</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 7</span> FALSE Morg… 32 32 4 64 64 16<span style="color: #555555;">.00</span> 2<span style="color: #555555;">.00</span> 1 1 0.5 20</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> FALSE Prot… 16 32 4 1 4 8<span style="color: #555555;">.00</span> 0.12 1 1 16<span style="color: #555555;">.0</span> 320</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> FALSE Ente… 32 32 8 64 64 32<span style="color: #555555;">.00</span> 4<span style="color: #555555;">.00</span> 1 1 0.5 20</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> FALSE Citr… 32 32 32 64 64 8<span style="color: #555555;">.00</span> 64<span style="color: #555555;">.00</span> 1 1 16<span style="color: #555555;">.0</span> 320</span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 490 more rows</span></span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 6 more variables: NIT &lt;mic&gt;, FOS &lt;mic&gt;, CIP &lt;mic&gt;, IPM &lt;mic&gt;, MEM &lt;mic&gt;,</span></span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># COL &lt;mic&gt;</span></span></span>
<span></span>
<span><span class="co"># Prepare a binary outcome and convert to ordered factor</span></span>
<span><span class="va">data</span> <span class="op">&lt;-</span> <span class="va">esbl_isolates</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>esbl <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a></span><span class="op">(</span><span class="va">esbl</span>, levels <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="cn">FALSE</span>, <span class="cn">TRUE</span><span class="op">)</span>, ordered <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
<p><strong>Explanation:</strong></p>
<ul>
<li>
<code>esbl_isolates</code>: Contains MIC test results and ESBL
status for each isolate.</li>
<li>
<code>mutate(esbl = ...)</code>: Converts the target column to an
ordered factor for classification.</li>
</ul>
</div>
<div class="section level3">
<h3 id="defining-the-workflow-1">
<strong>Defining the Workflow</strong><a class="anchor" aria-label="anchor" href="#defining-the-workflow-1"></a>
</h3>
<div class="section level4">
<h4 id="preprocessing-with-a-recipe-1">1. Preprocessing with a Recipe<a class="anchor" aria-label="anchor" href="#preprocessing-with-a-recipe-1"></a>
</h4>
<p>We use our <code><a href="../reference/amr-tidymodels.html">step_mic_log2()</a></code> function to log2-transform
MIC values, ensuring that MICs are numeric and properly scaled. All MIC
predictors can easily and agnostically selected using the new
<code><a href="../reference/amr-tidymodels.html">all_mic_predictors()</a></code>:</p>
<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="co"># Split into training and testing sets</span></span>
<span><span class="fu"><a href="https://rdrr.io/r/base/Random.html" class="external-link">set.seed</a></span><span class="op">(</span><span class="fl">123</span><span class="op">)</span></span>
<span><span class="va">split</span> <span class="op">&lt;-</span> <span class="fu">initial_split</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span>
<span><span class="va">training_data</span> <span class="op">&lt;-</span> <span class="fu">training</span><span class="op">(</span><span class="va">split</span><span class="op">)</span></span>
<span><span class="va">testing_data</span> <span class="op">&lt;-</span> <span class="fu">testing</span><span class="op">(</span><span class="va">split</span><span class="op">)</span></span>
<span></span>
<span><span class="co"># Define the recipe</span></span>
<span><span class="va">mic_recipe</span> <span class="op">&lt;-</span> <span class="fu">recipe</span><span class="op">(</span><span class="va">esbl</span> <span class="op">~</span> <span class="va">.</span>, data <span class="op">=</span> <span class="va">training_data</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">remove_role</span><span class="op">(</span><span class="va">genus</span>, old_role <span class="op">=</span> <span class="st">"predictor"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="co"># Remove non-informative variable</span></span>
<span> <span class="fu"><a href="../reference/amr-tidymodels.html">step_mic_log2</a></span><span class="op">(</span><span class="fu"><a href="../reference/amr-tidymodels.html">all_mic_predictors</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="co">#%&gt;% # Log2 transform all MIC predictors</span></span>
<span> <span class="co"># prep()</span></span>
<span></span>
<span><span class="va">mic_recipe</span></span>
<span><span class="co">#&gt; </span></span>
<span><span class="co">#&gt; <span style="color: #00BBBB;">──</span> <span style="font-weight: bold;">Recipe</span> <span style="color: #00BBBB;">──────────────────────────────────────────────────────────────────────</span></span></span>
<span><span class="co">#&gt; </span></span>
<span><span class="co">#&gt; ── Inputs</span></span>
<span><span class="co">#&gt; Number of variables by role</span></span>
<span><span class="co">#&gt; outcome: 1</span></span>
<span><span class="co">#&gt; predictor: 17</span></span>
<span><span class="co">#&gt; undeclared role: 1</span></span>
<span><span class="co">#&gt; </span></span>
<span><span class="co">#&gt; ── Operations</span></span>
<span><span class="co">#&gt; <span style="color: #00BBBB;">•</span> Log2 transformation of MIC columns: <span style="color: #0000BB;">all_mic_predictors()</span></span></span></code></pre></div>
<p><strong>Explanation:</strong></p>
<ul>
<li>
<code>remove_role()</code>: Removes irrelevant variables like
genus.</li>
<li>
<code><a href="../reference/amr-tidymodels.html">step_mic_log2()</a></code>: Applies
<code>log2(as.numeric(...))</code> to all MIC predictors in one go.</li>
<li>
<code>prep()</code>: Finalises the recipe based on training
data.</li>
</ul>
</div>
<div class="section level4">
<h4 id="specifying-the-model-1">2. Specifying the Model<a class="anchor" aria-label="anchor" href="#specifying-the-model-1"></a>
</h4>
<p>We use a simple logistic regression to model ESBL presence, though
recent models such as xgboost (<a href="https://parsnip.tidymodels.org/reference/details_boost_tree_xgboost.html" class="external-link">link
to <code>parsnip</code> manual</a>) could be much more precise.</p>
<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="co"># Define the model</span></span>
<span><span class="va">model</span> <span class="op">&lt;-</span> <span class="fu">logistic_reg</span><span class="op">(</span>mode <span class="op">=</span> <span class="st">"classification"</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">set_engine</span><span class="op">(</span><span class="st">"glm"</span><span class="op">)</span></span>
<span></span>
<span><span class="va">model</span></span>
<span><span class="co">#&gt; Logistic Regression Model Specification (classification)</span></span>
<span><span class="co">#&gt; </span></span>
<span><span class="co">#&gt; Computational engine: glm</span></span></code></pre></div>
<p><strong>Explanation:</strong></p>
<ul>
<li>
<code>logistic_reg()</code>: Specifies a binary classification
model.</li>
<li>
<code>set_engine("glm")</code>: Uses the base R GLM engine.</li>
</ul>
</div>
<div class="section level4">
<h4 id="building-the-workflow-1">3. Building the Workflow<a class="anchor" aria-label="anchor" href="#building-the-workflow-1"></a>
</h4>
<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="co"># Create workflow</span></span>
<span><span class="va">workflow_model</span> <span class="op">&lt;-</span> <span class="fu">workflow</span><span class="op">(</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">add_recipe</span><span class="op">(</span><span class="va">mic_recipe</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">add_model</span><span class="op">(</span><span class="va">model</span><span class="op">)</span></span>
<span></span>
<span><span class="va">workflow_model</span></span>
<span><span class="co">#&gt; ══ Workflow ════════════════════════════════════════════════════════════════════</span></span>
<span><span class="co">#&gt; <span style="font-style: italic;">Preprocessor:</span> Recipe</span></span>
<span><span class="co">#&gt; <span style="font-style: italic;">Model:</span> logistic_reg()</span></span>
<span><span class="co">#&gt; </span></span>
<span><span class="co">#&gt; ── Preprocessor ────────────────────────────────────────────────────────────────</span></span>
<span><span class="co">#&gt; 1 Recipe Step</span></span>
<span><span class="co">#&gt; </span></span>
<span><span class="co">#&gt; • step_mic_log2()</span></span>
<span><span class="co">#&gt; </span></span>
<span><span class="co">#&gt; ── Model ───────────────────────────────────────────────────────────────────────</span></span>
<span><span class="co">#&gt; Logistic Regression Model Specification (classification)</span></span>
<span><span class="co">#&gt; </span></span>
<span><span class="co">#&gt; Computational engine: glm</span></span></code></pre></div>
</div>
</div>
<div class="section level3">
<h3 id="training-and-evaluating-the-model-1">
<strong>Training and Evaluating the Model</strong><a class="anchor" aria-label="anchor" href="#training-and-evaluating-the-model-1"></a>
</h3>
<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="co"># Fit the model</span></span>
<span><span class="va">fitted</span> <span class="op">&lt;-</span> <span class="fu">fit</span><span class="op">(</span><span class="va">workflow_model</span>, <span class="va">training_data</span><span class="op">)</span></span>
<span></span>
<span><span class="co"># Generate predictions</span></span>
<span><span class="va">predictions</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/stats/predict.html" class="external-link">predict</a></span><span class="op">(</span><span class="va">fitted</span>, <span class="va">testing_data</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/bind_cols.html" class="external-link">bind_cols</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/predict.html" class="external-link">predict</a></span><span class="op">(</span><span class="va">fitted</span>, <span class="va">testing_data</span>, type <span class="op">=</span> <span class="st">"prob"</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="co"># add probabilities</span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/bind_cols.html" class="external-link">bind_cols</a></span><span class="op">(</span><span class="va">testing_data</span><span class="op">)</span></span>
<span></span>
<span><span class="co"># Evaluate model performance</span></span>
<span><span class="va">our_metrics</span> <span class="op">&lt;-</span> <span class="fu">metric_set</span><span class="op">(</span><span class="va">accuracy</span>, <span class="va">recall</span>, <span class="va">precision</span>, <span class="va">sensitivity</span>, <span class="va">specificity</span>, <span class="va">ppv</span>, <span class="va">npv</span><span class="op">)</span></span>
<span><span class="va">metrics</span> <span class="op">&lt;-</span> <span class="fu">our_metrics</span><span class="op">(</span><span class="va">predictions</span>, truth <span class="op">=</span> <span class="va">esbl</span>, estimate <span class="op">=</span> <span class="va">.pred_class</span><span class="op">)</span></span>
<span></span>
<span><span class="va">metrics</span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 7 × 3</span></span></span>
<span><span class="co">#&gt; .metric .estimator .estimate</span></span>
<span><span class="co">#&gt; <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> accuracy binary 0.92 </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> recall binary 0.921</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> precision binary 0.921</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> sensitivity binary 0.921</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">5</span> specificity binary 0.919</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">6</span> ppv binary 0.921</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">7</span> npv binary 0.919</span></span></code></pre></div>
<p><strong>Explanation:</strong></p>
<ul>
<li>
<code>fit()</code>: Trains the model on the processed training
data.</li>
<li>
<code><a href="https://rdrr.io/r/stats/predict.html" class="external-link">predict()</a></code>: Produces predictions for unseen test
data.</li>
<li>
<code>metric_set()</code>: Allows evaluating multiple classification
metrics. This will make <code>our_metrics</code> to become a function
that we can use to check the predictions with.</li>
</ul>
<p>It appears we can predict ESBL gene presence with a positive
predictive value (PPV) of 92.1% and a negative predictive value (NPV) of
91.9 using a simplistic logistic regression model.</p>
</div>
<div class="section level3">
<h3 id="visualising-predictions">
<strong>Visualising Predictions</strong><a class="anchor" aria-label="anchor" href="#visualising-predictions"></a>
</h3>
<p>We can visualise predictions by comparing predicted and actual ESBL
status.</p>
<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span>
<span></span>
<span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">predictions</span>, <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">esbl</span>, fill <span class="op">=</span> <span class="va">.pred_class</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
<span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_bar.html" class="external-link">geom_bar</a></span><span class="op">(</span>position <span class="op">=</span> <span class="st">"stack"</span><span class="op">)</span> <span class="op">+</span></span>
<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">"Predicted vs Actual ESBL Status"</span>,</span>
<span> x <span class="op">=</span> <span class="st">"Actual ESBL"</span>,</span>
<span> y <span class="op">=</span> <span class="st">"Count"</span><span class="op">)</span> <span class="op">+</span></span>
<span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_minimal</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
<p><img src="AMR_with_tidymodels_files/figure-html/unnamed-chunk-14-1.png" class="r-plt" alt="" width="720"></p>
<p>And plot the certainties too - how certain were the actual
predictions?</p>
<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">predictions</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>certainty <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse</a></span><span class="op">(</span><span class="va">.pred_class</span> <span class="op">==</span> <span class="st">"FALSE"</span>,</span>
<span> <span class="va">.pred_FALSE</span>,</span>
<span> <span class="va">.pred_TRUE</span><span class="op">)</span>,</span>
<span> correct <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse</a></span><span class="op">(</span><span class="va">esbl</span> <span class="op">==</span> <span class="va">.pred_class</span>, <span class="st">"Right"</span>, <span class="st">"Wrong"</span><span class="op">)</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://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq_len</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/nrow.html" class="external-link">nrow</a></span><span class="op">(</span><span class="va">predictions</span><span class="op">)</span><span class="op">)</span>,</span>
<span> y <span class="op">=</span> <span class="va">certainty</span>,</span>
<span> colour <span class="op">=</span> <span class="va">correct</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
<span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_manual.html" class="external-link">scale_colour_manual</a></span><span class="op">(</span>values <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>Right <span class="op">=</span> <span class="st">"green3"</span>, Wrong <span class="op">=</span> <span class="st">"red2"</span><span class="op">)</span>,</span>
<span> name <span class="op">=</span> <span class="st">"Correct?"</span><span class="op">)</span> <span class="op">+</span></span>
<span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_point.html" class="external-link">geom_point</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span> </span>
<span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_continuous.html" class="external-link">scale_y_continuous</a></span><span class="op">(</span>labels <span class="op">=</span> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste0</a></span><span class="op">(</span><span class="va">x</span> <span class="op">*</span> <span class="fl">100</span>, <span class="st">"%"</span><span class="op">)</span>,</span>
<span> limits <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0.5</span>, <span class="fl">1</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
<span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_minimal</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
<p><img src="AMR_with_tidymodels_files/figure-html/unnamed-chunk-15-1.png" class="r-plt" alt="" width="720">
### <strong>Conclusion</strong></p>
<p>In this example, we showcased how the new <code>AMR</code>-specific
recipe steps simplify working with <code>&lt;mic&gt;</code> columns in
<code>tidymodels</code>. The <code><a href="../reference/amr-tidymodels.html">step_mic_log2()</a></code> transformation
converts ordered MICs to log2-transformed numerics, improving
compatibility with classification models.</p>
<p>This pipeline enables realistic, reproducible, and interpretable
modelling of antimicrobial resistance data.</p>
<hr> <hr>
</div> </div>
</div>
<div class="section level2"> <div class="section level2">
<h2 id="example-2-predicting-amr-over-time">Example 2: Predicting AMR Over Time<a class="anchor" aria-label="anchor" href="#example-2-predicting-amr-over-time"></a> <h2 id="example-3-predicting-amr-over-time">Example 3: Predicting AMR Over Time<a class="anchor" aria-label="anchor" href="#example-3-predicting-amr-over-time"></a>
</h2> </h2>
<p>In this third example, we aim to predict antimicrobial resistance <p>In this third example, we aim to predict antimicrobial resistance
(AMR) trends over time using <code>tidymodels</code>. We will model (AMR) trends over time using <code>tidymodels</code>. We will model
@@ -461,8 +698,8 @@ amoxicillin-clavulanic acid <code>AMC</code>, and ciprofloxacin
<code>CIP</code>), based on historical data grouped by year and hospital <code>CIP</code>), based on historical data grouped by year and hospital
ward.</p> ward.</p>
<div class="section level3"> <div class="section level3">
<h3 id="objective-1"> <h3 id="objective-2">
<strong>Objective</strong><a class="anchor" aria-label="anchor" href="#objective-1"></a> <strong>Objective</strong><a class="anchor" aria-label="anchor" href="#objective-2"></a>
</h3> </h3>
<p>Our goal is to:</p> <p>Our goal is to:</p>
<ol style="list-style-type: decimal"> <ol style="list-style-type: decimal">
@@ -473,12 +710,12 @@ model.</li>
</ol> </ol>
</div> </div>
<div class="section level3"> <div class="section level3">
<h3 id="data-preparation-1"> <h3 id="data-preparation-2">
<strong>Data Preparation</strong><a class="anchor" aria-label="anchor" href="#data-preparation-1"></a> <strong>Data Preparation</strong><a class="anchor" aria-label="anchor" href="#data-preparation-2"></a>
</h3> </h3>
<p>We start by transforming the <code>example_isolates</code> dataset <p>We start by transforming the <code>example_isolates</code> dataset
into a structured time-series format.</p> into a structured time-series format.</p>
<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="co"># Load required libraries</span></span> <code class="sourceCode R"><span><span class="co"># Load required libraries</span></span>
<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://amr-for-r.org">AMR</a></span><span class="op">)</span></span> <span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://amr-for-r.org">AMR</a></span><span class="op">)</span></span>
<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://tidymodels.tidymodels.org" class="external-link">tidymodels</a></span><span class="op">)</span></span> <span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://tidymodels.tidymodels.org" class="external-link">tidymodels</a></span><span class="op">)</span></span>
@@ -525,15 +762,15 @@ rates by year and ward.</li>
</ul> </ul>
</div> </div>
<div class="section level3"> <div class="section level3">
<h3 id="defining-the-workflow-1"> <h3 id="defining-the-workflow-2">
<strong>Defining the Workflow</strong><a class="anchor" aria-label="anchor" href="#defining-the-workflow-1"></a> <strong>Defining the Workflow</strong><a class="anchor" aria-label="anchor" href="#defining-the-workflow-2"></a>
</h3> </h3>
<p>We now define the modelling workflow, which consists of a <p>We now define the modelling workflow, which consists of a
preprocessing step, a model specification, and the fitting process.</p> preprocessing step, a model specification, and the fitting process.</p>
<div class="section level4"> <div class="section level4">
<h4 id="preprocessing-with-a-recipe-1">1. Preprocessing with a Recipe<a class="anchor" aria-label="anchor" href="#preprocessing-with-a-recipe-1"></a> <h4 id="preprocessing-with-a-recipe-2">1. Preprocessing with a Recipe<a class="anchor" aria-label="anchor" href="#preprocessing-with-a-recipe-2"></a>
</h4> </h4>
<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb18"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="co"># Define the recipe</span></span> <code class="sourceCode R"><span><span class="co"># Define the recipe</span></span>
<span><span class="va">resistance_recipe_time</span> <span class="op">&lt;-</span> <span class="fu">recipe</span><span class="op">(</span><span class="va">res_AMX</span> <span class="op">~</span> <span class="va">year</span> <span class="op">+</span> <span class="va">gramstain</span>, data <span class="op">=</span> <span class="va">data_time</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="va">resistance_recipe_time</span> <span class="op">&lt;-</span> <span class="fu">recipe</span><span class="op">(</span><span class="va">res_AMX</span> <span class="op">~</span> <span class="va">year</span> <span class="op">+</span> <span class="va">gramstain</span>, data <span class="op">=</span> <span class="va">data_time</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">step_dummy</span><span class="op">(</span><span class="va">gramstain</span>, one_hot <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="co"># Convert categorical to numerical</span></span> <span> <span class="fu">step_dummy</span><span class="op">(</span><span class="va">gramstain</span>, one_hot <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="co"># Convert categorical to numerical</span></span>
@@ -566,10 +803,10 @@ variable.</li>
</ul> </ul>
</div> </div>
<div class="section level4"> <div class="section level4">
<h4 id="specifying-the-model-1">2. Specifying the Model<a class="anchor" aria-label="anchor" href="#specifying-the-model-1"></a> <h4 id="specifying-the-model-2">2. Specifying the Model<a class="anchor" aria-label="anchor" href="#specifying-the-model-2"></a>
</h4> </h4>
<p>We use a linear regression model to predict resistance trends.</p> <p>We use a linear regression model to predict resistance trends.</p>
<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb19"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="co"># Define the linear regression model</span></span> <code class="sourceCode R"><span><span class="co"># Define the linear regression model</span></span>
<span><span class="va">lm_model</span> <span class="op">&lt;-</span> <span class="fu">linear_reg</span><span class="op">(</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="va">lm_model</span> <span class="op">&lt;-</span> <span class="fu">linear_reg</span><span class="op">(</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">set_engine</span><span class="op">(</span><span class="st">"lm"</span><span class="op">)</span> <span class="co"># Use linear regression</span></span> <span> <span class="fu">set_engine</span><span class="op">(</span><span class="st">"lm"</span><span class="op">)</span> <span class="co"># Use linear regression</span></span>
@@ -588,10 +825,10 @@ engine.</li>
</ul> </ul>
</div> </div>
<div class="section level4"> <div class="section level4">
<h4 id="building-the-workflow-1">3. Building the Workflow<a class="anchor" aria-label="anchor" href="#building-the-workflow-1"></a> <h4 id="building-the-workflow-2">3. Building the Workflow<a class="anchor" aria-label="anchor" href="#building-the-workflow-2"></a>
</h4> </h4>
<p>We combine the preprocessing recipe and model into a workflow.</p> <p>We combine the preprocessing recipe and model into a workflow.</p>
<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb20"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="co"># Create workflow</span></span> <code class="sourceCode R"><span><span class="co"># Create workflow</span></span>
<span><span class="va">resistance_workflow_time</span> <span class="op">&lt;-</span> <span class="fu">workflow</span><span class="op">(</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="va">resistance_workflow_time</span> <span class="op">&lt;-</span> <span class="fu">workflow</span><span class="op">(</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">add_recipe</span><span class="op">(</span><span class="va">resistance_recipe_time</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">add_recipe</span><span class="op">(</span><span class="va">resistance_recipe_time</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
@@ -616,12 +853,12 @@ engine.</li>
</div> </div>
</div> </div>
<div class="section level3"> <div class="section level3">
<h3 id="training-and-evaluating-the-model-1"> <h3 id="training-and-evaluating-the-model-2">
<strong>Training and Evaluating the Model</strong><a class="anchor" aria-label="anchor" href="#training-and-evaluating-the-model-1"></a> <strong>Training and Evaluating the Model</strong><a class="anchor" aria-label="anchor" href="#training-and-evaluating-the-model-2"></a>
</h3> </h3>
<p>We split the data into training and testing sets, fit the model, and <p>We split the data into training and testing sets, fit the model, and
evaluate performance.</p> evaluate performance.</p>
<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb21"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="co"># Split the data</span></span> <code class="sourceCode R"><span><span class="co"># Split the data</span></span>
<span><span class="fu"><a href="https://rdrr.io/r/base/Random.html" class="external-link">set.seed</a></span><span class="op">(</span><span class="fl">123</span><span class="op">)</span></span> <span><span class="fu"><a href="https://rdrr.io/r/base/Random.html" class="external-link">set.seed</a></span><span class="op">(</span><span class="fl">123</span><span class="op">)</span></span>
<span><span class="va">data_split_time</span> <span class="op">&lt;-</span> <span class="fu">initial_split</span><span class="op">(</span><span class="va">data_time</span>, prop <span class="op">=</span> <span class="fl">0.8</span><span class="op">)</span></span> <span><span class="va">data_split_time</span> <span class="op">&lt;-</span> <span class="fu">initial_split</span><span class="op">(</span><span class="va">data_time</span>, prop <span class="op">=</span> <span class="fl">0.8</span><span class="op">)</span></span>
@@ -662,11 +899,11 @@ sets.</li>
</ul> </ul>
</div> </div>
<div class="section level3"> <div class="section level3">
<h3 id="visualising-predictions"> <h3 id="visualising-predictions-1">
<strong>Visualising Predictions</strong><a class="anchor" aria-label="anchor" href="#visualising-predictions"></a> <strong>Visualising Predictions</strong><a class="anchor" aria-label="anchor" href="#visualising-predictions-1"></a>
</h3> </h3>
<p>We plot resistance trends over time for amoxicillin.</p> <p>We plot resistance trends over time for amoxicillin.</p>
<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb22"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span> <code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span>
<span></span> <span></span>
<span><span class="co"># Plot actual vs predicted resistance over time</span></span> <span><span class="co"># Plot actual vs predicted resistance over time</span></span>
@@ -677,10 +914,10 @@ sets.</li>
<span> x <span class="op">=</span> <span class="st">"Year"</span>,</span> <span> x <span class="op">=</span> <span class="st">"Year"</span>,</span>
<span> y <span class="op">=</span> <span class="st">"Resistance Proportion"</span><span class="op">)</span> <span class="op">+</span></span> <span> y <span class="op">=</span> <span class="st">"Resistance Proportion"</span><span class="op">)</span> <span class="op">+</span></span>
<span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_minimal</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> <span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_minimal</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
<p><img src="AMR_with_tidymodels_files/figure-html/unnamed-chunk-14-1.png" class="r-plt" width="720"></p> <p><img src="AMR_with_tidymodels_files/figure-html/unnamed-chunk-21-1.png" class="r-plt" alt="" width="720"></p>
<p>Additionally, we can visualise resistance trends in <p>Additionally, we can visualise resistance trends in
<code>ggplot2</code> and directly add linear models there:</p> <code>ggplot2</code> and directly add linear models there:</p>
<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb23"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">data_time</span>, <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">year</span>, y <span class="op">=</span> <span class="va">res_AMX</span>, color <span class="op">=</span> <span class="va">gramstain</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span> <code class="sourceCode R"><span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="va">data_time</span>, <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">year</span>, y <span class="op">=</span> <span class="va">res_AMX</span>, color <span class="op">=</span> <span class="va">gramstain</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
<span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_path.html" class="external-link">geom_line</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span> <span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_path.html" class="external-link">geom_line</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
<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">"AMX Resistance Trends"</span>,</span> <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">"AMX Resistance Trends"</span>,</span>
@@ -691,7 +928,7 @@ sets.</li>
<span> formula <span class="op">=</span> <span class="va">y</span> <span class="op">~</span> <span class="va">x</span>,</span> <span> formula <span class="op">=</span> <span class="va">y</span> <span class="op">~</span> <span class="va">x</span>,</span>
<span> alpha <span class="op">=</span> <span class="fl">0.25</span><span class="op">)</span> <span class="op">+</span></span> <span> alpha <span class="op">=</span> <span class="fl">0.25</span><span class="op">)</span> <span class="op">+</span></span>
<span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_minimal</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> <span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_minimal</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
<p><img src="AMR_with_tidymodels_files/figure-html/unnamed-chunk-15-1.png" class="r-plt" width="720"></p> <p><img src="AMR_with_tidymodels_files/figure-html/unnamed-chunk-22-1.png" class="r-plt" alt="" width="720"></p>
</div> </div>
<div class="section level3"> <div class="section level3">
<h3 id="conclusion-1"> <h3 id="conclusion-1">

