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DESCRIPTION
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Package: AMR
Version: 0.8.0
Date: 2019-10-15
Version: 0.8.0.9000
Date: 2019-10-16
Title: Antimicrobial Resistance Analysis
Authors@R: c(
person(role = c("aut", "cre"),

9
NEWS.md
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# AMR 0.8.0
# AMR 0.8.0.9000
<small>Last updated: 16-Oct-2019</small>
### New
### Changes
# AMR 0.8.0
### Breaking
* Determination of first isolates now **excludes** all 'unknown' microorganisms at default, i.e. microbial code `"UNKNOWN"`. They can be included with the new parameter `include_unknown`:

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docs/404.html
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</button>
<span class="navbar-brand">
<a class="navbar-link" href="https://msberends.gitlab.io/AMR/index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9107</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9000</span>
</span>
</div>

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docs/LICENSE-text.html
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</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9107</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9000</span>
</span>
</div>

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docs/articles/AMR.html
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<h1>How to conduct AMR analysis</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">13 October 2019</h4>
<h4 class="date">16 October 2019</h4>
<div class="hidden name"><code>AMR.Rmd</code></div>
@ -196,7 +196,7 @@
<p><strong>Note:</strong> values on this page will change with every website update since they are based on randomly created values and the page was written in <a href="https://rmarkdown.rstudio.com/">R Markdown</a>. However, the methodology remains unchanged. This page was generated on 13 October 2019.</p>
<p><strong>Note:</strong> values on this page will change with every website update since they are based on randomly created values and the page was written in <a href="https://rmarkdown.rstudio.com/">R Markdown</a>. However, the methodology remains unchanged. This page was generated on 16 October 2019.</p>
<div id="introduction" class="section level1">
<h1 class="hasAnchor">
<a href="#introduction" class="anchor"></a>Introduction</h1>
@ -212,21 +212,21 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2019-10-13</td>
<td align="center">2019-10-16</td>
<td align="center">abcd</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">S</td>
</tr>
<tr class="even">
<td align="center">2019-10-13</td>
<td align="center">2019-10-16</td>
<td align="center">abcd</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">R</td>
</tr>
<tr class="odd">
<td align="center">2019-10-13</td>
<td align="center">2019-10-16</td>
<td align="center">efgh</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
@ -321,20 +321,42 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2011-07-28</td>
<td align="center">N6</td>
<td align="center">Hospital C</td>
<td align="center">2012-05-14</td>
<td align="center">G6</td>
<td align="center">Hospital B</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">M</td>
</tr>
<tr class="even">
<td align="center">2012-08-16</td>
<td align="center">Q6</td>
<td align="center">Hospital C</td>
<td align="center">2012-03-26</td>
<td align="center">F8</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="odd">
<td align="center">2010-04-06</td>
<td align="center">F7</td>
<td align="center">Hospital B</td>
<td align="center">Escherichia coli</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">M</td>
</tr>
<tr class="even">
<td align="center">2016-05-08</td>
<td align="center">O1</td>
<td align="center">Hospital B</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">S</td>
@ -343,48 +365,26 @@
<td align="center">F</td>
</tr>
<tr class="odd">
<td align="center">2017-05-07</td>
<td align="center">G5</td>
<td align="center">2017-05-22</td>
<td align="center">T6</td>
<td align="center">Hospital A</td>
<td align="center">Staphylococcus aureus</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">M</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">2015-10-29</td>
<td align="center">V10</td>
<td align="center">2012-06-06</td>
<td align="center">X7</td>
<td align="center">Hospital D</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="odd">
<td align="center">2013-08-21</td>
<td align="center">U1</td>
<td align="center">Hospital A</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2017-06-24</td>
<td align="center">K6</td>
<td align="center">Hospital A</td>
<td align="center">Staphylococcus aureus</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
<td align="center">F</td>
</tr>
</tbody>
</table>
@ -407,8 +407,8 @@
#
# Item Count Percent Cum. Count Cum. Percent
# --- ----- ------- -------- ----------- -------------
# 1 M 10,399 52.00% 10,399 52.00%
# 2 F 9,601 48.01% 20,000 100.00%</code></pre>
# 1 M 10,380 51.9% 10,380 51.9%
# 2 F 9,620 48.1% 20,000 100.0%</code></pre>
<p>So, we can draw at least two conclusions immediately. From a data scientists perspective, the data looks clean: only values <code>M</code> and <code>F</code>. From a researchers perspective: there are slightly more men. Nothing we didn’t already know.</p>
<p>The data is already quite clean, but we still need to transform some variables. The <code>bacteria</code> column now consists of text, and we want to add more variables based on microbial IDs later on. So, we will transform this column to valid IDs. The <code><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate()</a></code> function of the <code>dplyr</code> package makes this really easy:</p>
<div class="sourceCode" id="cb13"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb13-1" data-line-number="1">data &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span></a>
@ -438,14 +438,14 @@
<a class="sourceLine" id="cb15-18" data-line-number="18"><span class="co"># Pasteurella multocida (no changes)</span></a>
<a class="sourceLine" id="cb15-19" data-line-number="19"><span class="co"># Staphylococcus (no changes)</span></a>
<a class="sourceLine" id="cb15-20" data-line-number="20"><span class="co"># Streptococcus groups A, B, C, G (no changes)</span></a>
<a class="sourceLine" id="cb15-21" data-line-number="21"><span class="co"># Streptococcus pneumoniae (1,461 values changed)</span></a>
<a class="sourceLine" id="cb15-21" data-line-number="21"><span class="co"># Streptococcus pneumoniae (1,483 values changed)</span></a>
<a class="sourceLine" id="cb15-22" data-line-number="22"><span class="co"># Viridans group streptococci (no changes)</span></a>
<a class="sourceLine" id="cb15-23" data-line-number="23"><span class="co"># </span></a>
<a class="sourceLine" id="cb15-24" data-line-number="24"><span class="co"># EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes (v3.1, 2016)</span></a>
<a class="sourceLine" id="cb15-25" data-line-number="25"><span class="co"># Table 01: Intrinsic resistance in Enterobacteriaceae (1,290 values changed)</span></a>
<a class="sourceLine" id="cb15-25" data-line-number="25"><span class="co"># Table 01: Intrinsic resistance in Enterobacteriaceae (1,268 values changed)</span></a>
<a class="sourceLine" id="cb15-26" data-line-number="26"><span class="co"># Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria (no changes)</span></a>
<a class="sourceLine" id="cb15-27" data-line-number="27"><span class="co"># Table 03: Intrinsic resistance in other Gram-negative bacteria (no changes)</span></a>
<a class="sourceLine" id="cb15-28" data-line-number="28"><span class="co"># Table 04: Intrinsic resistance in Gram-positive bacteria (2,724 values changed)</span></a>
<a class="sourceLine" id="cb15-28" data-line-number="28"><span class="co"># Table 04: Intrinsic resistance in Gram-positive bacteria (2,755 values changed)</span></a>
<a class="sourceLine" id="cb15-29" data-line-number="29"><span class="co"># Table 08: Interpretive rules for B-lactam agents and Gram-positive cocci (no changes)</span></a>
<a class="sourceLine" id="cb15-30" data-line-number="30"><span class="co"># Table 09: Interpretive rules for B-lactam agents and Gram-negative rods (no changes)</span></a>
<a class="sourceLine" id="cb15-31" data-line-number="31"><span class="co"># Table 11: Interpretive rules for macrolides, lincosamides, and streptogramins (no changes)</span></a>
@ -453,24 +453,24 @@
<a class="sourceLine" id="cb15-33" data-line-number="33"><span class="co"># Table 13: Interpretive rules for quinolones (no changes)</span></a>
<a class="sourceLine" id="cb15-34" data-line-number="34"><span class="co"># </span></a>
<a class="sourceLine" id="cb15-35" data-line-number="35"><span class="co"># Other rules</span></a>
<a class="sourceLine" id="cb15-36" data-line-number="36"><span class="co"># Non-EUCAST: amoxicillin/clav acid = S where ampicillin = S (2,293 values changed)</span></a>
<a class="sourceLine" id="cb15-37" data-line-number="37"><span class="co"># Non-EUCAST: ampicillin = R where amoxicillin/clav acid = R (126 values changed)</span></a>
<a class="sourceLine" id="cb15-36" data-line-number="36"><span class="co"># Non-EUCAST: amoxicillin/clav acid = S where ampicillin = S (2,282 values changed)</span></a>
<a class="sourceLine" id="cb15-37" data-line-number="37"><span class="co"># Non-EUCAST: ampicillin = R where amoxicillin/clav acid = R (122 values changed)</span></a>
<a class="sourceLine" id="cb15-38" data-line-number="38"><span class="co"># Non-EUCAST: piperacillin = R where piperacillin/tazobactam = R (no changes)</span></a>
<a class="sourceLine" id="cb15-39" data-line-number="39"><span class="co"># Non-EUCAST: piperacillin/tazobactam = S where piperacillin = S (no changes)</span></a>
<a class="sourceLine" id="cb15-40" data-line-number="40"><span class="co"># Non-EUCAST: trimethoprim = R where trimethoprim/sulfa = R (no changes)</span></a>
<a class="sourceLine" id="cb15-41" data-line-number="41"><span class="co"># Non-EUCAST: trimethoprim/sulfa = S where trimethoprim = S (no changes)</span></a>
<a class="sourceLine" id="cb15-42" data-line-number="42"><span class="co"># </span></a>
<a class="sourceLine" id="cb15-43" data-line-number="43"><span class="co"># --------------------------------------------------------------------------</span></a>
<a class="sourceLine" id="cb15-44" data-line-number="44"><span class="co"># EUCAST rules affected 6,534 out of 20,000 rows, making a total of 7,894 edits</span></a>
<a class="sourceLine" id="cb15-44" data-line-number="44"><span class="co"># EUCAST rules affected 6,530 out of 20,000 rows, making a total of 7,910 edits</span></a>
<a class="sourceLine" id="cb15-45" data-line-number="45"><span class="co"># =&gt; added 0 test results</span></a>
