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guess_ab_col, benchmarks
This commit is contained in:
@ -111,6 +111,13 @@
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Use the G-test
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</a>
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</li>
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<li>
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<a href="../articles/benchmarks.html">
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<span class="fa fa-shipping-fast"></span>
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Other: benchmarks
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</a>
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</li>
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</ul>
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</li>
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<li>
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@ -171,7 +178,7 @@
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<h1>How to conduct AMR analysis</h1>
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<h4 class="author">Matthijs S. Berends</h4>
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<h4 class="date">08 January 2019</h4>
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<h4 class="date">11 January 2019</h4>
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<div class="hidden name"><code>AMR.Rmd</code></div>
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@ -180,7 +187,7 @@
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<p><strong>Note:</strong> values on this page will change with every website update since they are based on randomly created values and the page was written in <a href="https://rmarkdown.rstudio.com/">RMarkdown</a>. However, the methodology remains unchanged. This page was generated on 08 January 2019.</p>
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<p><strong>Note:</strong> values on this page will change with every website update since they are based on randomly created values and the page was written in <a href="https://rmarkdown.rstudio.com/">RMarkdown</a>. However, the methodology remains unchanged. This page was generated on 11 January 2019.</p>
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<div id="introduction" class="section level2">
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<h2 class="hasAnchor">
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<a href="#introduction" class="anchor"></a>Introduction</h2>
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@ -196,21 +203,21 @@
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</tr></thead>
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<tbody>
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<tr class="odd">
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<td align="center">2019-01-08</td>
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<td align="center">2019-01-11</td>
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<td align="center">abcd</td>
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<td align="center">Escherichia coli</td>
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<td align="center">S</td>
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<td align="center">S</td>
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</tr>
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<tr class="even">
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<td align="center">2019-01-08</td>
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<td align="center">2019-01-11</td>
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<td align="center">abcd</td>
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<td align="center">Escherichia coli</td>
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<td align="center">S</td>
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<td align="center">R</td>
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</tr>
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<tr class="odd">
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<td align="center">2019-01-08</td>
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<td align="center">2019-01-11</td>
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<td align="center">efgh</td>
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<td align="center">Escherichia coli</td>
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<td align="center">R</td>
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@ -268,18 +275,18 @@
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<div id="put-everything-together" class="section level4">
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<h4 class="hasAnchor">
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<a href="#put-everything-together" class="anchor"></a>Put everything together</h4>
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<p>Using the <code><a href="https://dplyr.tidyverse.org/reference/sample.html">sample()</a></code> function, we can randomly select items from all objects we defined earlier. To let our fake data reflect reality a bit, we will also approximately define the probabilities of bacteria and the antibiotic results with the <code>prob</code> parameter.</p>
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<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb7-1" data-line-number="1">data <-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/data.frame">data.frame</a></span>(<span class="dt">date =</span> <span class="kw"><a href="https://dplyr.tidyverse.org/reference/sample.html">sample</a></span>(dates, <span class="dv">5000</span>, <span class="dt">replace =</span> <span class="ot">TRUE</span>),</a>
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<a class="sourceLine" id="cb7-2" data-line-number="2"> <span class="dt">patient_id =</span> <span class="kw"><a href="https://dplyr.tidyverse.org/reference/sample.html">sample</a></span>(patients, <span class="dv">5000</span>, <span class="dt">replace =</span> <span class="ot">TRUE</span>),</a>
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<a class="sourceLine" id="cb7-3" data-line-number="3"> <span class="dt">hospital =</span> <span class="kw"><a href="https://dplyr.tidyverse.org/reference/sample.html">sample</a></span>(hospitals, <span class="dv">5000</span>, <span class="dt">replace =</span> <span class="ot">TRUE</span>, <span class="dt">prob =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="fl">0.30</span>, <span class="fl">0.35</span>, <span class="fl">0.15</span>, <span class="fl">0.20</span>)),</a>
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<a class="sourceLine" id="cb7-4" data-line-number="4"> <span class="dt">bacteria =</span> <span class="kw"><a href="https://dplyr.tidyverse.org/reference/sample.html">sample</a></span>(bacteria, <span class="dv">5000</span>, <span class="dt">replace =</span> <span class="ot">TRUE</span>, <span class="dt">prob =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="fl">0.50</span>, <span class="fl">0.25</span>, <span class="fl">0.15</span>, <span class="fl">0.10</span>)),</a>
|
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<a class="sourceLine" id="cb7-5" data-line-number="5"> <span class="dt">amox =</span> <span class="kw"><a href="https://dplyr.tidyverse.org/reference/sample.html">sample</a></span>(ab_interpretations, <span class="dv">5000</span>, <span class="dt">replace =</span> <span class="ot">TRUE</span>, <span class="dt">prob =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="fl">0.60</span>, <span class="fl">0.05</span>, <span class="fl">0.35</span>)),</a>
|
||||
<a class="sourceLine" id="cb7-6" data-line-number="6"> <span class="dt">amcl =</span> <span class="kw"><a href="https://dplyr.tidyverse.org/reference/sample.html">sample</a></span>(ab_interpretations, <span class="dv">5000</span>, <span class="dt">replace =</span> <span class="ot">TRUE</span>, <span class="dt">prob =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="fl">0.75</span>, <span class="fl">0.10</span>, <span class="fl">0.15</span>)),</a>
|
||||
<a class="sourceLine" id="cb7-7" data-line-number="7"> <span class="dt">cipr =</span> <span class="kw"><a href="https://dplyr.tidyverse.org/reference/sample.html">sample</a></span>(ab_interpretations, <span class="dv">5000</span>, <span class="dt">replace =</span> <span class="ot">TRUE</span>, <span class="dt">prob =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="fl">0.80</span>, <span class="fl">0.00</span>, <span class="fl">0.20</span>)),</a>
|
||||
<a class="sourceLine" id="cb7-8" data-line-number="8"> <span class="dt">gent =</span> <span class="kw"><a href="https://dplyr.tidyverse.org/reference/sample.html">sample</a></span>(ab_interpretations, <span class="dv">5000</span>, <span class="dt">replace =</span> <span class="ot">TRUE</span>, <span class="dt">prob =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="fl">0.92</span>, <span class="fl">0.00</span>, <span class="fl">0.08</span>))</a>
|
||||
<p>Using the <code><a href="https://www.rdocumentation.org/packages/dplyr/topics/sample">sample()</a></code> function, we can randomly select items from all objects we defined earlier. To let our fake data reflect reality a bit, we will also approximately define the probabilities of bacteria and the antibiotic results with the <code>prob</code> parameter.</p>
|
||||
<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb7-1" data-line-number="1">data <-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/data.frame">data.frame</a></span>(<span class="dt">date =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/sample">sample</a></span>(dates, <span class="dv">5000</span>, <span class="dt">replace =</span> <span class="ot">TRUE</span>),</a>
|
||||
<a class="sourceLine" id="cb7-2" data-line-number="2"> <span class="dt">patient_id =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/sample">sample</a></span>(patients, <span class="dv">5000</span>, <span class="dt">replace =</span> <span class="ot">TRUE</span>),</a>
|
||||
<a class="sourceLine" id="cb7-3" data-line-number="3"> <span class="dt">hospital =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/sample">sample</a></span>(hospitals, <span class="dv">5000</span>, <span class="dt">replace =</span> <span class="ot">TRUE</span>, <span class="dt">prob =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="fl">0.30</span>, <span class="fl">0.35</span>, <span class="fl">0.15</span>, <span class="fl">0.20</span>)),</a>
|
||||
<a class="sourceLine" id="cb7-4" data-line-number="4"> <span class="dt">bacteria =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/sample">sample</a></span>(bacteria, <span class="dv">5000</span>, <span class="dt">replace =</span> <span class="ot">TRUE</span>, <span class="dt">prob =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="fl">0.50</span>, <span class="fl">0.25</span>, <span class="fl">0.15</span>, <span class="fl">0.10</span>)),</a>
|
||||
<a class="sourceLine" id="cb7-5" data-line-number="5"> <span class="dt">amox =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/sample">sample</a></span>(ab_interpretations, <span class="dv">5000</span>, <span class="dt">replace =</span> <span class="ot">TRUE</span>, <span class="dt">prob =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="fl">0.60</span>, <span class="fl">0.05</span>, <span class="fl">0.35</span>)),</a>
|
||||
<a class="sourceLine" id="cb7-6" data-line-number="6"> <span class="dt">amcl =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/sample">sample</a></span>(ab_interpretations, <span class="dv">5000</span>, <span class="dt">replace =</span> <span class="ot">TRUE</span>, <span class="dt">prob =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="fl">0.75</span>, <span class="fl">0.10</span>, <span class="fl">0.15</span>)),</a>
|
||||