251
articles/AMR_with_tidymodels.md
View File

@@ -1,6 +1,6 @@
# AMR with tidymodels # AMR with tidymodels
> This page was entirely written by our [AMR for R > This page was almost entirely written by our [AMR for R
> Assistant](https://chat.amr-for-r.org), a ChatGPT manually-trained > Assistant](https://chat.amr-for-r.org), a ChatGPT manually-trained
> model able to answer any question about the `AMR` package. > model able to answer any question about the `AMR` package.
@@ -351,21 +351,250 @@ and reproducibly.
In this second example, we demonstrate how to use `<mic>` columns In this second example, we demonstrate how to use `<mic>` columns
directly in `tidymodels` workflows using AMR-specific recipe steps. This directly in `tidymodels` workflows using AMR-specific recipe steps. This
includes a transformation to `log2` scale using `step_mic_log2()`, which includes a transformation to `log2` scale using
prepares MIC values for use in classification models. [`step_mic_log2()`](https://amr-for-r.org/reference/amr-tidymodels.md),
which prepares MIC values for use in classification models.
This approach and idea formed the basis for the publication [DOI: This approach and idea formed the basis for the publication [DOI:
10.3389/fmicb.2025.1582703](https://doi.org/10.3389/fmicb.2025.1582703) 10.3389/fmicb.2025.1582703](https://doi.org/10.3389/fmicb.2025.1582703)
to model the presence of extended-spectrum beta-lactamases (ESBL). to model the presence of extended-spectrum beta-lactamases (ESBL) based
on MIC values.
> NOTE: THIS EXAMPLE WILL BE AVAILABLE IN A NEXT VERSION (#TODO) ### **Objective**
>
> The new AMR package version will contain new tidymodels selectors such Our goal is to:
> as `step_mic_log2()`.
1. Use raw MIC values to predict whether a bacterial isolate produces
ESBL.
2. Apply AMR-aware preprocessing in a `tidymodels` recipe.
3. Train a classification model and evaluate its predictive
performance.
### **Data Preparation**
We use the `esbl_isolates` dataset that comes with the AMR package.
``` r
# Load required libraries
library(AMR)
library(tidymodels)
# View the esbl_isolates data set
esbl_isolates
#> # A tibble: 500 × 19
#> esbl genus AMC AMP TZP CXM FOX CTX CAZ GEN TOB TMP SXT
#> <lgl> <chr> <mic> <mic> <mic> <mic> <mic> <mic> <mic> <mic> <mic> <mic> <mic>
#> 1 FALSE Esch… 32 32 4 64 64 8.00 8.00 1 1 16.0 20
#> 2 FALSE Esch… 32 32 4 64 64 4.00 8.00 1 1 16.0 320
#> 3 FALSE Esch… 4 2 64 8 4 8.00 0.12 16 16 0.5 20
#> 4 FALSE Kleb… 32 32 16 64 64 8.00 8.00 1 1 0.5 20
#> 5 FALSE Esch… 32 32 4 4 4 0.25 2.00 1 1 16.0 320
#> 6 FALSE Citr… 32 32 16 64 64 64.00 32.00 1 1 0.5 20
#> 7 FALSE Morg… 32 32 4 64 64 16.00 2.00 1 1 0.5 20
#> 8 FALSE Prot… 16 32 4 1 4 8.00 0.12 1 1 16.0 320
#> 9 FALSE Ente… 32 32 8 64 64 32.00 4.00 1 1 0.5 20
#> 10 FALSE Citr… 32 32 32 64 64 8.00 64.00 1 1 16.0 320
#> # ℹ 490 more rows
#> # ℹ 6 more variables: NIT <mic>, FOS <mic>, CIP <mic>, IPM <mic>, MEM <mic>,
#> # COL <mic>
# Prepare a binary outcome and convert to ordered factor
data <- esbl_isolates %>%
mutate(esbl = factor(esbl, levels = c(FALSE, TRUE), ordered = TRUE))
```
**Explanation:**
- `esbl_isolates`: Contains MIC test results and ESBL status for each
isolate.
- `mutate(esbl = ...)`: Converts the target column to an ordered factor
for classification.
### **Defining the Workflow**
#### 1. Preprocessing with a Recipe
We use our
[`step_mic_log2()`](https://amr-for-r.org/reference/amr-tidymodels.md)
function to log2-transform MIC values, ensuring that MICs are numeric
and properly scaled. All MIC predictors can easily and agnostically
selected using the new
[`all_mic_predictors()`](https://amr-for-r.org/reference/amr-tidymodels.md):
``` r
# Split into training and testing sets
set.seed(123)
split <- initial_split(data)
training_data <- training(split)
testing_data <- testing(split)
# Define the recipe
mic_recipe <- recipe(esbl ~ ., data = training_data) %>%
remove_role(genus, old_role = "predictor") %>% # Remove non-informative variable
step_mic_log2(all_mic_predictors()) #%>% # Log2 transform all MIC predictors
# prep()
mic_recipe
#>
#> ── Recipe ──────────────────────────────────────────────────────────────────────
#>
#> ── Inputs
#> Number of variables by role
#> outcome: 1
#> predictor: 17
#> undeclared role: 1
#>
#> ── Operations
#> • Log2 transformation of MIC columns: all_mic_predictors()
```
**Explanation:**
- `remove_role()`: Removes irrelevant variables like genus.
- [`step_mic_log2()`](https://amr-for-r.org/reference/amr-tidymodels.md):
Applies `log2(as.numeric(...))` to all MIC predictors in one go.
- `prep()`: Finalises the recipe based on training data.
#### 2. Specifying the Model
We use a simple logistic regression to model ESBL presence, though
recent models such as xgboost ([link to `parsnip`
manual](https://parsnip.tidymodels.org/reference/details_boost_tree_xgboost.html))
could be much more precise.
``` r
# Define the model
model <- logistic_reg(mode = "classification") %>%
set_engine("glm")
model
#> Logistic Regression Model Specification (classification)
#>
#> Computational engine: glm
```
**Explanation:**
- `logistic_reg()`: Specifies a binary classification model.
- `set_engine("glm")`: Uses the base R GLM engine.
#### 3. Building the Workflow
``` r
# Create workflow
workflow_model <- workflow() %>%
add_recipe(mic_recipe) %>%
add_model(model)
workflow_model
#> ══ Workflow ════════════════════════════════════════════════════════════════════
#> Preprocessor: Recipe
#> Model: logistic_reg()
#>
#> ── Preprocessor ────────────────────────────────────────────────────────────────
#> 1 Recipe Step
#>
#> • step_mic_log2()
#>
#> ── Model ───────────────────────────────────────────────────────────────────────
#> Logistic Regression Model Specification (classification)
#>
#> Computational engine: glm
```
### **Training and Evaluating the Model**
``` r
# Fit the model
fitted <- fit(workflow_model, training_data)
# Generate predictions
predictions <- predict(fitted, testing_data) %>%
bind_cols(predict(fitted, testing_data, type = "prob")) %>% # add probabilities
bind_cols(testing_data)
# Evaluate model performance
our_metrics <- metric_set(accuracy, recall, precision, sensitivity, specificity, ppv, npv)
metrics <- our_metrics(predictions, truth = esbl, estimate = .pred_class)
metrics
#> # A tibble: 7 × 3
#> .metric .estimator .estimate
#> <chr> <chr> <dbl>
#> 1 accuracy binary 0.92
#> 2 recall binary 0.921
#> 3 precision binary 0.921
#> 4 sensitivity binary 0.921
#> 5 specificity binary 0.919
#> 6 ppv binary 0.921
#> 7 npv binary 0.919
```
**Explanation:**
- `fit()`: Trains the model on the processed training data.
- [`predict()`](https://rdrr.io/r/stats/predict.html): Produces
predictions for unseen test data.
- `metric_set()`: Allows evaluating multiple classification metrics.
This will make `our_metrics` to become a function that we can use to
check the predictions with.
It appears we can predict ESBL gene presence with a positive predictive
value (PPV) of 92.1% and a negative predictive value (NPV) of 91.9 using
a simplistic logistic regression model.
### **Visualising Predictions**
We can visualise predictions by comparing predicted and actual ESBL
status.
``` r
library(ggplot2)
ggplot(predictions, aes(x = esbl, fill = .pred_class)) +
geom_bar(position = "stack") +
labs(title = "Predicted vs Actual ESBL Status",
x = "Actual ESBL",
y = "Count") +
theme_minimal()
```
![](AMR_with_tidymodels_files/figure-html/unnamed-chunk-14-1.png)
And plot the certainties too - how certain were the actual predictions?
``` r
predictions %>%
mutate(certainty = ifelse(.pred_class == "FALSE",
.pred_FALSE,
.pred_TRUE),
correct = ifelse(esbl == .pred_class, "Right", "Wrong")) %>%
ggplot(aes(x = seq_len(nrow(predictions)),
y = certainty,
colour = correct)) +
scale_colour_manual(values = c(Right = "green3", Wrong = "red2"),
name = "Correct?") +
geom_point() +
scale_y_continuous(labels = function(x) paste0(x * 100, "%"),
limits = c(0.5, 1)) +
theme_minimal()
```
![](AMR_with_tidymodels_files/figure-html/unnamed-chunk-15-1.png) \###
**Conclusion**
In this example, we showcased how the new `AMR`-specific recipe steps
simplify working with `<mic>` columns in `tidymodels`. The
[`step_mic_log2()`](https://amr-for-r.org/reference/amr-tidymodels.md)
transformation converts ordered MICs to log2-transformed numerics,
improving compatibility with classification models.
This pipeline enables realistic, reproducible, and interpretable
modelling of antimicrobial resistance data.
------------------------------------------------------------------------ ------------------------------------------------------------------------
## Example 2: Predicting AMR Over Time ## Example 3: Predicting AMR Over Time
In this third example, we aim to predict antimicrobial resistance (AMR) In this third example, we aim to predict antimicrobial resistance (AMR)
trends over time using `tidymodels`. We will model resistance to three trends over time using `tidymodels`. We will model resistance to three
@@ -573,7 +802,7 @@ ggplot(predictions_time, aes(x = year)) +
theme_minimal() theme_minimal()
``` ```
![](AMR_with_tidymodels_files/figure-html/unnamed-chunk-14-1.png) ![](AMR_with_tidymodels_files/figure-html/unnamed-chunk-21-1.png)
Additionally, we can visualise resistance trends in `ggplot2` and Additionally, we can visualise resistance trends in `ggplot2` and
directly add linear models there: directly add linear models there:
@@ -591,7 +820,7 @@ ggplot(data_time, aes(x = year, y = res_AMX, color = gramstain)) +
theme_minimal() theme_minimal()
``` ```
![](AMR_with_tidymodels_files/figure-html/unnamed-chunk-15-1.png) ![](AMR_with_tidymodels_files/figure-html/unnamed-chunk-22-1.png)
### **Conclusion** ### **Conclusion**

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@@ -30,7 +30,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

8
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@@ -30,7 +30,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -210,18 +210,18 @@ per drug explain the difference per microorganism.</p>
</h2> </h2>
<div class="sourceCode" id="cb6"><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="https://rdrr.io/r/stats/biplot.html" class="external-link">biplot</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span></span></code></pre></div> <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/stats/biplot.html" class="external-link">biplot</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span></span></code></pre></div>
<p><img src="PCA_files/figure-html/unnamed-chunk-5-1.png" class="r-plt" width="750"></p> <p><img src="PCA_files/figure-html/unnamed-chunk-5-1.png" class="r-plt" alt="" width="750"></p>
<p>But we can’t see the explanation of the points. Perhaps this works <p>But we can’t see the explanation of the points. Perhaps this works
better with our new <code><a href="../reference/ggplot_pca.html">ggplot_pca()</a></code> function, that better with our new <code><a href="../reference/ggplot_pca.html">ggplot_pca()</a></code> function, that
automatically adds the right labels and even groups:</p> automatically adds the right labels and even groups:</p>
<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/ggplot_pca.html">ggplot_pca</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span></span></code></pre></div> <code class="sourceCode R"><span><span class="fu"><a href="../reference/ggplot_pca.html">ggplot_pca</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span></span></code></pre></div>
<p><img src="PCA_files/figure-html/unnamed-chunk-6-1.png" class="r-plt" width="750"></p> <p><img src="PCA_files/figure-html/unnamed-chunk-6-1.png" class="r-plt" alt="" width="750"></p>
<p>You can also print an ellipse per group, and edit the appearance:</p> <p>You can also print an ellipse per group, and edit the appearance:</p>
<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/ggplot_pca.html">ggplot_pca</a></span><span class="op">(</span><span class="va">pca_result</span>, ellipse <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> <span class="op">+</span></span> <code class="sourceCode R"><span><span class="fu"><a href="../reference/ggplot_pca.html">ggplot_pca</a></span><span class="op">(</span><span class="va">pca_result</span>, ellipse <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> <span class="op">+</span></span>
<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> <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" class="r-plt" width="750"></p> <p><img src="PCA_files/figure-html/unnamed-chunk-7-1.png" class="r-plt" alt="" width="750"></p>
</div> </div>
</main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><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> </nav></aside>

