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@ -192,7 +192,7 @@
<h1>How to conduct AMR analysis</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">18 February 2019</h4>
<h4 class="date">20 February 2019</h4>
<div class="hidden name"><code>AMR.Rmd</code></div>
@ -201,7 +201,7 @@
<p><strong>Note:</strong> values on this page will change with every website update since they are based on randomly created values and the page was written in <a href="https://rmarkdown.rstudio.com/">RMarkdown</a>. However, the methodology remains unchanged. This page was generated on 18 February 2019.</p>
<p><strong>Note:</strong> values on this page will change with every website update since they are based on randomly created values and the page was written in <a href="https://rmarkdown.rstudio.com/">RMarkdown</a>. However, the methodology remains unchanged. This page was generated on 20 February 2019.</p>
<div id="introduction" class="section level1">
<h1 class="hasAnchor">
<a href="#introduction" class="anchor"></a>Introduction</h1>
@ -217,21 +217,21 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2019-02-18</td>
<td align="center">2019-02-20</td>
<td align="center">abcd</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">S</td>
</tr>
<tr class="even">
<td align="center">2019-02-18</td>
<td align="center">2019-02-20</td>
<td align="center">abcd</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">R</td>
</tr>
<tr class="odd">
<td align="center">2019-02-18</td>
<td align="center">2019-02-20</td>
<td align="center">efgh</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
@ -327,71 +327,71 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2011-01-25</td>
<td align="center">V6</td>
<td align="center">Hospital A</td>
<td align="center">Staphylococcus aureus</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2013-07-31</td>
<td align="center">A8</td>
<td align="center">Hospital D</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="odd">
<td align="center">2016-10-12</td>
<td align="center">Y3</td>
<td align="center">Hospital D</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2013-12-31</td>
<td align="center">B4</td>
<td align="center">2012-08-24</td>
<td align="center">V3</td>
<td align="center">Hospital B</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
<td align="center">F</td>
</tr>
<tr class="odd">
<td align="center">2014-08-10</td>
<td align="center">F9</td>
<td align="center">Hospital A</td>
<tr class="even">
<td align="center">2013-04-28</td>
<td align="center">S3</td>
<td align="center">Hospital B</td>
<td align="center">Staphylococcus aureus</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="odd">
<td align="center">2013-05-13</td>
<td align="center">F2</td>
<td align="center">Hospital D</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>
</tr>
<tr class="even">
<td align="center">2017-12-05</td>
<td align="center">H7</td>
<td align="center">Hospital A</td>
<td align="center">2017-04-04</td>
<td align="center">I9</td>
<td align="center">Hospital C</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="odd">
<td align="center">2015-12-23</td>
<td align="center">G9</td>
<td align="center">Hospital B</td>
<td align="center">Staphylococcus aureus</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="even">
<td align="center">2011-12-19</td>
<td align="center">T2</td>
<td align="center">Hospital B</td>
<td align="center">Staphylococcus aureus</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
</tbody>
</table>
<p>Now, let’s start the cleaning and the analysis!</p>
@ -411,8 +411,8 @@
#&gt;
#&gt; Item Count Percent Cum. Count Cum. Percent
#&gt; --- ----- ------- -------- ----------- -------------
#&gt; 1 M 10,283 51.4% 10,283 51.4%
#&gt; 2 F 9,717 48.6% 20,000 100.0%</code></pre>
#&gt; 1 M 10,471 52.4% 10,471 52.4%
#&gt; 2 F 9,529 47.6% 20,000 100.0%</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>
<div class="sourceCode" id="cb12"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb12-1" title="1">data &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span></a>
@ -443,10 +443,10 @@
<a class="sourceLine" id="cb14-19" title="19"><span class="co">#&gt; Kingella kingae (no changes)</span></a>
<a class="sourceLine" id="cb14-20" title="20"><span class="co">#&gt; </span></a>
<a class="sourceLine" id="cb14-21" title="21"><span class="co">#&gt; EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes (v3.1, 2016)</span></a>
<a class="sourceLine" id="cb14-22" title="22"><span class="co">#&gt; Table 1: Intrinsic resistance in Enterobacteriaceae (1294 changes)</span></a>
<a class="sourceLine" id="cb14-22" title="22"><span class="co">#&gt; Table 1: Intrinsic resistance in Enterobacteriaceae (1288 changes)</span></a>
<a class="sourceLine" id="cb14-23" title="23"><span class="co">#&gt; Table 2: Intrinsic resistance in non-fermentative Gram-negative bacteria (no changes)</span></a>
<a class="sourceLine" id="cb14-24" title="24"><span class="co">#&gt; Table 3: Intrinsic resistance in other Gram-negative bacteria (no changes)</span></a>
<a class="sourceLine" id="cb14-25" title="25"><span class="co">#&gt; Table 4: Intrinsic resistance in Gram-positive bacteria (2822 changes)</span></a>
<a class="sourceLine" id="cb14-25" title="25"><span class="co">#&gt; Table 4: Intrinsic resistance in Gram-positive bacteria (2757 changes)</span></a>
<a class="sourceLine" id="cb14-26" title="26"><span class="co">#&gt; Table 8: Interpretive rules for B-lactam agents and Gram-positive cocci (no changes)</span></a>
<a class="sourceLine" id="cb14-27" title="27"><span class="co">#&gt; Table 9: Interpretive rules for B-lactam agents and Gram-negative rods (no changes)</span></a>
<a class="sourceLine" id="cb14-28" title="28"><span class="co">#&gt; Table 10: Interpretive rules for B-lactam agents and other Gram-negative bacteria (no changes)</span></a>
@ -462,9 +462,9 @@
<a class="sourceLine" id="cb14-38" title="38"><span class="co">#&gt; Non-EUCAST: piperacillin/tazobactam = S where piperacillin = S (no changes)</span></a>
<a class="sourceLine" id="cb14-39" title="39"><span class="co">#&gt; Non-EUCAST: trimethoprim/sulfa = S where trimethoprim = S (no changes)</span></a>
<a class="sourceLine" id="cb14-40" title="40"><span class="co">#&gt; </span></a>
<a class="sourceLine" id="cb14-41" title="41"><span class="co">#&gt; =&gt; EUCAST rules affected 7,463 out of 20,000 rows</span></a>
<a class="sourceLine" id="cb14-41" title="41"><span class="co">#&gt; =&gt; EUCAST rules affected 7,243 out of 20,000 rows</span></a>
<a class="sourceLine" id="cb14-42" title="42"><span class="co">#&gt; -&gt; added 0 test results</span></a>
<a class="sourceLine" id="cb14-43" title="43"><span class="co">#&gt; -&gt; changed 4,116 test results (0 to S; 0 to I; 4,116 to R)</span></a></code></pre></div>
<a class="sourceLine" id="cb14-43" title="43"><span class="co">#&gt; -&gt; changed 4,045 test results (0 to S; 0 to I; 4,045 to R)</span></a></code></pre></div>
</div>
<div id="adding-new-variables" class="section level1">
<h1 class="hasAnchor">
@ -489,8 +489,8 @@
<a class="sourceLine" id="cb16-3" title="3"><span class="co">#&gt; </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" title="4"><span class="co">#&gt; </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" title="5"><span class="co">#&gt; </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" title="6"><span class="co">#&gt; =&gt; Found 5,654 first isolates (28.3% of total)</span></a></code></pre></div>
<p>So only 28.3% is suitable for resistance analysis! We can now filter on it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html">filter()</a></code> function, also from the <code>dplyr</code> package:</p>
<a class="sourceLine" id="cb16-6" title="6"><span class="co">#&gt; =&gt; Found 5,692 first isolates (28.5% of total)</span></a></code></pre></div>