<a class="sourceLine" id="cb7-7" data-line-number="7"> <span class="dt">cipr =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/sample">sample</a></span>(ab_interpretations, <span class="dv">5000</span>, <span class="dt">replace =</span> <span class="ot">TRUE</span>, <span class="dt">prob =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="fl">0.80</span>, <span class="fl">0.00</span>, <span class="fl">0.20</span>)),</a>
|
||||
<a class="sourceLine" id="cb7-8" data-line-number="8"> <span class="dt">gent =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/sample">sample</a></span>(ab_interpretations, <span class="dv">5000</span>, <span class="dt">replace =</span> <span class="ot">TRUE</span>, <span class="dt">prob =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="fl">0.92</span>, <span class="fl">0.00</span>, <span class="fl">0.08</span>))</a>
|
||||
<a class="sourceLine" id="cb7-9" data-line-number="9"> )</a></code></pre></div>
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<p>Using the <code><a href="https://dplyr.tidyverse.org/reference/join.html">left_join()</a></code> function from the <code>dplyr</code> package, we can ‘map’ the gender to the patient ID using the <code>patients_table</code> object we created earlier:</p>
|
||||
<div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb8-1" data-line-number="1">data <-<span class="st"> </span>data <span class="op">%>%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/join.html">left_join</a></span>(patients_table)</a></code></pre></div>
|
||||
<p>Using the <code><a href="https://www.rdocumentation.org/packages/dplyr/topics/join">left_join()</a></code> function from the <code>dplyr</code> package, we can ‘map’ the gender to the patient ID using the <code>patients_table</code> object we created earlier:</p>
|
||||
<div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb8-1" data-line-number="1">data <-<span class="st"> </span>data <span class="op">%>%</span><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/join">left_join</a></span>(patients_table)</a></code></pre></div>
|
||||
<p>The resulting data set contains 5,000 blood culture isolates. With the <code><a href="https://www.rdocumentation.org/packages/utils/topics/head">head()</a></code> function we can preview the first 6 values of this data set:</p>
|
||||
<div class="sourceCode" id="cb9"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb9-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/utils/topics/head">head</a></span>(data)</a></code></pre></div>
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<table class="table">
|
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@ -296,70 +303,70 @@
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</tr></thead>
|
||||
<tbody>
|
||||
<tr class="odd">
|
||||
<td align="center">2011-02-27</td>
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||||
<td align="center">M6</td>
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||||
<td align="center">Hospital C</td>
|
||||
<td align="center">2014-02-02</td>
|
||||
<td align="center">P8</td>
|
||||
<td align="center">Hospital D</td>
|
||||
<td align="center">Escherichia coli</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">M</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="center">2012-07-12</td>
|
||||
<td align="center">C2</td>
|
||||
<td align="center">Hospital B</td>
|
||||
<td align="center">Streptococcus pneumoniae</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">M</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="center">2016-09-13</td>
|
||||
<td align="center">O7</td>
|
||||
<td align="center">Hospital A</td>
|
||||
<td align="center">Escherichia coli</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">F</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="center">2016-12-05</td>
|
||||
<td align="center">E4</td>
|
||||
<td align="center">Hospital A</td>
|
||||
<td align="center">2013-10-26</td>
|
||||
<td align="center">Q1</td>
|
||||
<td align="center">Hospital B</td>
|
||||
<td align="center">Escherichia coli</td>
|
||||
<td align="center">I</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">F</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="center">2017-06-12</td>
|
||||
<td align="center">E5</td>
|
||||
<td align="center">Hospital D</td>
|
||||
<td align="center">Streptococcus pneumoniae</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">M</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="center">2013-06-16</td>
|
||||
<td align="center">K7</td>
|
||||
<td align="center">Hospital B</td>
|
||||
<td align="center">Escherichia coli</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">I</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">M</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="center">2017-10-05</td>
|
||||
<td align="center">M1</td>
|
||||
<td align="center">Hospital A</td>
|
||||
<td align="center">Escherichia coli</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">2013-01-11</td>
|
||||
<td align="center">M4</td>
|
||||
<td align="center">Hospital B</td>
|
||||
<td align="center">Staphylococcus aureus</td>
|
||||
<td align="center">I</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">M</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="center">2012-02-22</td>
|
||||
<td align="center">H9</td>
|
||||
<td align="center">Hospital C</td>
|
||||
<td align="center">Streptococcus pneumoniae</td>
|
||||
<td align="center">2016-11-18</td>
|
||||
<td align="center">W10</td>
|
||||
<td align="center">Hospital A</td>
|
||||
<td align="center">Staphylococcus aureus</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">M</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">F</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
@ -379,15 +386,15 @@
|
||||
#
|
||||
# Item Count Percent Cum. Count Cum. Percent
|
||||
# --- ----- ------ -------- ----------- -------------
|
||||
# 1 M 2,635 52.7% 2,635 52.7%
|
||||
# 2 F 2,365 47.3% 5,000 100.0%</code></pre>
|
||||
# 1 M 2,598 52.0% 2,598 52.0%
|
||||
# 2 F 2,402 48.0% 5,000 100.0%</code></pre>
|
||||
<p>So, we can draw at least two conclusions immediately. From a data scientist perspective, the data looks clean: only values <code>M</code> and <code>F</code>. From a researcher perspective: there are slightly more men. Nothing we didn’t already know.</p>
|
||||
<p>The data is already quite clean, but we still need to transform some variables. The <code>bacteria</code> column now consists of text, and we want to add more variables based on microbial IDs later on. So, we will transform this column to valid IDs. The <code><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate()</a></code> function of the <code>dplyr</code> package makes this really easy:</p>
|
||||
<p>The data is already quite clean, but we still need to transform some variables. The <code>bacteria</code> column now consists of text, and we want to add more variables based on microbial IDs later on. So, we will transform this column to valid IDs. The <code><a href="https://www.rdocumentation.org/packages/dplyr/topics/mutate">mutate()</a></code> function of the <code>dplyr</code> package makes this really easy:</p>
|
||||
<div class="sourceCode" id="cb12"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb12-1" data-line-number="1">data <-<span class="st"> </span>data <span class="op">%>%</span></a>
|
||||
<a class="sourceLine" id="cb12-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">bacteria =</span> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(bacteria))</a></code></pre></div>
|
||||
<p>We also want to transform the antibiotics, because in real life data we don’t know if they are really clean. The <code><a href="../reference/as.rsi.html">as.rsi()</a></code> function ensures reliability and reproducibility in these kind of variables. The <code><a href="https://dplyr.tidyverse.org/reference/summarise_all.html">mutate_at()</a></code> will run the <code><a href="../reference/as.rsi.html">as.rsi()</a></code> function on defined variables:</p>
|
||||
<a class="sourceLine" id="cb12-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/mutate">mutate</a></span>(<span class="dt">bacteria =</span> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(bacteria))</a></code></pre></div>
|
||||
<p>We also want to transform the antibiotics, because in real life data we don’t know if they are really clean. The <code><a href="../reference/as.rsi.html">as.rsi()</a></code> function ensures reliability and reproducibility in these kind of variables. The <code><a href="https://www.rdocumentation.org/packages/dplyr/topics/summarise_all">mutate_at()</a></code> will run the <code><a href="../reference/as.rsi.html">as.rsi()</a></code> function on defined variables:</p>
|
||||
<div class="sourceCode" id="cb13"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb13-1" data-line-number="1">data <-<span class="st"> </span>data <span class="op">%>%</span></a>
|
||||
<a class="sourceLine" id="cb13-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/summarise_all.html">mutate_at</a></span>(<span class="kw"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(amox<span class="op">:</span>gent), as.rsi)</a></code></pre></div>
|
||||
<a class="sourceLine" id="cb13-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/summarise_all">mutate_at</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/vars">vars</a></span>(amox<span class="op">:</span>gent), as.rsi)</a></code></pre></div>
|
||||
<p>Finally, we will apply <a href="http://www.eucast.org/expert_rules_and_intrinsic_resistance/">EUCAST rules</a> on our antimicrobial results. In Europe, most medical microbiological laboratories already apply these rules. Our package features their latest insights on intrinsic resistance and exceptional phenotypes. Moreover, the <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function can also apply additional rules, like forcing <help title="ATC: J01CA01">ampicillin</help> = R when <help title="ATC: J01CR02">amoxicillin/clavulanic acid</help> = R.</p>
|
||||
<p>Because the amoxicillin (column <code>amox</code>) and amoxicillin/clavulanic acid (column <code>amcl</code>) in our data were generated randomly, some rows will undoubtedly contain amox = S and amcl = R, which is technically impossible. The <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> fixes this:</p>
|
||||
<div class="sourceCode" id="cb14"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb14-1" data-line-number="1">data <-<span class="st"> </span><span class="kw"><a href="../reference/eucast_rules.html">eucast_rules</a></span>(data, <span class="dt">col_mo =</span> <span class="st">"bacteria"</span>)</a>
|
||||
@ -411,10 +418,10 @@
|
||||
<a class="sourceLine" id="cb14-19" data-line-number="19"><span class="co"># Kingella kingae (no changes)</span></a>
|
||||
<a class="sourceLine" id="cb14-20" data-line-number="20"><span class="co"># </span></a>
|
||||
<a class="sourceLine" id="cb14-21" data-line-number="21"><span class="co"># EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes (v3.1, 2016)</span></a>
|
||||
<a class="sourceLine" id="cb14-22" data-line-number="22"><span class="co"># Table 1: Intrinsic resistance in Enterobacteriaceae (349 changes)</span></a>
|
||||
<a class="sourceLine" id="cb14-22" data-line-number="22"><span class="co"># Table 1: Intrinsic resistance in Enterobacteriaceae (333 changes)</span></a>
|
||||
<a class="sourceLine" id="cb14-23" data-line-number="23"><span class="co"># Table 2: Intrinsic resistance in non-fermentative Gram-negative bacteria (no changes)</span></a>
|
||||
<a class="sourceLine" id="cb14-24" data-line-number="24"><span class="co"># Table 3: Intrinsic resistance in other Gram-negative bacteria (no changes)</span></a>
|
||||
<a class="sourceLine" id="cb14-25" data-line-number="25"><span class="co"># Table 4: Intrinsic resistance in Gram-positive bacteria (694 changes)</span></a>
|
||||
<a class="sourceLine" id="cb14-25" data-line-number="25"><span class="co"># Table 4: Intrinsic resistance in Gram-positive bacteria (692 changes)</span></a>