<a class="sourceLine" id="cb15-46" data-line-number="46"><span class="co"># </span></a>
<a class="sourceLine" id="cb15-47" data-line-number="47"><span class="co"># =&gt; changed 7,894 test results</span></a>
<a class="sourceLine" id="cb15-48" data-line-number="48"><span class="co"># - 126 test results changed from S to I</span></a>
<a class="sourceLine" id="cb15-49" data-line-number="49"><span class="co"># - 4,707 test results changed from S to R</span></a>
<a class="sourceLine" id="cb15-50" data-line-number="50"><span class="co"># - 1,073 test results changed from I to S</span></a>
<a class="sourceLine" id="cb15-51" data-line-number="51"><span class="co"># - 317 test results changed from I to R</span></a>
<a class="sourceLine" id="cb15-52" data-line-number="52"><span class="co"># - 1,653 test results changed from R to S</span></a>
<a class="sourceLine" id="cb15-53" data-line-number="53"><span class="co"># - 18 test results changed from R to I</span></a>
<a class="sourceLine" id="cb15-47" data-line-number="47"><span class="co"># =&gt; changed 7,910 test results</span></a>
<a class="sourceLine" id="cb15-48" data-line-number="48"><span class="co"># - 109 test results changed from S to I</span></a>
<a class="sourceLine" id="cb15-49" data-line-number="49"><span class="co"># - 4,678 test results changed from S to R</span></a>
<a class="sourceLine" id="cb15-50" data-line-number="50"><span class="co"># - 1,098 test results changed from I to S</span></a>
<a class="sourceLine" id="cb15-51" data-line-number="51"><span class="co"># - 322 test results changed from I to R</span></a>
<a class="sourceLine" id="cb15-52" data-line-number="52"><span class="co"># - 1,676 test results changed from R to S</span></a>
<a class="sourceLine" id="cb15-53" data-line-number="53"><span class="co"># - 27 test results changed from R to I</span></a>
<a class="sourceLine" id="cb15-54" data-line-number="54"><span class="co"># --------------------------------------------------------------------------</span></a>
<a class="sourceLine" id="cb15-55" data-line-number="55"><span class="co"># </span></a>
<a class="sourceLine" id="cb15-56" data-line-number="56"><span class="co"># Use eucast_rules(..., verbose = TRUE) (on your original data) to get a data.frame with all specified edits instead.</span></a></code></pre></div>
@ -498,8 +498,8 @@
<a class="sourceLine" id="cb17-3" data-line-number="3"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `bacteria` as input for `col_mo`.</span></a>
<a class="sourceLine" id="cb17-4" data-line-number="4"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `date` as input for `col_date`.</span></a>
<a class="sourceLine" id="cb17-5" data-line-number="5"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `patient_id` as input for `col_patient_id`.</span></a>
<a class="sourceLine" id="cb17-6" data-line-number="6"><span class="co"># =&gt; Found 5,663 first isolates (28.3% of total)</span></a></code></pre></div>
<p>So only 28.3% is suitable for resistance analysis! We can now filter on it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html">filter()</a></code> function, also from the <code>dplyr</code> package:</p>
<a class="sourceLine" id="cb17-6" data-line-number="6"><span class="co"># =&gt; Found 5,688 first isolates (28.4% of total)</span></a></code></pre></div>
<p>So only 28.4% is suitable for resistance analysis! We can now filter on it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html">filter()</a></code> function, also from the <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb18"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb18-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb18-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(first <span class="op">==</span><span class="st"> </span><span class="ot">TRUE</span>)</a></code></pre></div>
<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>
@ -509,7 +509,7 @@
<div id="first-weighted-isolates" class="section level2">
<h2 class="hasAnchor">
<a href="#first-weighted-isolates" class="anchor"></a>First <em>weighted</em> isolates</h2>
<p>We made a slight twist to the CLSI algorithm, to take into account the antimicrobial susceptibility profile. Have a look at all isolates of patient X9, sorted on date:</p>
<p>We made a slight twist to the CLSI algorithm, to take into account the antimicrobial susceptibility profile. Have a look at all isolates of patient I4, sorted on date:</p>
<table class="table">
<thead><tr class="header">
<th align="center">isolate</th>
@ -525,8 +525,8 @@
<tbody>
<tr class="odd">
<td align="center">1</td>
<td align="center">2010-01-31</td>
<td align="center">X9</td>
<td align="center">2010-02-10</td>
<td align="center">I4</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
@ -536,10 +536,10 @@
</tr>
<tr class="even">
<td align="center">2</td>
<td align="center">2010-04-03</td>
<td align="center">X9</td>
<td align="center">2010-02-19</td>
<td align="center">I4</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
@ -547,8 +547,8 @@
</tr>
<tr class="odd">
<td align="center">3</td>
<td align="center">2010-05-12</td>
<td align="center">X9</td>
<td align="center">2010-03-09</td>
<td align="center">I4</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -558,10 +558,10 @@
</tr>
<tr class="even">
<td align="center">4</td>
<td align="center">2010-08-29</td>
<td align="center">X9</td>
<td align="center">2010-04-06</td>
<td align="center">I4</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
@ -569,8 +569,8 @@
</tr>
<tr class="odd">
<td align="center">5</td>
<td align="center">2011-01-07</td>
<td align="center">X9</td>
<td align="center">2010-07-14</td>
<td align="center">I4</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -580,30 +580,30 @@
</tr>
<tr class="even">
<td align="center">6</td>
<td align="center">2011-04-20</td>
<td align="center">X9</td>
<td align="center">2010-08-03</td>
<td align="center">I4</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">7</td>
<td align="center">2011-06-24</td>
<td align="center">X9</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">FALSE</td>
</tr>
<tr class="odd">
<td align="center">7</td>
<td align="center">2010-09-19</td>
<td align="center">I4</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">8</td>
<td align="center">2011-07-10</td>
<td align="center">X9</td>
<td align="center">2010-09-19</td>
<td align="center">I4</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -613,21 +613,21 @@
</tr>
<tr class="odd">
<td align="center">9</td>
<td align="center">2011-11-07</td>
<td align="center">X9</td>
<td align="center">2010-10-05</td>
<td align="center">I4</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-12-20</td>
<td align="center">X9</td>
<td align="center">2010-12-30</td>
<td align="center">I4</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
@ -635,7 +635,7 @@
</tr>
</tbody>
</table>
<p>Only 2 isolates are marked as ‘first’ according to CLSI guideline. But when reviewing the antibiogram, it is obvious that some isolates are absolutely different strains and should be included too. This is why we weigh isolates, based on their antibiogram. The <code><a href="../reference/key_antibiotics.html">key_antibiotics()</a></code> function adds a vector with 18 key antibiotics: 6 broad spectrum ones, 6 small spectrum for Gram negatives and 6 small spectrum for Gram positives. These can be defined by the user.</p>
<p>Only 1 isolates are marked as ‘first’ according to CLSI guideline. But when reviewing the antibiogram, it is obvious that some isolates are absolutely different strains and should be included too. This is why we weigh isolates, based on their antibiogram. The <code><a href="../reference/key_antibiotics.html">key_antibiotics()</a></code> function adds a vector with 18 key antibiotics: 6 broad spectrum ones, 6 small spectrum for Gram negatives and 6 small spectrum for Gram positives. These can be defined by the user.</p>
<p>If a column exists with a name like ‘key(…)ab’ the <code><a href="../reference/first_isolate.html">first_isolate()</a></code> function will automatically use it and determine the first weighted isolates. Mind the NOTEs in below output:</p>
<div class="sourceCode" id="cb20"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb20-1" data-line-number="1">data &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb20-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">keyab =</span> <span class="kw"><a href="../reference/key_antibiotics.html">key_antibiotics</a></span>(.)) <span class="op">%&gt;%</span><span class="st"> </span></a>
@ -646,7 +646,7 @@
<a class="sourceLine" id="cb20-7" data-line-number="7"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `patient_id` as input for `col_patient_id`.</span></a>
<a class="sourceLine" id="cb20-8" data-line-number="8"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `keyab` as input for `col_keyantibiotics`. Use col_keyantibiotics = FALSE to prevent this.</span></a>
<a class="sourceLine" id="cb20-9" data-line-number="9"><span class="co"># [Criterion] Inclusion based on key antibiotics, ignoring I</span></a>
<a class="sourceLine" id="cb20-10" data-line-number="10"><span class="co"># =&gt; Found 15,141 first weighted isolates (75.7% of total)</span></a></code></pre></div>
<a class="sourceLine" id="cb20-10" data-line-number="10"><span class="co"># =&gt; Found 15,143 first weighted isolates (75.7% of total)</span></a></code></pre></div>
<table class="table">
<thead><tr class="header">
<th align="center">isolate</th>
@ -663,8 +663,8 @@
<tbody>
<tr class="odd">
<td align="center">1</td>
<td align="center">2010-01-31</td>
<td align="center">X9</td>
<td align="center">2010-02-10</td>
<td align="center">I4</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
@ -675,20 +675,20 @@
</tr>
<tr class="even">
<td align="center">2</td>
<td align="center">2010-04-03</td>
<td align="center">X9</td>
<td align="center">2010-02-19</td>
<td align="center">I4</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">3</td>
<td align="center">2010-05-12</td>
<td align="center">X9</td>
<td align="center">2010-03-09</td>
<td align="center">I4</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -699,10 +699,10 @@
</tr>
<tr class="even">
<td align="center">4</td>
<td align="center">2010-08-29</td>
<td align="center">X9</td>
<td align="center">2010-04-06</td>
<td align="center">I4</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
@ -711,8 +711,8 @@
</tr>
<tr class="odd">
<td align="center">5</td>
<td align="center">2011-01-07</td>
<td align="center">X9</td>
<td align="center">2010-07-14</td>
<td align="center">I4</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -723,71 +723,71 @@
</tr>
<tr class="even">
<td align="center">6</td>
<td align="center">2011-04-20</td>