<p>So only 28.5% is suitable for resistance analysis! We can now filter on it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html">filter()</a></code> function, also from the <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb17"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb17-1" title="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb17-2" title="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>
<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>
@ -516,8 +516,8 @@
<tbody>
<tr class="odd">
<td align="center">1</td>
<td align="center">2010-04-05</td>
<td align="center">Q7</td>
<td align="center">2010-01-31</td>
<td align="center">C6</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">R</td>
<td align="center">S</td>
@ -527,30 +527,30 @@
</tr>
<tr class="even">
<td align="center">2</td>
<td align="center">2010-05-10</td>
<td align="center">Q7</td>
<td align="center">2010-03-09</td>
<td align="center">C6</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>
</tr>
<tr class="odd">
<td align="center">3</td>
<td align="center">2010-06-22</td>
<td align="center">Q7</td>
<td align="center">2010-05-30</td>
<td align="center">C6</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">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">4</td>
<td align="center">2010-06-25</td>
<td align="center">Q7</td>
<td align="center">2010-06-22</td>
<td align="center">C6</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
@ -560,41 +560,41 @@
</tr>
<tr class="odd">
<td align="center">5</td>
<td align="center">2010-10-03</td>
<td align="center">Q7</td>
<td align="center">2011-01-10</td>
<td align="center">C6</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">I</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">6</td>
<td align="center">2010-10-08</td>
<td align="center">Q7</td>
<td align="center">2011-02-19</td>
<td align="center">C6</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">7</td>
<td align="center">2011-03-24</td>
<td align="center">Q7</td>
<td align="center">2011-02-21</td>
<td align="center">C6</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">I</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">8</td>
<td align="center">2011-03-27</td>
<td align="center">Q7</td>
<td align="center">2011-05-11</td>
<td align="center">C6</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
@ -604,21 +604,21 @@
</tr>
<tr class="odd">
<td align="center">9</td>
<td align="center">2011-05-11</td>
<td align="center">Q7</td>
<td align="center">2011-07-06</td>
<td align="center">C6</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">R</td>
<td align="center">TRUE</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-07-22</td>
<td align="center">Q7</td>
<td align="center">2011-08-11</td>
<td align="center">C6</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>
@ -637,7 +637,7 @@
<a class="sourceLine" id="cb19-7" title="7"><span class="co">#&gt; </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="cb19-8" title="8"><span class="co">#&gt; </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="cb19-9" title="9"><span class="co">#&gt; [Criterion] Inclusion based on key antibiotics, ignoring I.</span></a>
<a class="sourceLine" id="cb19-10" title="10"><span class="co">#&gt; =&gt; Found 15,805 first weighted isolates (79.0% of total)</span></a></code></pre></div>
<a class="sourceLine" id="cb19-10" title="10"><span class="co">#&gt; =&gt; Found 15,864 first weighted isolates (79.3% of total)</span></a></code></pre></div>
<table class="table">
<thead><tr class="header">
<th align="center">isolate</th>
@ -654,8 +654,8 @@
<tbody>
<tr class="odd">
<td align="center">1</td>
<td align="center">2010-04-05</td>
<td align="center">Q7</td>
<td align="center">2010-01-31</td>
<td align="center">C6</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">R</td>
<td align="center">S</td>
@ -666,11 +666,11 @@
</tr>
<tr class="even">
<td align="center">2</td>
<td align="center">2010-05-10</td>
<td align="center">Q7</td>
<td align="center">2010-03-09</td>
<td align="center">C6</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>
@ -678,11 +678,11 @@
</tr>
<tr class="odd">
<td align="center">3</td>
<td align="center">2010-06-22</td>
<td align="center">Q7</td>
<td align="center">2010-05-30</td>
<td align="center">C6</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">S</td>
<td align="center">FALSE</td>
@ -690,8 +690,8 @@
</tr>
<tr class="even">
<td align="center">4</td>
<td align="center">2010-06-25</td>
<td align="center">Q7</td>
<td align="center">2010-06-22</td>
<td align="center">C6</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">S</td>
<td align="center">S</td>
@ -702,83 +702,83 @@
</tr>
<tr class="odd">
<td align="center">5</td>
<td align="center">2010-10-03</td>
<td align="center">Q7</td>
<td align="center">2011-01-10</td>
<td align="center">C6</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">I</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">6</td>
<td align="center">2010-10-08</td>
<td align="center">Q7</td>
<td align="center">2011-02-19</td>
<td align="center">C6</td>
<td align="center">B_ESCHR_COL</td>
<td align="center">I</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>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">7</td>
<td align="center">2011-03-24</td>
<td align="center">Q7</td>
<td align="center">2011-02-21</td>
<td align="center">C6</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">I</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">8</td>
<td align="center">2011-03-27</td>
<td align="center">Q7</td>
<td align="center">2011-05-11</td>
<td align="center">C6</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">S</td>
<td align="center">FALSE</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">9</td>
<td align="center">2011-05-11</td>
<td align="center">Q7</td>
<td align="center">2011-07-06</td>
<td align="center">C6</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">R</td>
<td align="center">TRUE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-07-22</td>
<td align="center">Q7</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">FALSE</td>
<td align="center">TRUE</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-08-11</td>
<td align="center">C6</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">S</td>
<td align="center">FALSE</td>
<td align="center">FALSE</td>
</tr>
</tbody>
</table>
<p>Instead of 2, now 4 isolates are flagged. In total, 79% of all isolates are marked ‘first weighted’ - 50.8% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.</p>
<p>Instead of 2, now 6 isolates are flagged. In total, 79.3% of all isolates are marked ‘first weighted’ - 50.9% 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" title="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb20-2" title="2"><span class="st"> </span><span class="kw"><a href="../reference/first_isolate.html">filter_first_weighted_isolate</a></span>()</a></code></pre></div>
<p>So we end up with 15,805 isolates for analysis.</p>
<p>So we end up with 15,864 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" title="1">data_1st &lt;-<span class="st"> </span>data_1st <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb21-2" title="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>
@ -803,45 +803,45 @@
</tr></thead>
<tbody>
<tr class="odd">
<td>2</td>
<td align="center">2013-07-31</td>
<td align="center">A8</td>
<td align="center">Hospital D</td>
<td>1</td>
<td align="center">2012-08-24</td>
<td align="center">V3</td>
<td align="center">Hospital B</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">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>3</td>
<td align="center">2016-10-12</td>
<td align="center">Y3</td>
<td align="center">Hospital D</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">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>5</td>
<td align="center">2014-08-10</td>
<td align="center">F9</td>
<td align="center">Hospital A</td>
<tr class="even">
<td>2</td>
<td align="center">2013-04-28</td>
<td align="center">S3</td>
<td align="center">Hospital B</td>