|
||||
<a class="sourceLine" id="cb14-26" data-line-number="26"><span class="co"># Table 8: Interpretive rules for B-lactam agents and Gram-positive cocci (no changes)</span></a>
|
||||
<a class="sourceLine" id="cb14-27" data-line-number="27"><span class="co"># Table 9: Interpretive rules for B-lactam agents and Gram-negative rods (no changes)</span></a>
|
||||
<a class="sourceLine" id="cb14-28" data-line-number="28"><span class="co"># Table 10: Interpretive rules for B-lactam agents and other Gram-negative bacteria (no changes)</span></a>
|
||||
@ -430,14 +437,14 @@
|
||||
<a class="sourceLine" id="cb14-38" data-line-number="38"><span class="co"># Non-EUCAST: piperacillin/tazobactam = S where piperacillin = S (no changes)</span></a>
|
||||
<a class="sourceLine" id="cb14-39" data-line-number="39"><span class="co"># Non-EUCAST: trimethoprim/sulfa = S where trimethoprim = S (no changes)</span></a>
|
||||
<a class="sourceLine" id="cb14-40" data-line-number="40"><span class="co"># </span></a>
|
||||
<a class="sourceLine" id="cb14-41" data-line-number="41"><span class="co"># => EUCAST rules affected 1,854 out of 5,000 rows -> changed 1,043 test results.</span></a></code></pre></div>
|
||||
<a class="sourceLine" id="cb14-41" data-line-number="41"><span class="co"># => EUCAST rules affected 1,830 out of 5,000 rows -> changed 1,025 test results.</span></a></code></pre></div>
|
||||
</div>
|
||||
<div id="adding-new-variables" class="section level2">
|
||||
<h2 class="hasAnchor">
|
||||
<a href="#adding-new-variables" class="anchor"></a>Adding new variables</h2>
|
||||
<p>Now that we have the microbial ID, we can add some taxonomic properties:</p>
|
||||
<div class="sourceCode" id="cb15"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb15-1" data-line-number="1">data <-<span class="st"> </span>data <span class="op">%>%</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb15-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">gramstain =</span> <span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(bacteria),</a>
|
||||
<a class="sourceLine" id="cb15-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/mutate">mutate</a></span>(<span class="dt">gramstain =</span> <span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(bacteria),</a>
|
||||
<a class="sourceLine" id="cb15-3" data-line-number="3"> <span class="dt">genus =</span> <span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(bacteria),</a>
|
||||
<a class="sourceLine" id="cb15-4" data-line-number="4"> <span class="dt">species =</span> <span class="kw"><a href="../reference/mo_property.html">mo_species</a></span>(bacteria))</a></code></pre></div>
|
||||
<div id="first-isolates" class="section level3">
|
||||
@ -451,14 +458,14 @@
|
||||
</blockquote>
|
||||
<p>This <code>AMR</code> package includes this methodology with the <code><a href="../reference/first_isolate.html">first_isolate()</a></code> function. It adopts the episode of a year (can be changed by user) and it starts counting days after every selected isolate. This new variable can easily be added to our data:</p>
|
||||
<div class="sourceCode" id="cb16"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb16-1" data-line-number="1">data <-<span class="st"> </span>data <span class="op">%>%</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb16-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">first =</span> <span class="kw"><a href="../reference/first_isolate.html">first_isolate</a></span>(.))</a>
|
||||
<a class="sourceLine" id="cb16-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/mutate">mutate</a></span>(<span class="dt">first =</span> <span class="kw"><a href="../reference/first_isolate.html">first_isolate</a></span>(.))</a>
|
||||
<a class="sourceLine" id="cb16-3" data-line-number="3"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `bacteria` as input for `col_mo`.</span></a>
|
||||
<a class="sourceLine" id="cb16-4" data-line-number="4"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `date` as input for `col_date`.</span></a>
|
||||
<a class="sourceLine" id="cb16-5" data-line-number="5"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `patient_id` as input for `col_patient_id`.</span></a>
|
||||
<a class="sourceLine" id="cb16-6" data-line-number="6"><span class="co"># => Found 2,929 first isolates (58.6% of total)</span></a></code></pre></div>
|
||||
<p>So only 58.6% is suitable for resistance analysis! We can now filter on is with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html">filter()</a></code> function, also from the <code>dplyr</code> package:</p>
|
||||
<a class="sourceLine" id="cb16-6" data-line-number="6"><span class="co"># => Found 2,962 first isolates (59.2% of total)</span></a></code></pre></div>
|
||||
<p>So only 59.2% is suitable for resistance analysis! We can now filter on is with the <code><a href="https://www.rdocumentation.org/packages/dplyr/topics/filter">filter()</a></code> function, also from the <code>dplyr</code> package:</p>
|
||||
<div class="sourceCode" id="cb17"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb17-1" data-line-number="1">data_1st <-<span class="st"> </span>data <span class="op">%>%</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb17-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(first <span class="op">==</span><span class="st"> </span><span class="ot">TRUE</span>)</a></code></pre></div>
|
||||
<a class="sourceLine" id="cb17-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/filter">filter</a></span>(first <span class="op">==</span><span class="st"> </span><span class="ot">TRUE</span>)</a></code></pre></div>
|
||||
<p>For future use, the above two syntaxes can be shortened with the <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code> function:</p>
|
||||
<div class="sourceCode" id="cb18"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb18-1" data-line-number="1">data_1st <-<span class="st"> </span>data <span class="op">%>%</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb18-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/first_isolate.html">filter_first_isolate</a></span>()</a></code></pre></div>
|
||||
@ -482,21 +489,21 @@
|
||||
<tbody>
|
||||
<tr class="odd">
|
||||
<td align="center">1</td>
|
||||
<td align="center">2010-01-31</td>
|
||||
<td align="center">L4</td>
|
||||
<td align="center">2010-05-23</td>
|
||||
<td align="center">E7</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">TRUE</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="center">2</td>
|
||||
<td align="center">2010-08-01</td>
|
||||
<td align="center">L4</td>
|
||||
<td align="center">2010-08-03</td>
|
||||
<td align="center">E7</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
@ -504,52 +511,52 @@
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="center">3</td>
|
||||
<td align="center">2010-12-29</td>
|
||||
<td align="center">L4</td>
|
||||
<td align="center">2011-01-20</td>
|
||||
<td align="center">E7</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">I</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">FALSE</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="center">4</td>
|
||||
<td align="center">2011-01-21</td>
|
||||
<td align="center">L4</td>
|
||||
<td align="center">2011-02-21</td>
|
||||
<td align="center">E7</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">I</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">FALSE</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="center">5</td>
|
||||
<td align="center">2011-02-06</td>
|
||||
<td align="center">L4</td>
|
||||
<td align="center">2011-08-04</td>
|
||||
<td align="center">E7</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">I</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">TRUE</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="center">6</td>
|
||||
<td align="center">2011-05-30</td>
|
||||
<td align="center">L4</td>
|
||||
<td align="center">2011-11-15</td>
|
||||
<td align="center">E7</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">I</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">FALSE</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="center">7</td>
|
||||
<td align="center">2011-08-16</td>
|
||||
<td align="center">L4</td>
|
||||
<td align="center">2012-01-13</td>
|
||||
<td align="center">E7</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
@ -559,8 +566,8 @@
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="center">8</td>
|
||||
<td align="center">2012-01-15</td>
|
||||
<td align="center">L4</td>
|
||||
<td align="center">2012-03-10</td>
|
||||
<td align="center">E7</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
@ -570,22 +577,22 @@
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="center">9</td>
|
||||
<td align="center">2014-07-16</td>
|
||||
<td align="center">L4</td>
|
||||
<td align="center">2012-11-09</td>
|
||||
<td align="center">E7</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">TRUE</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="center">10</td>
|
||||
<td align="center">2014-09-19</td>
|
||||
<td align="center">L4</td>
|
||||
<td align="center">2013-04-06</td>
|
||||
<td align="center">E7</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">FALSE</td>
|
||||
@ -595,8 +602,8 @@
|
||||
<p>Only 3 isolates are marked as ‘first’ according to CLSI guideline. But when reviewing the antibiogram, it is obvious that some isolates are absolutely different strains and show be included too. This is why we weigh isolates, based on their antibiogram. The <code><a href="../reference/key_antibiotics.html">key_antibiotics()</a></code> function adds a vector with 18 key antibiotics: 6 broad spectrum ones, 6 small spectrum for Gram negatives and 6 small spectrum for Gram positives. These can be defined by the user.</p>
|
||||
<p>If a column exists with a name like ‘key(…)ab’ the <code><a href="../reference/first_isolate.html">first_isolate()</a></code> function will automatically use it and determine the first weighted isolates. Mind the NOTEs in below output:</p>
|
||||
<div class="sourceCode" id="cb19"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb19-1" data-line-number="1">data <-<span class="st"> </span>data <span class="op">%>%</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb19-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">keyab =</span> <span class="kw"><a href="../reference/key_antibiotics.html">key_antibiotics</a></span>(.)) <span class="op">%>%</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb19-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">first_weighted =</span> <span class="kw"><a href="../reference/first_isolate.html">first_isolate</a></span>(.))</a>
|
||||
<a class="sourceLine" id="cb19-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/mutate">mutate</a></span>(<span class="dt">keyab =</span> <span class="kw"><a href="../reference/key_antibiotics.html">key_antibiotics</a></span>(.)) <span class="op">%>%</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb19-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/mutate">mutate</a></span>(<span class="dt">first_weighted =</span> <span class="kw"><a href="../reference/first_isolate.html">first_isolate</a></span>(.))</a>
|
||||
<a class="sourceLine" id="cb19-4" data-line-number="4"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `bacteria` as input for `col_mo`.</span></a>
|
||||
<a class="sourceLine" id="cb19-5" data-line-number="5"><span class="co"># amox amcl cipr gent </span></a>
|
||||
<a class="sourceLine" id="cb19-6" data-line-number="6"><span class="co"># "amox" "amcl" "cipr" "gent" </span></a>
|
||||
@ -608,7 +615,7 @@
|
||||
<a class="sourceLine" id="cb19-12" data-line-number="12"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `patient_id` as input for `col_patient_id`.</span></a>
|
||||
<a class="sourceLine" id="cb19-13" data-line-number="13"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `keyab` as input for `col_keyantibiotics`. Use col_keyantibiotics = FALSE to prevent this.</span></a>