<td align="center">X9</td>
<td align="center">2010-08-03</td>
<td align="center">I4</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">TRUE</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">7</td>
<td align="center">2011-06-24</td>
<td align="center">X9</td>
<td align="center">2010-09-19</td>
<td align="center">I4</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">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="even">
<td align="center">8</td>
<td align="center">2011-07-10</td>
<td align="center">X9</td>
<td align="center">2010-09-19</td>
<td align="center">I4</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
<td align="center">FALSE</td>
</tr>
<tr class="odd">
<td align="center">9</td>
<td align="center">2011-11-07</td>
<td align="center">X9</td>
<td align="center">2010-10-05</td>
<td align="center">I4</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-12-20</td>
<td align="center">X9</td>
<td align="center">2010-12-30</td>
<td align="center">I4</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
<td align="center">FALSE</td>
</tr>
</tbody>
</table>
<p>Instead of 2, now 8 isolates are flagged. In total, 75.7% of all isolates are marked ‘first weighted’ - 47.4% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.</p>
<p>Instead of 1, now 6 isolates are flagged. In total, 75.7% of all isolates are marked ‘first weighted’ - 47.3% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.</p>
<p>As with <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code>, there’s a shortcut for this new algorithm too:</p>
<div class="sourceCode" id="cb21"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb21-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb21-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/first_isolate.html">filter_first_weighted_isolate</a></span>()</a></code></pre></div>
<p>So we end up with 15,141 isolates for analysis.</p>
<p>So we end up with 15,143 isolates for analysis.</p>
<p>We can remove unneeded columns:</p>
<div class="sourceCode" id="cb22"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb22-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data_1st <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb22-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="op">-</span><span class="kw"><a href="https://rdrr.io/r/base/c.html">c</a></span>(first, keyab))</a></code></pre></div>
@ -795,6 +795,7 @@
<div class="sourceCode" id="cb23"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb23-1" data-line-number="1"><span class="kw"><a href="https://rdrr.io/r/utils/head.html">head</a></span>(data_1st)</a></code></pre></div>
<table class="table">
<thead><tr class="header">
<th></th>
<th align="center">date</th>
<th align="center">patient_id</th>
<th align="center">hospital</th>
@ -811,95 +812,101 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2011-07-28</td>
<td align="center">N6</td>
<td align="center">Hospital C</td>
<td>1</td>
<td align="center">2012-05-14</td>
<td align="center">G6</td>
<td align="center">Hospital B</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">R</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="even">
<td align="center">2012-08-16</td>
<td align="center">Q6</td>
<td align="center">Hospital C</td>
<td>3</td>
<td align="center">2010-04-06</td>
<td align="center">F7</td>
<td align="center">Hospital B</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">R</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 align="center">2017-05-07</td>
<td align="center">G5</td>
<td>5</td>
<td align="center">2017-05-22</td>
<td align="center">T6</td>
<td align="center">Hospital A</td>
<td align="center">B_STPHY_AURS</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">M</td>
<td align="center">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 align="center">2015-10-29</td>
<td align="center">V10</td>
<td>6</td>
<td align="center">2012-06-06</td>
<td align="center">X7</td>
<td align="center">Hospital D</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">2013-08-21</td>
<td align="center">U1</td>
<td align="center">Hospital A</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">2017-06-24</td>
<td align="center">K6</td>
<td align="center">Hospital A</td>
<td align="center">B_STPHY_AURS</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
<td align="center">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>7</td>
<td align="center">2010-02-15</td>
<td align="center">O1</td>
<td align="center">Hospital A</td>
<td align="center">B_STPHY_AURS</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram-positive</td>
<td align="center">Staphylococcus</td>
<td align="center">aureus</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td>9</td>
<td align="center">2016-11-25</td>
<td align="center">C6</td>
<td align="center">Hospital B</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
</tbody>
</table>
<p>Time for the analysis!</p>
@ -919,7 +926,7 @@
<div class="sourceCode" id="cb25"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb25-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/clean/man/freq.html">freq</a></span>(genus, species)</a></code></pre></div>
<p><strong>Frequency table</strong></p>
<p>Class: character<br>
Length: 15,141 (of which NA: 0 = 0%)<br>
Length: 15,143 (of which NA: 0 = 0%)<br>
Unique: 4</p>
<p>Shortest: 16<br>
Longest: 24</p>
@ -936,33 +943,33 @@ Longest: 24</p>
<tr class="odd">
<td align="left">1</td>
<td align="left">Escherichia coli</td>
<td align="right">7,470</td>
<td align="right">49.34%</td>
<td align="right">7,470</td>
<td align="right">49.34%</td>
<td align="right">7,512</td>
<td align="right">49.61%</td>
<td align="right">7,512</td>
<td align="right">49.61%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">Staphylococcus aureus</td>
<td align="right">3,803</td>
<td align="right">25.12%</td>
<td align="right">11,273</td>
<td align="right">74.45%</td>
<td align="right">3,819</td>
<td align="right">25.22%</td>
<td align="right">11,331</td>
<td align="right">74.83%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">Streptococcus pneumoniae</td>
<td align="right">2,290</td>
<td align="right">15.12%</td>
<td align="right">13,563</td>
<td align="right">89.58%</td>
<td align="right">2,243</td>
<td align="right">14.81%</td>
<td align="right">13,574</td>
<td align="right">89.64%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">Klebsiella pneumoniae</td>
<td align="right">1,578</td>
<td align="right">10.42%</td>
<td align="right">15,141</td>
<td align="right">1,569</td>
<td align="right">10.36%</td>
<td align="right">15,143</td>
<td align="right">100.00%</td>
</tr>
</tbody>
@ -973,7 +980,7 @@ Longest: 24</p>
<a href="#resistance-percentages" class="anchor"></a>Resistance percentages</h2>
<p>The functions <code><a href="../reference/portion.html">portion_S()</a></code>, <code><a href="../reference/portion.html">portion_SI()</a></code>, <code><a href="../reference/portion.html">portion_I()</a></code>, <code><a href="../reference/portion.html">portion_IR()</a></code> and <code><a href="../reference/portion.html">portion_R()</a></code> can be used to determine the portion of a specific antimicrobial outcome. As per the EUCAST guideline of 2019, we calculate resistance as the portion of R (<code><a href="../reference/portion.html">portion_R()</a></code>) and susceptibility as the portion of S and I (<code><a href="../reference/portion.html">portion_SI()</a></code>). These functions can be used on their own:</p>
<div class="sourceCode" id="cb26"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb26-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/portion.html">portion_R</a></span>(AMX)</a>
<a class="sourceLine" id="cb26-2" data-line-number="2"><span class="co"># [1] 0.4656231</span></a></code></pre></div>
<a class="sourceLine" id="cb26-2" data-line-number="2"><span class="co"># [1] 0.4667503</span></a></code></pre></div>
<p>Or can be used in conjuction with <code><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/summarise.html">summarise()</a></code>, both from the <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb27"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb27-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb27-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital) <span class="op">%&gt;%</span><span class="st"> </span></a>
@ -986,19 +993,19 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Hospital A</td>
<td align="center">0.4748959</td>
<td align="center">0.4672547</td>
</tr>
<tr class="even">
<td align="center">Hospital B</td>
<td align="center">0.4543224</td>
<td align="center">0.4670225</td>
</tr>
<tr class="odd">
<td align="center">Hospital C</td>
<td align="center">0.4659041</td>
<td align="center">0.4648625</td>
</tr>
<tr class="even">
<td align="center">Hospital D</td>
<td align="center">0.4712529</td>
<td align="center">0.4669489</td>
</tr>
</tbody>
</table>
@ -1016,23 +1023,23 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Hospital A</td>
<td align="center">0.4748959</td>
<td align="center">4561</td>
<td align="center">0.4672547</td>
<td align="center">4535</td>
</tr>
<tr class="even">
<td align="center">Hospital B</td>
<td align="center">0.4543224</td>
<td align="center">5298</td>
<td align="center">0.4670225</td>
<td align="center">5246</td>
</tr>
<tr class="odd">
<td align="center">Hospital C</td>
<td align="center">0.4659041</td>
<td align="center">2273</td>
<td align="center">0.4648625</td>
<td align="center">2291</td>
</tr>
<tr class="even">
<td align="center">Hospital D</td>
<td align="center">0.4712529</td>
<td align="center">3009</td>
<td align="center">0.4669489</td>
<td align="center">3071</td>
</tr>
</tbody>
</table>
@ -1052,27 +1059,27 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Escherichia</td>
<td align="center">0.9285141</td>
<td align="center">0.8966533</td>
<td align="center">0.9929050</td>
<td align="center">0.9247870</td>
<td align="center">0.8880458</td>
<td align="center">0.9928115</td>
</tr>
<tr class="even">
<td align="center">Klebsiella</td>
<td align="center">0.8225602</td>
<td align="center">0.9017744</td>
<td align="center">0.9866920</td>
<td align="center">0.8132569</td>
<td align="center">0.8986616</td>
<td align="center">0.9859783</td>
</tr>
<tr class="odd">
<td align="center">Staphylococcus</td>
<td align="center">0.9250592</td>
<td align="center">0.9261110</td>
<td align="center">0.9968446</td>
<td align="center">0.9138518</td>
<td align="center">0.9185651</td>
<td align="center">0.9934538</td>
</tr>
<tr class="even">
<td align="center">Streptococcus</td>
<td align="center">0.6200873</td>
<td align="center">0.6290682</td>
<td align="center">0.0000000</td>
<td align="center">0.6200873</td>
<td align="center">0.6290682</td>
</tr>
</tbody>
</table>