4
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@@ -30,7 +30,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -311,7 +311,7 @@ using the included <code><a href="../reference/ggplot_sir.html">ggplot_sir()</a>
<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">Country</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/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">Country</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/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">Country</span>, <span class="va">AMP_ND2</span>, <span class="va">AMC_ED20</span>, <span class="va">CAZ_ED10</span>, <span class="va">CIP_ED5</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/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">Country</span>, <span class="va">AMP_ND2</span>, <span class="va">AMC_ED20</span>, <span class="va">CAZ_ED10</span>, <span class="va">CIP_ED5</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="../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> <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" class="r-plt" width="720"></p> <p><img src="WHONET_files/figure-html/unnamed-chunk-7-1.png" class="r-plt" alt="" width="720"></p>
</div> </div>
</main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><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> </nav></aside>

2
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@@ -30,7 +30,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
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@@ -30,7 +30,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -80,7 +80,7 @@
<main id="main" class="col-md-9"><div class="page-header"> <main id="main" class="col-md-9"><div class="page-header">
<img src="../logo.svg" class="logo" alt=""><h1>Download data sets for download / own use</h1> <img src="../logo.svg" class="logo" alt=""><h1>Download data sets for download / own use</h1>
<h4 data-toc-skip class="date">15 December 2025</h4> <h4 data-toc-skip class="date">22 December 2025</h4>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/datasets.Rmd" class="external-link"><code>vignettes/datasets.Rmd</code></a></small> <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 class="d-none name"><code>datasets.Rmd</code></div>

2
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
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@@ -7,7 +7,7 @@
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<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
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2
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@@ -33,7 +33,7 @@
<a class="navbar-brand me-2" href="index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

2
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@@ -859,6 +859,8 @@ information about how to work with functions in this package.
: Data Set with Clinical Breakpoints for SIR Interpretation : Data Set with Clinical Breakpoints for SIR Interpretation
- [`example_isolates`](https://amr-for-r.org/reference/example_isolates.md) - [`example_isolates`](https://amr-for-r.org/reference/example_isolates.md)
: Data Set with 2 000 Example Isolates : Data Set with 2 000 Example Isolates
- [`esbl_isolates`](https://amr-for-r.org/reference/esbl_isolates.md) :
Data Set with 500 ESBL Isolates
- [`microorganisms.codes`](https://amr-for-r.org/reference/microorganisms.codes.md) - [`microorganisms.codes`](https://amr-for-r.org/reference/microorganisms.codes.md)
: Data Set with 6 036 Common Microorganism Codes : Data Set with 6 036 Common Microorganism Codes
- [`microorganisms.groups`](https://amr-for-r.org/reference/microorganisms.groups.md) - [`microorganisms.groups`](https://amr-for-r.org/reference/microorganisms.groups.md)

20
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -49,9 +49,19 @@
</div> </div>
<div class="section level2"> <div class="section level2">
<h2 class="pkg-version" data-toc-text="3.0.1.9004" id="amr-3019004">AMR 3.0.1.9004<a class="anchor" aria-label="anchor" href="#amr-3019004"></a></h2> <h2 class="pkg-version" data-toc-text="3.0.1.9007" id="amr-3019007">AMR 3.0.1.9007<a class="anchor" aria-label="anchor" href="#amr-3019007"></a></h2>
<div class="section level4"> <div class="section level4">
<h4 id="changed-3-0-1-9004">Changed<a class="anchor" aria-label="anchor" href="#changed-3-0-1-9004"></a></h4> <h4 id="new-3-0-1-9007">New<a class="anchor" aria-label="anchor" href="#new-3-0-1-9007"></a></h4>
<ul><li>Integration with the <strong>tidymodels</strong> framework to allow seamless use of SIR, MIC and disk data in modelling pipelines via <code>recipes</code>
<ul><li>
<code><a href="../reference/amr-tidymodels.html">step_mic_log2()</a></code> to transform <code>&lt;mic&gt;</code> columns with log2, and <code><a href="../reference/amr-tidymodels.html">step_sir_numeric()</a></code> to convert <code>&lt;sir&gt;</code> columns to numeric</li>
<li>New <code>tidyselect</code> helpers: <code><a href="../reference/amr-tidymodels.html">all_sir()</a></code>, <code><a href="../reference/amr-tidymodels.html">all_sir_predictors()</a></code>, <code><a href="../reference/amr-tidymodels.html">all_mic()</a></code>, <code><a href="../reference/amr-tidymodels.html">all_mic_predictors()</a></code>, <code><a href="../reference/amr-tidymodels.html">all_disk()</a></code>, <code><a href="../reference/amr-tidymodels.html">all_disk_predictors()</a></code>
</li>
</ul></li>
<li>Data set <code>esbl_isolates</code> to practise with AMR modelling</li>
</ul></div>
<div class="section level4">
<h4 id="changed-3-0-1-9007">Changed<a class="anchor" aria-label="anchor" href="#changed-3-0-1-9007"></a></h4>
<ul><li>Fixed a bug in <code><a href="../reference/antibiogram.html">antibiogram()</a></code> for when no antimicrobials are set</li> <ul><li>Fixed a bug in <code><a href="../reference/antibiogram.html">antibiogram()</a></code> for when no antimicrobials are set</li>
<li>Added taniborbactam (<code>TAN</code>) and cefepime/taniborbactam (<code>FTA</code>) to the <code>antimicrobials</code> data set</li> <li>Added taniborbactam (<code>TAN</code>) and cefepime/taniborbactam (<code>FTA</code>) to the <code>antimicrobials</code> data set</li>
<li>Fixed a bug in <code><a href="../reference/as.sir.html">as.sir()</a></code> where for numeric input the arguments <code>S</code>, <code>i</code>, and <code>R</code> would not be considered (<a href="https://github.com/msberends/AMR/issues/244" class="external-link">#244</a>)</li> <li>Fixed a bug in <code><a href="../reference/as.sir.html">as.sir()</a></code> where for numeric input the arguments <code>S</code>, <code>i</code>, and <code>R</code> would not be considered (<a href="https://github.com/msberends/AMR/issues/244" class="external-link">#244</a>)</li>
@@ -104,7 +114,7 @@
<p>This package now supports not only tools for AMR data analysis in clinical settings, but also for veterinary and environmental microbiology. This was made possible through a collaboration with the <a href="https://www.upei.ca/avc" class="external-link">University of Prince Edward Island’s Atlantic Veterinary College</a>, Canada. To celebrate this great improvement of the package, we also updated the package logo to reflect this change.</p> <p>This package now supports not only tools for AMR data analysis in clinical settings, but also for veterinary and environmental microbiology. This was made possible through a collaboration with the <a href="https://www.upei.ca/avc" class="external-link">University of Prince Edward Island’s Atlantic Veterinary College</a>, Canada. To celebrate this great improvement of the package, we also updated the package logo to reflect this change.</p>
<div class="section level4"> <div class="section level4">
<h4 id="breaking-3-0-0">Breaking<a class="anchor" aria-label="anchor" href="#breaking-3-0-0"></a></h4> <h4 id="breaking-3-0-0">Breaking<a class="anchor" aria-label="anchor" href="#breaking-3-0-0"></a></h4>
<ul><li>Dataset <code>antibiotics</code> has been renamed to <code>antimicrobials</code> as the data set contains more than just antibiotics. Using <code>antibiotics</code> will still work, but now returns a warning.</li> <ul><li>Data set <code>antibiotics</code> has been renamed to <code>antimicrobials</code> as the data set contains more than just antibiotics. Using <code>antibiotics</code> will still work, but now returns a warning.</li>
<li>Removed all functions and references that used the deprecated <code>rsi</code> class, which were all replaced with their <code>sir</code> equivalents over two years ago.</li> <li>Removed all functions and references that used the deprecated <code>rsi</code> class, which were all replaced with their <code>sir</code> equivalents over two years ago.</li>
<li>Functions <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code> and <code><a href="../reference/resistance_predict.html">sir_predict()</a></code> are now deprecated and will be removed in a future version. Use the <code>tidymodels</code> framework instead, for which we <a href="https://amr-for-r.org/articles/AMR_with_tidymodels.html">wrote a basic introduction</a>.</li> <li>Functions <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code> and <code><a href="../reference/resistance_predict.html">sir_predict()</a></code> are now deprecated and will be removed in a future version. Use the <code>tidymodels</code> framework instead, for which we <a href="https://amr-for-r.org/articles/AMR_with_tidymodels.html">wrote a basic introduction</a>.</li>
</ul></div> </ul></div>
@@ -122,7 +132,7 @@
</ul></li> </ul></li>
<li> <li>
<strong>Support for WISCA antibiograms</strong> <strong>Support for WISCA antibiograms</strong>
<ul><li>The <code><a href="../reference/antibiogram.html">antibiogram()</a></code> function now supports creating true Weighted-Incidence Syndromic Combination Antibiograms (WISCA), a powerful Bayesian method for estimating regimen coverage probabilities using pathogen incidence and antimicrobial susceptibility data. WISCA offers improved precision for syndrome-specific treatment, even in datasets with sparse data. A dedicated <code><a href="../reference/antibiogram.html">wisca()</a></code> function is also available for easy usage.</li> <ul><li>The <code><a href="../reference/antibiogram.html">antibiogram()</a></code> function now supports creating true Weighted-Incidence Syndromic Combination Antibiograms (WISCA), a powerful Bayesian method for estimating regimen coverage probabilities using pathogen incidence and antimicrobial susceptibility data. WISCA offers improved precision for syndrome-specific treatment, even in data sets with sparse data. A dedicated <code><a href="../reference/antibiogram.html">wisca()</a></code> function is also available for easy usage.</li>
</ul></li> </ul></li>
<li> <li>
<strong>More global coverage of languages</strong> <strong>More global coverage of languages</strong>

25
news/index.md
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@@ -1,6 +1,23 @@
# Changelog # Changelog
## AMR 3.0.1.9004 ## AMR 3.0.1.9007
#### New
- Integration with the **tidymodels** framework to allow seamless use of
SIR, MIC and disk data in modelling pipelines via `recipes`
- [`step_mic_log2()`](https://amr-for-r.org/reference/amr-tidymodels.md)
to transform `<mic>` columns with log2, and
[`step_sir_numeric()`](https://amr-for-r.org/reference/amr-tidymodels.md)
to convert `<sir>` columns to numeric
- New `tidyselect` helpers:
[`all_sir()`](https://amr-for-r.org/reference/amr-tidymodels.md),
[`all_sir_predictors()`](https://amr-for-r.org/reference/amr-tidymodels.md),
[`all_mic()`](https://amr-for-r.org/reference/amr-tidymodels.md),
[`all_mic_predictors()`](https://amr-for-r.org/reference/amr-tidymodels.md),
[`all_disk()`](https://amr-for-r.org/reference/amr-tidymodels.md),
[`all_disk_predictors()`](https://amr-for-r.org/reference/amr-tidymodels.md)
- Data set `esbl_isolates` to practise with AMR modelling
#### Changed #### Changed
@@ -119,8 +136,8 @@ this change.
#### Breaking #### Breaking
- Dataset `antibiotics` has been renamed to `antimicrobials` as the data - Data set `antibiotics` has been renamed to `antimicrobials` as the
set contains more than just antibiotics. Using `antibiotics` will data set contains more than just antibiotics. Using `antibiotics` will
still work, but now returns a warning. still work, but now returns a warning.
- Removed all functions and references that used the deprecated `rsi` - Removed all functions and references that used the deprecated `rsi`
class, which were all replaced with their `sir` equivalents over two class, which were all replaced with their `sir` equivalents over two
@@ -158,7 +175,7 @@ this change.
Combination Antibiograms (WISCA), a powerful Bayesian method for Combination Antibiograms (WISCA), a powerful Bayesian method for
estimating regimen coverage probabilities using pathogen incidence estimating regimen coverage probabilities using pathogen incidence
and antimicrobial susceptibility data. WISCA offers improved and antimicrobial susceptibility data. WISCA offers improved
precision for syndrome-specific treatment, even in datasets with precision for syndrome-specific treatment, even in data sets with
sparse data. A dedicated sparse data. A dedicated
[`wisca()`](https://amr-for-r.org/reference/antibiogram.md) function [`wisca()`](https://amr-for-r.org/reference/antibiogram.md) function
is also available for easy usage. is also available for easy usage.

2
pkgdown.yml
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@@ -10,7 +10,7 @@ articles:
PCA: PCA.html PCA: PCA.html
WHONET: WHONET.html WHONET: WHONET.html
WISCA: WISCA.html WISCA: WISCA.html
last_built: 2025-12-15T12:28Z last_built: 2025-12-22T08:44Z
urls: urls:
reference: https://amr-for-r.org/reference reference: https://amr-for-r.org/reference
article: https://amr-for-r.org/articles article: https://amr-for-r.org/articles

2
reference/AMR-deprecated.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

2
reference/AMR-options.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

2
reference/AMR.html
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@@ -21,7 +21,7 @@ The AMR package is available in English, Arabic, Bengali, Chinese, Czech, Danish
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

2
reference/WHOCC.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

2
reference/WHONET.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

2
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

2
reference/ab_property.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

2
reference/add_custom_antimicrobials.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

2
reference/add_custom_microorganisms.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

22
reference/age.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -112,16 +112,16 @@
<span class="r-in"><span></span></span> <span class="r-in"><span></span></span>
<span class="r-in"><span><span class="va">df</span></span></span> <span class="r-in"><span><span class="va">df</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> birth_date age age_exact age_at_y2k</span> <span class="r-out co"><span class="r-pr">#&gt;</span> birth_date age age_exact age_at_y2k</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1 1980-02-27 45 45.79726 19</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 1 1980-02-27 45 45.81644 19</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2 1953-07-26 72 72.38904 46</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 2 1953-07-26 72 72.40822 46</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3 1949-09-02 76 76.28493 50</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 3 1949-09-02 76 76.30411 50</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 4 1986-08-03 39 39.36712 13</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 4 1986-08-03 39 39.38630 13</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 5 1932-11-19 93 93.07123 67</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 5 1932-11-19 93 93.09041 67</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 6 1949-03-30 76 76.71233 50</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 6 1949-03-30 76 76.73151 50</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 7 1996-06-23 29 29.47945 3</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 7 1996-06-23 29 29.49863 3</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 8 1963-09-16 62 62.24658 36</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 8 1963-09-16 62 62.26575 36</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 9 1952-05-16 73 73.58356 47</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 9 1952-05-16 73 73.60274 47</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 10 1952-11-14 73 73.08493 47</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 10 1952-11-14 73 73.10411 47</span>
</code></pre></div> </code></pre></div>
</div> </div>
</main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2> </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>