|
||||
<a class="sourceLine" id="cb19-14" data-line-number="14"><span class="co"># [Criterion] Inclusion based on key antibiotics, ignoring I.</span></a>
|
||||
<a class="sourceLine" id="cb19-15" data-line-number="15"><span class="co"># => Found 4,435 first weighted isolates (88.7% of total)</span></a></code></pre></div>
|
||||
<a class="sourceLine" id="cb19-15" data-line-number="15"><span class="co"># => Found 4,399 first weighted isolates (88.0% of total)</span></a></code></pre></div>
|
||||
<table class="table">
|
||||
<thead><tr class="header">
|
||||
<th align="center">isolate</th>
|
||||
@ -625,80 +632,80 @@
|
||||
<tbody>
|
||||
<tr class="odd">
|
||||
<td align="center">1</td>
|
||||
<td align="center">2010-01-31</td>
|
||||
<td align="center">L4</td>
|
||||
<td align="center">2010-05-23</td>
|
||||
<td align="center">E7</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">TRUE</td>
|
||||
<td align="center">TRUE</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="center">2</td>
|
||||
<td align="center">2010-08-01</td>
|
||||
<td align="center">L4</td>
|
||||
<td align="center">2010-08-03</td>
|
||||
<td align="center">E7</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">FALSE</td>
|
||||
<td align="center">FALSE</td>
|
||||
<td align="center">TRUE</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="center">3</td>
|
||||
<td align="center">2010-12-29</td>
|
||||
<td align="center">L4</td>
|
||||
<td align="center">2011-01-20</td>
|
||||
<td align="center">E7</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">I</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">FALSE</td>
|
||||
<td align="center">TRUE</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="center">4</td>
|
||||
<td align="center">2011-01-21</td>
|
||||
<td align="center">L4</td>
|
||||
<td align="center">2011-02-21</td>
|
||||
<td align="center">E7</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">I</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">FALSE</td>
|
||||
<td align="center">TRUE</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="center">5</td>
|
||||
<td align="center">2011-02-06</td>
|
||||
<td align="center">L4</td>
|
||||
<td align="center">2011-08-04</td>
|
||||
<td align="center">E7</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">I</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">TRUE</td>
|
||||
<td align="center">TRUE</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="center">6</td>
|
||||
<td align="center">2011-05-30</td>
|
||||
<td align="center">L4</td>
|
||||
<td align="center">2011-11-15</td>
|
||||
<td align="center">E7</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">I</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">FALSE</td>
|
||||
<td align="center">FALSE</td>
|
||||
<td align="center">TRUE</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="center">7</td>
|
||||
<td align="center">2011-08-16</td>
|
||||
<td align="center">L4</td>
|
||||
<td align="center">2012-01-13</td>
|
||||
<td align="center">E7</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
@ -709,8 +716,8 @@
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="center">8</td>
|
||||
<td align="center">2012-01-15</td>
|
||||
<td align="center">L4</td>
|
||||
<td align="center">2012-03-10</td>
|
||||
<td align="center">E7</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
@ -721,23 +728,23 @@
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="center">9</td>
|
||||
<td align="center">2014-07-16</td>
|
||||
<td align="center">L4</td>
|
||||
<td align="center">2012-11-09</td>
|
||||
<td align="center">E7</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">TRUE</td>
|
||||
<td align="center">TRUE</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="center">10</td>
|
||||
<td align="center">2014-09-19</td>
|
||||
<td align="center">L4</td>
|
||||
<td align="center">2013-04-06</td>
|
||||
<td align="center">E7</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">FALSE</td>
|
||||
@ -745,14 +752,14 @@
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<p>Instead of 3, now 8 isolates are flagged. In total, 88.7% of all isolates are marked ‘first weighted’ - 147.3% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.</p>
|
||||
<p>Instead of 3, now 10 isolates are flagged. In total, 88% of all isolates are marked ‘first weighted’ - 147.2% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.</p>
|
||||
<p>As with <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code>, there’s a shortcut for this new algorithm too:</p>
|
||||
<div class="sourceCode" id="cb20"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb20-1" data-line-number="1">data_1st <-<span class="st"> </span>data <span class="op">%>%</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb20-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/first_isolate.html">filter_first_weighted_isolate</a></span>()</a></code></pre></div>
|
||||
<p>So we end up with 4,435 isolates for analysis.</p>
|
||||
<p>So we end up with 4,399 isolates for analysis.</p>
|
||||
<p>We can remove unneeded columns:</p>
|
||||
<div class="sourceCode" id="cb21"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb21-1" data-line-number="1">data_1st <-<span class="st"> </span>data_1st <span class="op">%>%</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb21-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="op">-</span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(first, keyab))</a></code></pre></div>
|
||||
<a class="sourceLine" id="cb21-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/select">select</a></span>(<span class="op">-</span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(first, keyab))</a></code></pre></div>
|
||||
<p>Now our data looks like:</p>
|
||||
<div class="sourceCode" id="cb22"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb22-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/utils/topics/head">head</a></span>(data_1st)</a></code></pre></div>
|
||||
<table class="table">
|
||||
@ -775,43 +782,11 @@
|
||||
<tbody>
|
||||
<tr class="odd">
|
||||
<td>1</td>
|
||||
<td align="center">2011-02-27</td>
|
||||
<td align="center">M6</td>
|
||||
<td align="center">Hospital C</td>
|
||||
<td align="center">2014-02-02</td>
|
||||
<td align="center">P8</td>
|
||||
<td align="center">Hospital D</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">M</td>
|
||||
<td align="center">Gram negative</td>
|
||||
<td align="center">Escherichia</td>
|
||||
<td align="center">coli</td>
|
||||
<td align="center">TRUE</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td>2</td>
|
||||
<td align="center">2012-07-12</td>
|
||||
<td align="center">C2</td>
|
||||
<td align="center">Hospital B</td>
|
||||
<td align="center">B_STRPTC_PNE</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">M</td>
|
||||
<td align="center">Gram positive</td>
|
||||
<td align="center">Streptococcus</td>
|
||||
<td align="center">pneumoniae</td>
|
||||
<td align="center">TRUE</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td>3</td>
|
||||
<td align="center">2016-09-13</td>
|
||||
<td align="center">O7</td>
|
||||
<td align="center">Hospital A</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
@ -822,30 +797,30 @@
|
||||
<td align="center">TRUE</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td>5</td>
|
||||
<td align="center">2017-10-05</td>
|
||||
<td align="center">M1</td>
|
||||
<td align="center">Hospital A</td>
|
||||
<td>2</td>
|
||||
<td align="center">2013-10-26</td>
|
||||
<td align="center">Q1</td>
|
||||
<td align="center">Hospital B</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">I</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">M</td>
|
||||
<td align="center">F</td>
|
||||
<td align="center">Gram negative</td>
|
||||
<td align="center">Escherichia</td>
|
||||
<td align="center">coli</td>
|
||||
<td align="center">TRUE</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td>6</td>
|
||||
<td align="center">2012-02-22</td>
|
||||
<td align="center">H9</td>
|
||||
<td align="center">Hospital C</td>
|
||||
<td>3</td>
|
||||
<td align="center">2017-06-12</td>
|
||||
<td align="center">E5</td>
|
||||
<td align="center">Hospital D</td>
|
||||
<td align="center">B_STRPTC_PNE</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">M</td>
|
||||
<td align="center">Gram positive</td>
|
||||
@ -854,15 +829,47 @@
|
||||
<td align="center">TRUE</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td>7</td>
|
||||
<td align="center">2011-01-13</td>
|
||||
<td align="center">S6</td>
|
||||
<td align="center">Hospital D</td>
|
||||
<td>4</td>
|
||||
<td align="center">2013-06-16</td>
|
||||
<td align="center">K7</td>
|
||||
<td align="center">Hospital B</td>
|
||||
<td align="center">B_ESCHR_COL</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">I</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">M</td>
|
||||
<td align="center">Gram negative</td>
|
||||
<td align="center">Escherichia</td>
|
||||
<td align="center">coli</td>
|
||||
<td align="center">TRUE</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td>5</td>
|
||||
<td align="center">2013-01-11</td>
|
||||
<td align="center">M4</td>
|
||||
<td align="center">Hospital B</td>
|
||||
<td align="center">B_STPHY_AUR</td>
|
||||
<td align="center">I</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">M</td>
|
||||
<td align="center">Gram positive</td>
|
||||
<td align="center">Staphylococcus</td>
|
||||
<td align="center">aureus</td>
|
||||
<td align="center">TRUE</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td>7</td>
|
||||
<td align="center">2012-01-05</td>
|
||||
<td align="center">S10</td>
|
||||
<td align="center">Hospital D</td>
|
||||
<td align="center">B_STPHY_AUR</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">I</td>
|
||||
<td align="center">R</td>
|
||||
<td align="center">S</td>
|
||||
<td align="center">F</td>
|
||||
<td align="center">Gram positive</td>
|
||||
<td align="center">Staphylococcus</td>
|
||||
@ -884,7 +891,7 @@
|
||||
<div class="sourceCode" id="cb24"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb24-1" data-line-number="1">data_1st <span class="op">%>%</span><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(genus, species)</a></code></pre></div>
|
||||
<p><strong>Frequency table of <code>genus</code> and <code>species</code></strong><br>
|
||||
Columns: 2<br>
|
||||
Length: 4,435 (of which NA: 0 = 0.00%)<br>
|
||||
Length: 4,399 (of which NA: 0 = 0.00%)<br>
|
||||
Unique: 4</p>
|
||||
<p>Shortest: 16<br>
|
||||
Longest: 24</p>
|
||||
@ -901,33 +908,33 @@ Longest: 24</p>
|
||||
<tr class="odd">
|
||||
<td align="left">1</td>
|
||||
<td align="left">Escherichia coli</td>
|
||||
<td align="right">2,203</td>
|
||||
<td align="right">49.7%</td>
|
||||
<td align="right">2,203</td>
|
||||
<td align="right">49.7%</td>
|
||||
<td align="right">2,138</td>
|
||||
<td align="right">48.6%</td>
|
||||
<td align="right">2,138</td>
|
||||
<td align="right">48.6%</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="left">2</td>
|
||||
<td align="left">Staphylococcus aureus</td>
|
||||
<td align="right">1,072</td>
|
||||
<td align="right">24.2%</td>
|
||||
<td align="right">3,275</td>
|
||||
<td align="right">73.8%</td>
|
||||
<td align="right">1,070</td>
|
||||
<td align="right">24.3%</td>
|
||||
<td align="right">3,208</td>
|
||||
<td align="right">72.9%</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="left">3</td>
|
||||
<td align="left">Streptococcus pneumoniae</td>
|
||||
<td align="right">689</td>
|
||||
<td align="right">15.5%</td>
|
||||
<td align="right">3,964</td>
|
||||
<td align="right">89.4%</td>
|
||||
<td align="right">697</td>
|
||||
<td align="right">15.8%</td>
|
||||
<td align="right">3,905</td>
|
||||
<td align="right">88.8%</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="left">4</td>
|
||||