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docs/articles/EUCAST.html
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@ -187,7 +187,7 @@
<h1>How to apply EUCAST rules</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">13 October 2019</h4>
<h4 class="date">16 October 2019</h4>
<div class="hidden name"><code>EUCAST.Rmd</code></div>

58
docs/articles/MDR.html
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@ -187,7 +187,7 @@
<h1>How to determine multi-drug resistance (MDR)</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">13 October 2019</h4>
<h4 class="date">16 October 2019</h4>
<div class="hidden name"><code>MDR.Rmd</code></div>
@ -230,18 +230,18 @@
<p>The data set looks like this now:</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" data-line-number="1"><span class="kw"><a href="https://rdrr.io/r/utils/head.html">head</a></span>(my_TB_data)</a>
<a class="sourceLine" id="cb3-2" data-line-number="2"><span class="co"># rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin</span></a>
<a class="sourceLine" id="cb3-3" data-line-number="3"><span class="co"># 1 R S S I S S</span></a>
<a class="sourceLine" id="cb3-4" data-line-number="4"><span class="co"># 2 I R S R S R</span></a>
<a class="sourceLine" id="cb3-5" data-line-number="5"><span class="co"># 3 S S R R R R</span></a>
<a class="sourceLine" id="cb3-6" data-line-number="6"><span class="co"># 4 S R R S S S</span></a>
<a class="sourceLine" id="cb3-7" data-line-number="7"><span class="co"># 5 S R R S R R</span></a>
<a class="sourceLine" id="cb3-8" data-line-number="8"><span class="co"># 6 R S S R R S</span></a>
<a class="sourceLine" id="cb3-3" data-line-number="3"><span class="co"># 1 S S R S R S</span></a>
<a class="sourceLine" id="cb3-4" data-line-number="4"><span class="co"># 2 S R R S S R</span></a>
<a class="sourceLine" id="cb3-5" data-line-number="5"><span class="co"># 3 R R S S R S</span></a>
<a class="sourceLine" id="cb3-6" data-line-number="6"><span class="co"># 4 R R R S S S</span></a>
<a class="sourceLine" id="cb3-7" data-line-number="7"><span class="co"># 5 R R R R R R</span></a>
<a class="sourceLine" id="cb3-8" data-line-number="8"><span class="co"># 6 R R R I S R</span></a>
<a class="sourceLine" id="cb3-9" data-line-number="9"><span class="co"># kanamycin</span></a>
<a class="sourceLine" id="cb3-10" data-line-number="10"><span class="co"># 1 R</span></a>
<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># 2 R</span></a>
<a class="sourceLine" id="cb3-12" data-line-number="12"><span class="co"># 3 I</span></a>
<a class="sourceLine" id="cb3-10" data-line-number="10"><span class="co"># 1 I</span></a>
<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># 2 S</span></a>
<a class="sourceLine" id="cb3-12" data-line-number="12"><span class="co"># 3 R</span></a>
<a class="sourceLine" id="cb3-13" data-line-number="13"><span class="co"># 4 S</span></a>
<a class="sourceLine" id="cb3-14" data-line-number="14"><span class="co"># 5 S</span></a>
<a class="sourceLine" id="cb3-14" data-line-number="14"><span class="co"># 5 R</span></a>
<a class="sourceLine" id="cb3-15" data-line-number="15"><span class="co"># 6 S</span></a></code></pre></div>
<p>We can now add the interpretation of MDR-TB to our data set:</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" data-line-number="1">my_TB_data<span class="op">$</span>mdr &lt;-<span class="st"> </span><span class="kw"><a href="../reference/mdro.html">mdr_tb</a></span>(my_TB_data)</a>
@ -275,40 +275,40 @@ Unique: 5</p>
<tr class="odd">
<td align="left">1</td>
<td align="left">Mono-resistant</td>
<td align="right">3246</td>
<td align="right">64.92%</td>
<td align="right">3246</td>
<td align="right">64.92%</td>
<td align="right">3276</td>
<td align="right">65.52%</td>
<td align="right">3276</td>
<td align="right">65.52%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">Negative</td>
<td align="right">681</td>
<td align="right">13.62%</td>
<td align="right">3927</td>
<td align="right">78.54%</td>
<td align="right">658</td>
<td align="right">13.16%</td>
<td align="right">3934</td>
<td align="right">78.68%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">Multi-drug-resistant</td>
<td align="right">593</td>
<td align="right">11.86%</td>
<td align="right">4520</td>
<td align="right">90.40%</td>
<td align="right">616</td>
<td align="right">12.32%</td>
<td align="right">4550</td>
<td align="right">91.00%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">Poly-resistant</td>
<td align="right">276</td>
<td align="right">5.52%</td>
<td align="right">4796</td>
<td align="right">95.92%</td>
<td align="right">256</td>
<td align="right">5.12%</td>
<td align="right">4806</td>
<td align="right">96.12%</td>
</tr>
<tr class="odd">
<td align="left">5</td>
<td align="left">Extensive drug-resistant</td>
<td align="right">204</td>
<td align="right">4.08%</td>
<td align="right">194</td>
<td align="right">3.88%</td>
<td align="right">5000</td>
<td align="right">100.00%</td>
</tr>