<td align="center">B_STPHY_AUR</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram positive</td>
<td align="center">Staphylococcus</td>
<td align="center">aureus</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td>3</td>
<td align="center">2013-05-13</td>
<td align="center">F2</td>
<td align="center">Hospital D</td>
<td align="center">B_STPHY_AUR</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>
@ -851,53 +851,53 @@
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td>5</td>
<td align="center">2015-12-23</td>
<td align="center">G9</td>
<td align="center">Hospital B</td>
<td align="center">B_STPHY_AUR</td>
<td align="center">S</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="odd">
<td>6</td>
<td align="center">2017-12-05</td>
<td align="center">H7</td>
<td align="center">2011-12-19</td>
<td align="center">T2</td>
<td align="center">Hospital B</td>
<td align="center">B_STPHY_AUR</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram 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">2011-11-26</td>
<td align="center">J1</td>
<td align="center">Hospital A</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">R</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>7</td>
<td align="center">2014-02-06</td>
<td align="center">D7</td>
<td align="center">Hospital C</td>
<td align="center">B_STPHY_AUR</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">R</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>8</td>
<td align="center">2013-05-11</td>
<td align="center">A5</td>
<td align="center">Hospital A</td>
<td align="center">B_STPHY_AUR</td>
<td align="center">S</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>
</tbody>
</table>
<p>Time for the analysis!</p>
@ -915,9 +915,9 @@
<div class="sourceCode" id="cb23"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb23-1" title="1"><span class="kw"><a href="../reference/freq.html">freq</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/paste">paste</a></span>(data_1st<span class="op">$</span>genus, data_1st<span class="op">$</span>species))</a></code></pre></div>
<p>Or can be used like the <code>dplyr</code> way, which is easier readable:</p>
<div class="sourceCode" id="cb24"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb24-1" title="1">data_1st <span class="op">%&gt;%</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> from a <code>data.frame</code> (15,805 x 13)</strong></p>
<p><strong>Frequency table of <code>genus</code> and <code>species</code> from a <code>data.frame</code> (15,864 x 13)</strong></p>
<p>Columns: 2<br>
Length: 15,805 (of which NA: 0 = 0.00%)<br>
Length: 15,864 (of which NA: 0 = 0.00%)<br>
Unique: 4</p>
<p>Shortest: 16<br>
Longest: 24</p>
@ -934,33 +934,33 @@ Longest: 24</p>
<tr class="odd">
<td align="left">1</td>
<td align="left">Escherichia coli</td>
<td align="right">7,815</td>
<td align="right">49.4%</td>
<td align="right">7,815</td>
<td align="right">49.4%</td>
<td align="right">7,849</td>
<td align="right">49.5%</td>
<td align="right">7,849</td>
<td align="right">49.5%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">Staphylococcus aureus</td>
<td align="right">3,988</td>
<td align="right">25.2%</td>
<td align="right">11,803</td>
<td align="right">74.7%</td>
<td align="right">4,010</td>
<td align="right">25.3%</td>
<td align="right">11,859</td>
<td align="right">74.8%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">Streptococcus pneumoniae</td>
<td align="right">2,476</td>
<td align="right">15.7%</td>
<td align="right">14,279</td>
<td align="right">90.3%</td>
<td align="right">2,443</td>
<td align="right">15.4%</td>
<td align="right">14,302</td>
<td align="right">90.2%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">Klebsiella pneumoniae</td>
<td align="right">1,526</td>
<td align="right">9.7%</td>
<td align="right">15,805</td>
<td align="right">1,562</td>
<td align="right">9.8%</td>
<td align="right">15,864</td>
<td align="right">100.0%</td>
</tr>
</tbody>
@ -971,7 +971,7 @@ Longest: 24</p>
<a href="#resistance-percentages" class="anchor"></a>Resistance percentages</h2>
<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" title="1">data_1st <span class="op">%&gt;%</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" title="2"><span class="co">#&gt; [1] 0.4771275</span></a></code></pre></div>
<a class="sourceLine" id="cb25-2" title="2"><span class="co">#&gt; [1] 0.4777484</span></a></code></pre></div>
<p>Or can be used in conjuction with <code><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/summarise.html">summarise()</a></code>, both from the <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb26"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb26-1" title="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb26-2" title="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital) <span class="op">%&gt;%</span><span class="st"> </span></a>
@ -984,19 +984,19 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Hospital A</td>
<td align="center">0.4661749</td>
<td align="center">0.4814277</td>
</tr>
<tr class="even">
<td align="center">Hospital B</td>
<td align="center">0.4820906</td>
<td align="center">0.4811252</td>
</tr>
<tr class="odd">
<td align="center">Hospital C</td>
<td align="center">0.4847862</td>
<td align="center">0.4843815</td>
</tr>
<tr class="even">
<td align="center">Hospital D</td>
<td align="center">0.4790875</td>
<td align="center">0.4610721</td>
</tr>
</tbody>
</table>
@ -1014,23 +1014,23 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Hospital A</td>
<td align="center">0.4661749</td>
<td align="center">4745</td>
<td align="center">0.4814277</td>
<td align="center">4819</td>
</tr>
<tr class="even">
<td align="center">Hospital B</td>
<td align="center">0.4820906</td>
<td align="center">5472</td>
<td align="center">0.4811252</td>
<td align="center">5510</td>
</tr>
<tr class="odd">
<td align="center">Hospital C</td>
<td align="center">0.4847862</td>
<td align="center">2432</td>
<td align="center">0.4843815</td>
<td align="center">2401</td>
</tr>
<tr class="even">
<td align="center">Hospital D</td>
<td align="center">0.4790875</td>
<td align="center">3156</td>
<td align="center">0.4610721</td>
<td align="center">3134</td>
</tr>
</tbody>
</table>
@ -1050,27 +1050,27 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Escherichia</td>
<td align="center">0.7332054</td>
<td align="center">0.9033909</td>
<td align="center">0.9754319</td>
<td align="center">0.7180533</td>
<td align="center">0.8983310</td>
<td align="center">0.9704421</td>
</tr>
<tr class="even">
<td align="center">Klebsiella</td>
<td align="center">0.7142857</td>
<td align="center">0.9095675</td>
<td align="center">0.9737877</td>
<td align="center">0.7189501</td>
<td align="center">0.8879641</td>
<td align="center">0.9654289</td>
</tr>
<tr class="odd">
<td align="center">Staphylococcus</td>
<td align="center">0.7179037</td>
<td align="center">0.9162487</td>
<td align="center">0.9779338</td>
<td align="center">0.7231920</td>
<td align="center">0.9216958</td>
<td align="center">0.9790524</td>
</tr>
<tr class="even">
<td align="center">Streptococcus</td>
<td align="center">0.7289984</td>
<td align="center">0.7372084</td>
<td align="center">0.0000000</td>
<td align="center">0.7289984</td>
<td align="center">0.7372084</td>
</tr>
</tbody>
</table>

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<h1>How to apply EUCAST rules</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">18 February 2019</h4>
<h4 class="date">20 February 2019</h4>
<div class="hidden name"><code>EUCAST.Rmd</code></div>

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<h1>How to use the <em>G</em>-test</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">18 February 2019</h4>
<h4 class="date">20 February 2019</h4>
<div class="hidden name"><code>G_test.Rmd</code></div>

2
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@ -192,7 +192,7 @@