<td align="left">Klebsiella pneumoniae</td>
|
||||
<td align="right">471</td>
|
||||
<td align="right">10.6%</td>
|
||||
<td align="right">4,435</td>
|
||||
<td align="right">494</td>
|
||||
<td align="right">11.2%</td>
|
||||
<td align="right">4,399</td>
|
||||
<td align="right">100.0%</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
@ -937,11 +944,11 @@ Longest: 24</p>
|
||||
<a href="#resistance-percentages" class="anchor"></a>Resistance percentages</h3>
|
||||
<p>The functions <code>portion_R</code>, <code>portion_RI</code>, <code>portion_I</code>, <code>portion_IS</code> and <code>portion_S</code> can be used to determine the portion of a specific antimicrobial outcome. They can be used on their own:</p>
|
||||
<div class="sourceCode" id="cb25"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb25-1" data-line-number="1">data_1st <span class="op">%>%</span><span class="st"> </span><span class="kw"><a href="../reference/portion.html">portion_IR</a></span>(amox)</a>
|
||||
<a class="sourceLine" id="cb25-2" data-line-number="2"><span class="co"># [1] 0.4617813</span></a></code></pre></div>
|
||||
<p>Or can be used in conjuction with <code><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/summarise.html">summarise()</a></code>, both from the <code>dplyr</code> package:</p>
|
||||
<a class="sourceLine" id="cb25-2" data-line-number="2"><span class="co"># [1] 0.4819277</span></a></code></pre></div>
|
||||
<p>Or can be used in conjuction with <code><a href="https://www.rdocumentation.org/packages/dplyr/topics/group_by">group_by()</a></code> and <code><a href="https://www.rdocumentation.org/packages/dplyr/topics/summarise">summarise()</a></code>, both from the <code>dplyr</code> package:</p>
|
||||
<div class="sourceCode" id="cb26"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb26-1" data-line-number="1">data_1st <span class="op">%>%</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb26-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital) <span class="op">%>%</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb26-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/summarise.html">summarise</a></span>(<span class="dt">amoxicillin =</span> <span class="kw"><a href="../reference/portion.html">portion_IR</a></span>(amox))</a></code></pre></div>
|
||||
<a class="sourceLine" id="cb26-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/group_by">group_by</a></span>(hospital) <span class="op">%>%</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb26-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/summarise">summarise</a></span>(<span class="dt">amoxicillin =</span> <span class="kw"><a href="../reference/portion.html">portion_IR</a></span>(amox))</a></code></pre></div>
|
||||
<table class="table">
|
||||
<thead><tr class="header">
|
||||
<th align="center">hospital</th>
|
||||
@ -950,26 +957,26 @@ Longest: 24</p>
|
||||
<tbody>
|
||||
<tr class="odd">
|
||||
<td align="center">Hospital A</td>
|
||||
<td align="center">0.4504164</td>
|
||||
<td align="center">0.4591382</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="center">Hospital B</td>
|
||||
<td align="center">0.4782034</td>
|
||||
<td align="center">0.5000000</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="center">Hospital C</td>
|
||||
<td align="center">0.4670571</td>
|
||||
<td align="center">0.4682171</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="center">Hospital D</td>
|
||||
<td align="center">0.4471101</td>
|
||||
<td align="center">0.4953380</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<p>Of course it would be very convenient to know the number of isolates responsible for the percentages. For that purpose the <code><a href="../reference/count.html">n_rsi()</a></code> can be used, which works exactly like <code><a href="https://dplyr.tidyverse.org/reference/n_distinct.html">n_distinct()</a></code> from the <code>dplyr</code> package. It counts all isolates available for every group (i.e. values S, I or R):</p>
|
||||
<p>Of course it would be very convenient to know the number of isolates responsible for the percentages. For that purpose the <code><a href="../reference/count.html">n_rsi()</a></code> can be used, which works exactly like <code><a href="https://www.rdocumentation.org/packages/dplyr/topics/n_distinct">n_distinct()</a></code> from the <code>dplyr</code> package. It counts all isolates available for every group (i.e. values S, I or R):</p>
|
||||
<div class="sourceCode" id="cb27"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb27-1" data-line-number="1">data_1st <span class="op">%>%</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb27-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital) <span class="op">%>%</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb27-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/summarise.html">summarise</a></span>(<span class="dt">amoxicillin =</span> <span class="kw"><a href="../reference/portion.html">portion_IR</a></span>(amox),</a>
|
||||
<a class="sourceLine" id="cb27-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/group_by">group_by</a></span>(hospital) <span class="op">%>%</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb27-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/summarise">summarise</a></span>(<span class="dt">amoxicillin =</span> <span class="kw"><a href="../reference/portion.html">portion_IR</a></span>(amox),</a>
|
||||
<a class="sourceLine" id="cb27-4" data-line-number="4"> <span class="dt">available =</span> <span class="kw"><a href="../reference/count.html">n_rsi</a></span>(amox))</a></code></pre></div>
|
||||
<table class="table">
|
||||
<thead><tr class="header">
|
||||
@ -980,30 +987,30 @@ Longest: 24</p>
|
||||
<tbody>
|
||||
<tr class="odd">
|
||||
<td align="center">Hospital A</td>
|
||||
<td align="center">0.4504164</td>
|
||||
<td align="center">1321</td>
|
||||
<td align="center">0.4591382</td>
|
||||
<td align="center">1346</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="center">Hospital B</td>
|
||||
<td align="center">0.4782034</td>
|
||||
<td align="center">1514</td>
|
||||
<td align="center">0.5000000</td>
|
||||
<td align="center">1550</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="center">Hospital C</td>
|
||||
<td align="center">0.4670571</td>
|
||||
<td align="center">683</td>
|
||||
<td align="center">0.4682171</td>
|
||||
<td align="center">645</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="center">Hospital D</td>
|
||||
<td align="center">0.4471101</td>
|
||||
<td align="center">917</td>
|
||||
<td align="center">0.4953380</td>
|
||||
<td align="center">858</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<p>These functions can also be used to get the portion of multiple antibiotics, to calculate co-resistance very easily:</p>
|
||||
<div class="sourceCode" id="cb28"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb28-1" data-line-number="1">data_1st <span class="op">%>%</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb28-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(genus) <span class="op">%>%</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb28-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/summarise.html">summarise</a></span>(<span class="dt">amoxicillin =</span> <span class="kw"><a href="../reference/portion.html">portion_S</a></span>(amcl),</a>
|
||||
<a class="sourceLine" id="cb28-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/group_by">group_by</a></span>(genus) <span class="op">%>%</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb28-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/summarise">summarise</a></span>(<span class="dt">amoxicillin =</span> <span class="kw"><a href="../reference/portion.html">portion_S</a></span>(amcl),</a>
|
||||
<a class="sourceLine" id="cb28-4" data-line-number="4"> <span class="dt">gentamicin =</span> <span class="kw"><a href="../reference/portion.html">portion_S</a></span>(gent),</a>
|
||||
<a class="sourceLine" id="cb28-5" data-line-number="5"> <span class="st">"amox + gent"</span> =<span class="st"> </span><span class="kw"><a href="../reference/portion.html">portion_S</a></span>(amcl, gent))</a></code></pre></div>
|
||||
<table class="table">
|
||||
@ -1016,37 +1023,37 @@ Longest: 24</p>
|
||||
<tbody>
|
||||
<tr class="odd">
|
||||
<td align="center">Escherichia</td>
|
||||
<td align="center">0.7162960</td>
|
||||
<td align="center">0.9051294</td>
|
||||
<td align="center">0.9786655</td>
|
||||
<td align="center">0.7193639</td>
|
||||
<td align="center">0.9111319</td>
|
||||
<td align="center">0.9742750</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="center">Klebsiella</td>
|
||||
<td align="center">0.7494692</td>
|
||||
<td align="center">0.9129512</td>
|
||||
<td align="center">0.9766454</td>
|
||||
<td align="center">0.7226721</td>
|
||||
<td align="center">0.9028340</td>
|
||||
<td align="center">0.9777328</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="center">Staphylococcus</td>
|
||||
<td align="center">0.7341418</td>
|
||||
<td align="center">0.9244403</td>
|
||||
<td align="center">0.9776119</td>
|
||||
<td align="center">0.7392523</td>
|
||||
<td align="center">0.9084112</td>
|
||||
<td align="center">0.9831776</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="center">Streptococcus</td>
|
||||
<td align="center">0.7576197</td>
|
||||
<td align="center">0.7532281</td>
|
||||
<td align="center">0.0000000</td>
|
||||
<td align="center">0.7576197</td>
|
||||
<td align="center">0.7532281</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<p>To make a transition to the next part, let’s see how this difference could be plotted:</p>
|
||||
<div class="sourceCode" id="cb29"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb29-1" data-line-number="1">data_1st <span class="op">%>%</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb29-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(genus) <span class="op">%>%</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb29-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/summarise.html">summarise</a></span>(<span class="st">"1. Amoxicillin"</span> =<span class="st"> </span><span class="kw"><a href="../reference/portion.html">portion_S</a></span>(amcl),</a>
|
||||
<a class="sourceLine" id="cb29-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/group_by">group_by</a></span>(genus) <span class="op">%>%</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb29-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/summarise">summarise</a></span>(<span class="st">"1. Amoxicillin"</span> =<span class="st"> </span><span class="kw"><a href="../reference/portion.html">portion_S</a></span>(amcl),</a>
|
||||
<a class="sourceLine" id="cb29-4" data-line-number="4"> <span class="st">"2. Gentamicin"</span> =<span class="st"> </span><span class="kw"><a href="../reference/portion.html">portion_S</a></span>(gent),</a>
|
||||
<a class="sourceLine" id="cb29-5" data-line-number="5"> <span class="st">"3. Amox + gent"</span> =<span class="st"> </span><span class="kw"><a href="../reference/portion.html">portion_S</a></span>(amcl, gent)) <span class="op">%>%</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb29-6" data-line-number="6"><span class="st"> </span>tidyr<span class="op">::</span><span class="kw"><a href="https://tidyr.tidyverse.org/reference/gather.html">gather</a></span>(<span class="st">"Antibiotic"</span>, <span class="st">"S"</span>, <span class="op">-</span>genus) <span class="op">%>%</span></a>
|
||||
<a class="sourceLine" id="cb29-6" data-line-number="6"><span class="st"> </span>tidyr<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/tidyr/topics/gather">gather</a></span>(<span class="st">"Antibiotic"</span>, <span class="st">"S"</span>, <span class="op">-</span>genus) <span class="op">%>%</span></a>
|
||||
<a class="sourceLine" id="cb29-7" data-line-number="7"><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot</a></span>(<span class="kw"><a href="https://ggplot2.tidyverse.org/reference/aes.html">aes</a></span>(<span class="dt">x =</span> genus,</a>