2
docs/articles/SPSS.html
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@ -187,7 +187,7 @@
<h1>How to import data from SPSS / SAS / Stata</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">13 October 2019</h4>
<h4 class="date">16 October 2019</h4>
<div class="hidden name"><code>SPSS.Rmd</code></div>

2
docs/articles/WHONET.html
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@ -187,7 +187,7 @@
<h1>How to work with WHONET data</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">13 October 2019</h4>
<h4 class="date">16 October 2019</h4>
<div class="hidden name"><code>WHONET.Rmd</code></div>

115
docs/articles/benchmarks.html
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@ -187,7 +187,7 @@
<h1>Benchmarks</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">13 October 2019</h4>
<h4 class="date">16 October 2019</h4>
<div class="hidden name"><code>benchmarks.Rmd</code></div>
@ -221,36 +221,21 @@
<a class="sourceLine" id="cb2-16" data-line-number="16"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb2-17" data-line-number="17"><span class="kw"><a href="https://rdrr.io/r/base/print.html">print</a></span>(S.aureus, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">2</span>)</a>
<a class="sourceLine" id="cb2-18" data-line-number="18"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb2-19" data-line-number="19"><span class="co"># expr min lq mean median uq max</span></a>
<a class="sourceLine" id="cb2-20" data-line-number="20"><span class="co"># as.mo("sau") 9.5 9.7 15 10 11 34</span></a>
<a class="sourceLine" id="cb2-21" data-line-number="21"><span class="co"># as.mo("stau") 31.0 32.0 38 33 34 62</span></a>
<a class="sourceLine" id="cb2-22" data-line-number="22"><span class="co"># as.mo("STAU") 31.0 32.0 39 35 39 56</span></a>
<a class="sourceLine" id="cb2-23" data-line-number="23"><span class="co"># as.mo("staaur") 9.6 10.0 17 11 31 31</span></a>
<a class="sourceLine" id="cb2-24" data-line-number="24"><span class="co"># as.mo("STAAUR") 9.6 9.8 13 10 10 34</span></a>
<a class="sourceLine" id="cb2-25" data-line-number="25"><span class="co"># as.mo("S. aureus") 24.0 25.0 27 25 28 33</span></a>
<a class="sourceLine" id="cb2-26" data-line-number="26"><span class="co"># as.mo("S aureus") 24.0 25.0 31 25 43 51</span></a>
<a class="sourceLine" id="cb2-27" data-line-number="27"><span class="co"># as.mo("Staphylococcus aureus") 29.0 30.0 32 31 34 39</span></a>
<a class="sourceLine" id="cb2-28" data-line-number="28"><span class="co"># as.mo("Staphylococcus aureus (MRSA)") 550.0 580.0 610 600 620 680</span></a>
<a class="sourceLine" id="cb2-29" data-line-number="29"><span class="co"># as.mo("Sthafilokkockus aaureuz") 290.0 310.0 360 340 380 530</span></a>
<a class="sourceLine" id="cb2-30" data-line-number="30"><span class="co"># as.mo("MRSA") 9.6 10.0 16 10 30 32</span></a>
<a class="sourceLine" id="cb2-31" data-line-number="31"><span class="co"># as.mo("VISA") 19.0 20.0 21 20 21 22</span></a>
<a class="sourceLine" id="cb2-32" data-line-number="32"><span class="co"># as.mo("VRSA") 20.0 20.0 26 21 24 46</span></a>
<a class="sourceLine" id="cb2-33" data-line-number="33"><span class="co"># as.mo(22242419) 18.0 18.0 19 19 19 22</span></a>
<a class="sourceLine" id="cb2-34" data-line-number="34"><span class="co"># neval</span></a>
<a class="sourceLine" id="cb2-35" data-line-number="35"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-36" data-line-number="36"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-37" data-line-number="37"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-38" data-line-number="38"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-39" data-line-number="39"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-40" data-line-number="40"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-41" data-line-number="41"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-42" data-line-number="42"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-43" data-line-number="43"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-44" data-line-number="44"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-45" data-line-number="45"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-46" data-line-number="46"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-47" data-line-number="47"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-48" data-line-number="48"><span class="co"># 10</span></a></code></pre></div>
<a class="sourceLine" id="cb2-19" data-line-number="19"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb2-20" data-line-number="20"><span class="co"># as.mo("sau") 9.9 10 14 11 12 35 10</span></a>
<a class="sourceLine" id="cb2-21" data-line-number="21"><span class="co"># as.mo("stau") 33.0 33 39 38 39 52 10</span></a>
<a class="sourceLine" id="cb2-22" data-line-number="22"><span class="co"># as.mo("STAU") 32.0 36 44 38 56 68 10</span></a>
<a class="sourceLine" id="cb2-23" data-line-number="23"><span class="co"># as.mo("staaur") 10.0 10 13 11 11 34 10</span></a>
<a class="sourceLine" id="cb2-24" data-line-number="24"><span class="co"># as.mo("STAAUR") 10.0 11 19 12 33 42 10</span></a>
<a class="sourceLine" id="cb2-25" data-line-number="25"><span class="co"># as.mo("S. aureus") 25.0 26 32 28 32 53 10</span></a>
<a class="sourceLine" id="cb2-26" data-line-number="26"><span class="co"># as.mo("S aureus") 24.0 25 31 27 30 52 10</span></a>
<a class="sourceLine" id="cb2-27" data-line-number="27"><span class="co"># as.mo("Staphylococcus aureus") 31.0 32 39 34 38 84 10</span></a>
<a class="sourceLine" id="cb2-28" data-line-number="28"><span class="co"># as.mo("Staphylococcus aureus (MRSA)") 610.0 640 680 680 710 770 10</span></a>
<a class="sourceLine" id="cb2-29" data-line-number="29"><span class="co"># as.mo("Sthafilokkockus aaureuz") 330.0 340 350 350 360 370 10</span></a>
<a class="sourceLine" id="cb2-30" data-line-number="30"><span class="co"># as.mo("MRSA") 9.8 10 13 11 12 34 10</span></a>
<a class="sourceLine" id="cb2-31" data-line-number="31"><span class="co"># as.mo("VISA") 20.0 22 29 24 31 57 10</span></a>
<a class="sourceLine" id="cb2-32" data-line-number="32"><span class="co"># as.mo("VRSA") 20.0 20 29 23 42 47 10</span></a>
<a class="sourceLine" id="cb2-33" data-line-number="33"><span class="co"># as.mo(22242419) 21.0 23 30 25 43 47 10</span></a></code></pre></div>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-5-1.png" width="562.5"></p>
<p>In the table above, all measurements are shown in milliseconds (thousands of seconds). A value of 5 milliseconds means it can determine 200 input values per second. It case of 100 milliseconds, this is only 10 input values per second. The second input is the only one that has to be looked up thoroughly. All the others are known codes (the first one is a WHONET code) or common laboratory codes, or common full organism names like the last one. Full organism names are always preferred.</p>
<p>To achieve this speed, the <code>as.mo</code> function also takes into account the prevalence of human pathogenic microorganisms. The downside is of course that less prevalent microorganisms will be determined less fast. See this example for the ID of <em>Methanosarcina semesiae</em> (<code>B_MTHNSR_SEMS</code>), a bug probably never found before in humans:</p>
@ -262,19 +247,19 @@
<a class="sourceLine" id="cb3-6" data-line-number="6"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb3-7" data-line-number="7"><span class="kw"><a href="https://rdrr.io/r/base/print.html">print</a></span>(M.semesiae, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">4</span>)</a>
<a class="sourceLine" id="cb3-8" data-line-number="8"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb3-9" data-line-number="9"><span class="co"># expr min lq mean median uq</span></a>
<a class="sourceLine" id="cb3-10" data-line-number="10"><span class="co"># as.mo("metsem") 1293.00 1304.00 1394.00 1316.00 1395.00</span></a>
<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># as.mo("METSEM") 1232.00 1278.00 1510.00 1309.00 1518.00</span></a>
<a class="sourceLine" id="cb3-12" data-line-number="12"><span class="co"># as.mo("M. semesiae") 1874.00 1928.00 2063.00 1961.00 2167.00</span></a>
<a class="sourceLine" id="cb3-13" data-line-number="13"><span class="co"># as.mo("M. semesiae") 1883.00 1926.00 2091.00 1978.00 2060.00</span></a>
<a class="sourceLine" id="cb3-14" data-line-number="14"><span class="co"># as.mo("Methanosarcina semesiae") 30.23 31.64 35.26 31.82 38.29</span></a>
<a class="sourceLine" id="cb3-9" data-line-number="9"><span class="co"># expr min lq mean median uq</span></a>
<a class="sourceLine" id="cb3-10" data-line-number="10"><span class="co"># as.mo("metsem") 1343.00 1385.00 1398.00 1403.00 1418.0</span></a>
<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># as.mo("METSEM") 1299.00 1356.00 1397.00 1396.00 1442.0</span></a>
<a class="sourceLine" id="cb3-12" data-line-number="12"><span class="co"># as.mo("M. semesiae") 1892.00 2028.00 2052.00 2041.00 2084.0</span></a>
<a class="sourceLine" id="cb3-13" data-line-number="13"><span class="co"># as.mo("M. semesiae") 1990.00 2017.00 2062.00 2032.00 2094.0</span></a>
<a class="sourceLine" id="cb3-14" data-line-number="14"><span class="co"># as.mo("Methanosarcina semesiae") 32.63 33.24 38.58 35.82 40.2</span></a>
<a class="sourceLine" id="cb3-15" data-line-number="15"><span class="co"># max neval</span></a>
<a class="sourceLine" id="cb3-16" data-line-number="16"><span class="co"># 1929.00 10</span></a>
<a class="sourceLine" id="cb3-17" data-line-number="17"><span class="co"># 2721.00 10</span></a>
<a class="sourceLine" id="cb3-18" data-line-number="18"><span class="co"># 2676.00 10</span></a>
<a class="sourceLine" id="cb3-19" data-line-number="19"><span class="co"># 2974.00 10</span></a>
<a class="sourceLine" id="cb3-20" data-line-number="20"><span class="co"># 52.65 10</span></a></code></pre></div>