20
reference/age.md
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@@ -81,14 +81,14 @@ df$age_at_y2k <- age(df$birth_date, "2000-01-01")
df df
#> birth_date age age_exact age_at_y2k #> birth_date age age_exact age_at_y2k
#> 1 1980-02-27 45 45.79726 19 #> 1 1980-02-27 45 45.81644 19
#> 2 1953-07-26 72 72.38904 46 #> 2 1953-07-26 72 72.40822 46
#> 3 1949-09-02 76 76.28493 50 #> 3 1949-09-02 76 76.30411 50
#> 4 1986-08-03 39 39.36712 13 #> 4 1986-08-03 39 39.38630 13
#> 5 1932-11-19 93 93.07123 67 #> 5 1932-11-19 93 93.09041 67
#> 6 1949-03-30 76 76.71233 50 #> 6 1949-03-30 76 76.73151 50
#> 7 1996-06-23 29 29.47945 3 #> 7 1996-06-23 29 29.49863 3
#> 8 1963-09-16 62 62.24658 36 #> 8 1963-09-16 62 62.26575 36
#> 9 1952-05-16 73 73.58356 47 #> 9 1952-05-16 73 73.60274 47
#> 10 1952-11-14 73 73.08493 47 #> 10 1952-11-14 73 73.10411 47
``` ```

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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
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8
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<head>
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<meta name="robots" content="noindex">
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<img src="../logo.svg" class="logo" alt=""><h1>AMR Extensions for Tidymodels</h1>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/tidymodels.R" class="external-link"><code>R/tidymodels.R</code></a></small>
<div class="d-none name"><code>amr-tidymodels.Rd</code></div>
</div>
<div class="ref-description section level2">
<p>This family of functions allows using AMR-specific data types such as <code>&lt;sir&gt;</code> and <code>&lt;mic&gt;</code> inside <code>tidymodels</code> pipelines.</p>
</div>
<div class="section level2">
<h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
<div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">all_sir</span><span class="op">(</span><span class="op">)</span></span>
<span></span>
<span><span class="fu">all_sir_predictors</span><span class="op">(</span><span class="op">)</span></span>
<span></span>
<span><span class="fu">all_mic</span><span class="op">(</span><span class="op">)</span></span>
<span></span>
<span><span class="fu">all_mic_predictors</span><span class="op">(</span><span class="op">)</span></span>
<span></span>
<span><span class="fu">all_disk</span><span class="op">(</span><span class="op">)</span></span>
<span></span>
<span><span class="fu">all_disk_predictors</span><span class="op">(</span><span class="op">)</span></span>
<span></span>
<span><span class="fu">step_mic_log2</span><span class="op">(</span><span class="va">recipe</span>, <span class="va">...</span>, role <span class="op">=</span> <span class="cn">NA</span>, trained <span class="op">=</span> <span class="cn">FALSE</span>, columns <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span> skip <span class="op">=</span> <span class="cn">FALSE</span>, id <span class="op">=</span> <span class="fu">recipes</span><span class="fu">::</span><span class="fu"><a href="https://recipes.tidymodels.org/reference/rand_id.html" class="external-link">rand_id</a></span><span class="op">(</span><span class="st">"mic_log2"</span><span class="op">)</span><span class="op">)</span></span>
<span></span>
<span><span class="fu">step_sir_numeric</span><span class="op">(</span><span class="va">recipe</span>, <span class="va">...</span>, role <span class="op">=</span> <span class="cn">NA</span>, trained <span class="op">=</span> <span class="cn">FALSE</span>, columns <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span> skip <span class="op">=</span> <span class="cn">FALSE</span>, id <span class="op">=</span> <span class="fu">recipes</span><span class="fu">::</span><span class="fu"><a href="https://recipes.tidymodels.org/reference/rand_id.html" class="external-link">rand_id</a></span><span class="op">(</span><span class="st">"sir_numeric"</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
</div>
<div class="section level2">
<h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
<dl><dt id="arg-recipe">recipe<a class="anchor" aria-label="anchor" href="#arg-recipe"></a></dt>
<dd><p>A recipe object. The step will be added to the sequence of
operations for this recipe.</p></dd>
<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
<dd><p>One or more selector functions to choose variables for this step.
See <code><a href="https://recipes.tidymodels.org/reference/selections.html" class="external-link">selections()</a></code> for more details.</p></dd>
<dt id="arg-role">role<a class="anchor" aria-label="anchor" href="#arg-role"></a></dt>
<dd><p>Not used by this step since no new variables are created.</p></dd>
<dt id="arg-trained">trained<a class="anchor" aria-label="anchor" href="#arg-trained"></a></dt>
<dd><p>A logical to indicate if the quantities for preprocessing have
been estimated.</p></dd>
<dt id="arg-skip">skip<a class="anchor" aria-label="anchor" href="#arg-skip"></a></dt>
<dd><p>A logical. Should the step be skipped when the recipe is baked by
<code><a href="https://recipes.tidymodels.org/reference/bake.html" class="external-link">bake()</a></code>? While all operations are baked when <code><a href="https://recipes.tidymodels.org/reference/prep.html" class="external-link">prep()</a></code> is run, some
operations may not be able to be conducted on new data (e.g. processing the
outcome variable(s)). Care should be taken when using <code>skip = TRUE</code> as it
may affect the computations for subsequent operations.</p></dd>
<dt id="arg-id">id<a class="anchor" aria-label="anchor" href="#arg-id"></a></dt>
<dd><p>A character string that is unique to this step to identify it.</p></dd>
</dl></div>
<div class="section level2">
<h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
<p>You can read more in our online <a href="https://amr-for-r.org/articles/AMR_with_tidymodels.html">AMR with tidymodels introduction</a>.</p>
<p>Tidyselect helpers include:</p><ul><li><p><code>all_sir()</code> and <code>all_sir_predictors()</code> to select <code><a href="as.sir.html">&lt;sir&gt;</a></code> columns</p></li>
<li><p><code>all_mic()</code> and <code>all_mic_predictors()</code> to select <code><a href="as.mic.html">&lt;mic&gt;</a></code> columns</p></li>
<li><p><code>all_disk()</code> and <code>all_disk_predictors()</code> to select <code><a href="as.disk.html">&lt;disk&gt;</a></code> columns</p></li>
</ul><p>Pre-processing pipeline steps include:</p><ul><li><p><code>step_sir_numeric()</code> to convert SIR columns to numeric (via <code><a href="https://rdrr.io/r/base/numeric.html" class="external-link">as.numeric()</a></code>), to be used with <code>all_sir_predictors()</code>: <code>"S"</code> = 1, <code>"I"</code>/<code>"SDD"</code> = 2, <code>"R"</code> = 3. All other values are rendered <code>NA</code>. Keep this in mind for further processing, especially if the model does not allow for <code>NA</code> values.</p></li>
<li><p><code>step_mic_log2()</code> to convert MIC columns to numeric (via <code><a href="https://rdrr.io/r/base/numeric.html" class="external-link">as.numeric()</a></code>) and apply a log2 transform, to be used with <code>all_mic_predictors()</code></p></li>
</ul><p>These steps integrate with <code><a href="https://recipes.tidymodels.org/reference/recipe.html" class="external-link">recipes::recipe()</a></code> and work like standard preprocessing steps. They are useful for preparing data for modelling, especially with classification models.</p>
</div>
<div class="section level2">
<h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
<div class="dont-index"><p><code><a href="https://recipes.tidymodels.org/reference/recipe.html" class="external-link">recipes::recipe()</a></code>, <code><a href="as.sir.html">as.sir()</a></code>, <code><a href="as.mic.html">as.mic()</a></code>, <code><a href="as.disk.html">as.disk()</a></code></p></div>
</div>
<div class="section level2">
<h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
<div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://tidymodels.tidymodels.org" class="external-link">"tidymodels"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># The below approach formed the basis for this paper: DOI 10.3389/fmicb.2025.1582703</span></span></span>
<span class="r-in"><span> <span class="co"># Presence of ESBL genes was predicted based on raw MIC values.</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># example data set in the AMR package</span></span></span>
<span class="r-in"><span> <span class="va">esbl_isolates</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># Prepare a binary outcome and convert to ordered factor</span></span></span>
<span class="r-in"><span> <span class="va">data</span> <span class="op">&lt;-</span> <span class="va">esbl_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>esbl <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a></span><span class="op">(</span><span class="va">esbl</span>, levels <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="cn">FALSE</span>, <span class="cn">TRUE</span><span class="op">)</span>, ordered <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span><span class="op">)</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># Split into training and testing sets</span></span></span>
<span class="r-in"><span> <span class="va">split</span> <span class="op">&lt;-</span> <span class="fu">initial_split</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></span>
<span class="r-in"><span> <span class="va">training_data</span> <span class="op">&lt;-</span> <span class="fu">training</span><span class="op">(</span><span class="va">split</span><span class="op">)</span></span></span>
<span class="r-in"><span> <span class="va">testing_data</span> <span class="op">&lt;-</span> <span class="fu">testing</span><span class="op">(</span><span class="va">split</span><span class="op">)</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># Create and prep a recipe with MIC log2 transformation</span></span></span>
<span class="r-in"><span> <span class="va">mic_recipe</span> <span class="op">&lt;-</span> <span class="fu">recipe</span><span class="op">(</span><span class="va">esbl</span> <span class="op">~</span> <span class="va">.</span>, data <span class="op">=</span> <span class="va">training_data</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="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># Optionally remove non-predictive variables</span></span></span>
<span class="r-in"><span> <span class="fu">remove_role</span><span class="op">(</span><span class="va">genus</span>, old_role <span class="op">=</span> <span class="st">"predictor"</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="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># Apply the log2 transformation to all MIC predictors</span></span></span>
<span class="r-in"><span> <span class="fu">step_mic_log2</span><span class="op">(</span><span class="fu">all_mic_predictors</span><span class="op">(</span><span class="op">)</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="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># And apply the preparation steps</span></span></span>
<span class="r-in"><span> <span class="fu">prep</span><span class="op">(</span><span class="op">)</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># View prepped recipe</span></span></span>
<span class="r-in"><span> <span class="va">mic_recipe</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># Apply the recipe to training and testing data</span></span></span>
<span class="r-in"><span> <span class="va">out_training</span> <span class="op">&lt;-</span> <span class="fu">bake</span><span class="op">(</span><span class="va">mic_recipe</span>, new_data <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span></span></span>
<span class="r-in"><span> <span class="va">out_testing</span> <span class="op">&lt;-</span> <span class="fu">bake</span><span class="op">(</span><span class="va">mic_recipe</span>, new_data <span class="op">=</span> <span class="va">testing_data</span><span class="op">)</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># Fit a logistic regression model</span></span></span>
<span class="r-in"><span> <span class="va">fitted</span> <span class="op">&lt;-</span> <span class="fu">logistic_reg</span><span class="op">(</span>mode <span class="op">=</span> <span class="st">"classification"</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="r-in"><span> <span class="fu">set_engine</span><span class="op">(</span><span class="st">"glm"</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="r-in"><span> <span class="fu">fit</span><span class="op">(</span><span class="va">esbl</span> <span class="op">~</span> <span class="va">.</span>, data <span class="op">=</span> <span class="va">out_training</span><span class="op">)</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># Generate predictions on the test set</span></span></span>
<span class="r-in"><span> <span class="va">predictions</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/stats/predict.html" class="external-link">predict</a></span><span class="op">(</span><span class="va">fitted</span>, <span class="va">out_testing</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="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/bind_cols.html" class="external-link">bind_cols</a></span><span class="op">(</span><span class="va">out_testing</span><span class="op">)</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># Evaluate predictions using standard classification metrics</span></span></span>
<span class="r-in"><span> <span class="va">our_metrics</span> <span class="op">&lt;-</span> <span class="fu">metric_set</span><span class="op">(</span><span class="va">accuracy</span>,</span></span>
<span class="r-in"><span> <span class="va">recall</span>,</span></span>
<span class="r-in"><span> <span class="va">precision</span>,</span></span>
<span class="r-in"><span> <span class="va">sensitivity</span>,</span></span>
<span class="r-in"><span> <span class="va">specificity</span>,</span></span>
<span class="r-in"><span> <span class="va">ppv</span>,</span></span>
<span class="r-in"><span> <span class="va">npv</span><span class="op">)</span></span></span>
<span class="r-in"><span> <span class="va">metrics</span> <span class="op">&lt;-</span> <span class="fu">our_metrics</span><span class="op">(</span><span class="va">predictions</span>, truth <span class="op">=</span> <span class="va">esbl</span>, estimate <span class="op">=</span> <span class="va">.pred_class</span><span class="op">)</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="co"># Show performance</span></span></span>
<span class="r-in"><span> <span class="va">metrics</span></span></span>
<span class="r-in"><span><span class="op">}</span></span></span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> Loading required package: tidymodels</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> ── <span style="font-weight: bold;">Attaching packages</span> ────────────────────────────────────── tidymodels 1.4.1 ──</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">broom </span> 1.0.11 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">rsample </span> 1.3.1 </span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">dials </span> 1.4.2 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">tailor </span> 0.1.0 </span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">infer </span> 1.1.0 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">tidyr </span> 1.3.2 </span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">modeldata </span> 1.5.1 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">tune </span> 2.0.1 </span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">parsnip </span> 1.4.0 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">workflows </span> 1.3.0 </span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">purrr </span> 1.2.0 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">workflowsets</span> 1.1.1 </span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">recipes </span> 1.3.1 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">yardstick </span> 1.3.2 </span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> ── <span style="font-weight: bold;">Conflicts</span> ───────────────────────────────────────── tidymodels_conflicts() ──</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #BB0000;">✖</span> <span style="color: #0000BB;">purrr</span>::<span style="color: #00BB00;">discard()</span> masks <span style="color: #0000BB;">scales</span>::discard()</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #BB0000;">✖</span> <span style="color: #0000BB;">dplyr</span>::<span style="color: #00BB00;">filter()</span> masks <span style="color: #0000BB;">stats</span>::filter()</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #BB0000;">✖</span> <span style="color: #0000BB;">dplyr</span>::<span style="color: #00BB00;">lag()</span> masks <span style="color: #0000BB;">stats</span>::lag()</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #BB0000;">✖</span> <span style="color: #0000BB;">recipes</span>::<span style="color: #00BB00;">step()</span> masks <span style="color: #0000BB;">stats</span>::step()</span>
<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>glm.fit: fitted probabilities numerically 0 or 1 occurred</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 7 × 3</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> .metric .estimator .estimate</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> accuracy binary 0.936</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> recall binary 0.954</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> precision binary 0.925</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> sensitivity binary 0.954</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span> specificity binary 0.917</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">6</span> ppv binary 0.925</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">7</span> npv binary 0.948</span>
</code></pre></div>
</div>
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</nav></aside></div>
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<p><code>AMR</code> (for R). Free and open-source, licenced under the <a target="_blank" href="https://github.com/msberends/AMR/blob/main/LICENSE" class="external-link">GNU General Public License version 2.0 (GPL-2)</a>.<br>Developed at the <a target="_blank" href="https://www.rug.nl" class="external-link">University of Groningen</a> and <a target="_blank" href="https://www.umcg.nl" class="external-link">University Medical Center Groningen</a> in The Netherlands.</p>
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192
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@@ -0,0 +1,192 @@
# AMR Extensions for Tidymodels
This family of functions allows using AMR-specific data types such as
`<sir>` and `<mic>` inside `tidymodels` pipelines.
## Usage
``` r
all_sir()
all_sir_predictors()
all_mic()
all_mic_predictors()
all_disk()
all_disk_predictors()
step_mic_log2(recipe, ..., role = NA, trained = FALSE, columns = NULL,
skip = FALSE, id = recipes::rand_id("mic_log2"))
step_sir_numeric(recipe, ..., role = NA, trained = FALSE, columns = NULL,
skip = FALSE, id = recipes::rand_id("sir_numeric"))
```
## Arguments
- recipe:
A recipe object. The step will be added to the sequence of operations
for this recipe.
- ...:
One or more selector functions to choose variables for this step. See
[`selections()`](https://recipes.tidymodels.org/reference/selections.html)
for more details.
- role:
Not used by this step since no new variables are created.
- trained:
A logical to indicate if the quantities for preprocessing have been
estimated.
- skip:
A logical. Should the step be skipped when the recipe is baked by
[`bake()`](https://recipes.tidymodels.org/reference/bake.html)? While
all operations are baked when
[`prep()`](https://recipes.tidymodels.org/reference/prep.html) is run,
some operations may not be able to be conducted on new data (e.g.
processing the outcome variable(s)). Care should be taken when using
`skip = TRUE` as it may affect the computations for subsequent
operations.
- id:
A character string that is unique to this step to identify it.
## Details
You can read more in our online [AMR with tidymodels
introduction](https://amr-for-r.org/articles/AMR_with_tidymodels.html).
Tidyselect helpers include:
- `all_sir()` and `all_sir_predictors()` to select
[`<sir>`](https://amr-for-r.org/reference/as.sir.md) columns
- `all_mic()` and `all_mic_predictors()` to select
[`<mic>`](https://amr-for-r.org/reference/as.mic.md) columns
- `all_disk()` and `all_disk_predictors()` to select
[`<disk>`](https://amr-for-r.org/reference/as.disk.md) columns
Pre-processing pipeline steps include:
- `step_sir_numeric()` to convert SIR columns to numeric (via
[`as.numeric()`](https://rdrr.io/r/base/numeric.html)), to be used
with `all_sir_predictors()`: `"S"` = 1, `"I"`/`"SDD"` = 2, `"R"` = 3.
All other values are rendered `NA`. Keep this in mind for further
processing, especially if the model does not allow for `NA` values.
- `step_mic_log2()` to convert MIC columns to numeric (via
[`as.numeric()`](https://rdrr.io/r/base/numeric.html)) and apply a
log2 transform, to be used with `all_mic_predictors()`
These steps integrate with
[`recipes::recipe()`](https://recipes.tidymodels.org/reference/recipe.html)
and work like standard preprocessing steps. They are useful for
preparing data for modelling, especially with classification models.
## See also
[`recipes::recipe()`](https://recipes.tidymodels.org/reference/recipe.html),
[`as.sir()`](https://amr-for-r.org/reference/as.sir.md),
[`as.mic()`](https://amr-for-r.org/reference/as.mic.md),
[`as.disk()`](https://amr-for-r.org/reference/as.disk.md)
## Examples
``` r
if (require("tidymodels")) {
# The below approach formed the basis for this paper: DOI 10.3389/fmicb.2025.1582703
# Presence of ESBL genes was predicted based on raw MIC values.
# example data set in the AMR package
esbl_isolates
# Prepare a binary outcome and convert to ordered factor
data <- esbl_isolates %>%
mutate(esbl = factor(esbl, levels = c(FALSE, TRUE), ordered = TRUE))
# Split into training and testing sets
split <- initial_split(data)
training_data <- training(split)
testing_data <- testing(split)
# Create and prep a recipe with MIC log2 transformation
mic_recipe <- recipe(esbl ~ ., data = training_data) %>%
# Optionally remove non-predictive variables
remove_role(genus, old_role = "predictor") %>%
# Apply the log2 transformation to all MIC predictors
step_mic_log2(all_mic_predictors()) %>%
# And apply the preparation steps
prep()
# View prepped recipe
mic_recipe
# Apply the recipe to training and testing data
out_training <- bake(mic_recipe, new_data = NULL)
out_testing <- bake(mic_recipe, new_data = testing_data)
# Fit a logistic regression model
fitted <- logistic_reg(mode = "classification") %>%
set_engine("glm") %>%
fit(esbl ~ ., data = out_training)
# Generate predictions on the test set
predictions <- predict(fitted, out_testing) %>%
bind_cols(out_testing)
# Evaluate predictions using standard classification metrics
our_metrics <- metric_set(accuracy,
recall,
precision,
sensitivity,
specificity,
ppv,
npv)
metrics <- our_metrics(predictions, truth = esbl, estimate = .pred_class)
# Show performance
metrics
}
#> Loading required package: tidymodels
#> ── Attaching packages ────────────────────────────────────── tidymodels 1.4.1 ──
#> ✔ broom 1.0.11 ✔ rsample 1.3.1
#> ✔ dials 1.4.2 ✔ tailor 0.1.0
#> ✔ infer 1.1.0 ✔ tidyr 1.3.2
#> ✔ modeldata 1.5.1 ✔ tune 2.0.1
#> ✔ parsnip 1.4.0 ✔ workflows 1.3.0
#> ✔ purrr 1.2.0 ✔ workflowsets 1.1.1
#> ✔ recipes 1.3.1 ✔ yardstick 1.3.2
#> ── Conflicts ───────────────────────────────────────── tidymodels_conflicts() ──
#> ✖ purrr::discard() masks scales::discard()
#> ✖ dplyr::filter() masks stats::filter()
#> ✖ dplyr::lag() masks stats::lag()
#> ✖ recipes::step() masks stats::step()
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
#> # A tibble: 7 × 3
#> .metric .estimator .estimate
#> <chr> <chr> <dbl>
#> 1 accuracy binary 0.936
#> 2 recall binary 0.954
#> 3 precision binary 0.925
#> 4 sensitivity binary 0.954
#> 5 specificity binary 0.917
#> 6 ppv binary 0.925
#> 7 npv binary 0.948
```

16
reference/antibiogram.html
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@@ -9,7 +9,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -282,7 +282,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
<span><span class="co"># this is equal to:</span></span> <span><span class="co"># this is equal to:</span></span>
<span><span class="fu"><a href="../reference/antibiogram.html">wisca</a></span><span class="op">(</span><span class="va">your_data</span>,</span> <span><span class="fu"><a href="../reference/antibiogram.html">wisca</a></span><span class="op">(</span><span class="va">your_data</span>,</span>
<span> antimicrobials <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><p></p></div> <span> antimicrobials <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><p></p></div>
<p>WISCA uses a sophisticated Bayesian decision model to combine both local and pooled antimicrobial resistance data. This approach not only evaluates local patterns but can also draw on multi-centre datasets to improve regimen accuracy, even in low-incidence infections like paediatric bloodstream infections (BSIs).</p></li> <p>WISCA uses a sophisticated Bayesian decision model to combine both local and pooled antimicrobial resistance data. This approach not only evaluates local patterns but can also draw on multi-centre data sets to improve regimen accuracy, even in low-incidence infections like paediatric bloodstream infections (BSIs).</p></li>
</ol></div> </ol></div>
<div class="section"> <div class="section">
@@ -587,9 +587,9 @@ Adhering to previously described approaches (see Source) and especially the Baye
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Type: WISCA with 95% CI</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Type: WISCA with 95% CI</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> `Syndromic Group` `Piperacillin/tazobactam` Piperacillin/tazobactam + Gentam…¹</span> <span class="r-out co"><span class="r-pr">#&gt;</span> `Syndromic Group` `Piperacillin/tazobactam` Piperacillin/tazobactam + Gentam…¹</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> Clinical 73.4% (67.6-78.6%) 92.4% (90.6-93.7%) </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> Clinical 73.5% (68.1-78.6%) 92.3% (90.8-93.8%) </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> ICU 57.4% (49.7-65.6%) 85% (82.1-87.6%) </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> ICU 57.3% (49.8-64.9%) 84.8% (82-87.7%) </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> Outpatient 56.9% (46.9-66.7%) 74.4% (69-79.7%) </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> Outpatient 56.8% (47-67%) 74.4% (68.6-79.7%) </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ abbreviated name: ¹​`Piperacillin/tazobactam + Gentamicin`</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ abbreviated name: ¹​`Piperacillin/tazobactam + Gentamicin`</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 1 more variable: `Piperacillin/tazobactam + Tobramycin` &lt;chr&gt;</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 1 more variable: `Piperacillin/tazobactam + Tobramycin` &lt;chr&gt;</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram,</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram,</span></span>
@@ -614,9 +614,9 @@ Adhering to previously described approaches (see Source) and especially the Baye
<span class="r-out co"><span class="r-pr">#&gt;</span> </span> <span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> |Syndromic Group |Piperacillin/tazobactam |</span> <span class="r-out co"><span class="r-pr">#&gt;</span> |Syndromic Group |Piperacillin/tazobactam |</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> |:---------------|:-----------------------|</span> <span class="r-out co"><span class="r-pr">#&gt;</span> |:---------------|:-----------------------|</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> |Clinical |73.6% (68.4-79%) |</span> <span class="r-out co"><span class="r-pr">#&gt;</span> |Clinical |73.6% (68.5-78.7%) |</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> |ICU |57.4% (49.7-65.4%) |</span> <span class="r-out co"><span class="r-pr">#&gt;</span> |ICU |57.4% (49.3-65.8%) |</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> |Outpatient |57% (47.2-66.7%) |</span> <span class="r-out co"><span class="r-pr">#&gt;</span> |Outpatient |57% (47.1-67.3%) |</span>
<span class="r-in"><span></span></span> <span class="r-in"><span></span></span>
<span class="r-in"><span></span></span> <span class="r-in"><span></span></span>
<span class="r-in"><span><span class="co"># Generate plots with ggplot2 or base R --------------------------------</span></span></span> <span class="r-in"><span><span class="co"># Generate plots with ggplot2 or base R --------------------------------</span></span></span>

18
reference/antibiogram.md
View File

@@ -427,9 +427,9 @@ pathogen, but rather by syndrome.
WISCA uses a sophisticated Bayesian decision model to combine both WISCA uses a sophisticated Bayesian decision model to combine both
local and pooled antimicrobial resistance data. This approach not local and pooled antimicrobial resistance data. This approach not
only evaluates local patterns but can also draw on multi-centre only evaluates local patterns but can also draw on multi-centre data
datasets to improve regimen accuracy, even in low-incidence sets to improve regimen accuracy, even in low-incidence infections
infections like paediatric bloodstream infections (BSIs). like paediatric bloodstream infections (BSIs).
### Grouped tibbles ### Grouped tibbles
@@ -777,9 +777,9 @@ antibiogram(example_isolates,
#> # Type: WISCA with 95% CI #> # Type: WISCA with 95% CI
#> `Syndromic Group` `Piperacillin/tazobactam` Piperacillin/tazobactam + Gentam…¹ #> `Syndromic Group` `Piperacillin/tazobactam` Piperacillin/tazobactam + Gentam…¹
#> <chr> <chr> <chr> #> <chr> <chr> <chr>
#> 1 Clinical 73.4% (67.6-78.6%) 92.4% (90.6-93.7%) #> 1 Clinical 73.5% (68.1-78.6%) 92.3% (90.8-93.8%)
#> 2 ICU 57.4% (49.7-65.6%) 85% (82.1-87.6%) #> 2 ICU 57.3% (49.8-64.9%) 84.8% (82-87.7%)
#> 3 Outpatient 56.9% (46.9-66.7%) 74.4% (69-79.7%) #> 3 Outpatient 56.8% (47-67%) 74.4% (68.6-79.7%)
#> # ℹ abbreviated name: ¹​`Piperacillin/tazobactam + Gentamicin` #> # ℹ abbreviated name: ¹​`Piperacillin/tazobactam + Gentamicin`
#> # ℹ 1 more variable: `Piperacillin/tazobactam + Tobramycin` <chr> #> # ℹ 1 more variable: `Piperacillin/tazobactam + Tobramycin` <chr>
#> # Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram, #> # Use `ggplot2::autoplot()` or base R `plot()` to create a plot of this antibiogram,
@@ -804,9 +804,9 @@ if (requireNamespace("knitr")) {
#> #>
#> |Syndromic Group |Piperacillin/tazobactam | #> |Syndromic Group |Piperacillin/tazobactam |
#> |:---------------|:-----------------------| #> |:---------------|:-----------------------|
#> |Clinical |73.6% (68.4-79%) | #> |Clinical |73.6% (68.5-78.7%) |
#> |ICU |57.4% (49.7-65.4%) | #> |ICU |57.4% (49.3-65.8%) |
#> |Outpatient |57% (47.2-66.7%) | #> |Outpatient |57% (47.1-67.3%) |
# Generate plots with ggplot2 or base R -------------------------------- # Generate plots with ggplot2 or base R --------------------------------

5
reference/antimicrobial_selectors.html
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@@ -17,7 +17,7 @@ my_data_with_all_these_columns %&amp;gt;%
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -670,6 +670,9 @@ my_data_with_all_these_columns %&amp;gt;%
<span class="r-msg co"><span class="r-pr">#&gt;</span> Loading required package: data.table</span> <span class="r-msg co"><span class="r-pr">#&gt;</span> Loading required package: data.table</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> </span> <span class="r-msg co"><span class="r-pr">#&gt;</span> </span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> Attaching package: ‘data.table’</span> <span class="r-msg co"><span class="r-pr">#&gt;</span> Attaching package: ‘data.table’</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> The following object is masked from ‘package:purrr’:</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> </span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> transpose</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> The following objects are masked from ‘package:dplyr’:</span> <span class="r-msg co"><span class="r-pr">#&gt;</span> The following objects are masked from ‘package:dplyr’:</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> </span> <span class="r-msg co"><span class="r-pr">#&gt;</span> </span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> between, first, last</span> <span class="r-msg co"><span class="r-pr">#&gt;</span> between, first, last</span>

3
reference/antimicrobial_selectors.md
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@@ -1013,6 +1013,9 @@ if (require("data.table")) {
#> Loading required package: data.table #> Loading required package: data.table
#> #>
#> Attaching package: ‘data.table’ #> Attaching package: ‘data.table’
#> The following object is masked from ‘package:purrr’:
#>
#> transpose
#> The following objects are masked from ‘package:dplyr’: #> The following objects are masked from ‘package:dplyr’:
#> #>
#> between, first, last #> between, first, last

2
reference/antimicrobials.html
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@@ -9,7 +9,7 @@ The antibiotics data set has been renamed to antimicrobials. The old name will b
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
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2
reference/as.ab.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
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2
reference/as.av.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
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2
reference/as.disk.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

2
reference/as.mic.html
View File

@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

2
reference/as.mo.html
View File

@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
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14
reference/as.sir.html
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@@ -9,7 +9,7 @@ Breakpoints are currently implemented from EUCAST 2011-2025 and CLSI 2011-2025,
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -416,10 +416,10 @@ Breakpoints are currently implemented from EUCAST 2011-2025 and CLSI 2011-2025,
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 4 × 18</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 4 × 18</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> datetime index method ab_given mo_given host_given input_given</span> <span class="r-out co"><span class="r-pr">#&gt;</span> datetime index method ab_given mo_given host_given input_given</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dttm&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dttm&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> 2025-12-15 <span style="color: #949494;">12:29:02</span> 1 MIC amoxicillin Escherich… human 8 </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> 2025-12-22 <span style="color: #949494;">08:45:24</span> 1 MIC amoxicillin Escherich… human 8 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> 2025-12-15 <span style="color: #949494;">12:29:02</span> 1 MIC cipro Escherich… human 0.256 </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> 2025-12-22 <span style="color: #949494;">08:45:24</span> 1 MIC cipro Escherich… human 0.256 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> 2025-12-15 <span style="color: #949494;">12:29:02</span> 1 DISK tobra Escherich… human 16 </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> 2025-12-22 <span style="color: #949494;">08:45:24</span> 1 DISK tobra Escherich… human 16 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> 2025-12-15 <span style="color: #949494;">12:29:03</span> 1 DISK genta Escherich… human 18 </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> 2025-12-22 <span style="color: #949494;">08:45:24</span> 1 DISK genta Escherich… human 18 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 11 more variables: ab &lt;ab&gt;, mo &lt;mo&gt;, host &lt;chr&gt;, input &lt;chr&gt;,</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 11 more variables: ab &lt;ab&gt;, mo &lt;mo&gt;, host &lt;chr&gt;, input &lt;chr&gt;,</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># outcome &lt;sir&gt;, notes &lt;chr&gt;, guideline &lt;chr&gt;, ref_table &lt;chr&gt;, uti &lt;lgl&gt;,</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># outcome &lt;sir&gt;, notes &lt;chr&gt;, guideline &lt;chr&gt;, ref_table &lt;chr&gt;, uti &lt;lgl&gt;,</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># breakpoint_S_R &lt;chr&gt;, site &lt;chr&gt;</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># breakpoint_S_R &lt;chr&gt;, site &lt;chr&gt;</span></span>
@@ -620,12 +620,12 @@ Breakpoints are currently implemented from EUCAST 2011-2025 and CLSI 2011-2025,
<span class="r-in"><span><span class="co"># For CLEANING existing SIR values -------------------------------------</span></span></span> <span class="r-in"><span><span class="co"># For CLEANING existing SIR values -------------------------------------</span></span></span>
<span class="r-in"><span></span></span> <span class="r-in"><span></span></span>
<span class="r-in"><span><span class="fu">as.sir</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"S"</span>, <span class="st">"SDD"</span>, <span class="st">"I"</span>, <span class="st">"R"</span>, <span class="st">"NI"</span>, <span class="st">"A"</span>, <span class="st">"B"</span>, <span class="st">"C"</span><span class="op">)</span><span class="op">)</span></span></span> <span class="r-in"><span><span class="fu">as.sir</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"S"</span>, <span class="st">"SDD"</span>, <span class="st">"I"</span>, <span class="st">"R"</span>, <span class="st">"NI"</span>, <span class="st">"A"</span>, <span class="st">"B"</span>, <span class="st">"C"</span><span class="op">)</span><span class="op">)</span></span></span>
<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>in <span style="background-color: #444444;">`as.sir()`</span>: 3 results in index '20' truncated (38%) that were invalid</span> <span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>in <span style="background-color: #444444;">`as.sir()`</span>: 3 results in index '21' truncated (38%) that were invalid</span>
<span class="r-wrn co"><span class="r-pr">#&gt;</span> antimicrobial interpretations: "A", "B", and "C"</span> <span class="r-wrn co"><span class="r-pr">#&gt;</span> antimicrobial interpretations: "A", "B", and "C"</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Class 'sir'</span> <span class="r-out co"><span class="r-pr">#&gt;</span> Class 'sir'</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] S SDD I R NI &lt;NA&gt; &lt;NA&gt; &lt;NA&gt;</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [1] S SDD I R NI &lt;NA&gt; &lt;NA&gt; &lt;NA&gt;</span>
<span class="r-in"><span><span class="fu">as.sir</span><span class="op">(</span><span class="st">"&lt;= 0.002; S"</span><span class="op">)</span> <span class="co"># will return "S"</span></span></span> <span class="r-in"><span><span class="fu">as.sir</span><span class="op">(</span><span class="st">"&lt;= 0.002; S"</span><span class="op">)</span> <span class="co"># will return "S"</span></span></span>
<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>in <span style="background-color: #444444;">`as.sir()`</span>: 1 result in index '20' truncated (100%) that were invalid</span> <span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>in <span style="background-color: #444444;">`as.sir()`</span>: 1 result in index '21' truncated (100%) that were invalid</span>
<span class="r-wrn co"><span class="r-pr">#&gt;</span> antimicrobial interpretations: "&lt;= 0.002; S"</span> <span class="r-wrn co"><span class="r-pr">#&gt;</span> antimicrobial interpretations: "&lt;= 0.002; S"</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Class 'sir'</span> <span class="r-out co"><span class="r-pr">#&gt;</span> Class 'sir'</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] &lt;NA&gt;</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [1] &lt;NA&gt;</span>

12
reference/as.sir.md
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@@ -648,10 +648,10 @@ sir_interpretation_history()
#> # A tibble: 4 × 18 #> # A tibble: 4 × 18
#> datetime index method ab_given mo_given host_given input_given #> datetime index method ab_given mo_given host_given input_given
#> <dttm> <int> <chr> <chr> <chr> <chr> <chr> #> <dttm> <int> <chr> <chr> <chr> <chr> <chr>
#> 1 2025-12-15 12:29:02 1 MIC amoxicillin Escherich… human 8 #> 1 2025-12-22 08:45:24 1 MIC amoxicillin Escherich… human 8
#> 2 2025-12-15 12:29:02 1 MIC cipro Escherich… human 0.256 #> 2 2025-12-22 08:45:24 1 MIC cipro Escherich… human 0.256
#> 3 2025-12-15 12:29:02 1 DISK tobra Escherich… human 16 #> 3 2025-12-22 08:45:24 1 DISK tobra Escherich… human 16
#> 4 2025-12-15 12:29:03 1 DISK genta Escherich… human 18 #> 4 2025-12-22 08:45:24 1 DISK genta Escherich… human 18
#> # ℹ 11 more variables: ab <ab>, mo <mo>, host <chr>, input <chr>, #> # ℹ 11 more variables: ab <ab>, mo <mo>, host <chr>, input <chr>,
#> # outcome <sir>, notes <chr>, guideline <chr>, ref_table <chr>, uti <lgl>, #> # outcome <sir>, notes <chr>, guideline <chr>, ref_table <chr>, uti <lgl>,
#> # breakpoint_S_R <chr>, site <chr> #> # breakpoint_S_R <chr>, site <chr>
@@ -852,12 +852,12 @@ as.sir(
# For CLEANING existing SIR values ------------------------------------- # For CLEANING existing SIR values -------------------------------------
as.sir(c("S", "SDD", "I", "R", "NI", "A", "B", "C")) as.sir(c("S", "SDD", "I", "R", "NI", "A", "B", "C"))
#> Warning: in `as.sir()`: 3 results in index '20' truncated (38%) that were invalid #> Warning: in `as.sir()`: 3 results in index '21' truncated (38%) that were invalid
#> antimicrobial interpretations: "A", "B", and "C" #> antimicrobial interpretations: "A", "B", and "C"
#> Class 'sir' #> Class 'sir'
#> [1] S SDD I R NI <NA> <NA> <NA> #> [1] S SDD I R NI <NA> <NA> <NA>
as.sir("<= 0.002; S") # will return "S" as.sir("<= 0.002; S") # will return "S"
#> Warning: in `as.sir()`: 1 result in index '20' truncated (100%) that were invalid #> Warning: in `as.sir()`: 1 result in index '21' truncated (100%) that were invalid
#> antimicrobial interpretations: "<= 0.002; S" #> antimicrobial interpretations: "<= 0.002; S"
#> Class 'sir' #> Class 'sir'
#> [1] <NA> #> [1] <NA>

2
reference/atc_online.html
View File

@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
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2
reference/av_from_text.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
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2