|
||||
<a class="sourceLine" id="cb29-8" data-line-number="8"> <span class="dt">y =</span> S,</a>
|
||||
<a class="sourceLine" id="cb29-9" data-line-number="9"> <span class="dt">fill =</span> Antibiotic)) <span class="op">+</span></a>
|
||||
@ -1076,7 +1083,7 @@ Longest: 24</p>
|
||||
<p>Omit the <code>translate_ab = FALSE</code> to have the antibiotic codes (amox, amcl, cipr, gent) translated to official WHO names (amoxicillin, amoxicillin and betalactamase inhibitor, ciprofloxacin, gentamicin).</p>
|
||||
<p>If we group on e.g. the <code>genus</code> column and add some additional functions from our package, we can create this:</p>
|
||||
<div class="sourceCode" id="cb32"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb32-1" data-line-number="1"><span class="co"># group the data on `genus`</span></a>
|
||||
<a class="sourceLine" id="cb32-2" data-line-number="2"><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot</a></span>(data_1st <span class="op">%>%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(genus)) <span class="op">+</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb32-2" data-line-number="2"><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot</a></span>(data_1st <span class="op">%>%</span><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/group_by">group_by</a></span>(genus)) <span class="op">+</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb32-3" data-line-number="3"><span class="st"> </span><span class="co"># create bars with genus on x axis</span></a>
|
||||
<a class="sourceLine" id="cb32-4" data-line-number="4"><span class="st"> </span><span class="co"># it looks for variables with class `rsi`,</span></a>
|
||||
<a class="sourceLine" id="cb32-5" data-line-number="5"><span class="st"> </span><span class="co"># of which we have 4 (earlier created with `as.rsi`)</span></a>
|
||||
@ -1098,7 +1105,7 @@ Longest: 24</p>
|
||||
<p><img src="AMR_files/figure-html/plot%204-1.png" width="720"></p>
|
||||
<p>To simplify this, we also created the <code><a href="../reference/ggplot_rsi.html">ggplot_rsi()</a></code> function, which combines almost all above functions:</p>
|
||||
<div class="sourceCode" id="cb33"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb33-1" data-line-number="1">data_1st <span class="op">%>%</span><span class="st"> </span></a>
|
||||
<a class="sourceLine" id="cb33-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(genus) <span class="op">%>%</span></a>
|
||||
<a class="sourceLine" id="cb33-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/group_by">group_by</a></span>(genus) <span class="op">%>%</span></a>
|
||||
<a class="sourceLine" id="cb33-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="../reference/ggplot_rsi.html">ggplot_rsi</a></span>(<span class="dt">x =</span> <span class="st">"genus"</span>,</a>
|
||||
<a class="sourceLine" id="cb33-4" data-line-number="4"> <span class="dt">facet =</span> <span class="st">"Antibiotic"</span>,</a>
|
||||
<a class="sourceLine" id="cb33-5" data-line-number="5"> <span class="dt">breaks =</span> <span class="dv">0</span><span class="op">:</span><span class="dv">4</span> <span class="op">*</span><span class="st"> </span><span class="dv">25</span>,</a>
|
||||
@ -1132,12 +1139,12 @@ Longest: 24</p>
|
||||
</table>
|
||||
<p>We can transform the data and apply the test in only a couple of lines:</p>
|
||||
<div class="sourceCode" id="cb34"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb34-1" data-line-number="1">septic_patients <span class="op">%>%</span></a>
|
||||
<a class="sourceLine" id="cb34-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(hospital_id <span class="op">%in%</span><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">"A"</span>, <span class="st">"D"</span>)) <span class="op">%>%</span><span class="st"> </span><span class="co"># filter on only hospitals A and D</span></a>
|
||||
<a class="sourceLine" id="cb34-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(hospital_id, fosf) <span class="op">%>%</span><span class="st"> </span><span class="co"># select the hospitals and fosfomycin</span></a>
|
||||
<a class="sourceLine" id="cb34-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital_id) <span class="op">%>%</span><span class="st"> </span><span class="co"># group on the hospitals</span></a>
|
||||
<a class="sourceLine" id="cb34-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/filter">filter</a></span>(hospital_id <span class="op">%in%</span><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">"A"</span>, <span class="st">"D"</span>)) <span class="op">%>%</span><span class="st"> </span><span class="co"># filter on only hospitals A and D</span></a>
|
||||
<a class="sourceLine" id="cb34-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/select">select</a></span>(hospital_id, fosf) <span class="op">%>%</span><span class="st"> </span><span class="co"># select the hospitals and fosfomycin</span></a>
|
||||
<a class="sourceLine" id="cb34-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/group_by">group_by</a></span>(hospital_id) <span class="op">%>%</span><span class="st"> </span><span class="co"># group on the hospitals</span></a>
|
||||
<a class="sourceLine" id="cb34-5" data-line-number="5"><span class="st"> </span><span class="kw"><a href="../reference/count.html">count_df</a></span>(<span class="dt">combine_IR =</span> <span class="ot">TRUE</span>) <span class="op">%>%</span><span class="st"> </span><span class="co"># count all isolates per group (hospital_id)</span></a>
|
||||
<a class="sourceLine" id="cb34-6" data-line-number="6"><span class="st"> </span>tidyr<span class="op">::</span><span class="kw"><a href="https://tidyr.tidyverse.org/reference/spread.html">spread</a></span>(hospital_id, Value) <span class="op">%>%</span><span class="st"> </span><span class="co"># transform output so A and D are columns</span></a>
|
||||
<a class="sourceLine" id="cb34-7" data-line-number="7"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(A, D) <span class="op">%>%</span><span class="st"> </span><span class="co"># and select these only</span></a>
|
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<a class="sourceLine" id="cb34-6" data-line-number="6"><span class="st"> </span>tidyr<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/tidyr/topics/spread">spread</a></span>(hospital_id, Value) <span class="op">%>%</span><span class="st"> </span><span class="co"># transform output so A and D are columns</span></a>
|
||||
<a class="sourceLine" id="cb34-7" data-line-number="7"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/select">select</a></span>(A, D) <span class="op">%>%</span><span class="st"> </span><span class="co"># and select these only</span></a>
|
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<a class="sourceLine" id="cb34-8" data-line-number="8"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/matrix">as.matrix</a></span>() <span class="op">%>%</span><span class="st"> </span><span class="co"># transform to good old matrix for fisher.test()</span></a>
|
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<a class="sourceLine" id="cb34-9" data-line-number="9"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/stats/topics/fisher.test">fisher.test</a></span>() <span class="co"># do Fisher's Exact Test</span></a>
|
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<a class="sourceLine" id="cb34-10" data-line-number="10"><span class="co"># </span></a>
|
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Use the G-test
|
||||
</a>
|
||||
</li>
|
||||
<li>
|
||||
<a href="../articles/benchmarks.html">
|
||||
<span class="fa fa-shipping-fast"></span>
|
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|
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Other: benchmarks
|
||||
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|
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|
||||
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|
||||
</li>
|
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|
||||
@ -171,7 +178,7 @@
|
||||
<h1>How to apply EUCAST rules</h1>
|
||||
<h4 class="author">Matthijs S. Berends</h4>
|
||||
|
||||
<h4 class="date">08 January 2019</h4>
|
||||
<h4 class="date">11 January 2019</h4>
|
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|
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|
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<div class="hidden name"><code>EUCAST.Rmd</code></div>
|
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|
||||
@ -111,6 +111,13 @@
|
||||
Use the G-test
|
||||
</a>
|
||||
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|
||||
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|
||||
<a href="../articles/benchmarks.html">
|
||||
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|
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|
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Other: benchmarks
|
||||
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|
||||
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|
||||
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|
||||
</li>
|
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<li>
|
||||
@ -171,7 +178,7 @@
|
||||
<h1>How to use the <em>G</em>-test</h1>
|
||||
<h4 class="author">Matthijs S. Berends</h4>
|
||||
|
||||
<h4 class="date">08 January 2019</h4>
|
||||
<h4 class="date">11 January 2019</h4>
|
||||
|
||||
|
||||
<div class="hidden name"><code>G_test.Rmd</code></div>
|
||||
|
||||
@ -111,6 +111,13 @@
|
||||
Use the G-test
|
||||
</a>
|
||||
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|
||||
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|
||||
<a href="../articles/benchmarks.html">
|
||||
<span class="fa fa-shipping-fast"></span>
|
||||
|
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Other: benchmarks
|
||||
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|
||||
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|
||||
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|
||||
</li>
|
||||
<li>
|
||||
@ -171,7 +178,7 @@
|
||||
<h1>How to predict antimicrobial resistance</h1>
|
||||
<h4 class="author">Matthijs S. Berends</h4>
|
||||
|
||||
<h4 class="date">08 January 2019</h4>
|
||||
<h4 class="date">11 January 2019</h4>
|
||||
|
||||
|
||||
<div class="hidden name"><code>Predict.Rmd</code></div>
|
||||
|
||||
@ -111,6 +111,13 @@
|
||||
Use the G-test
|
||||
</a>
|
||||
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|
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|
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<a href="../articles/benchmarks.html">
|
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|
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|
||||
</li>
|
||||
<li>
|
||||
@ -171,7 +178,7 @@
|
||||
<h1>How to get properties of an antibiotic</h1>
|
||||
<h4 class="author">Matthijs S. Berends</h4>
|
||||
|
||||
<h4 class="date">08 January 2019</h4>
|
||||
<h4 class="date">11 January 2019</h4>
|
||||
|
||||
|
||||
<div class="hidden name"><code>ab_property.Rmd</code></div>
|
||||
|
||||
371
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Normal file
371
docs/articles/benchmarks.html
Normal file
@ -0,0 +1,371 @@
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<h1>Benchmarks</h1>
|
||||
<h4 class="author">Matthijs S. Berends</h4>
|
||||
|
||||
<h4 class="date">11 January 2019</h4>
|
||||
|
||||
|
||||
<div class="hidden name"><code>benchmarks.Rmd</code></div>
|
||||
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||||
</div>
|
||||
|
||||
|
||||
|
||||
<p>One of the most important features of this package is the complete microbial taxonomic database, supplied by ITIS (<a href="https://www.itis.gov" class="uri">https://www.itis.gov</a>). We created a function <code><a href="../reference/as.mo.html">as.mo()</a></code> that transforms any user input value to a valid microbial ID by using AI (Artificial Intelligence) and based on the taxonomic tree of ITIS.</p>