<h1>How to work with WHONET data</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">18 February 2019</h4>
<h4 class="date">20 February 2019</h4>
<div class="hidden name"><code>WHONET.Rmd</code></div>

2
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@ -192,7 +192,7 @@
<h1>How to get properties of an antibiotic</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">18 February 2019</h4>
<h4 class="date">20 February 2019</h4>
<div class="hidden name"><code>atc_property.Rmd</code></div>

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@ -192,7 +192,7 @@
<h1>Benchmarks</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">14 February 2019</h4>
<h4 class="date">20 February 2019</h4>
<div class="hidden name"><code>benchmarks.Rmd</code></div>
@ -201,161 +201,183 @@
<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. Its function <code><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark()</a></code> calculates different input expressions independently of each others and runs every expression 100 times.</p>
<p>One of the most important features of this package is the complete microbial taxonomic database, supplied by the Catalogue of Life (<a href="http://catalogueoflife.org" class="uri">http://catalogueoflife.org</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) combined with the taxonomic tree of Catalogue of Life.</p>
<p>Using the <code>microbenchmark</code> package, we can review the calculation performance of this function. Its function <code><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark()</a></code> runs different input expressions independently of each other and measures their time-to-result.</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" title="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(microbenchmark)</a>
<a class="sourceLine" id="cb1-2" title="2"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(AMR)</a></code></pre></div>
<p>In the next test, we try to ‘coerce’ different input values for <em>Staphylococcus aureus</em>. The actual result is the same every time: it returns its 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" title="1">benchmark &lt;-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"sau"</span>),</a>
<a class="sourceLine" id="cb2-2" title="2"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"stau"</span>),</a>
<a class="sourceLine" id="cb2-3" title="3"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"staaur"</span>),</a>
<a class="sourceLine" id="cb2-4" title="4"> <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" title="5"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"S. aureus"</span>),</a>
<a class="sourceLine" id="cb2-6" title="6"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"STAAUR"</span>),</a>
<a class="sourceLine" id="cb2-7" title="7"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"Staphylococcus aureus"</span>),</a>
<a class="sourceLine" id="cb2-8" title="8"> <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="cb2-9" title="9"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(benchmark, <span class="dt">unit =</span> <span class="st">"ms"</span>)</a>
<a class="sourceLine" id="cb2-10" title="10"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb2-11" title="11"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb2-12" title="12"><span class="co"># as.mo("sau") 18.983141 19.121148 19.9676944 19.1967505 19.2871260 38.635012 100</span></a>
<a class="sourceLine" id="cb2-13" title="13"><span class="co"># as.mo("stau") 37.503863 37.692049 38.9856547 37.8244335 37.9851040 57.576107 100</span></a>
<a class="sourceLine" id="cb2-14" title="14"><span class="co"># as.mo("staaur") 18.945427 19.122579 19.6392560 19.2241285 19.3536140 38.687672 100</span></a>
<a class="sourceLine" id="cb2-15" title="15"><span class="co"># as.mo("S. aureus") 15.305229 15.471103 16.3477096 15.5545630 15.6689280 36.363005 100</span></a>
<a class="sourceLine" id="cb2-16" title="16"><span class="co"># as.mo("S. aureus") 15.308232 15.469881 16.5269706 15.5506870 15.6277560 42.155292 100</span></a>
<a class="sourceLine" id="cb2-17" title="17"><span class="co"># as.mo("STAAUR") 18.984049 19.117166 19.6104597 19.2219285 19.3161095 38.638783 100</span></a>
<a class="sourceLine" id="cb2-18" title="18"><span class="co"># as.mo("Staphylococcus aureus") 8.103546 8.198285 8.6422018 8.2636915 8.3200535 27.002527 100</span></a>
<a class="sourceLine" id="cb2-19" title="19"><span class="co"># as.mo("B_STPHY_AUR") 0.156236 0.196779 0.2017926 0.2035535 0.2115505 0.241861 100</span></a>
<a class="sourceLine" id="cb2-20" title="20"></a>
<a class="sourceLine" id="cb2-21" title="21"><span class="kw"><a href="https://www.rdocumentation.org/packages/graphics/topics/par">par</a></span>(<span class="dt">mar =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="dv">5</span>, <span class="dv">15</span>, <span class="dv">4</span>, <span class="dv">2</span>)) <span class="co"># set more space for left margin text (15)</span></a>
<a class="sourceLine" id="cb2-22" title="22"><span class="kw"><a href="https://www.rdocumentation.org/packages/graphics/topics/boxplot">boxplot</a></span>(benchmark, <span class="dt">horizontal =</span> <span class="ot">TRUE</span>, <span class="dt">las =</span> <span class="dv">1</span>, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">log =</span> <span class="ot">FALSE</span>, <span class="dt">xlab =</span> <span class="st">""</span>, <span class="dt">ylim =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="dv">0</span>, <span class="dv">200</span>),</a>
<a class="sourceLine" id="cb2-23" title="23"> <span class="dt">main =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/expression">expression</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/paste">paste</a></span>(<span class="st">"Benchmark of "</span>, <span class="kw"><a href="https://www.rdocumentation.org/packages/grDevices/topics/plotmath">italic</a></span>(<span class="st">"Staphylococcus aureus"</span>))))</a></code></pre></div>
<p><img src="../reference/figures/benchmark_1.png"></p>
<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 8 milliseconds means it can determine 125 input values per second. It case of 40 milliseconds, this is only 25 input values per second. The more an input value resembles a full name, the faster the result will be found. In case of <code><a href="../reference/as.mo.html">as.mo("B_STPHY_AUR")</a></code>, the input is already a valid MO code, so it only almost takes no time at all (0.0002 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" title="1">benchmark &lt;-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</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" title="2"> <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" title="3"> <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" title="4"> <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" title="5"> <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" title="6"> <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" title="7"> <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" title="8"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(benchmark, <span class="dt">unit =</span> <span class="st">"ms"</span>)</a>
<a class="sourceLine" id="cb3-9" title="9"></a>
<a class="sourceLine" id="cb3-10" title="10"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb3-11" title="11"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb3-12" title="12"><span class="co"># as.mo("buno") 125.141333 125.8553210 129.5727691 126.3899910 127.0954925 194.51985 100</span></a>
<a class="sourceLine" id="cb3-13" title="13"><span class="co"># as.mo("burnod") 142.300359 144.1611750 147.0642288 144.6074960 145.5243025 176.91649 100</span></a>
<a class="sourceLine" id="cb3-14" title="14"><span class="co"># as.mo("B. nodosa") 81.530132 81.9360840 83.3915418 82.1852770 82.6848870 102.63184 100</span></a>
<a class="sourceLine" id="cb3-15" title="15"><span class="co"># as.mo("B. nodosa") 81.109547 81.9836805 84.7595894 82.3437825 82.8282705 110.67036 100</span></a>