reference/av_property.html
View File

@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
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2
reference/availability.html
View File

@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
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2
reference/bug_drug_combinations.html
View File

@@ -7,7 +7,7 @@
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<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="96x96" href="../favicon-96x96.png"><link rel="icon" type="”image/svg+xml”" href="../favicon.svg"><link rel="apple-touch-icon" sizes="180x180" href="../apple-touch-icon.png"><link rel="icon" sizes="any" href="../favicon.ico"><link rel="manifest" href="../site.webmanifest"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.10/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.10/font.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints"><meta name="description" content="Data set containing clinical breakpoints to interpret MIC and disk diffusion to SIR values, according to international guidelines. This dataset contain breakpoints for humans, 7 different animal groups, and ECOFFs. <!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="96x96" href="../favicon-96x96.png"><link rel="icon" type="”image/svg+xml”" href="../favicon.svg"><link rel="apple-touch-icon" sizes="180x180" href="../apple-touch-icon.png"><link rel="icon" sizes="any" href="../favicon.ico"><link rel="manifest" href="../site.webmanifest"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.10/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.10/font.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Data Set with Clinical Breakpoints for SIR Interpretation — clinical_breakpoints"><meta name="description" content="Data set containing clinical breakpoints to interpret MIC and disk diffusion to SIR values, according to international guidelines. This data set contains breakpoints for humans, 7 different animal groups, and ECOFFs.
These breakpoints are currently implemented: These breakpoints are currently implemented:
For clinical microbiology: EUCAST 2011-2025 and CLSI 2011-2025; For clinical microbiology: EUCAST 2011-2025 and CLSI 2011-2025;
For veterinary microbiology: EUCAST 2021-2025 and CLSI 2019-2025; For veterinary microbiology: EUCAST 2021-2025 and CLSI 2019-2025;
For ECOFFs (Epidemiological Cut-off Values): EUCAST 2020-2025 and CLSI 2022-2025. For ECOFFs (Epidemiological Cut-off Values): EUCAST 2020-2025 and CLSI 2022-2025.
Use as.sir() to transform MICs or disks measurements to SIR values."><meta property="og:description" content="Data set containing clinical breakpoints to interpret MIC and disk diffusion to SIR values, according to international guidelines. This dataset contain breakpoints for humans, 7 different animal groups, and ECOFFs. Use as.sir() to transform MICs or disks measurements to SIR values."><meta property="og:description" content="Data set containing clinical breakpoints to interpret MIC and disk diffusion to SIR values, according to international guidelines. This data set contains breakpoints for humans, 7 different animal groups, and ECOFFs.
These breakpoints are currently implemented: These breakpoints are currently implemented:
For clinical microbiology: EUCAST 2011-2025 and CLSI 2011-2025; For clinical microbiology: EUCAST 2011-2025 and CLSI 2011-2025;
For veterinary microbiology: EUCAST 2021-2025 and CLSI 2019-2025; For veterinary microbiology: EUCAST 2021-2025 and CLSI 2019-2025;
@@ -21,7 +21,7 @@ Use as.sir() to transform MICs or disks measurements to SIR values."><meta prope
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@@ -64,7 +64,7 @@ Use as.sir() to transform MICs or disks measurements to SIR values."><meta prope
</div> </div>
<div class="ref-description section level2"> <div class="ref-description section level2">
<p>Data set containing clinical breakpoints to interpret MIC and disk diffusion to SIR values, according to international guidelines. This dataset contain breakpoints for humans, 7 different animal groups, and ECOFFs.</p> <p>Data set containing clinical breakpoints to interpret MIC and disk diffusion to SIR values, according to international guidelines. This data set contains breakpoints for humans, 7 different animal groups, and ECOFFs.</p>
<p>These breakpoints are currently implemented:</p><ul><li><p>For <strong>clinical microbiology</strong>: EUCAST 2011-2025 and CLSI 2011-2025;</p></li> <p>These breakpoints are currently implemented:</p><ul><li><p>For <strong>clinical microbiology</strong>: EUCAST 2011-2025 and CLSI 2011-2025;</p></li>
<li><p>For <strong>veterinary microbiology</strong>: EUCAST 2021-2025 and CLSI 2019-2025;</p></li> <li><p>For <strong>veterinary microbiology</strong>: EUCAST 2021-2025 and CLSI 2019-2025;</p></li>
<li><p>For <strong>ECOFFs</strong> (Epidemiological Cut-off Values): EUCAST 2020-2025 and CLSI 2022-2025.</p></li> <li><p>For <strong>ECOFFs</strong> (Epidemiological Cut-off Values): EUCAST 2020-2025 and CLSI 2022-2025.</p></li>

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Data set containing clinical breakpoints to interpret MIC and disk Data set containing clinical breakpoints to interpret MIC and disk
diffusion to SIR values, according to international guidelines. This diffusion to SIR values, according to international guidelines. This
dataset contain breakpoints for humans, 7 different animal groups, and data set contains breakpoints for humans, 7 different animal groups, and
ECOFFs. ECOFFs.
These breakpoints are currently implemented: These breakpoints are currently implemented:

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<img src="../logo.svg" class="logo" alt=""><h1>Data Set with 500 ESBL Isolates</h1>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/R/data.R" class="external-link"><code>R/data.R</code></a></small>
<div class="d-none name"><code>esbl_isolates.Rd</code></div>
</div>
<div class="ref-description section level2">
<p>A data set containing 500 microbial isolates with MIC values of common antibiotics and a binary <code>esbl</code> column for extended-spectrum beta-lactamase (ESBL) production. This data set contains randomised fictitious data but reflects reality and can be used to practise AMR-related machine learning, e.g., classification modelling with <a href="https://amr-for-r.org/articles/AMR_with_tidymodels.html">tidymodels</a>.</p>
</div>
<div class="section level2">
<h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
<div class="sourceCode"><pre class="sourceCode r"><code><span><span class="va">esbl_isolates</span></span></code></pre></div>
</div>
<div class="section level2">
<h2 id="format">Format<a class="anchor" aria-label="anchor" href="#format"></a></h2>
<p>A <a href="https://tibble.tidyverse.org/reference/tibble.html" class="external-link">tibble</a> with 500 observations and 19 variables:</p><ul><li><p><code>esbl</code><br> Logical indicator if the isolate is ESBL-producing</p></li>
<li><p><code>genus</code><br> Genus of the microorganism</p></li>
<li><p><code>AMC:COL</code><br> MIC values for 17 antimicrobial agents, transformed to class <code><a href="as.mic.html">mic</a></code> (see <code><a href="as.mic.html">as.mic()</a></code>)</p></li>
</ul></div>
<div class="section level2">
<h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
<p>See our <a href="amr-tidymodels.html">tidymodels integration</a> for an example using this data set.</p>
</div>
<div class="section level2">
<h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
<div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">esbl_isolates</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 500 × 19</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> esbl genus AMC AMP TZP CXM FOX CTX CAZ GEN TOB TMP SXT</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;lgl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mic&gt;</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> FALSE Esch… 32 32 4 64 64 8<span style="color: #555555;">.00</span> 8<span style="color: #555555;">.00</span> 1 1 16<span style="color: #555555;">.0</span> 20</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> FALSE Esch… 32 32 4 64 64 4<span style="color: #555555;">.00</span> 8<span style="color: #555555;">.00</span> 1 1 16<span style="color: #555555;">.0</span> 320</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> FALSE Esch… 4 2 64 8 4 8<span style="color: #555555;">.00</span> 0.12 16 16 0.5 20</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> FALSE Kleb… 32 32 16 64 64 8<span style="color: #555555;">.00</span> 8<span style="color: #555555;">.00</span> 1 1 0.5 20</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> FALSE Esch… 32 32 4 4 4 0.25 2<span style="color: #555555;">.00</span> 1 1 16<span style="color: #555555;">.0</span> 320</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> FALSE Citr… 32 32 16 64 64 64<span style="color: #555555;">.00</span> 32<span style="color: #555555;">.00</span> 1 1 0.5 20</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> FALSE Morg… 32 32 4 64 64 16<span style="color: #555555;">.00</span> 2<span style="color: #555555;">.00</span> 1 1 0.5 20</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> FALSE Prot… 16 32 4 1 4 8<span style="color: #555555;">.00</span> 0.12 1 1 16<span style="color: #555555;">.0</span> 320</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> FALSE Ente… 32 32 8 64 64 32<span style="color: #555555;">.00</span> 4<span style="color: #555555;">.00</span> 1 1 0.5 20</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> FALSE Citr… 32 32 32 64 64 8<span style="color: #555555;">.00</span> 64<span style="color: #555555;">.00</span> 1 1 16<span style="color: #555555;">.0</span> 320</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 490 more rows</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 6 more variables: NIT &lt;mic&gt;, FOS &lt;mic&gt;, CIP &lt;mic&gt;, IPM &lt;mic&gt;, MEM &lt;mic&gt;,</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># COL &lt;mic&gt;</span></span>
</code></pre></div>
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58
reference/esbl_isolates.md Normal file
View File

@@ -0,0 +1,58 @@
# Data Set with 500 ESBL Isolates
A data set containing 500 microbial isolates with MIC values of common
antibiotics and a binary `esbl` column for extended-spectrum
beta-lactamase (ESBL) production. This data set contains randomised
fictitious data but reflects reality and can be used to practise
AMR-related machine learning, e.g., classification modelling with
[tidymodels](https://amr-for-r.org/articles/AMR_with_tidymodels.html).
## Usage
``` r
esbl_isolates
```
## Format
A [tibble](https://tibble.tidyverse.org/reference/tibble.html) with 500
observations and 19 variables:
- `esbl`
Logical indicator if the isolate is ESBL-producing
- `genus`
Genus of the microorganism
- `AMC:COL`
MIC values for 17 antimicrobial agents, transformed to class
[`mic`](https://amr-for-r.org/reference/as.mic.md) (see
[`as.mic()`](https://amr-for-r.org/reference/as.mic.md))
## Details
See our [tidymodels
integration](https://amr-for-r.org/reference/amr-tidymodels.md) for an
example using this data set.
## Examples
``` r
esbl_isolates
#> # A tibble: 500 × 19
#> esbl genus AMC AMP TZP CXM FOX CTX CAZ GEN TOB TMP SXT
#> <lgl> <chr> <mic> <mic> <mic> <mic> <mic> <mic> <mic> <mic> <mic> <mic> <mic>
#> 1 FALSE Esch… 32 32 4 64 64 8.00 8.00 1 1 16.0 20
#> 2 FALSE Esch… 32 32 4 64 64 4.00 8.00 1 1 16.0 320
#> 3 FALSE Esch… 4 2 64 8 4 8.00 0.12 16 16 0.5 20
#> 4 FALSE Kleb… 32 32 16 64 64 8.00 8.00 1 1 0.5 20
#> 5 FALSE Esch… 32 32 4 4 4 0.25 2.00 1 1 16.0 320
#> 6 FALSE Citr… 32 32 16 64 64 64.00 32.00 1 1 0.5 20
#> 7 FALSE Morg… 32 32 4 64 64 16.00 2.00 1 1 0.5 20
#> 8 FALSE Prot… 16 32 4 1 4 8.00 0.12 1 1 16.0 320
#> 9 FALSE Ente… 32 32 8 64 64 32.00 4.00 1 1 0.5 20
#> 10 FALSE Citr… 32 32 32 64 64 8.00 64.00 1 1 16.0 320
#> # ℹ 490 more rows
#> # ℹ 6 more variables: NIT <mic>, FOS <mic>, CIP <mic>, IPM <mic>, MEM <mic>,
#> # COL <mic>
```

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@@ -9,7 +9,7 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
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reference/example_isolates.html
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@@ -7,7 +7,7 @@
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reference/first_isolate.html
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@@ -9,7 +9,7 @@
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116
reference/get_episode.html
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@@ -7,7 +7,7 @@
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<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
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@@ -154,28 +154,28 @@
<span class="r-in"><span><span class="va">df</span> <span class="op">&lt;-</span> <span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/sample.html" class="external-link">sample</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq_len</a></span><span class="op">(</span><span class="fl">2000</span><span class="op">)</span>, size <span class="op">=</span> <span class="fl">100</span><span class="op">)</span>, <span class="op">]</span></span></span> <span class="r-in"><span><span class="va">df</span> <span class="op">&lt;-</span> <span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/sample.html" class="external-link">sample</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq_len</a></span><span class="op">(</span><span class="fl">2000</span><span class="op">)</span>, size <span class="op">=</span> <span class="fl">100</span><span class="op">)</span>, <span class="op">]</span></span></span>
<span class="r-in"><span></span></span> <span class="r-in"><span></span></span>
<span class="r-in"><span><span class="fu">get_episode</span><span class="op">(</span><span class="va">df</span><span class="op">$</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">60</span><span class="op">)</span> <span class="co"># indices</span></span></span> <span class="r-in"><span><span class="fu">get_episode</span><span class="op">(</span><span class="va">df</span><span class="op">$</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">60</span><span class="op">)</span> <span class="co"># indices</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 17 19 32 7 48 16 36 11 41 30 43 42 3 37 6 42 16 46 12 6 38 15 31 23 44</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [1] 43 9 7 14 28 40 49 29 19 27 10 44 18 22 42 12 8 36 13 3 46 5 4 35 38</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [26] 35 42 21 10 21 18 22 9 29 40 8 22 14 31 47 18 26 28 18 25 20 11 49 8 27</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [26] 16 22 23 16 10 42 13 2 45 18 19 39 32 22 36 40 45 39 40 11 23 25 39 26 23</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [51] 50 23 46 3 27 6 31 1 33 10 23 31 11 20 46 13 4 24 4 27 8 48 16 2 20</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [51] 25 12 17 23 30 30 34 16 21 37 40 26 11 7 4 16 43 22 47 37 39 31 25 41 1</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [76] 35 31 19 33 34 16 14 33 17 46 24 15 17 7 9 39 14 50 5 12 2 45 35 8 28</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [76] 45 39 23 32 45 20 22 15 14 13 43 9 38 29 6 48 24 21 23 44 19 31 1 3 33</span>
<span class="r-in"><span><span class="fu">is_new_episode</span><span class="op">(</span><span class="va">df</span><span class="op">$</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">60</span><span class="op">)</span> <span class="co"># TRUE/FALSE</span></span></span> <span class="r-in"><span><span class="fu">is_new_episode</span><span class="op">(</span><span class="va">df</span><span class="op">$</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">60</span><span class="op">)</span> <span class="co"># TRUE/FALSE</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [13] TRUE TRUE TRUE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [13] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [25] TRUE TRUE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [25] TRUE TRUE FALSE TRUE FALSE FALSE FALSE FALSE TRUE TRUE FALSE FALSE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [37] FALSE TRUE FALSE TRUE FALSE TRUE TRUE FALSE TRUE TRUE FALSE TRUE</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [37] TRUE TRUE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE TRUE FALSE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [49] FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [49] TRUE FALSE FALSE FALSE TRUE FALSE TRUE FALSE TRUE FALSE TRUE TRUE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [61] FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE FALSE FALSE FALSE FALSE</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [61] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE TRUE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [73] FALSE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [73] FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE TRUE FALSE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [85] FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE TRUE FALSE FALSE</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [85] FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE FALSE FALSE FALSE FALSE</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [97] TRUE FALSE FALSE FALSE</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [97] FALSE FALSE FALSE TRUE</span>
<span class="r-in"><span></span></span> <span class="r-in"><span></span></span>
<span class="r-in"><span><span class="co"># filter on results from the third 60-day episode only, using base R</span></span></span> <span class="r-in"><span><span class="co"># filter on results from the third 60-day episode only, using base R</span></span></span>
<span class="r-in"><span><span class="va">df</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html" class="external-link">which</a></span><span class="op">(</span><span class="fu">get_episode</span><span class="op">(</span><span class="va">df</span><span class="op">$</span><span class="va">date</span>, <span class="fl">60</span><span class="op">)</span> <span class="op">==</span> <span class="fl">3</span><span class="op">)</span>, <span class="op">]</span></span></span> <span class="r-in"><span><span class="va">df</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html" class="external-link">which</a></span><span class="op">(</span><span class="fu">get_episode</span><span class="op">(</span><span class="va">df</span><span class="op">$</span><span class="va">date</span>, <span class="fl">60</span><span class="op">)</span> <span class="op">==</span> <span class="fl">3</span><span class="op">)</span>, <span class="op">]</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 2 × 46</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 2 × 46</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> date patient age gender ward mo PEN OXA FLC AMX </span> <span class="r-out co"><span class="r-pr">#&gt;</span> date patient age gender ward mo PEN OXA FLC AMX </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;date&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span> <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;date&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span> <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> 2002-07-23 F35553 51 M ICU <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>AURS <span style="color: #080808; background-color: #FF5F5F;"> R </span> <span style="color: #B2B2B2;"> NA</span> <span style="color: #080808; background-color: #5FD7AF;"> S </span> <span style="color: #080808; background-color: #FF5F5F;"> R </span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> 2002-11-04 304347 62 M Clinical <span style="color: #949494;">B_</span>STRPT<span style="color: #949494;">_</span>PNMN <span style="color: #080808; background-color: #5FD7AF;"> S </span> <span style="color: #B2B2B2;"> NA</span> <span style="color: #B2B2B2;"> NA</span> <span style="color: #080808; background-color: #5FD7AF;"> S </span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> 2002-07-23 F35553 51 M ICU <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>AURS <span style="color: #080808; background-color: #FF5F5F;"> R </span> <span style="color: #B2B2B2;"> NA</span> <span style="color: #080808; background-color: #5FD7AF;"> S </span> <span style="color: #080808; background-color: #FF5F5F;"> R </span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> 2002-10-18 E55128 57 F ICU <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>AURS <span style="color: #080808; background-color: #FF5F5F;"> R </span> <span style="color: #B2B2B2;"> NA</span> <span style="color: #080808; background-color: #5FD7AF;"> S </span> <span style="color: #080808; background-color: #FF5F5F;"> R </span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 36 more variables: AMC &lt;sir&gt;, AMP &lt;sir&gt;, TZP &lt;sir&gt;, CZO &lt;sir&gt;, FEP &lt;sir&gt;,</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 36 more variables: AMC &lt;sir&gt;, AMP &lt;sir&gt;, TZP &lt;sir&gt;, CZO &lt;sir&gt;, FEP &lt;sir&gt;,</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># CXM &lt;sir&gt;, FOX &lt;sir&gt;, CTX &lt;sir&gt;, CAZ &lt;sir&gt;, CRO &lt;sir&gt;, GEN &lt;sir&gt;,</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># CXM &lt;sir&gt;, FOX &lt;sir&gt;, CTX &lt;sir&gt;, CAZ &lt;sir&gt;, CRO &lt;sir&gt;, GEN &lt;sir&gt;,</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># TOB &lt;sir&gt;, AMK &lt;sir&gt;, KAN &lt;sir&gt;, TMP &lt;sir&gt;, SXT &lt;sir&gt;, NIT &lt;sir&gt;,</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># TOB &lt;sir&gt;, AMK &lt;sir&gt;, KAN &lt;sir&gt;, TMP &lt;sir&gt;, SXT &lt;sir&gt;, NIT &lt;sir&gt;,</span></span>
@@ -209,19 +209,19 @@
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html" class="external-link">arrange</a></span><span class="op">(</span><span class="va">patient</span>, <span class="va">condition</span>, <span class="va">date</span><span class="op">)</span></span></span> <span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html" class="external-link">arrange</a></span><span class="op">(</span><span class="va">patient</span>, <span class="va">condition</span>, <span class="va">date</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="op">}</span></span></span> <span class="r-in"><span><span class="op">}</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 100 × 4</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 100 × 4</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Groups: patient, condition [95]</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Groups: patient, condition [96]</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> patient date condition new_episode</span> <span class="r-out co"><span class="r-pr">#&gt;</span> patient date condition new_episode</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;date&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;lgl&gt;</span> </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;date&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;lgl&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 011307 2011-09-20 B TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 022060 2004-05-04 A TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 011307 2011-09-20 C TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 060287 2007-03-11 A TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> 021368 2016-03-25 A TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> 0E2483 2007-04-06 C TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 060287 2007-03-11 B TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 101305 2006-12-13 A TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 078381 2014-07-17 A TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 141061 2014-10-22 A TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 097186 2015-10-28 B TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 146F70 2009-08-14 A TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> 0DBB93 2003-10-02 A TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> 15D386 2004-08-01 B TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> 0DBF93 2015-12-03 C TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> 187841 2008-04-22 C TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 114570 2003-04-22 A TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 195736 2008-08-29 C TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 141061 2014-10-22 C TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 195736 2008-08-29 C FALSE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 90 more rows</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 90 more rows</span></span>
<span class="r-in"><span></span></span> <span class="r-in"><span></span></span>
<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span> <span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
@@ -235,19 +235,19 @@
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html" class="external-link">arrange</a></span><span class="op">(</span><span class="va">patient</span>, <span class="va">ward</span>, <span class="va">date</span><span class="op">)</span></span></span> <span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html" class="external-link">arrange</a></span><span class="op">(</span><span class="va">patient</span>, <span class="va">ward</span>, <span class="va">date</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="op">}</span></span></span> <span class="r-in"><span><span class="op">}</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 100 × 5</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 100 × 5</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Groups: ward, patient [93]</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Groups: ward, patient [91]</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> ward date patient new_index new_logical</span> <span class="r-out co"><span class="r-pr">#&gt;</span> ward date patient new_index new_logical</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;date&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;lgl&gt;</span> </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;date&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;lgl&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> Clinical 2011-09-20 011307 1 TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> ICU 2004-05-04 022060 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> Clinical 2011-09-20 011307 1 FALSE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> Clinical 2007-03-11 060287 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> Outpatient 2016-03-25 021368 1 TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> Clinical 2007-04-06 0E2483 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> Clinical 2007-03-11 060287 1 TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> Clinical 2006-12-13 101305 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> ICU 2014-07-17 078381 1 TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> Clinical 2014-10-22 141061 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> Clinical 2015-10-28 097186 1 TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> Clinical 2009-08-14 146F70 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> ICU 2003-10-02 0DBB93 1 TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> ICU 2004-08-01 15D386 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> ICU 2015-12-03 0DBF93 1 TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> Clinical 2008-04-22 187841 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> ICU 2003-04-22 114570 1 TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> Clinical 2008-08-29 195736 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> Clinical 2014-10-22 141061 1 TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> Clinical 2008-08-29 195736 1 FALSE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 90 more rows</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 90 more rows</span></span>
<span class="r-in"><span></span></span> <span class="r-in"><span></span></span>
<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span> <span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
@@ -263,9 +263,9 @@
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 3 × 5</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 3 × 5</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> ward n_patients n_episodes_365 n_episodes_60 n_episodes_30</span> <span class="r-out co"><span class="r-pr">#&gt;</span> ward n_patients n_episodes_365 n_episodes_60 n_episodes_30</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> Clinical 51 12 33 43</span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> Clinical 58 14 38 44</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> ICU 31 11 26 30</span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> ICU 26 7 20 23</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> Outpatient 11 8 11 11</span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> Outpatient 7 4 6 7</span>
<span class="r-in"><span></span></span> <span class="r-in"><span></span></span>
<span class="r-in"><span><span class="co"># grouping on patients and microorganisms leads to the same</span></span></span> <span class="r-in"><span><span class="co"># grouping on patients and microorganisms leads to the same</span></span></span>
<span class="r-in"><span><span class="co"># results as first_isolate() when using 'episode-based':</span></span></span> <span class="r-in"><span><span class="co"># results as first_isolate() when using 'episode-based':</span></span></span>
@@ -283,7 +283,7 @@
<span class="r-in"><span></span></span> <span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/identical.html" class="external-link">identical</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">y</span><span class="op">)</span></span></span> <span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/identical.html" class="external-link">identical</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">y</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="op">}</span></span></span> <span class="r-in"><span><span class="op">}</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] TRUE</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [1] FALSE</span>
<span class="r-in"><span></span></span> <span class="r-in"><span></span></span>
<span class="r-in"><span><span class="co"># but is_new_episode() has a lot more flexibility than first_isolate(),</span></span></span> <span class="r-in"><span><span class="co"># but is_new_episode() has a lot more flexibility than first_isolate(),</span></span></span>
<span class="r-in"><span><span class="co"># since you can now group on anything that seems relevant:</span></span></span> <span class="r-in"><span><span class="co"># since you can now group on anything that seems relevant:</span></span></span>
@@ -294,19 +294,19 @@
<span class="r-in"><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="fu"><a href="https://dplyr.tidyverse.org/reference/group_data.html" class="external-link">group_vars</a></span><span class="op">(</span><span class="va">.</span><span class="op">)</span>, <span class="va">flag_episode</span><span class="op">)</span></span></span> <span class="r-in"><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="fu"><a href="https://dplyr.tidyverse.org/reference/group_data.html" class="external-link">group_vars</a></span><span class="op">(</span><span class="va">.</span><span class="op">)</span>, <span class="va">flag_episode</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="op">}</span></span></span> <span class="r-in"><span><span class="op">}</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 100 × 4</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 100 × 4</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Groups: patient, mo, ward [95]</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Groups: patient, mo, ward [96]</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> patient mo ward flag_episode</span> <span class="r-out co"><span class="r-pr">#&gt;</span> patient mo ward flag_episode</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;lgl&gt;</span> </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;lgl&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 690B42 <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI ICU TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 917895 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>CPTS ICU TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 550406 <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI Outpatient TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 022060 <span style="color: #949494;">B_</span>ENTRBC<span style="color: #949494;">_</span>CLOC ICU TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> F86227 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>CONS Clinical TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> C36883 <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 859863 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>EPDR ICU TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 5DF436 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>AURS ICU TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 987C84 <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI Clinical TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 971739 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>CONS Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> E19440 <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI ICU TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 488175 <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> F42C5F <span style="color: #949494;">B_</span>MRGNL<span style="color: #949494;">_</span>MRGN Clinical TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> 5DB1C8 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>CPTS Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> F54261 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>AURS Clinical TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> BC9909 <span style="color: #949494;">B_</span>ENTRBC<span style="color: #949494;">_</span>CLOC Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 5D1690 <span style="color: #949494;">B_</span>ESCHR<span style="color: #949494;">_</span>COLI Outpatient TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 5B78D5 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>AURS Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 874171 <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>CONS Clinical TRUE </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 284FFF <span style="color: #949494;">B_</span>STPHY<span style="color: #949494;">_</span>EPDR Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 90 more rows</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 90 more rows</span></span>
<span class="r-in"><span><span class="co"># }</span></span></span> <span class="r-in"><span><span class="co"># }</span></span></span>
</code></pre></div> </code></pre></div>

114
reference/get_episode.md
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@@ -178,28 +178,28 @@ x
df <- example_isolates[sample(seq_len(2000), size = 100), ] df <- example_isolates[sample(seq_len(2000), size = 100), ]
get_episode(df$date, episode_days = 60) # indices get_episode(df$date, episode_days = 60) # indices
#> [1] 17 19 32 7 48 16 36 11 41 30 43 42 3 37 6 42 16 46 12 6 38 15 31 23 44 #> [1] 43 9 7 14 28 40 49 29 19 27 10 44 18 22 42 12 8 36 13 3 46 5 4 35 38
#> [26] 35 42 21 10 21 18 22 9 29 40 8 22 14 31 47 18 26 28 18 25 20 11 49 8 27 #> [26] 16 22 23 16 10 42 13 2 45 18 19 39 32 22 36 40 45 39 40 11 23 25 39 26 23
#> [51] 50 23 46 3 27 6 31 1 33 10 23 31 11 20 46 13 4 24 4 27 8 48 16 2 20 #> [51] 25 12 17 23 30 30 34 16 21 37 40 26 11 7 4 16 43 22 47 37 39 31 25 41 1
#> [76] 35 31 19 33 34 16 14 33 17 46 24 15 17 7 9 39 14 50 5 12 2 45 35 8 28 #> [76] 45 39 23 32 45 20 22 15 14 13 43 9 38 29 6 48 24 21 23 44 19 31 1 3 33
is_new_episode(df$date, episode_days = 60) # TRUE/FALSE is_new_episode(df$date, episode_days = 60) # TRUE/FALSE
#> [1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE #> [1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
#> [13] TRUE TRUE TRUE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE #> [13] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
#> [25] TRUE TRUE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE #> [25] TRUE TRUE FALSE TRUE FALSE FALSE FALSE FALSE TRUE TRUE FALSE FALSE
#> [37] FALSE TRUE FALSE TRUE FALSE TRUE TRUE FALSE TRUE TRUE FALSE TRUE #> [37] TRUE TRUE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE TRUE FALSE
#> [49] FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE #> [49] TRUE FALSE FALSE FALSE TRUE FALSE TRUE FALSE TRUE FALSE TRUE TRUE
#> [61] FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE FALSE FALSE FALSE FALSE #> [61] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE TRUE
#> [73] FALSE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE #> [73] FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE TRUE FALSE
#> [85] FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE TRUE FALSE FALSE #> [85] FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE FALSE FALSE FALSE FALSE
#> [97] TRUE FALSE FALSE FALSE #> [97] FALSE FALSE FALSE TRUE
# filter on results from the third 60-day episode only, using base R # filter on results from the third 60-day episode only, using base R
df[which(get_episode(df$date, 60) == 3), ] df[which(get_episode(df$date, 60) == 3), ]
#> # A tibble: 2 × 46 #> # A tibble: 2 × 46
#> date patient age gender ward mo PEN OXA FLC AMX #> date patient age gender ward mo PEN OXA FLC AMX
#> <date> <chr> <dbl> <chr> <chr> <mo> <sir> <sir> <sir> <sir> #> <date> <chr> <dbl> <chr> <chr> <mo> <sir> <sir> <sir> <sir>
#> 1 2002-07-23 F35553 51 M ICU B_STPHY_AURS R NA S R #> 1 2002-11-04 304347 62 M Clinical B_STRPT_PNMN S NA NA S
#> 2 2002-07-23 F35553 51 M ICU B_STPHY_AURS R NA S R #> 2 2002-10-18 E55128 57 F ICU B_STPHY_AURS R NA S R
#> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>, #> # ℹ 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>, FEP <sir>,
#> # CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>, #> # CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>, GEN <sir>,
#> # TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, #> # TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>,
@@ -233,19 +233,19 @@ if (require("dplyr")) {
arrange(patient, condition, date) arrange(patient, condition, date)
} }
#> # A tibble: 100 × 4 #> # A tibble: 100 × 4
#> # Groups: patient, condition [95] #> # Groups: patient, condition [96]
#> patient date condition new_episode #> patient date condition new_episode
#> <chr> <date> <chr> <lgl> #> <chr> <date> <chr> <lgl>
#> 1 011307 2011-09-20 B TRUE #> 1 022060 2004-05-04 A TRUE
#> 2 011307 2011-09-20 C TRUE #> 2 060287 2007-03-11 A TRUE
#> 3 021368 2016-03-25 A TRUE #> 3 0E2483 2007-04-06 C TRUE
#> 4 060287 2007-03-11 B TRUE #> 4 101305 2006-12-13 A TRUE
#> 5 078381 2014-07-17 A TRUE #> 5 141061 2014-10-22 A TRUE
#> 6 097186 2015-10-28 B TRUE #> 6 146F70 2009-08-14 A TRUE
#> 7 0DBB93 2003-10-02 A TRUE #> 7 15D386 2004-08-01 B TRUE
#> 8 0DBF93 2015-12-03 C TRUE #> 8 187841 2008-04-22 C TRUE
#> 9 114570 2003-04-22 A TRUE #> 9 195736 2008-08-29 C TRUE
#> 10 141061 2014-10-22 C TRUE #> 10 195736 2008-08-29 C FALSE
#> # ℹ 90 more rows #> # ℹ 90 more rows
if (require("dplyr")) { if (require("dplyr")) {
@@ -259,19 +259,19 @@ if (require("dplyr")) {
arrange(patient, ward, date) arrange(patient, ward, date)
} }
#> # A tibble: 100 × 5 #> # A tibble: 100 × 5
#> # Groups: ward, patient [93] #> # Groups: ward, patient [91]
#> ward date patient new_index new_logical #> ward date patient new_index new_logical
#> <chr> <date> <chr> <int> <lgl> #> <chr> <date> <chr> <int> <lgl>
#> 1 Clinical 2011-09-20 011307 1 TRUE #> 1 ICU 2004-05-04 022060 1 TRUE
#> 2 Clinical 2011-09-20 011307 1 FALSE #> 2 Clinical 2007-03-11 060287 1 TRUE
#> 3 Outpatient 2016-03-25 021368 1 TRUE #> 3 Clinical 2007-04-06 0E2483 1 TRUE
#> 4 Clinical 2007-03-11 060287 1 TRUE #> 4 Clinical 2006-12-13 101305 1 TRUE
#> 5 ICU 2014-07-17 078381 1 TRUE #> 5 Clinical 2014-10-22 141061 1 TRUE
#> 6 Clinical 2015-10-28 097186 1 TRUE #> 6 Clinical 2009-08-14 146F70 1 TRUE
#> 7 ICU 2003-10-02 0DBB93 1 TRUE #> 7 ICU 2004-08-01 15D386 1 TRUE
#> 8 ICU 2015-12-03 0DBF93 1 TRUE #> 8 Clinical 2008-04-22 187841 1 TRUE
#> 9 ICU 2003-04-22 114570 1 TRUE #> 9 Clinical 2008-08-29 195736 1 TRUE
#> 10 Clinical 2014-10-22 141061 1 TRUE #> 10 Clinical 2008-08-29 195736 1 FALSE
#> # ℹ 90 more rows #> # ℹ 90 more rows
if (require("dplyr")) { if (require("dplyr")) {
@@ -287,9 +287,9 @@ if (require("dplyr")) {
#> # A tibble: 3 × 5 #> # A tibble: 3 × 5
#> ward n_patients n_episodes_365 n_episodes_60 n_episodes_30 #> ward n_patients n_episodes_365 n_episodes_60 n_episodes_30
#> <chr> <int> <int> <int> <int> #> <chr> <int> <int> <int> <int>
#> 1 Clinical 51 12 33 43 #> 1 Clinical 58 14 38 44
#> 2 ICU 31 11 26 30 #> 2 ICU 26 7 20 23
#> 3 Outpatient 11 8 11 11 #> 3 Outpatient 7 4 6 7
# grouping on patients and microorganisms leads to the same # grouping on patients and microorganisms leads to the same
# results as first_isolate() when using 'episode-based': # results as first_isolate() when using 'episode-based':
@@ -307,7 +307,7 @@ if (require("dplyr")) {
identical(x, y) identical(x, y)
} }
#> [1] TRUE #> [1] FALSE
# but is_new_episode() has a lot more flexibility than first_isolate(), # but is_new_episode() has a lot more flexibility than first_isolate(),
# since you can now group on anything that seems relevant: # since you can now group on anything that seems relevant:
@@ -318,19 +318,19 @@ if (require("dplyr")) {
select(group_vars(.), flag_episode) select(group_vars(.), flag_episode)
} }
#> # A tibble: 100 × 4 #> # A tibble: 100 × 4
#> # Groups: patient, mo, ward [95] #> # Groups: patient, mo, ward [96]
#> patient mo ward flag_episode #> patient mo ward flag_episode
#> <chr> <mo> <chr> <lgl> #> <chr> <mo> <chr> <lgl>
#> 1 690B42 B_ESCHR_COLI ICU TRUE #> 1 917895 B_STPHY_CPTS ICU TRUE
#> 2 550406 B_ESCHR_COLI Outpatient TRUE #> 2 022060 B_ENTRBC_CLOC ICU TRUE
#> 3 F86227 B_STPHY_CONS Clinical TRUE #> 3 C36883 B_ESCHR_COLI Clinical TRUE
#> 4 859863 B_STPHY_EPDR ICU TRUE #> 4 5DF436 B_STPHY_AURS ICU TRUE
#> 5 987C84 B_ESCHR_COLI Clinical TRUE #> 5 971739 B_STPHY_CONS Clinical TRUE
#> 6 E19440 B_ESCHR_COLI ICU TRUE #> 6 488175 B_ESCHR_COLI Clinical TRUE
#> 7 F42C5F B_MRGNL_MRGN Clinical TRUE #> 7 5DB1C8 B_STPHY_CPTS Clinical TRUE
#> 8 F54261 B_STPHY_AURS Clinical TRUE #> 8 BC9909 B_ENTRBC_CLOC Clinical TRUE
#> 9 5D1690 B_ESCHR_COLI Outpatient TRUE #> 9 5B78D5 B_STPHY_AURS Clinical TRUE
#> 10 874171 B_STPHY_CONS Clinical TRUE #> 10 284FFF B_STPHY_EPDR Clinical TRUE
#> # ℹ 90 more rows #> # ℹ 90 more rows
# } # }
``` ```