|
||||
<p>Using the <code>microbenchmark</code> package, we can review the calculation performance of this function.</p>
|
||||
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(microbenchmark)</a></code></pre></div>
|
||||
<p>In the next test, we try to ‘coerce’ different input values for <em>Staphylococcus aureus</em>. The actual result is the same every time: it returns its MO code <code>B_STPHY_AUR</code> (<em>B</em> stands for <em>Bacteria</em>, the taxonomic kingdom).</p>
|
||||
<p>But the calculation time differs a lot. Here, the AI effect can be reviewed best:</p>
|
||||
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb2-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="dt">A =</span> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"stau"</span>),</a>
|
||||
<a class="sourceLine" id="cb2-2" data-line-number="2"> <span class="dt">B =</span> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"staaur"</span>),</a>
|
||||
<a class="sourceLine" id="cb2-3" data-line-number="3"> <span class="dt">C =</span> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"S. aureus"</span>),</a>
|
||||
<a class="sourceLine" id="cb2-4" data-line-number="4"> <span class="dt">D =</span> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"S. aureus"</span>),</a>
|
||||
<a class="sourceLine" id="cb2-5" data-line-number="5"> <span class="dt">E =</span> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"STAAUR"</span>),</a>
|
||||
<a class="sourceLine" id="cb2-6" data-line-number="6"> <span class="dt">F =</span> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"Staphylococcus aureus"</span>),</a>
|
||||
<a class="sourceLine" id="cb2-7" data-line-number="7"> <span class="dt">G =</span> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"B_STPHY_AUR"</span>),</a>
|
||||
<a class="sourceLine" id="cb2-8" data-line-number="8"> <span class="dt">times =</span> <span class="dv">10</span>,</a>
|
||||
<a class="sourceLine" id="cb2-9" data-line-number="9"> <span class="dt">unit =</span> <span class="st">"ms"</span>)</a>
|
||||
<a class="sourceLine" id="cb2-10" data-line-number="10"><span class="co"># Unit: milliseconds</span></a>
|
||||
<a class="sourceLine" id="cb2-11" data-line-number="11"><span class="co"># expr min lq mean median uq max neval</span></a>
|
||||
<a class="sourceLine" id="cb2-12" data-line-number="12"><span class="co"># A 34.745551 34.798630 35.2596102 34.8994810 35.258325 38.067062 10</span></a>
|
||||
<a class="sourceLine" id="cb2-13" data-line-number="13"><span class="co"># B 7.095386 7.125348 7.2219948 7.1613865 7.240377 7.495857 10</span></a>
|
||||
<a class="sourceLine" id="cb2-14" data-line-number="14"><span class="co"># C 11.677114 11.733826 11.8304789 11.7715050 11.843756 12.317559 10</span></a>
|
||||
<a class="sourceLine" id="cb2-15" data-line-number="15"><span class="co"># D 11.694435 11.730054 11.9859313 11.8775585 12.206371 12.750016 10</span></a>
|
||||
<a class="sourceLine" id="cb2-16" data-line-number="16"><span class="co"># E 7.044402 7.117387 7.2271630 7.1923610 7.246104 7.742396 10</span></a>
|
||||
<a class="sourceLine" id="cb2-17" data-line-number="17"><span class="co"># F 6.642326 6.778446 6.8988042 6.8753165 6.923577 7.513945 10</span></a>
|
||||
<a class="sourceLine" id="cb2-18" data-line-number="18"><span class="co"># G 0.106788 0.131023 0.1351229 0.1357725 0.144014 0.146458 10</span></a></code></pre></div>
|
||||
<p>In the table above, all measurements are shown in milliseconds (thousands of seconds), tested on a quite regular Linux server from 2007 (Core 2 Duo 2.7 GHz, 2 GB DDR2 RAM). A value of 6.9 milliseconds means it will roughly determine 144 input values per second. It case of 39.2 milliseconds, this is only 26 input values per second. The more an input value resembles a full name (like C, D and F), the faster the result will be found. In case of G, the input is already a valid MO code, so it only almost takes no time at all (0.0001 seconds on our server).</p>
|
||||
<p>To achieve this speed, the <code>as.mo</code> function also takes into account the prevalence of human pathogenic microorganisms. The downside is of course that less prevalent microorganisms will be determined far less faster. See this example for the ID of <em>Burkholderia nodosa</em> (<code>B_BRKHL_NOD</code>):</p>
|
||||
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="dt">A =</span> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"buno"</span>),</a>
|
||||
<a class="sourceLine" id="cb3-2" data-line-number="2"> <span class="dt">B =</span> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"burnod"</span>),</a>
|
||||
<a class="sourceLine" id="cb3-3" data-line-number="3"> <span class="dt">C =</span> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"B. nodosa"</span>),</a>
|
||||
<a class="sourceLine" id="cb3-4" data-line-number="4"> <span class="dt">D =</span> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"B. nodosa"</span>),</a>
|
||||
<a class="sourceLine" id="cb3-5" data-line-number="5"> <span class="dt">E =</span> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"BURNOD"</span>),</a>
|
||||
<a class="sourceLine" id="cb3-6" data-line-number="6"> <span class="dt">F =</span> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"Burkholderia nodosa"</span>),</a>
|
||||
<a class="sourceLine" id="cb3-7" data-line-number="7"> <span class="dt">G =</span> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"B_BRKHL_NOD"</span>),</a>
|
||||
<a class="sourceLine" id="cb3-8" data-line-number="8"> <span class="dt">times =</span> <span class="dv">10</span>,</a>
|
||||
<a class="sourceLine" id="cb3-9" data-line-number="9"> <span class="dt">unit =</span> <span class="st">"ms"</span>)</a>
|
||||
<a class="sourceLine" id="cb3-10" data-line-number="10"><span class="co"># Unit: milliseconds</span></a>
|
||||
<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># expr min lq mean median uq max neval</span></a>
|
||||
<a class="sourceLine" id="cb3-12" data-line-number="12"><span class="co"># A 124.175427 124.474837 125.8610536 125.3750560 126.160945 131.485994 10</span></a>
|
||||
<a class="sourceLine" id="cb3-13" data-line-number="13"><span class="co"># B 154.249713 155.364729 160.9077032 156.8738940 157.136183 197.315105 10</span></a>
|
||||
<a class="sourceLine" id="cb3-14" data-line-number="14"><span class="co"># C 66.066571 66.162393 66.5538611 66.4488130 66.698077 67.623404 10</span></a>
|
||||
<a class="sourceLine" id="cb3-15" data-line-number="15"><span class="co"># D 86.747693 86.918665 90.7831016 87.8149725 89.440982 116.767991 10</span></a>
|
||||
<a class="sourceLine" id="cb3-16" data-line-number="16"><span class="co"># E 154.863827 155.208563 162.6535954 158.4062465 168.593785 187.378088 10</span></a>
|
||||
<a class="sourceLine" id="cb3-17" data-line-number="17"><span class="co"># F 32.427028 32.638648 32.9929454 32.7860475 32.992813 34.674241 10</span></a>
|
||||
<a class="sourceLine" id="cb3-18" data-line-number="18"><span class="co"># G 0.213155 0.216578 0.2369226 0.2338985 0.253734 0.285581 10</span></a></code></pre></div>
|
||||
<p>That takes up to 11 times as much time! A value of 158.4 milliseconds means it can only determine ~6 different input values per second. We can conclude that looking up arbitrary codes of less prevalent microorganisms is the worst way to go, in terms of calculation performance.</p>
|
||||
<p>To relieve this pitfall and further improve performance, two important calculations take almost no time at all: <strong>repetitive results</strong> and <strong>already precalculated results</strong>.</p>
|
||||
<div id="repetitive-results" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#repetitive-results" class="anchor"></a>Repetitive results</h3>
|
||||
<p>Repetitive results mean that unique values are present more than once. Unique values will only be calculated once by <code><a href="../reference/as.mo.html">as.mo()</a></code>. We will use <code><a href="../reference/mo_property.html">mo_fullname()</a></code> for this test - a helper function that returns the full microbial name (genus, species and possibly subspecies) and uses <code><a href="../reference/as.mo.html">as.mo()</a></code> internally.</p>
|
||||
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(dplyr)</a>
|
||||
<a class="sourceLine" id="cb4-2" data-line-number="2"><span class="co"># take 500,000 random MO codes from the septic_patients data set</span></a>
|
||||
<a class="sourceLine" id="cb4-3" data-line-number="3">x =<span class="st"> </span>septic_patients <span class="op">%>%</span></a>
|
||||
<a class="sourceLine" id="cb4-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/sample">sample_n</a></span>(<span class="dv">500000</span>, <span class="dt">replace =</span> <span class="ot">TRUE</span>) <span class="op">%>%</span></a>
|
||||
<a class="sourceLine" id="cb4-5" data-line-number="5"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/pull">pull</a></span>(mo)</a>
|
||||
<a class="sourceLine" id="cb4-6" data-line-number="6"> </a>
|
||||
<a class="sourceLine" id="cb4-7" data-line-number="7"><span class="co"># got the right length?</span></a>
|
||||
<a class="sourceLine" id="cb4-8" data-line-number="8"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/length">length</a></span>(x)</a>
|
||||
<a class="sourceLine" id="cb4-9" data-line-number="9"><span class="co"># [1] 500000</span></a>
|
||||
<a class="sourceLine" id="cb4-10" data-line-number="10"></a>
|
||||
<a class="sourceLine" id="cb4-11" data-line-number="11"><span class="co"># and how many unique values do we have?</span></a>
|
||||
<a class="sourceLine" id="cb4-12" data-line-number="12"><span class="kw"><a href="https://www.rdocumentation.org/packages/dplyr/topics/n_distinct">n_distinct</a></span>(x)</a>
|
||||
<a class="sourceLine" id="cb4-13" data-line-number="13"><span class="co"># [1] 96</span></a>
|
||||
<a class="sourceLine" id="cb4-14" data-line-number="14"></a>
|
||||
<a class="sourceLine" id="cb4-15" data-line-number="15"><span class="co"># only 96, but distributed in 500,000 results. now let's see:</span></a>
|
||||
<a class="sourceLine" id="cb4-16" data-line-number="16"><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="dt">X =</span> <span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(x),</a>
|
||||
<a class="sourceLine" id="cb4-17" data-line-number="17"> <span class="dt">times =</span> <span class="dv">10</span>,</a>
|
||||
<a class="sourceLine" id="cb4-18" data-line-number="18"> <span class="dt">unit =</span> <span class="st">"ms"</span>)</a>
|
||||
<a class="sourceLine" id="cb4-19" data-line-number="19"><span class="co"># Unit: milliseconds</span></a>
|
||||
<a class="sourceLine" id="cb4-20" data-line-number="20"><span class="co"># expr min lq mean median uq max neval</span></a>
|
||||
<a class="sourceLine" id="cb4-21" data-line-number="21"><span class="co"># X 114.9342 117.1076 129.6448 120.2047 131.5005 168.6371 10</span></a></code></pre></div>
|
||||
<p>So transforming 500,000 values (!) of 96 unique values only takes 0.12 seconds (120 ms). You only lose time on your unique input values.</p>
|
||||
<p>Results of a tenfold - 5,000,000 values:</p>
|
||||
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" data-line-number="1"><span class="co"># Unit: milliseconds</span></a>
|
||||
<a class="sourceLine" id="cb5-2" data-line-number="2"><span class="co"># expr min lq mean median uq max neval</span></a>
|
||||
<a class="sourceLine" id="cb5-3" data-line-number="3"><span class="co"># X 882.9045 901.3011 1001.677 940.3421 1168.088 1226.846 10</span></a></code></pre></div>
|
||||
<p>Even the full names of 5 <em>Million</em> values are calculated within a second.</p>
|
||||
</div>
|
||||
<div id="precalculated-results" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#precalculated-results" class="anchor"></a>Precalculated results</h3>
|
||||