<a class="sourceLine" id="cb3-16" title="16"><span class="co"># as.mo("BURNOD") 143.163527 143.9134485 148.7192688 144.5582580 145.7489115 314.92070 100</span></a>
<a class="sourceLine" id="cb3-17" title="17"><span class="co"># as.mo("Burkholderia nodosa") 36.226325 36.5499000 37.1309929 36.6581540 36.7551985 56.25597 100</span></a>
<a class="sourceLine" id="cb3-18" title="18"><span class="co"># as.mo("B_BRKHL_NOD") 0.172509 0.3038455 0.4806591 0.3078265 0.3121215 19.16173 100</span></a>
<a class="sourceLine" id="cb3-19" title="19"></a>
<a class="sourceLine" id="cb3-20" title="20"><span class="kw"><a href="https://www.rdocumentation.org/packages/graphics/topics/boxplot">boxplot</a></span>(benchmark, <span class="dt">horizontal =</span> <span class="ot">TRUE</span>, <span class="dt">las =</span> <span class="dv">1</span>, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">log =</span> <span class="ot">FALSE</span>, <span class="dt">xlab =</span> <span class="st">""</span>, <span class="dt">ylim =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="dv">0</span>, <span class="dv">200</span>),</a>
<a class="sourceLine" id="cb3-21" title="21"> <span class="dt">main =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/expression">expression</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/paste">paste</a></span>(<span class="st">"Benchmark of "</span>, <span class="kw"><a href="https://www.rdocumentation.org/packages/grDevices/topics/plotmath">italic</a></span>(<span class="st">"Burkholderia nodosa"</span>))))</a></code></pre></div>
<p><img src="../reference/figures/benchmark_2.png"></p>
<p>That takes up to 8 times as much time! A value of 145 milliseconds means it can only determine ~7 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>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb2-1" title="1">S.aureus &lt;-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"sau"</span>),</a>
<a class="sourceLine" id="cb2-2" title="2"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"stau"</span>),</a>
<a class="sourceLine" id="cb2-3" title="3"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"staaur"</span>),</a>
<a class="sourceLine" id="cb2-4" title="4"> <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" title="5"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"S. aureus"</span>),</a>
<a class="sourceLine" id="cb2-6" title="6"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"STAAUR"</span>),</a>
<a class="sourceLine" id="cb2-7" title="7"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"Staphylococcus aureus"</span>),</a>
<a class="sourceLine" id="cb2-8" title="8"> <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="cb2-9" title="9"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb2-10" title="10"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(S.aureus, <span class="dt">unit =</span> <span class="st">"ms"</span>)</a>
<a class="sourceLine" id="cb2-11" title="11"><span class="co">#&gt; Unit: milliseconds</span></a>
<a class="sourceLine" id="cb2-12" title="12"><span class="co">#&gt; expr min lq mean median</span></a>
<a class="sourceLine" id="cb2-13" title="13"><span class="co">#&gt; as.mo("sau") 42.58139 42.645368 43.3006677 42.970095</span></a>
<a class="sourceLine" id="cb2-14" title="14"><span class="co">#&gt; as.mo("stau") 76.60094 77.168264 83.7686909 77.316642</span></a>
<a class="sourceLine" id="cb2-15" title="15"><span class="co">#&gt; as.mo("staaur") 42.86607 42.947083 43.5035571 43.497293</span></a>
<a class="sourceLine" id="cb2-16" title="16"><span class="co">#&gt; as.mo("S. aureus") 18.39354 18.432582 22.4304233 18.495928</span></a>
<a class="sourceLine" id="cb2-17" title="17"><span class="co">#&gt; as.mo("S. aureus") 18.46513 18.559903 18.6640991 18.579110</span></a>
<a class="sourceLine" id="cb2-18" title="18"><span class="co">#&gt; as.mo("STAAUR") 42.71975 42.788612 44.3280682 43.069864</span></a>
<a class="sourceLine" id="cb2-19" title="19"><span class="co">#&gt; as.mo("Staphylococcus aureus") 11.56285 11.591419 15.9457298 11.667161</span></a>
<a class="sourceLine" id="cb2-20" title="20"><span class="co">#&gt; as.mo("B_STPHY_AUR") 0.40487 0.450128 0.5036822 0.481417</span></a>
<a class="sourceLine" id="cb2-21" title="21"><span class="co">#&gt; uq max neval</span></a>
<a class="sourceLine" id="cb2-22" title="22"><span class="co">#&gt; 43.448543 45.058105 10</span></a>
<a class="sourceLine" id="cb2-23" title="23"><span class="co">#&gt; 78.335591 127.180349 10</span></a>
<a class="sourceLine" id="cb2-24" title="24"><span class="co">#&gt; 43.817095 44.999509 10</span></a>
<a class="sourceLine" id="cb2-25" title="25"><span class="co">#&gt; 19.007097 56.501460 10</span></a>
<a class="sourceLine" id="cb2-26" title="26"><span class="co">#&gt; 18.651814 19.373275 10</span></a>
<a class="sourceLine" id="cb2-27" title="27"><span class="co">#&gt; 43.741388 54.703256 10</span></a>
<a class="sourceLine" id="cb2-28" title="28"><span class="co">#&gt; 12.323077 50.121808 10</span></a>
<a class="sourceLine" id="cb2-29" title="29"><span class="co">#&gt; 0.519271 0.766578 10</span></a></code></pre></div>
<p>In the table above, all measurements are shown in milliseconds (thousands of seconds). A value of 10 milliseconds means it can determine 100 input values per second. It case of 50 milliseconds, this is only 20 input values per second. The more an input value resembles a full name, the faster the result will be found. In case of <code><a href="../reference/as.mo.html">as.mo("B_STPHY_AUR")</a></code>, the input is already a valid MO code, so it only almost takes no time at all (404 millionths of seconds).</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>Mycoplasma leonicaptivi</em> (<code>B_MYCPL_LEO</code>), a bug probably never found before in humans:</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" title="1">M.leonicaptivi &lt;-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"myle"</span>),</a>
<a class="sourceLine" id="cb3-2" title="2"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"mycleo"</span>),</a>
<a class="sourceLine" id="cb3-3" title="3"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"M. leonicaptivi"</span>),</a>
<a class="sourceLine" id="cb3-4" title="4"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"M. leonicaptivi"</span>),</a>
<a class="sourceLine" id="cb3-5" title="5"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"MYCLEO"</span>),</a>
<a class="sourceLine" id="cb3-6" title="6"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"Mycoplasma leonicaptivi"</span>),</a>
<a class="sourceLine" id="cb3-7" title="7"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"B_MYCPL_LEO"</span>),</a>
<a class="sourceLine" id="cb3-8" title="8"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb3-9" title="9"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(M.leonicaptivi, <span class="dt">unit =</span> <span class="st">"ms"</span>)</a>
<a class="sourceLine" id="cb3-10" title="10"><span class="co">#&gt; Unit: milliseconds</span></a>
<a class="sourceLine" id="cb3-11" title="11"><span class="co">#&gt; expr min lq mean</span></a>
<a class="sourceLine" id="cb3-12" title="12"><span class="co">#&gt; as.mo("myle") 112.28656 112.372601 112.751678</span></a>
<a class="sourceLine" id="cb3-13" title="13"><span class="co">#&gt; as.mo("mycleo") 382.46812 382.757612 383.432440</span></a>
<a class="sourceLine" id="cb3-14" title="14"><span class="co">#&gt; as.mo("M. leonicaptivi") 202.68674 203.654949 210.461303</span></a>
<a class="sourceLine" id="cb3-15" title="15"><span class="co">#&gt; as.mo("M. leonicaptivi") 202.89759 203.440956 203.816387</span></a>
<a class="sourceLine" id="cb3-16" title="16"><span class="co">#&gt; as.mo("MYCLEO") 382.27864 383.090895 401.904482</span></a>
<a class="sourceLine" id="cb3-17" title="17"><span class="co">#&gt; as.mo("Mycoplasma leonicaptivi") 102.99676 103.191196 109.196394</span></a>