<p>That takes 15.8 times as much time on average. A value of 100 milliseconds means it can only determine ~10 different input values per second. We can conclude that looking up arbitrary codes of less prevalent microorganisms is the worst way to go, in terms of calculation performance. Full names (like <em>Methanosarcina semesiae</em>) are almost fast - these are the most probable input from most data sets.</p>
<a class="sourceLine" id="cb3-16" data-line-number="16"><span class="co"># 1437.00 10</span></a>
<a class="sourceLine" id="cb3-17" data-line-number="17"><span class="co"># 1488.00 10</span></a>
<a class="sourceLine" id="cb3-18" data-line-number="18"><span class="co"># 2169.00 10</span></a>
<a class="sourceLine" id="cb3-19" data-line-number="19"><span class="co"># 2245.00 10</span></a>
<a class="sourceLine" id="cb3-20" data-line-number="20"><span class="co"># 57.04 10</span></a></code></pre></div>
<p>That takes 14.3 times as much time on average. A value of 100 milliseconds means it can only determine ~10 different input values per second. We can conclude that looking up arbitrary codes of less prevalent microorganisms is the worst way to go, in terms of calculation performance. Full names (like <em>Methanosarcina semesiae</em>) are almost fast - these are the most probable input from most data sets.</p>
<p>In the figure below, we compare <em>Escherichia coli</em> (which is very common) with <em>Prevotella brevis</em> (which is moderately common) and with <em>Methanosarcina semesiae</em> (which is uncommon):</p>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-9-1.png" width="562.5"></p>
<p>In reality, the <code><a href="../reference/as.mo.html">as.mo()</a></code> functions <strong>learns from its own output to speed up determinations for next times</strong>. In above figure, this effect was disabled to show the difference with the boxplot below - when you would use <code><a href="../reference/as.mo.html">as.mo()</a></code> yourself:</p>
@ -311,8 +296,8 @@
<a class="sourceLine" id="cb4-24" data-line-number="24"><span class="kw"><a href="https://rdrr.io/r/base/print.html">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb4-25" data-line-number="25"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb4-26" data-line-number="26"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb4-27" data-line-number="27"><span class="co"># mo_name(x) 596 604 651 641 663 813 10</span></a></code></pre></div>
<p>So transforming 500,000 values (!!) of 50 unique values only takes 0.64 seconds (641 ms). You only lose time on your unique input values.</p>
<a class="sourceLine" id="cb4-27" data-line-number="27"><span class="co"># mo_name(x) 645 661 683 672 686 771 10</span></a></code></pre></div>
<p>So transforming 500,000 values (!!) of 50 unique values only takes 0.67 seconds (671 ms). You only lose time on your unique input values.</p>
</div>
<div id="precalculated-results" class="section level3">
<h3 class="hasAnchor">
@ -324,10 +309,10 @@
<a class="sourceLine" id="cb5-4" data-line-number="4"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb5-5" data-line-number="5"><span class="kw"><a href="https://rdrr.io/r/base/print.html">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb5-6" data-line-number="6"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb5-7" data-line-number="7"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb5-8" data-line-number="8"><span class="co"># A 6.300 6.460 6.79 6.500 6.810 8.32 10</span></a>
<a class="sourceLine" id="cb5-9" data-line-number="9"><span class="co"># B 24.600 24.700 28.70 25.600 26.600 51.30 10</span></a>
<a class="sourceLine" id="cb5-10" data-line-number="10"><span class="co"># C 0.778 0.828 0.93 0.854 0.872 1.63 10</span></a></code></pre></div>
<a class="sourceLine" id="cb5-7" data-line-number="7"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb5-8" data-line-number="8"><span class="co"># A 6.380 6.530 7.750 7.180 8.21 11.30 10</span></a>
<a class="sourceLine" id="cb5-9" data-line-number="9"><span class="co"># B 24.300 25.500 30.400 26.900 31.60 54.80 10</span></a>
<a class="sourceLine" id="cb5-10" data-line-number="10"><span class="co"># C 0.803 0.827 0.926 0.869 0.95 1.22 10</span></a></code></pre></div>
<p>So going from <code><a href="../reference/mo_property.html">mo_name("Staphylococcus aureus")</a></code> to <code>"Staphylococcus aureus"</code> takes 0.0009 seconds - it doesn’t even start calculating <em>if the result would be the same as the expected resulting value</em>. That goes for all helper functions:</p>
<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb6-1" data-line-number="1">run_it &lt;-<span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span>(<span class="dt">A =</span> <span class="kw"><a href="../reference/mo_property.html">mo_species</a></span>(<span class="st">"aureus"</span>),</a>
<a class="sourceLine" id="cb6-2" data-line-number="2"> <span class="dt">B =</span> <span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(<span class="st">"Staphylococcus"</span>),</a>
@ -341,14 +326,14 @@
<a class="sourceLine" id="cb6-10" data-line-number="10"><span class="kw"><a href="https://rdrr.io/r/base/print.html">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb6-11" data-line-number="11"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb6-12" data-line-number="12"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb6-13" data-line-number="13"><span class="co"># A 0.457 0.463 0.477 0.476 0.483 0.511 10</span></a>
<a class="sourceLine" id="cb6-14" data-line-number="14"><span class="co"># B 0.486 0.496 0.508 0.499 0.512 0.569 10</span></a>
<a class="sourceLine" id="cb6-15" data-line-number="15"><span class="co"># C 0.781 0.803 0.825 0.829 0.847 0.854 10</span></a>
<a class="sourceLine" id="cb6-16" data-line-number="16"><span class="co"># D 0.479 0.495 0.528 0.510 0.517 0.749 10</span></a>
<a class="sourceLine" id="cb6-17" data-line-number="17"><span class="co"># E 0.457 0.464 0.484 0.475 0.498 0.547 10</span></a>
<a class="sourceLine" id="cb6-18" data-line-number="18"><span class="co"># F 0.458 0.464 0.472 0.468 0.477 0.496 10</span></a>
<a class="sourceLine" id="cb6-19" data-line-number="19"><span class="co"># G 0.446 0.453 0.462 0.459 0.467 0.499 10</span></a>
<a class="sourceLine" id="cb6-20" data-line-number="20"><span class="co"># H 0.426 0.458 0.467 0.467 0.472 0.507 10</span></a></code></pre></div>
<a class="sourceLine" id="cb6-13" data-line-number="13"><span class="co"># A 0.509 0.530 0.681 0.565 0.661 1.630 10</span></a>
<a class="sourceLine" id="cb6-14" data-line-number="14"><span class="co"># B 0.518 0.526 0.598 0.553 0.564 0.875 10</span></a>
<a class="sourceLine" id="cb6-15" data-line-number="15"><span class="co"># C 0.848 0.882 1.100 0.990 1.180 1.920 10</span></a>
<a class="sourceLine" id="cb6-16" data-line-number="16"><span class="co"># D 0.566 0.592 0.734 0.714 0.765 1.120 10</span></a>
<a class="sourceLine" id="cb6-17" data-line-number="17"><span class="co"># E 0.486 0.522 0.555 0.542 0.551 0.681 10</span></a>
<a class="sourceLine" id="cb6-18" data-line-number="18"><span class="co"># F 0.466 0.493 0.598 0.553 0.586 1.110 10</span></a>
<a class="sourceLine" id="cb6-19" data-line-number="19"><span class="co"># G 0.462 0.498 0.598 0.525 0.671 0.921 10</span></a>
<a class="sourceLine" id="cb6-20" data-line-number="20"><span class="co"># H 0.480 0.489 0.566 0.508 0.628 0.756 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">
@ -374,14 +359,14 @@
<a class="sourceLine" id="cb7-17" data-line-number="17"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb7-18" data-line-number="18"><span class="kw"><a href="https://rdrr.io/r/base/print.html">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">4</span>)</a>
<a class="sourceLine" id="cb7-19" data-line-number="19"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb7-20" data-line-number="20"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb7-21" data-line-number="21"><span class="co"># en 19.99 20.17 25.15 20.21 22.19 43.86 10</span></a>
<a class="sourceLine" id="cb7-22" data-line-number="22"><span class="co"># de 21.17 21.47 26.00 21.51 21.85 44.12 10</span></a>
<a class="sourceLine" id="cb7-23" data-line-number="23"><span class="co"># nl 26.69 26.71 27.24 27.10 27.80 28.04 10</span></a>
<a class="sourceLine" id="cb7-24" data-line-number="24"><span class="co"># es 21.20 21.36 24.26 21.51 21.85 43.76 10</span></a>
<a class="sourceLine" id="cb7-25" data-line-number="25"><span class="co"># it 21.09 21.24 26.27 21.59 22.46 46.14 10</span></a>
<a class="sourceLine" id="cb7-26" data-line-number="26"><span class="co"># fr 21.16 21.35 23.98 21.51 22.11 44.93 10</span></a>
<a class="sourceLine" id="cb7-27" data-line-number="27"><span class="co"># pt 21.10 21.13 21.35 21.28 21.37 22.24 10</span></a></code></pre></div>
<a class="sourceLine" id="cb7-20" data-line-number="20"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb7-21" data-line-number="21"><span class="co"># en 20.01 20.76 28.07 22.47 29.04 54.04 10</span></a>
<a class="sourceLine" id="cb7-22" data-line-number="22"><span class="co"># de 21.95 22.28 26.91 22.72 24.24 58.36 10</span></a>
<a class="sourceLine" id="cb7-23" data-line-number="23"><span class="co"># nl 27.57 27.96 47.86 31.50 54.01 149.80 10</span></a>
<a class="sourceLine" id="cb7-24" data-line-number="24"><span class="co"># es 22.08 22.13 28.59 24.11 26.45 58.61 10</span></a>
<a class="sourceLine" id="cb7-25" data-line-number="25"><span class="co"># it 21.73 22.33 25.39 25.30 26.90 29.57 10</span></a>
<a class="sourceLine" id="cb7-26" data-line-number="26"><span class="co"># fr 22.23 22.98 24.95 23.45 23.70 34.08 10</span></a>
<a class="sourceLine" id="cb7-27" data-line-number="27"><span class="co"># pt 22.02 23.03 24.80 24.37 27.14 28.33 10</span></a></code></pre></div>
<p>Currently supported are German, Dutch, Spanish, Italian, French and Portuguese.</p>
</div>
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</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9107</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9000</span>
</span>
</div>