2
reference/ggplot_pca.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
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2
reference/ggplot_sir.html
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@@ -7,7 +7,7 @@
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2
reference/guess_ab_col.html
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@@ -7,7 +7,7 @@
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<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
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9
reference/index.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
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@@ -409,6 +409,13 @@
</dt> </dt>
<dd>Data Set with 2 000 Example Isolates</dd> <dd>Data Set with 2 000 Example Isolates</dd>
<dt>
<code><a href="esbl_isolates.html">esbl_isolates</a></code>
</dt>
<dd>Data Set with 500 ESBL Isolates</dd>
<dt> <dt>
<code><a href="microorganisms.codes.html">microorganisms.codes</a></code> <code><a href="microorganisms.codes.html">microorganisms.codes</a></code>

2
reference/index.md
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@@ -391,6 +391,8 @@ information about how to work with functions in this package.
: Data Set with Clinical Breakpoints for SIR Interpretation : Data Set with Clinical Breakpoints for SIR Interpretation
- [`example_isolates`](https://amr-for-r.org/reference/example_isolates.md) - [`example_isolates`](https://amr-for-r.org/reference/example_isolates.md)
: Data Set with 2 000 Example Isolates : Data Set with 2 000 Example Isolates
- [`esbl_isolates`](https://amr-for-r.org/reference/esbl_isolates.md) :
Data Set with 500 ESBL Isolates
- [`microorganisms.codes`](https://amr-for-r.org/reference/microorganisms.codes.md) - [`microorganisms.codes`](https://amr-for-r.org/reference/microorganisms.codes.md)
: Data Set with 6 036 Common Microorganism Codes : Data Set with 6 036 Common Microorganism Codes
- [`microorganisms.groups`](https://amr-for-r.org/reference/microorganisms.groups.md) - [`microorganisms.groups`](https://amr-for-r.org/reference/microorganisms.groups.md)