<a class="sourceLine" id="cb3-18" title="18"><span class="co">#&gt; as.mo("B_MYCPL_LEO") 0.32155 0.564807 4.320068</span></a>
<a class="sourceLine" id="cb3-19" title="19"><span class="co">#&gt; median uq max neval</span></a>
<a class="sourceLine" id="cb3-20" title="20"><span class="co">#&gt; 112.540884 112.76874 113.76321 10</span></a>
<a class="sourceLine" id="cb3-21" title="21"><span class="co">#&gt; 383.232219 384.05897 385.28587 10</span></a>
<a class="sourceLine" id="cb3-22" title="22"><span class="co">#&gt; 204.255445 205.80976 242.53035 10</span></a>
<a class="sourceLine" id="cb3-23" title="23"><span class="co">#&gt; 203.613673 203.82802 206.15038 10</span></a>
<a class="sourceLine" id="cb3-24" title="24"><span class="co">#&gt; 386.478757 421.87837 437.26978 10</span></a>
<a class="sourceLine" id="cb3-25" title="25"><span class="co">#&gt; 103.596136 104.65940 142.25748 10</span></a>
<a class="sourceLine" id="cb3-26" title="26"><span class="co">#&gt; 0.593652 0.62522 37.96384 10</span></a></code></pre></div>
<p>That takes 6 times as much time on average! A value of 100 milliseconds means it can only determine ~10 different input values per second. We can conclude that looking up arbitrary codes of less prevalent microorganisms is the worst way to go, in terms of calculation performance:</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" title="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/graphics/topics/par">par</a></span>(<span class="dt">mar =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="dv">5</span>, <span class="dv">16</span>, <span class="dv">4</span>, <span class="dv">2</span>)) <span class="co"># set more space for left margin text (16)</span></a>
<a class="sourceLine" id="cb4-2" title="2"></a>
<a class="sourceLine" id="cb4-3" title="3"><span class="co"># highest value on y axis</span></a>
<a class="sourceLine" id="cb4-4" title="4">max_y_axis &lt;-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/Extremes">max</a></span>(S.aureus<span class="op">$</span>time, M.leonicaptivi<span class="op">$</span>time, <span class="dt">na.rm =</span> <span class="ot">TRUE</span>) <span class="op">/</span><span class="st"> </span><span class="fl">1e6</span></a>
<a class="sourceLine" id="cb4-5" title="5"></a>
<a class="sourceLine" id="cb4-6" title="6"><span class="kw"><a href="https://www.rdocumentation.org/packages/graphics/topics/boxplot">boxplot</a></span>(S.aureus, <span class="dt">horizontal =</span> <span class="ot">TRUE</span>, <span class="dt">las =</span> <span class="dv">1</span>, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">log =</span> <span class="ot">FALSE</span>, <span class="dt">xlab =</span> <span class="st">""</span>, <span class="dt">ylim =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="dv">0</span>, max_y_axis),</a>
<a class="sourceLine" id="cb4-7" title="7"> <span class="dt">main =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/expression">expression</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/paste">paste</a></span>(<span class="st">"Benchmark of "</span>, <span class="kw"><a href="https://www.rdocumentation.org/packages/grDevices/topics/plotmath">italic</a></span>(<span class="st">"Staphylococcus aureus"</span>))))</a></code></pre></div>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-4-1.png" width="720"></p>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" title="1"></a>
<a class="sourceLine" id="cb5-2" title="2"><span class="kw"><a href="https://www.rdocumentation.org/packages/graphics/topics/boxplot">boxplot</a></span>(M.leonicaptivi, <span class="dt">horizontal =</span> <span class="ot">TRUE</span>, <span class="dt">las =</span> <span class="dv">1</span>, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">log =</span> <span class="ot">FALSE</span>, <span class="dt">xlab =</span> <span class="st">""</span>, <span class="dt">ylim =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="dv">0</span>, max_y_axis),</a>
<a class="sourceLine" id="cb5-3" title="3"> <span class="dt">main =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/expression">expression</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/paste">paste</a></span>(<span class="st">"Benchmark of "</span>, <span class="kw"><a href="https://www.rdocumentation.org/packages/grDevices/topics/plotmath">italic</a></span>(<span class="st">"Mycoplasma leonicaptivi"</span>))))</a></code></pre></div>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-4-2.png" width="720"></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" title="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" title="2"><span class="co"># take 500,000 random MO codes from the septic_patients data set</span></a>
<a class="sourceLine" id="cb4-3" title="3">x =<span class="st"> </span>septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb4-4" title="4"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/sample.html">sample_n</a></span>(<span class="dv">500000</span>, <span class="dt">replace =</span> <span class="ot">TRUE</span>) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb4-5" title="5"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/pull.html">pull</a></span>(mo)</a>
<a class="sourceLine" id="cb4-6" title="6"> </a>
<a class="sourceLine" id="cb4-7" title="7"><span class="co"># got the right length?</span></a>
<a class="sourceLine" id="cb4-8" title="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" title="9"><span class="co"># [1] 500000</span></a>
<a class="sourceLine" id="cb4-10" title="10"></a>
<a class="sourceLine" id="cb4-11" title="11"><span class="co"># and how many unique values do we have?</span></a>
<a class="sourceLine" id="cb4-12" title="12"><span class="kw"><a href="https://dplyr.tidyverse.org/reference/n_distinct.html">n_distinct</a></span>(x)</a>
<a class="sourceLine" id="cb4-13" title="13"><span class="co"># [1] 96</span></a>
<a class="sourceLine" id="cb4-14" title="14"></a>
<a class="sourceLine" id="cb4-15" title="15"><span class="co"># only 96, but distributed in 500,000 results. now let's see:</span></a>
<a class="sourceLine" id="cb4-16" title="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" title="17"> <span class="dt">times =</span> <span class="dv">10</span>,</a>
<a class="sourceLine" id="cb4-18" title="18"> <span class="dt">unit =</span> <span class="st">"ms"</span>)</a>
<a class="sourceLine" id="cb4-19" title="19"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb4-20" title="20"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb4-21" title="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" title="1"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb5-2" title="2"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb5-3" title="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 determining the full names of 5 <em>Million</em> values is done within a second.</p>
<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) which uses <code><a href="../reference/as.mo.html">as.mo()</a></code> internally.</p>
<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb6-1" title="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(dplyr)</a>
<a class="sourceLine" id="cb6-2" title="2"><span class="co">#&gt; </span></a>
<a class="sourceLine" id="cb6-3" title="3"><span class="co">#&gt; Attaching package: 'dplyr'</span></a>
<a class="sourceLine" id="cb6-4" title="4"><span class="co">#&gt; The following objects are masked from 'package:stats':</span></a>
<a class="sourceLine" id="cb6-5" title="5"><span class="co">#&gt; </span></a>
<a class="sourceLine" id="cb6-6" title="6"><span class="co">#&gt; filter, lag</span></a>
<a class="sourceLine" id="cb6-7" title="7"><span class="co">#&gt; The following objects are masked from 'package:base':</span></a>
<a class="sourceLine" id="cb6-8" title="8"><span class="co">#&gt; </span></a>
<a class="sourceLine" id="cb6-9" title="9"><span class="co">#&gt; intersect, setdiff, setequal, union</span></a>