2
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@ -187,7 +187,7 @@
<h1>How to predict antimicrobial resistance</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">13 October 2019</h4>
<h4 class="date">16 October 2019</h4>
<div class="hidden name"><code>resistance_predict.Rmd</code></div>

2
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@ -84,7 +84,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9107</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9000</span>
</span>
</div>

4
docs/index.html
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@ -45,7 +45,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9107</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9000</span>
</span>
</div>
@ -196,7 +196,7 @@
<div id="what-is-amr-for-r" class="section level3">
<h3 class="hasAnchor">
<a href="#what-is-amr-for-r" class="anchor"></a>What is <code>AMR</code> (for R)?</h3>
<p><code>AMR</code> is a free and open-source <a href="https://www.r-project.org">R package</a> to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. Since its first public release in early 2018, this package has been downloaded over 20,000 times from more than 40 countries <small>(source: <a href="https://cran-logs.rstudio.com">CRAN logs, 2019</a>)</small>.</p>
<p><code>AMR</code> is a free and open-source <a href="https://www.r-project.org">R package</a> to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. Since its first public release in early 2018, this package has been downloaded over 25,000 times from more than 60 countries <small>(source: <a href="https://cran-logs.rstudio.com">CRAN logs, 2019</a>)</small>.</p>
<p>After installing this package, R knows <a href="./reference/microorganisms.html"><strong>~70,000 microorganisms</strong></a> (distinct microbial species) and <a href="./reference/antibiotics.html"><strong>~450 antibiotics</strong></a> by name and code, and knows all about valid RSI and MIC values. It supports any data format, including WHONET/EARS-Net data.</p>
<p>We created this package for both routine analysis and academic research (as part of our PhD theses) at the Faculty of Medical Sciences of the University of Groningen, the Netherlands, and the Medical Microbiology &amp; Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG). This R package is <a href="./news">actively maintained</a> and is free software (see <a href="#copyright">Copyright</a>).</p>
<p><strong>Used to SPSS?</strong> Read our <a href="./articles/SPSS.html">tutorial on how to import data from SPSS, SAS or Stata</a>.</p>