2
reference/intrinsic_resistant.html
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@@ -7,7 +7,7 @@
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@@ -7,7 +7,7 @@
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2
reference/join.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
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2
reference/key_antimicrobials.html
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@@ -7,7 +7,7 @@
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6
reference/kurtosis.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
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@@ -91,9 +91,9 @@
<div class="section level2"> <div class="section level2">
<h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2> <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
<div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="fu">kurtosis</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="fl">10000</span><span class="op">)</span><span class="op">)</span></span></span> <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="fu">kurtosis</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="fl">10000</span><span class="op">)</span><span class="op">)</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 3.071712</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [1] 3.069947</span>
<span class="r-in"><span><span class="fu">kurtosis</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="fl">10000</span><span class="op">)</span>, excess <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> <span class="r-in"><span><span class="fu">kurtosis</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="fl">10000</span><span class="op">)</span>, excess <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] -0.02774835</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [1] -0.02599697</span>
</code></pre></div> </code></pre></div>
</div> </div>
</main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2> </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>

4
reference/kurtosis.md
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@@ -45,7 +45,7 @@ kurtosis(x, na.rm = FALSE, excess = FALSE)
``` r ``` r
kurtosis(rnorm(10000)) kurtosis(rnorm(10000))
#> [1] 3.071712 #> [1] 3.069947
kurtosis(rnorm(10000), excess = TRUE) kurtosis(rnorm(10000), excess = TRUE)
#> [1] -0.02774835 #> [1] -0.02599697
``` ```

4
reference/like.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -107,6 +107,8 @@
<h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2> <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
<div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># data.table has a more limited version of %like%, so unload it:</span></span></span> <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># data.table has a more limited version of %like%, so unload it:</span></span></span>
<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/try.html" class="external-link">try</a></span><span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/detach.html" class="external-link">detach</a></span><span class="op">(</span><span class="st">"package:data.table"</span>, unload <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>, silent <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> <span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/try.html" class="external-link">try</a></span><span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/detach.html" class="external-link">detach</a></span><span class="op">(</span><span class="st">"package:data.table"</span>, unload <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>, silent <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span>
<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>‘data.table’ namespace cannot be unloaded:</span>
<span class="r-wrn co"><span class="r-pr">#&gt;</span> namespace ‘data.table’ is imported by ‘prodlim’ so cannot be unloaded</span>
<span class="r-in"><span></span></span> <span class="r-in"><span></span></span>
<span class="r-in"><span><span class="va">a</span> <span class="op">&lt;-</span> <span class="st">"This is a test"</span></span></span> <span class="r-in"><span><span class="va">a</span> <span class="op">&lt;-</span> <span class="st">"This is a test"</span></span></span>
<span class="r-in"><span><span class="va">b</span> <span class="op">&lt;-</span> <span class="st">"TEST"</span></span></span> <span class="r-in"><span><span class="va">b</span> <span class="op">&lt;-</span> <span class="st">"TEST"</span></span></span>