<a class="sourceLine" id="cb6-10" title="10"><span class="co"># take 500,000 random MO codes from the septic_patients data set</span></a>
<a class="sourceLine" id="cb6-11" title="11">x =<span class="st"> </span>septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb6-12" title="12"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/sample.html">sample_n</a></span>(<span class="dv">500000</span>, <span class="dt">replace =</span> <span class="ot">TRUE</span>) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb6-13" title="13"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/pull.html">pull</a></span>(mo)</a>
<a class="sourceLine" id="cb6-14" title="14"> </a>
<a class="sourceLine" id="cb6-15" title="15"><span class="co"># got the right length?</span></a>
<a class="sourceLine" id="cb6-16" title="16"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/length">length</a></span>(x)</a>
<a class="sourceLine" id="cb6-17" title="17"><span class="co">#&gt; [1] 500000</span></a>
<a class="sourceLine" id="cb6-18" title="18"></a>
<a class="sourceLine" id="cb6-19" title="19"><span class="co"># and how many unique values do we have?</span></a>
<a class="sourceLine" id="cb6-20" title="20"><span class="kw"><a href="https://dplyr.tidyverse.org/reference/n_distinct.html">n_distinct</a></span>(x)</a>
<a class="sourceLine" id="cb6-21" title="21"><span class="co">#&gt; [1] 95</span></a>
<a class="sourceLine" id="cb6-22" title="22"></a>
<a class="sourceLine" id="cb6-23" title="23"><span class="co"># now let's see:</span></a>
<a class="sourceLine" id="cb6-24" title="24">run_it &lt;-<span class="st"> </span><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="cb6-25" title="25"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb6-26" title="26"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>)</a>
<a class="sourceLine" id="cb6-27" title="27"><span class="co">#&gt; Unit: milliseconds</span></a>
<a class="sourceLine" id="cb6-28" title="28"><span class="co">#&gt; expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb6-29" title="29"><span class="co">#&gt; X 435.7086 442.1682 465.5949 468.8453 477.1915 505.961 10</span></a></code></pre></div>
<p>So transforming 500,000 values (!) of 95 unique values only takes 0.47 seconds (468 ms). You only lose time on your unique input values.</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" title="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" title="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" title="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" title="4"> <span class="dt">times =</span> <span class="dv">10</span>,</a>
<a class="sourceLine" id="cb6-5" title="5"> <span class="dt">unit =</span> <span class="st">"ms"</span>)</a>
<a class="sourceLine" id="cb6-6" title="6"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb6-7" title="7"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb6-8" title="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" title="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" title="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" title="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" title="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" title="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" title="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" title="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" title="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" title="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" title="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" title="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" title="10"> <span class="dt">times =</span> <span class="dv">10</span>,</a>
<a class="sourceLine" id="cb7-11" title="11"> <span class="dt">unit =</span> <span class="st">"ms"</span>)</a>
<a class="sourceLine" id="cb7-12" title="12"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb7-13" title="13"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb7-14" title="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" title="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" title="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" title="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" title="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" title="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" title="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" title="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" title="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 class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb7-1" title="1">run_it &lt;-<span class="st"> </span><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="cb7-2" title="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="cb7-3" title="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" title="4"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb7-5" title="5"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>)</a>
<a class="sourceLine" id="cb7-6" title="6"><span class="co">#&gt; Unit: milliseconds</span></a>
<a class="sourceLine" id="cb7-7" title="7"><span class="co">#&gt; expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb7-8" title="8"><span class="co">#&gt; A 38.887977 38.920313 39.3674024 39.076862 39.258415 42.166327 10</span></a>
<a class="sourceLine" id="cb7-9" title="9"><span class="co">#&gt; B 19.589084 19.631059 19.8682396 19.781567 19.955611 20.751941 10</span></a>
<a class="sourceLine" id="cb7-10" title="10"><span class="co">#&gt; C 0.255829 0.382732 0.4199913 0.400156 0.499156 0.564807 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 0.0004 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="cb8"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb8-1" title="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="cb8-2" title="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="cb8-3" title="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="cb8-4" title="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="cb8-5" title="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="cb8-6" title="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="cb8-7" title="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="cb8-8" title="8"> <span class="dt">H =</span> <span class="kw"><a href="../reference/mo_property.html">mo_kingdom</a></span>(<span class="st">"Bacteria"</span>),</a>
<a class="sourceLine" id="cb8-9" title="9"> <span class="dt">times =</span> <span class="dv">10</span>,</a>
<a class="sourceLine" id="cb8-10" title="10"> <span class="dt">unit =</span> <span class="st">"ms"</span>)</a>
<a class="sourceLine" id="cb8-11" title="11"><span class="co">#&gt; Unit: milliseconds</span></a>
<a class="sourceLine" id="cb8-12" title="12"><span class="co">#&gt; expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb8-13" title="13"><span class="co">#&gt; A 0.250242 0.292496 0.3891774 0.4266960 0.456902 0.520388 10</span></a>
<a class="sourceLine" id="cb8-14" title="14"><span class="co">#&gt; B 0.259461 0.311702 0.3428727 0.3412800 0.374141 0.443912 10</span></a>
<a class="sourceLine" id="cb8-15" title="15"><span class="co">#&gt; C 0.290960 0.313169 0.4334429 0.4097595 0.520389 0.725373 10</span></a>
<a class="sourceLine" id="cb8-16" title="16"><span class="co">#&gt; D 0.271823 0.282789 0.3187217 0.3192800 0.352909 0.375398 10</span></a>
<a class="sourceLine" id="cb8-17" title="17"><span class="co">#&gt; E 0.245353 0.270985 0.3081197 0.2960235 0.330839 0.429036 10</span></a>
<a class="sourceLine" id="cb8-18" title="18"><span class="co">#&gt; F 0.246122 0.266585 0.2991101 0.3089435 0.332794 0.351582 10</span></a>
<a class="sourceLine" id="cb8-19" title="19"><span class="co">#&gt; G 0.271893 0.272452 0.3085039 0.2850580 0.368204 0.385525 10</span></a>
<a class="sourceLine" id="cb8-20" title="20"><span class="co">#&gt; H 0.252686 0.259251 0.3161791 0.2985025 0.334820 0.422680 10</span></a></code></pre></div>