<p>What about precalculated results? If the input is an already precalculated result of a helper function like <code><a href="../reference/mo_property.html">mo_fullname()</a></code>, it almost doesn’t take any time at all (see ‘C’ below):</p>
|
||||
<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb6-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="dt">A =</span> <span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"B_STPHY_AUR"</span>),</a>
|
||||
<a class="sourceLine" id="cb6-2" data-line-number="2"> <span class="dt">B =</span> <span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"S. aureus"</span>),</a>
|
||||
<a class="sourceLine" id="cb6-3" data-line-number="3"> <span class="dt">C =</span> <span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"Staphylococcus aureus"</span>),</a>
|
||||
<a class="sourceLine" id="cb6-4" data-line-number="4"> <span class="dt">times =</span> <span class="dv">10</span>,</a>
|
||||
<a class="sourceLine" id="cb6-5" data-line-number="5"> <span class="dt">unit =</span> <span class="st">"ms"</span>)</a>
|
||||
<a class="sourceLine" id="cb6-6" data-line-number="6"><span class="co"># Unit: milliseconds</span></a>
|
||||
<a class="sourceLine" id="cb6-7" data-line-number="7"><span class="co"># expr min lq mean median uq max neval</span></a>
|
||||
<a class="sourceLine" id="cb6-8" data-line-number="8"><span class="co"># A 11.364086 11.460537 11.5104799 11.4795330 11.524860 11.818263 10</span></a>
|
||||
<a class="sourceLine" id="cb6-9" data-line-number="9"><span class="co"># B 11.976454 12.012352 12.1704592 12.0853020 12.210004 12.881737 10</span></a>
|
||||
<a class="sourceLine" id="cb6-10" data-line-number="10"><span class="co"># C 0.095823 0.102528 0.1167754 0.1153785 0.132629 0.140661 10</span></a></code></pre></div>
|
||||
<p>So going from <code><a href="../reference/mo_property.html">mo_fullname("Staphylococcus aureus")</a></code> to <code>"Staphylococcus aureus"</code> takes 0.0001 seconds - it doesn’t even start calculating <em>if the result would be the same as the expected resulting value</em>. That goes for all helper functions:</p>
|
||||
<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb7-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="dt">A =</span> <span class="kw"><a href="../reference/mo_property.html">mo_species</a></span>(<span class="st">"aureus"</span>),</a>
|
||||
<a class="sourceLine" id="cb7-2" data-line-number="2"> <span class="dt">B =</span> <span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(<span class="st">"Staphylococcus"</span>),</a>
|
||||
<a class="sourceLine" id="cb7-3" data-line-number="3"> <span class="dt">C =</span> <span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"Staphylococcus aureus"</span>),</a>
|
||||
<a class="sourceLine" id="cb7-4" data-line-number="4"> <span class="dt">D =</span> <span class="kw"><a href="../reference/mo_property.html">mo_family</a></span>(<span class="st">"Staphylococcaceae"</span>),</a>
|
||||
<a class="sourceLine" id="cb7-5" data-line-number="5"> <span class="dt">E =</span> <span class="kw"><a href="../reference/mo_property.html">mo_order</a></span>(<span class="st">"Bacillales"</span>),</a>
|
||||
<a class="sourceLine" id="cb7-6" data-line-number="6"> <span class="dt">F =</span> <span class="kw"><a href="../reference/mo_property.html">mo_class</a></span>(<span class="st">"Bacilli"</span>),</a>
|
||||
<a class="sourceLine" id="cb7-7" data-line-number="7"> <span class="dt">G =</span> <span class="kw"><a href="../reference/mo_property.html">mo_phylum</a></span>(<span class="st">"Firmicutes"</span>),</a>
|
||||
<a class="sourceLine" id="cb7-8" data-line-number="8"> <span class="dt">H =</span> <span class="kw"><a href="../reference/mo_property.html">mo_subkingdom</a></span>(<span class="st">"Posibacteria"</span>),</a>
|
||||
<a class="sourceLine" id="cb7-9" data-line-number="9"> <span class="dt">I =</span> <span class="kw"><a href="../reference/mo_property.html">mo_kingdom</a></span>(<span class="st">"Bacteria"</span>),</a>
|
||||
<a class="sourceLine" id="cb7-10" data-line-number="10"> <span class="dt">times =</span> <span class="dv">10</span>,</a>
|
||||
<a class="sourceLine" id="cb7-11" data-line-number="11"> <span class="dt">unit =</span> <span class="st">"ms"</span>)</a>
|
||||
<a class="sourceLine" id="cb7-12" data-line-number="12"><span class="co"># Unit: milliseconds</span></a>
|
||||
<a class="sourceLine" id="cb7-13" data-line-number="13"><span class="co"># expr min lq mean median uq max neval</span></a>
|
||||
<a class="sourceLine" id="cb7-14" data-line-number="14"><span class="co"># A 0.105181 0.121314 0.1478538 0.1465265 0.166711 0.211409 10</span></a>
|
||||
<a class="sourceLine" id="cb7-15" data-line-number="15"><span class="co"># B 0.132558 0.146388 0.1584278 0.1499835 0.164895 0.208477 10</span></a>
|
||||
<a class="sourceLine" id="cb7-16" data-line-number="16"><span class="co"># C 0.135492 0.160355 0.2341847 0.1884665 0.348857 0.395931 10</span></a>
|
||||
<a class="sourceLine" id="cb7-17" data-line-number="17"><span class="co"># D 0.109650 0.115727 0.1270481 0.1264130 0.128648 0.168317 10</span></a>
|
||||
<a class="sourceLine" id="cb7-18" data-line-number="18"><span class="co"># E 0.081574 0.096940 0.0992582 0.0980915 0.101479 0.120477 10</span></a>
|
||||
<a class="sourceLine" id="cb7-19" data-line-number="19"><span class="co"># F 0.081575 0.088489 0.0988463 0.0989650 0.103365 0.126482 10</span></a>
|
||||
<a class="sourceLine" id="cb7-20" data-line-number="20"><span class="co"># G 0.091981 0.095333 0.1043568 0.1001530 0.111327 0.129625 10</span></a>
|
||||
<a class="sourceLine" id="cb7-21" data-line-number="21"><span class="co"># H 0.092610 0.093169 0.1009135 0.0985455 0.101828 0.120406 10</span></a>
|
||||
<a class="sourceLine" id="cb7-22" data-line-number="22"><span class="co"># I 0.087371 0.091213 0.1069758 0.0941815 0.109302 0.192831 10</span></a></code></pre></div>
|
||||
<p>Of course, when running <code><a href="../reference/mo_property.html">mo_phylum("Firmicutes")</a></code> the function has zero knowledge about the actual microorganism, namely <em>S. aureus</em>. But since the result would be <code>"Firmicutes"</code> too, there is no point in calculating the result. And because this package ‘knows’ all phyla of all known microorganisms (according to ITIS), it can just return the initial value immediately.</p>
|
||||
</div>
|
||||
<div id="results-in-other-languages" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#results-in-other-languages" class="anchor"></a>Results in other languages</h3>
|
||||
<p>When the system language is non-English and supported by this <code>AMR</code> package, some functions take a little while longer:</p>
|
||||
<div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb8-1" data-line-number="1"><span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"en"</span>) <span class="co"># or just mo_fullname("CoNS") on an English system</span></a>
|
||||
<a class="sourceLine" id="cb8-2" data-line-number="2"><span class="co"># "Coagulase Negative Staphylococcus (CoNS)"</span></a>
|
||||
<a class="sourceLine" id="cb8-3" data-line-number="3"></a>
|
||||
<a class="sourceLine" id="cb8-4" data-line-number="4"><span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"fr"</span>) <span class="co"># or just mo_fullname("CoNS") on a French system</span></a>
|
||||
<a class="sourceLine" id="cb8-5" data-line-number="5"><span class="co"># "Staphylococcus à coagulase négative (CoNS)"</span></a>
|
||||
<a class="sourceLine" id="cb8-6" data-line-number="6"></a>
|
||||
<a class="sourceLine" id="cb8-7" data-line-number="7"><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="dt">en =</span> <span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"en"</span>),</a>
|
||||
<a class="sourceLine" id="cb8-8" data-line-number="8"> <span class="dt">de =</span> <span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"de"</span>),</a>
|
||||
<a class="sourceLine" id="cb8-9" data-line-number="9"> <span class="dt">nl =</span> <span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"nl"</span>),</a>
|
||||
<a class="sourceLine" id="cb8-10" data-line-number="10"> <span class="dt">es =</span> <span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"es"</span>),</a>
|
||||
<a class="sourceLine" id="cb8-11" data-line-number="11"> <span class="dt">it =</span> <span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"it"</span>),</a>
|
||||
<a class="sourceLine" id="cb8-12" data-line-number="12"> <span class="dt">fr =</span> <span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"fr"</span>),</a>
|
||||
<a class="sourceLine" id="cb8-13" data-line-number="13"> <span class="dt">pt =</span> <span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"pt"</span>),</a>
|
||||
<a class="sourceLine" id="cb8-14" data-line-number="14"> <span class="dt">times =</span> <span class="dv">10</span>,</a>
|
||||
<a class="sourceLine" id="cb8-15" data-line-number="15"> <span class="dt">unit =</span> <span class="st">"ms"</span>)</a>
|
||||
<a class="sourceLine" id="cb8-16" data-line-number="16"><span class="co"># Unit: milliseconds</span></a>
|
||||
<a class="sourceLine" id="cb8-17" data-line-number="17"><span class="co"># expr min lq mean median uq max neval</span></a>
|
||||
<a class="sourceLine" id="cb8-18" data-line-number="18"><span class="co"># en 6.093583 6.51724 6.555105 6.562986 6.630663 6.99698 100</span></a>
|
||||
<a class="sourceLine" id="cb8-19" data-line-number="19"><span class="co"># de 13.934874 14.35137 16.891587 14.462210 14.764658 43.63956 100</span></a>
|
||||
<a class="sourceLine" id="cb8-20" data-line-number="20"><span class="co"># nl 13.900092 14.34729 15.943268 14.424565 14.581535 43.76283 100</span></a>
|
||||
<a class="sourceLine" id="cb8-21" data-line-number="21"><span class="co"># es 13.833813 14.34596 14.574783 14.439757 14.653994 17.49168 100</span></a>
|
||||
<a class="sourceLine" id="cb8-22" data-line-number="22"><span class="co"># it 13.811883 14.36621 15.179060 14.453515 14.812359 43.64284 100</span></a>
|
||||
<a class="sourceLine" id="cb8-23" data-line-number="23"><span class="co"># fr 13.798683 14.37019 16.344731 14.468775 14.697610 48.62923 100</span></a>
|
||||
<a class="sourceLine" id="cb8-24" data-line-number="24"><span class="co"># pt 13.789674 14.36244 15.706321 14.443772 14.679905 44.76701 100</span></a></code></pre></div>
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||||
<p>Currently supported are German, Dutch, Spanish, Italian, French and Portuguese.</p>
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@ -111,6 +111,13 @@
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Use the G-test
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Other: benchmarks
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@ -171,7 +178,7 @@
|
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<h1>How to create frequency tables</h1>
|
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<h4 class="author">Matthijs S. Berends</h4>
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<h4 class="date">08 January 2019</h4>
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<h4 class="date">11 January 2019</h4>
|
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<div class="hidden name"><code>freq.Rmd</code></div>
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@ -149,6 +149,13 @@
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Use the G-test
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Use the G-test
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@ -171,7 +178,7 @@
|
||||
<h1>How to get properties of a microorganism</h1>
|
||||
<h4 class="author">Matthijs S. Berends</h4>
|
||||
|
||||
<h4 class="date">08 January 2019</h4>
|
||||
<h4 class="date">11 January 2019</h4>
|
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<div class="hidden name"><code>mo_property.Rmd</code></div>
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Reference in New Issue
Block a user