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@ -84,7 +84,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9107</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9000</span>
</span>
</div>
@ -231,11 +231,24 @@
</div>
<div id="amr-0-7-1-9107" class="section level1">
<div id="amr-0-8-0-9000" class="section level1">
<h1 class="page-header">
<a href="#amr-0-7-1-9107" class="anchor"></a>AMR 0.7.1.9107<small> Unreleased </small>
<a href="#amr-0-8-0-9000" class="anchor"></a>AMR 0.8.0.9000<small> Unreleased </small>
</h1>
<p><small>Last updated: 16-Oct-2019</small></p>
<div id="new" class="section level3">
<h3 class="hasAnchor">
<a href="#new" class="anchor"></a>New</h3>
</div>
<div id="changes" class="section level3">
<h3 class="hasAnchor">
<a href="#changes" class="anchor"></a>Changes</h3>
</div>
</div>
<div id="amr-0-8-0" class="section level1">
<h1 class="page-header">
<a href="#amr-0-8-0" class="anchor"></a>AMR 0.8.0<small> 2019-10-15 </small>
</h1>
<p><small>Last updated: 15-Oct-2019</small></p>
<div id="breaking" class="section level3">
<h3 class="hasAnchor">
<a href="#breaking" class="anchor"></a>Breaking</h3>
@ -262,9 +275,9 @@ This is important, because a value like <code>"testvalue"</code> could never be
<li><p>Renamed data set <code>septic_patients</code> to <code>example_isolates</code></p></li>
</ul>
</div>
<div id="new" class="section level3">
<div id="new-1" class="section level3">
<h3 class="hasAnchor">
<a href="#new" class="anchor"></a>New</h3>
<a href="#new-1" class="anchor"></a>New</h3>
<ul>
<li>
<p>Function <code><a href="../reference/bug_drug_combinations.html">bug_drug_combinations()</a></code> to quickly get a <code>data.frame</code> with the results of all bug-drug combinations in a data set. The column containing microorganism codes is guessed automatically and its input is transformed with <code><a href="../reference/mo_property.html">mo_shortname()</a></code> at default:</p>
@ -387,9 +400,9 @@ Since this is a major change, usage of the old <code>also_single_tested</code> w
<h1 class="page-header">
<a href="#amr-0-7-1" class="anchor"></a>AMR 0.7.1<small> 2019-06-23 </small>
</h1>
<div id="new-1" class="section level4">
<div id="new-2" class="section level4">
<h4 class="hasAnchor">
<a href="#new-1" class="anchor"></a>New</h4>
<a href="#new-2" class="anchor"></a>New</h4>
<ul>
<li>
<p>Function <code><a href="../reference/portion.html">rsi_df()</a></code> to transform a <code>data.frame</code> to a data set containing only the microbial interpretation (S, I, R), the antibiotic, the percentage of S/I/R and the number of available isolates. This is a convenient combination of the existing functions <code><a href="../reference/count.html">count_df()</a></code> and <code><a href="../reference/portion.html">portion_df()</a></code> to immediately show resistance percentages and number of available isolates:</p>
@ -468,9 +481,9 @@ Since this is a major change, usage of the old <code>also_single_tested</code> w
<h1 class="page-header">
<a href="#amr-0-7-0" class="anchor"></a>AMR 0.7.0<small> 2019-06-03 </small>
</h1>
<div id="new-2" class="section level4">
<div id="new-3" class="section level4">
<h4 class="hasAnchor">
<a href="#new-2" class="anchor"></a>New</h4>
<a href="#new-3" class="anchor"></a>New</h4>
<ul>
<li>Support for translation of disk diffusion and MIC values to RSI values (i.e. antimicrobial interpretations). Supported guidelines are EUCAST (2011 to 2019) and CLSI (2011 to 2019). Use <code><a href="../reference/as.rsi.html">as.rsi()</a></code> on an MIC value (created with <code><a href="../reference/as.mic.html">as.mic()</a></code>), a disk diffusion value (created with the new <code><a href="../reference/as.disk.html">as.disk()</a></code>) or on a complete date set containing columns with MIC or disk diffusion values.</li>
<li>Function <code><a href="../reference/mo_property.html">mo_name()</a></code> as alias of <code><a href="../reference/mo_property.html">mo_fullname()</a></code>
@ -585,9 +598,9 @@ Please <a href="https://gitlab.com/msberends/AMR/issues/new?issue%5Btitle%5D=EUC
<li>Contains the complete manual of this package and all of its functions with an explanation of their parameters</li>
<li>Contains a comprehensive tutorial about how to conduct antimicrobial resistance analysis, import data from WHONET or SPSS and many more.</li>
</ul>
<div id="new-3" class="section level4">
<div id="new-4" class="section level4">
<h4 class="hasAnchor">
<a href="#new-3" class="anchor"></a>New</h4>
<a href="#new-4" class="anchor"></a>New</h4>
<ul>
<li>
<strong>BREAKING</strong>: removed deprecated functions, parameters and references to ‘bactid’. Use <code><a href="../reference/as.mo.html">as.mo()</a></code> to identify an MO code.</li>
@ -812,9 +825,9 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
<h1 class="page-header">
<a href="#amr-0-5-0" class="anchor"></a>AMR 0.5.0<small> 2018-11-30 </small>
</h1>
<div id="new-4" class="section level4">
<div id="new-5" class="section level4">
<h4 class="hasAnchor">
<a href="#new-4" class="anchor"></a>New</h4>
<a href="#new-5" class="anchor"></a>New</h4>
<ul>
<li>Repository moved to GitLab: <a href="https://gitlab.com/msberends/AMR" class="uri">https://gitlab.com/msberends/AMR</a>
</li>
@ -939,9 +952,9 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
<h1 class="page-header">
<a href="#amr-0-4-0" class="anchor"></a>AMR 0.4.0<small> 2018-10-01 </small>
</h1>
<div id="new-5" class="section level4">
<div id="new-6" class="section level4">
<h4 class="hasAnchor">
<a href="#new-5" class="anchor"></a>New</h4>
<a href="#new-6" class="anchor"></a>New</h4>
<ul>
<li>The data set <code>microorganisms</code> now contains <strong>all microbial taxonomic data from ITIS</strong> (kingdoms Bacteria, Fungi and Protozoa), the Integrated Taxonomy Information System, available via <a href="https://itis.gov" class="uri">https://itis.gov</a>. The data set now contains more than 18,000 microorganisms with all known bacteria, fungi and protozoa according ITIS with genus, species, subspecies, family, order, class, phylum and subkingdom. The new data set <code>microorganisms.old</code> contains all previously known taxonomic names from those kingdoms.</li>
<li>New functions based on the existing function <code>mo_property</code>:
@ -1074,9 +1087,9 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
<h1 class="page-header">
<a href="#amr-0-3-0" class="anchor"></a>AMR 0.3.0<small> 2018-08-14 </small>
</h1>
<div id="new-6" class="section level4">
<div id="new-7" class="section level4">
<h4 class="hasAnchor">
<a href="#new-6" class="anchor"></a>New</h4>
<a href="#new-7" class="anchor"></a>New</h4>
<ul>
<li>
<strong>BREAKING</strong>: <code>rsi_df</code> was removed in favour of new functions <code>portion_R</code>, <code>portion_IR</code>, <code>portion_I</code>, <code>portion_SI</code> and <code>portion_S</code> to selectively calculate resistance or susceptibility. These functions are 20 to 30 times faster than the old <code>rsi</code> function. The old function still works, but is deprecated.
@ -1211,9 +1224,9 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
<h1 class="page-header">
<a href="#amr-0-2-0" class="anchor"></a>AMR 0.2.0<small> 2018-05-03 </small>
</h1>
<div id="new-7" class="section level4">
<div id="new-8" class="section level4">
<h4 class="hasAnchor">
<a href="#new-7" class="anchor"></a>New</h4>
<a href="#new-8" class="anchor"></a>New</h4>
<ul>
<li>Full support for Windows, Linux and macOS</li>
<li>Full support for old R versions, only R-3.0.0 (April 2013) or later is needed (needed packages may have other dependencies)</li>
@ -1292,7 +1305,8 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
<div id="tocnav">
<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked">
<li><a href="#amr-0-7-1-9107">0.7.1.9107</a></li>
<li><a href="#amr-0-8-0-9000">0.8.0.9000</a></li>
<li><a href="#amr-0-8-0">0.8.0</a></li>
<li><a href="#amr-0-7-1">0.7.1</a></li>
<li><a href="#amr-0-7-0">0.7.0</a></li>
<li><a href="#amr-0-6-1">0.6.1</a></li>

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@ -84,7 +84,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9107</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9000</span>
</span>
</div>

2
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@ -6,7 +6,7 @@
### What is `AMR` (for R)?
`AMR` is a free and open-source [R package](https://www.r-project.org) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. Since its first public release in early 2018, this package has been downloaded over 20,000 times from more than 40 countries <small>(source: [CRAN logs, 2019](https://cran-logs.rstudio.com))</small>.
`AMR` is a free and open-source [R package](https://www.r-project.org) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. Since its first public release in early 2018, this package has been downloaded over 25,000 times from more than 60 countries <small>(source: [CRAN logs, 2019](https://cran-logs.rstudio.com))</small>.
After installing this package, R knows [**~70,000 microorganisms**](./reference/microorganisms.html) (distinct microbial species) and [**~450 antibiotics**](./reference/antibiotics.html) by name and code, and knows all about valid RSI and MIC values. It supports any data format, including WHONET/EARS-Net data.