2
reference/like.md
View File

@@ -88,6 +88,8 @@ inserted text will be iterated over `%like%` -\> `%unlike%` -\>
``` r ``` r
# data.table has a more limited version of %like%, so unload it: # data.table has a more limited version of %like%, so unload it:
try(detach("package:data.table", unload = TRUE), silent = TRUE) try(detach("package:data.table", unload = TRUE), silent = TRUE)
#> Warning: ‘data.table’ namespace cannot be unloaded:
#> namespace ‘data.table’ is imported by ‘prodlim’ so cannot be unloaded
a <- "This is a test" a <- "This is a test"
b <- "TEST" b <- "TEST"

2
reference/mdro.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

88
reference/mean_amr_distance.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -110,30 +110,30 @@
<div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">sir</span> <span class="op">&lt;-</span> <span class="fu"><a href="random.html">random_sir</a></span><span class="op">(</span><span class="fl">10</span><span class="op">)</span></span></span> <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">sir</span> <span class="op">&lt;-</span> <span class="fu"><a href="random.html">random_sir</a></span><span class="op">(</span><span class="fl">10</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="va">sir</span></span></span> <span class="r-in"><span><span class="va">sir</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Class 'sir'</span> <span class="r-out co"><span class="r-pr">#&gt;</span> Class 'sir'</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] I I R I R S S S I S</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [1] R R I R I I S R S I</span>
<span class="r-in"><span><span class="fu">mean_amr_distance</span><span class="op">(</span><span class="va">sir</span><span class="op">)</span></span></span> <span class="r-in"><span><span class="fu">mean_amr_distance</span><span class="op">(</span><span class="va">sir</span><span class="op">)</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] -0.4743416 -0.4743416 1.8973666 -0.4743416 1.8973666 -0.4743416</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [1] 1.1618950 1.1618950 -0.7745967 1.1618950 -0.7745967 -0.7745967</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [7] -0.4743416 -0.4743416 -0.4743416 -0.4743416</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [7] -0.7745967 1.1618950 -0.7745967 -0.7745967</span>
<span class="r-in"><span></span></span> <span class="r-in"><span></span></span>
<span class="r-in"><span><span class="va">mic</span> <span class="op">&lt;-</span> <span class="fu"><a href="random.html">random_mic</a></span><span class="op">(</span><span class="fl">10</span><span class="op">)</span></span></span> <span class="r-in"><span><span class="va">mic</span> <span class="op">&lt;-</span> <span class="fu"><a href="random.html">random_mic</a></span><span class="op">(</span><span class="fl">10</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="va">mic</span></span></span> <span class="r-in"><span><span class="va">mic</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Class 'mic'</span> <span class="r-out co"><span class="r-pr">#&gt;</span> Class 'mic'</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.004 2 0.002 0.0001 0.004 0.002 &gt;=4 0.0002 0.032 0.004 </span> <span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.032 0.5 1 &gt;=8 4 0.016 &gt;=8 1 0.004 0.008</span>
<span class="r-in"><span><span class="fu">mean_amr_distance</span><span class="op">(</span><span class="va">mic</span><span class="op">)</span></span></span> <span class="r-in"><span><span class="fu">mean_amr_distance</span><span class="op">(</span><span class="va">mic</span><span class="op">)</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] -0.2047915 1.5799751 -0.4038557 -1.2641969 -0.2047915 -0.4038557</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [1] -0.7311752 0.2104422 0.4478776 1.1601837 0.9227483 -0.9686106</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [7] 1.7790393 -1.0651327 0.3924011 -0.2047915</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [7] 1.1601837 0.4478776 -1.4434813 -1.2060459</span>
<span class="r-in"><span><span class="co"># equal to the Z-score of their log2:</span></span></span> <span class="r-in"><span><span class="co"># equal to the Z-score of their log2:</span></span></span>
<span class="r-in"><span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log2</a></span><span class="op">(</span><span class="va">mic</span><span class="op">)</span> <span class="op">-</span> <span class="fu"><a href="https://rdrr.io/r/base/mean.html" class="external-link">mean</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log2</a></span><span class="op">(</span><span class="va">mic</span><span class="op">)</span><span class="op">)</span><span class="op">)</span> <span class="op">/</span> <span class="fu"><a href="https://rdrr.io/r/stats/sd.html" class="external-link">sd</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log2</a></span><span class="op">(</span><span class="va">mic</span><span class="op">)</span><span class="op">)</span></span></span> <span class="r-in"><span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log2</a></span><span class="op">(</span><span class="va">mic</span><span class="op">)</span> <span class="op">-</span> <span class="fu"><a href="https://rdrr.io/r/base/mean.html" class="external-link">mean</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log2</a></span><span class="op">(</span><span class="va">mic</span><span class="op">)</span><span class="op">)</span><span class="op">)</span> <span class="op">/</span> <span class="fu"><a href="https://rdrr.io/r/stats/sd.html" class="external-link">sd</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log2</a></span><span class="op">(</span><span class="va">mic</span><span class="op">)</span><span class="op">)</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] -0.2047915 1.5799751 -0.4038557 -1.2641969 -0.2047915 -0.4038557</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [1] -0.7311752 0.2104422 0.4478776 1.1601837 0.9227483 -0.9686106</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [7] 1.7790393 -1.0651327 0.3924011 -0.2047915</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [7] 1.1601837 0.4478776 -1.4434813 -1.2060459</span>
<span class="r-in"><span></span></span> <span class="r-in"><span></span></span>
<span class="r-in"><span><span class="va">disk</span> <span class="op">&lt;-</span> <span class="fu"><a href="random.html">random_disk</a></span><span class="op">(</span><span class="fl">10</span><span class="op">)</span></span></span> <span class="r-in"><span><span class="va">disk</span> <span class="op">&lt;-</span> <span class="fu"><a href="random.html">random_disk</a></span><span class="op">(</span><span class="fl">10</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="va">disk</span></span></span> <span class="r-in"><span><span class="va">disk</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Class 'disk'</span> <span class="r-out co"><span class="r-pr">#&gt;</span> Class 'disk'</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 43 12 28 32 22 31 35 25 43 35</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [1] 50 49 38 33 31 17 42 43 46 37</span>
<span class="r-in"><span><span class="fu">mean_amr_distance</span><span class="op">(</span><span class="va">disk</span><span class="op">)</span></span></span> <span class="r-in"><span><span class="fu">mean_amr_distance</span><span class="op">(</span><span class="va">disk</span><span class="op">)</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 1.30998909 -1.96498364 -0.27467513 0.14790199 -0.90854082 0.04225771</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [1] 1.15131286 1.05032051 -0.06059541 -0.56555720 -0.76754191 -2.18143490</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [7] 0.46483484 -0.59160798 1.30998909 0.46483484</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [7] 0.34337401 0.44436637 0.74734344 -0.16158777</span>
<span class="r-in"><span></span></span> <span class="r-in"><span></span></span>
<span class="r-in"><span><span class="va">y</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> <span class="r-in"><span><span class="va">y</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>
<span class="r-in"><span> id <span class="op">=</span> <span class="va">LETTERS</span><span class="op">[</span><span class="fl">1</span><span class="op">:</span><span class="fl">10</span><span class="op">]</span>,</span></span> <span class="r-in"><span> id <span class="op">=</span> <span class="va">LETTERS</span><span class="op">[</span><span class="fl">1</span><span class="op">:</span><span class="fl">10</span><span class="op">]</span>,</span></span>
@@ -144,35 +144,35 @@
<span class="r-in"><span><span class="op">)</span></span></span> <span class="r-in"><span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="va">y</span></span></span> <span class="r-in"><span><span class="va">y</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> id amox cipr gent tobr</span> <span class="r-out co"><span class="r-pr">#&gt;</span> id amox cipr gent tobr</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1 A S 31 2 &gt;=16</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 1 A I 27 &gt;=2 8</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2 B S 27 &lt;=1 8</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 2 B S 28 1 8</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3 C R 25 2 4</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 3 C R 33 1 8</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 4 D R 25 &lt;=1 2</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 4 D R 32 1 16</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 5 E I 31 &lt;=1 2</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 5 E I 25 0.5 16</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 6 F S 32 &lt;=1 8</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 6 F I 19 0.5 8</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 7 G I 29 2 2</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 7 G S 23 0.5 16</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 8 H S 18 &lt;=1 4</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 8 H R 27 0.5 8</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 9 I S 28 &lt;=1 4</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 9 I S 29 1 8</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 10 J R 17 &lt;=1 2</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 10 J R 32 0.5 16</span>
<span class="r-in"><span><span class="fu">mean_amr_distance</span><span class="op">(</span><span class="va">y</span><span class="op">)</span></span></span> <span class="r-in"><span><span class="fu">mean_amr_distance</span><span class="op">(</span><span class="va">y</span><span class="op">)</span></span></span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #0000BB;">ℹ Calculating mean AMR distance based on columns "amox", "cipr", "gent",</span></span> <span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #0000BB;">ℹ Calculating mean AMR distance based on columns "amox", "cipr", "gent",</span></span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #0000BB;"> and "tobr"</span></span> <span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #0000BB;"> and "tobr"</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.90606144 -0.03989270 0.66241774 -0.09230226 -0.32300020 0.19914999</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.08471751 -0.21572693 0.55391610 0.98093500 -0.26046456 -1.08721162</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> [7] 0.09893189 -0.70734036 -0.22925499 -0.47477055</span> <span class="r-out co"><span class="r-pr">#&gt;</span> [7] -0.37467261 -0.14625651 -0.15862291 0.62338653</span>
<span class="r-in"><span><span class="va">y</span><span class="op">$</span><span class="va">amr_distance</span> <span class="op">&lt;-</span> <span class="fu">mean_amr_distance</span><span class="op">(</span><span class="va">y</span>, <span class="fu"><a href="as.mic.html">is.mic</a></span><span class="op">(</span><span class="va">y</span><span class="op">)</span><span class="op">)</span></span></span> <span class="r-in"><span><span class="va">y</span><span class="op">$</span><span class="va">amr_distance</span> <span class="op">&lt;-</span> <span class="fu">mean_amr_distance</span><span class="op">(</span><span class="va">y</span>, <span class="fu"><a href="as.mic.html">is.mic</a></span><span class="op">(</span><span class="va">y</span><span class="op">)</span><span class="op">)</span></span></span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #0000BB;">ℹ Calculating mean AMR distance based on columns "gent" and "tobr"</span></span> <span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #0000BB;">ℹ Calculating mean AMR distance based on columns "gent" and "tobr"</span></span>
<span class="r-in"><span><span class="va">y</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/order.html" class="external-link">order</a></span><span class="op">(</span><span class="va">y</span><span class="op">$</span><span class="va">amr_distance</span><span class="op">)</span>, <span class="op">]</span></span></span> <span class="r-in"><span><span class="va">y</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/order.html" class="external-link">order</a></span><span class="op">(</span><span class="va">y</span><span class="op">$</span><span class="va">amr_distance</span><span class="op">)</span>, <span class="op">]</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> id amox cipr gent tobr amr_distance</span> <span class="r-out co"><span class="r-pr">#&gt;</span> id amox cipr gent tobr amr_distance</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 4 D R 25 &lt;=1 2 -0.7848712</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 6 F I 19 0.5 8 -0.8163565</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 5 E I 31 &lt;=1 2 -0.7848712</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 8 H R 27 0.5 8 -0.8163565</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 10 J R 17 &lt;=1 2 -0.7848712</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 2 B S 28 1 8 -0.1012596</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 8 H S 18 &lt;=1 4 -0.3105295</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 3 C R 33 1 8 -0.1012596</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 9 I S 28 &lt;=1 4 -0.3105295</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 9 I S 29 1 8 -0.1012596</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2 B S 27 &lt;=1 8 0.1638121</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 5 E I 25 0.5 16 0.1518893</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 6 F S 32 &lt;=1 8 0.1638121</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 7 G S 23 0.5 16 0.1518893</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 7 G I 29 2 2 0.2502272</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 10 J R 32 0.5 16 0.1518893</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3 C R 25 2 4 0.7245688</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 1 A I 27 &gt;=2 8 0.6138374</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1 A S 31 2 &gt;=16 1.6732521</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 4 D R 32 1 16 0.8669863</span>
<span class="r-in"><span></span></span> <span class="r-in"><span></span></span>
<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span> <span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
<span class="r-in"><span> <span class="va">y</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span> <span class="r-in"><span> <span class="va">y</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
@@ -185,16 +185,16 @@
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #0000BB;">ℹ Calculating mean AMR distance based on columns "amox", "cipr", "gent",</span></span> <span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #0000BB;">ℹ Calculating mean AMR distance based on columns "amox", "cipr", "gent",</span></span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #0000BB;"> and "tobr"</span></span> <span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #0000BB;"> and "tobr"</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> id amox cipr gent tobr amr_distance check_id_C</span> <span class="r-out co"><span class="r-pr">#&gt;</span> id amox cipr gent tobr amr_distance check_id_C</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1 C R 25 2 4 0.66241774 0.0000000</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 1 C R 33 1 8 0.55391610 0.00000000</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2 A S 31 2 &gt;=16 0.90606144 0.2436437</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 2 J R 32 0.5 16 0.62338653 0.06947042</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3 F S 32 &lt;=1 8 0.19914999 0.4632678</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 3 D R 32 1 16 0.98093500 0.42701889</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 4 G I 29 2 2 0.09893189 0.5634858</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 4 A I 27 &gt;=2 8 0.08471751 0.46919859</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 5 B S 27 &lt;=1 8 -0.03989270 0.7023104</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 5 H R 27 0.5 8 -0.14625651 0.70017262</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 6 D R 25 &lt;=1 2 -0.09230226 0.7547200</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 6 I S 29 1 8 -0.15862291 0.71253901</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 7 I S 28 &lt;=1 4 -0.22925499 0.8916727</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 7 B S 28 1 8 -0.21572693 0.76964304</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 8 E I 31 &lt;=1 2 -0.32300020 0.9854179</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 8 E I 25 0.5 16 -0.26046456 0.81438066</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 9 J R 17 &lt;=1 2 -0.47477055 1.1371883</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 9 G S 23 0.5 16 -0.37467261 0.92858871</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 10 H S 18 &lt;=1 4 -0.70734036 1.3697581</span> <span class="r-out co"><span class="r-pr">#&gt;</span> 10 F I 19 0.5 8 -1.08721162 1.64112773</span>
<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span> <span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
<span class="r-in"><span> <span class="co"># support for groups</span></span></span> <span class="r-in"><span> <span class="co"># support for groups</span></span></span>
<span class="r-in"><span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span> <span class="r-in"><span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>

86
reference/mean_amr_distance.md
View File

@@ -85,30 +85,30 @@ suspicious.
sir <- random_sir(10) sir <- random_sir(10)
sir sir
#> Class 'sir' #> Class 'sir'
#> [1] I I R I R S S S I S #> [1] R R I R I I S R S I
mean_amr_distance(sir) mean_amr_distance(sir)
#> [1] -0.4743416 -0.4743416 1.8973666 -0.4743416 1.8973666 -0.4743416 #> [1] 1.1618950 1.1618950 -0.7745967 1.1618950 -0.7745967 -0.7745967
#> [7] -0.4743416 -0.4743416 -0.4743416 -0.4743416 #> [7] -0.7745967 1.1618950 -0.7745967 -0.7745967
mic <- random_mic(10) mic <- random_mic(10)
mic mic
#> Class 'mic' #> Class 'mic'
#> [1] 0.004 2 0.002 0.0001 0.004 0.002 >=4 0.0002 0.032 0.004 #> [1] 0.032 0.5 1 >=8 4 0.016 >=8 1 0.004 0.008
mean_amr_distance(mic) mean_amr_distance(mic)
#> [1] -0.2047915 1.5799751 -0.4038557 -1.2641969 -0.2047915 -0.4038557 #> [1] -0.7311752 0.2104422 0.4478776 1.1601837 0.9227483 -0.9686106
#> [7] 1.7790393 -1.0651327 0.3924011 -0.2047915 #> [7] 1.1601837 0.4478776 -1.4434813 -1.2060459
# equal to the Z-score of their log2: # equal to the Z-score of their log2:
(log2(mic) - mean(log2(mic))) / sd(log2(mic)) (log2(mic) - mean(log2(mic))) / sd(log2(mic))
#> [1] -0.2047915 1.5799751 -0.4038557 -1.2641969 -0.2047915 -0.4038557 #> [1] -0.7311752 0.2104422 0.4478776 1.1601837 0.9227483 -0.9686106
#> [7] 1.7790393 -1.0651327 0.3924011 -0.2047915 #> [7] 1.1601837 0.4478776 -1.4434813 -1.2060459
disk <- random_disk(10) disk <- random_disk(10)
disk disk
#> Class 'disk' #> Class 'disk'
#> [1] 43 12 28 32 22 31 35 25 43 35 #> [1] 50 49 38 33 31 17 42 43 46 37
mean_amr_distance(disk) mean_amr_distance(disk)
#> [1] 1.30998909 -1.96498364 -0.27467513 0.14790199 -0.90854082 0.04225771 #> [1] 1.15131286 1.05032051 -0.06059541 -0.56555720 -0.76754191 -2.18143490
#> [7] 0.46483484 -0.59160798 1.30998909 0.46483484 #> [7] 0.34337401 0.44436637 0.74734344 -0.16158777
y <- data.frame( y <- data.frame(
id = LETTERS[1:10], id = LETTERS[1:10],
@@ -119,35 +119,35 @@ y <- data.frame(
) )
y y
#> id amox cipr gent tobr #> id amox cipr gent tobr
#> 1 A S 31 2 >=16 #> 1 A I 27 >=2 8
#> 2 B S 27 <=1 8 #> 2 B S 28 1 8
#> 3 C R 25 2 4 #> 3 C R 33 1 8
#> 4 D R 25 <=1 2 #> 4 D R 32 1 16
#> 5 E I 31 <=1 2 #> 5 E I 25 0.5 16
#> 6 F S 32 <=1 8 #> 6 F I 19 0.5 8
#> 7 G I 29 2 2 #> 7 G S 23 0.5 16
#> 8 H S 18 <=1 4 #> 8 H R 27 0.5 8
#> 9 I S 28 <=1 4 #> 9 I S 29 1 8
#> 10 J R 17 <=1 2 #> 10 J R 32 0.5 16
mean_amr_distance(y) mean_amr_distance(y)
#> ℹ Calculating mean AMR distance based on columns "amox", "cipr", "gent", #> ℹ Calculating mean AMR distance based on columns "amox", "cipr", "gent",
#> and "tobr" #> and "tobr"
#> [1] 0.90606144 -0.03989270 0.66241774 -0.09230226 -0.32300020 0.19914999 #> [1] 0.08471751 -0.21572693 0.55391610 0.98093500 -0.26046456 -1.08721162
#> [7] 0.09893189 -0.70734036 -0.22925499 -0.47477055 #> [7] -0.37467261 -0.14625651 -0.15862291 0.62338653
y$amr_distance <- mean_amr_distance(y, is.mic(y)) y$amr_distance <- mean_amr_distance(y, is.mic(y))
#> ℹ Calculating mean AMR distance based on columns "gent" and "tobr" #> ℹ Calculating mean AMR distance based on columns "gent" and "tobr"
y[order(y$amr_distance), ] y[order(y$amr_distance), ]
#> id amox cipr gent tobr amr_distance #> id amox cipr gent tobr amr_distance
#> 4 D R 25 <=1 2 -0.7848712 #> 6 F I 19 0.5 8 -0.8163565
#> 5 E I 31 <=1 2 -0.7848712 #> 8 H R 27 0.5 8 -0.8163565
#> 10 J R 17 <=1 2 -0.7848712 #> 2 B S 28 1 8 -0.1012596
#> 8 H S 18 <=1 4 -0.3105295 #> 3 C R 33 1 8 -0.1012596
#> 9 I S 28 <=1 4 -0.3105295 #> 9 I S 29 1 8 -0.1012596
#> 2 B S 27 <=1 8 0.1638121 #> 5 E I 25 0.5 16 0.1518893
#> 6 F S 32 <=1 8 0.1638121 #> 7 G S 23 0.5 16 0.1518893
#> 7 G I 29 2 2 0.2502272 #> 10 J R 32 0.5 16 0.1518893
#> 3 C R 25 2 4 0.7245688 #> 1 A I 27 >=2 8 0.6138374
#> 1 A S 31 2 >=16 1.6732521 #> 4 D R 32 1 16 0.8669863
if (require("dplyr")) { if (require("dplyr")) {
y %>% y %>%
@@ -160,16 +160,16 @@ if (require("dplyr")) {
#> ℹ Calculating mean AMR distance based on columns "amox", "cipr", "gent", #> ℹ Calculating mean AMR distance based on columns "amox", "cipr", "gent",
#> and "tobr" #> and "tobr"
#> id amox cipr gent tobr amr_distance check_id_C #> id amox cipr gent tobr amr_distance check_id_C
#> 1 C R 25 2 4 0.66241774 0.0000000 #> 1 C R 33 1 8 0.55391610 0.00000000
#> 2 A S 31 2 >=16 0.90606144 0.2436437 #> 2 J R 32 0.5 16 0.62338653 0.06947042
#> 3 F S 32 <=1 8 0.19914999 0.4632678 #> 3 D R 32 1 16 0.98093500 0.42701889
#> 4 G I 29 2 2 0.09893189 0.5634858 #> 4 A I 27 >=2 8 0.08471751 0.46919859
#> 5 B S 27 <=1 8 -0.03989270 0.7023104 #> 5 H R 27 0.5 8 -0.14625651 0.70017262
#> 6 D R 25 <=1 2 -0.09230226 0.7547200 #> 6 I S 29 1 8 -0.15862291 0.71253901
#> 7 I S 28 <=1 4 -0.22925499 0.8916727 #> 7 B S 28 1 8 -0.21572693 0.76964304
#> 8 E I 31 <=1 2 -0.32300020 0.9854179 #> 8 E I 25 0.5 16 -0.26046456 0.81438066
#> 9 J R 17 <=1 2 -0.47477055 1.1371883 #> 9 G S 23 0.5 16 -0.37467261 0.92858871
#> 10 H S 18 <=1 4 -0.70734036 1.3697581 #> 10 F I 19 0.5 8 -1.08721162 1.64112773
if (require("dplyr")) { if (require("dplyr")) {
# support for groups # support for groups
example_isolates %>% example_isolates %>%

2
reference/microorganisms.codes.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

2
reference/microorganisms.groups.html
View File

@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

2
reference/microorganisms.html
View File

@@ -9,7 +9,7 @@ This data set is carefully crafted, yet made 100% reproducible from public and a
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

2
reference/mo_matching_score.html
View File

@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

2
reference/mo_property.html
View File

@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

2
reference/mo_source.html
View File

@@ -9,7 +9,7 @@ This is the fastest way to have your organisation (or analysis) specific codes p
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

2
reference/pca.html
View File

@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a> <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="">3.0.1.9004</small> <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9007</small>
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