<p>Of course, when running <code><a href="../reference/mo_property.html">mo_phylum("Firmicutes")</a></code> the function has zero knowledge about the actual microorganism, namely <em>S. aureus</em>. But since the result would be <code>"Firmicutes"</code> too, there is no point in calculating the result. And because this package ‘knows’ all phyla of all known bacteria (according to the Catalogue of Life), it can just return the initial value immediately.</p>
</div>
<div id="results-in-other-languages" class="section level3">
<h3 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" title="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" title="2"><span class="co"># "Coagulase Negative Staphylococcus (CoNS)"</span></a>
<a class="sourceLine" id="cb8-3" title="3"></a>
<a class="sourceLine" id="cb8-4" title="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" title="5"><span class="co"># "Staphylococcus à coagulase négative (CoNS)"</span></a>
<a class="sourceLine" id="cb8-6" title="6"></a>
<a class="sourceLine" id="cb8-7" title="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" title="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" title="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" title="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" title="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" title="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" title="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" title="14"> <span class="dt">times =</span> <span class="dv">10</span>,</a>
<a class="sourceLine" id="cb8-15" title="15"> <span class="dt">unit =</span> <span class="st">"ms"</span>)</a>
<a class="sourceLine" id="cb8-16" title="16"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb8-17" title="17"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb8-18" title="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" title="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" title="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" title="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" title="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" title="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" title="24"><span class="co"># pt 13.789674 14.36244 15.706321 14.443772 14.679905 44.76701 100</span></a></code></pre></div>
<div class="sourceCode" id="cb9"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb9-1" title="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="cb9-2" title="2"><span class="co">#&gt; [1] "Coagulase Negative Staphylococcus (CoNS)"</span></a>
<a class="sourceLine" id="cb9-3" title="3"></a>
<a class="sourceLine" id="cb9-4" title="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="cb9-5" title="5"><span class="co">#&gt; [1] "Staphylococcus à coagulase négative (CoNS)"</span></a>
<a class="sourceLine" id="cb9-6" title="6"></a>
<a class="sourceLine" id="cb9-7" title="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="cb9-8" title="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="cb9-9" title="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="cb9-10" title="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="cb9-11" title="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="cb9-12" title="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="cb9-13" title="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="cb9-14" title="14"> <span class="dt">times =</span> <span class="dv">10</span>,</a>
<a class="sourceLine" id="cb9-15" title="15"> <span class="dt">unit =</span> <span class="st">"ms"</span>)</a>
<a class="sourceLine" id="cb9-16" title="16"><span class="co">#&gt; Unit: milliseconds</span></a>
<a class="sourceLine" id="cb9-17" title="17"><span class="co">#&gt; expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb9-18" title="18"><span class="co">#&gt; en 10.67105 11.03136 11.06332 11.07271 11.15310 11.45006 10</span></a>
<a class="sourceLine" id="cb9-19" title="19"><span class="co">#&gt; de 19.13393 19.50080 26.13799 19.61419 20.23400 52.66501 10</span></a>
<a class="sourceLine" id="cb9-20" title="20"><span class="co">#&gt; nl 19.05410 19.53789 22.94707 19.59205 20.12616 52.47399 10</span></a>
<a class="sourceLine" id="cb9-21" title="21"><span class="co">#&gt; es 19.31635 19.55221 26.22342 19.58633 20.01875 52.97636 10</span></a>
<a class="sourceLine" id="cb9-22" title="22"><span class="co">#&gt; it 19.21725 19.47105 19.63980 19.58053 19.68162 20.58914 10</span></a>
<a class="sourceLine" id="cb9-23" title="23"><span class="co">#&gt; fr 19.07854 19.45450 19.67303 19.56153 19.64517 20.45651 10</span></a>
<a class="sourceLine" id="cb9-24" title="24"><span class="co">#&gt; pt 19.00668 19.28388 19.53493 19.57857 19.66423 20.55317 10</span></a></code></pre></div>
<p>Currently supported are German, Dutch, Spanish, Italian, French and Portuguese.</p>
</div>
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<h1>How to create frequency tables</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">18 February 2019</h4>
<h4 class="date">20 February 2019</h4>
<div class="hidden name"><code>freq.Rmd</code></div>
@ -258,16 +258,16 @@ Longest: 1</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" title="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/colnames">colnames</a></span>(microorganisms)</a>
<a class="sourceLine" id="cb3-2" title="2"><span class="co"># [1] "mo" "col_id" "fullname" "kingdom" "phylum" </span></a>
<a class="sourceLine" id="cb3-3" title="3"><span class="co"># [6] "class" "order" "family" "genus" "species" </span></a>
<a class="sourceLine" id="cb3-4" title="4"><span class="co"># [11] "subspecies" "rank" "ref"</span></a></code></pre></div>
<p>If we compare the dimensions between the old and new dataset, we can see that these 12 variables were added:</p>
<a class="sourceLine" id="cb3-4" title="4"><span class="co"># [11] "subspecies" "rank" "ref" "species_id"</span></a></code></pre></div>
<p>If we compare the dimensions between the old and new dataset, we can see that these 13 variables were added:</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" title="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/dim">dim</a></span>(septic_patients)</a>
<a class="sourceLine" id="cb4-2" title="2"><span class="co"># [1] 2000 49</span></a>
<a class="sourceLine" id="cb4-3" title="3"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/dim">dim</a></span>(my_patients)</a>
<a class="sourceLine" id="cb4-4" title="4"><span class="co"># [1] 2000 61</span></a></code></pre></div>
<a class="sourceLine" id="cb4-4" title="4"><span class="co"># [1] 2000 62</span></a></code></pre></div>
<p>So now the <code>genus</code> and <code>species</code> variables are available. A frequency table of these combined variables can be created like this:</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" title="1">my_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb5-2" title="2"><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(genus, species, <span class="dt">nmax =</span> <span class="dv">15</span>)</a></code></pre></div>
<p><strong>Frequency table of <code>genus</code> and <code>species</code> from a <code>data.frame</code> (2,000 x 61)</strong></p>
<p><strong>Frequency table of <code>genus</code> and <code>species</code> from a <code>data.frame</code> (2,000 x 62)</strong></p>
<p>Columns: 2<br>
Length: 2,000 (of which NA: 0 = 0.00%)<br>
Unique: 95</p>

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<h1>How to get properties of a microorganism</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">18 February 2019</h4>
<h4 class="date">20 February 2019</h4>
<div class="hidden name"><code>mo_property.Rmd</code></div>

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<h1>How to predict antimicrobial resistance</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">18 February 2019</h4>
<h4 class="date">20 February 2019</h4>
<div class="hidden name"><code>resistance_predict.Rmd</code></div>