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(v.1.5.0.9000) implementation of EUCAST rules v11 (2021)

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<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">1.4.0.9053</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.5.0</span>
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.5.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.5.0.9000</span>
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<title>Data sets with 557 antimicrobials — antibiotics • AMR (for R)</title>
<title>Data sets with 558 antimicrobials — antibiotics • AMR (for R)</title>
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<meta property="og:description" content="Two data sets containing all antibiotics/antimycotics and antivirals. Use as.ab() or one of the ab_* functions to retrieve values from the antibiotics data set. Three identifiers are included in this data set: an antibiotic ID (ab, primarily used in this package) as defined by WHONET/EARS-Net, an ATC code (atc) as defined by the WHO, and a Compound ID (cid) as found in PubChem. Other properties in this data set are derived from one or more of these codes." />
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<h1>Data sets with 557 antimicrobials</h1>
<h1>Data sets with 558 antimicrobials</h1>
<small class="dont-index">Source: <a href='https://github.com/msberends/AMR/blob/master/R/data.R'><code>R/data.R</code></a></small>
<div class="hidden name"><code>antibiotics.Rd</code></div>
</div>
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<h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
<h3 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>For the antibiotics data set: a <a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a> with 455 observations and 14 variables:</h3>
<h3 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>For the antibiotics data set: a <a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a> with 456 observations and 14 variables:</h3>
<ul>
<li><p><code>ab</code><br /> Antibiotic ID as used in this package (such as <code>AMC</code>), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available</p></li>

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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">1.5.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.5.0.9000</span>
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</div>
@ -387,14 +387,14 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
<p>With ambiguous user input in <code>as.mo()</code> and all the <code><a href='mo_property.html'>mo_*</a></code> functions, the returned results are chosen based on their matching score using <code><a href='mo_matching_score.html'>mo_matching_score()</a></code>. This matching score \(m\), is calculated as:</p>
<p>$$m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}$$</p>
<p><img src='figures/mo_matching_score.png' width="300px" alt="mo matching score" /></p>
<p>where:</p><ul>
<li><p>\(x\) is the user input;</p></li>
<li><p>\(n\) is a taxonomic name (genus, species, and subspecies);</p></li>
<li><p>\(l_n\) is the length of \(n\);</p></li>
<li><p>lev is the <a href='https://en.wikipedia.org/wiki/Levenshtein_distance'>Levenshtein distance function</a>, which counts any insertion, deletion and substitution as 1 that is needed to change \(x\) into \(n\);</p></li>
<li><p>\(p_n\) is the human pathogenic prevalence group of \(n\), as described below;</p></li>
<li><p>\(k_n\) is the taxonomic kingdom of \(n\), set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.</p></li>
<li><p><i>x</i> is the user input;</p></li>
<li><p><i>n</i> is a taxonomic name (genus, species, and subspecies);</p></li>
<li><p><i>l<sub>n</sub></i> is the length of <i>n</i>;</p></li>
<li><p><i>lev</i> is the <a href="https://en.wikipedia.org/wiki/Levenshtein_distance">Levenshtein distance function</a>, which counts any insertion, deletion and substitution as 1 that is needed to change <i>x</i> into <i>n</i>;</p></li>
<li><p><i>p<sub>n</sub></i> is the human pathogenic prevalence group of <i>n</i>, as described below;</p></li>
<li><p><i>k<sub>n</sub></i> is the taxonomic kingdom of <i>n</i>, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.</p></li>
</ul>
<p>The grouping into human pathogenic prevalence (\(p\)) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. <strong>Group 1</strong> (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is <em>Enterococcus</em>, <em>Staphylococcus</em> or <em>Streptococcus</em>. This group consequently contains all common Gram-negative bacteria, such as <em>Pseudomonas</em> and <em>Legionella</em> and all species within the order Enterobacterales. <strong>Group 2</strong> consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is <em>Absidia</em>, <em>Acremonium</em>, <em>Actinotignum</em>, <em>Alternaria</em>, <em>Anaerosalibacter</em>, <em>Apophysomyces</em>, <em>Arachnia</em>, <em>Aspergillus</em>, <em>Aureobacterium</em>, <em>Aureobasidium</em>, <em>Bacteroides</em>, <em>Basidiobolus</em>, <em>Beauveria</em>, <em>Blastocystis</em>, <em>Branhamella</em>, <em>Calymmatobacterium</em>, <em>Candida</em>, <em>Capnocytophaga</em>, <em>Catabacter</em>, <em>Chaetomium</em>, <em>Chryseobacterium</em>, <em>Chryseomonas</em>, <em>Chrysonilia</em>, <em>Cladophialophora</em>, <em>Cladosporium</em>, <em>Conidiobolus</em>, <em>Cryptococcus</em>, <em>Curvularia</em>, <em>Exophiala</em>, <em>Exserohilum</em>, <em>Flavobacterium</em>, <em>Fonsecaea</em>, <em>Fusarium</em>, <em>Fusobacterium</em>, <em>Hendersonula</em>, <em>Hypomyces</em>, <em>Koserella</em>, <em>Lelliottia</em>, <em>Leptosphaeria</em>, <em>Leptotrichia</em>, <em>Malassezia</em>, <em>Malbranchea</em>, <em>Mortierella</em>, <em>Mucor</em>, <em>Mycocentrospora</em>, <em>Mycoplasma</em>, <em>Nectria</em>, <em>Ochroconis</em>, <em>Oidiodendron</em>, <em>Phoma</em>, <em>Piedraia</em>, <em>Pithomyces</em>, <em>Pityrosporum</em>, <em>Prevotella</em>,\<em>Pseudallescheria</em>, <em>Rhizomucor</em>, <em>Rhizopus</em>, <em>Rhodotorula</em>, <em>Scolecobasidium</em>, <em>Scopulariopsis</em>, <em>Scytalidium</em>,<em>Sporobolomyces</em>, <em>Stachybotrys</em>, <em>Stomatococcus</em>, <em>Treponema</em>, <em>Trichoderma</em>, <em>Trichophyton</em>, <em>Trichosporon</em>, <em>Tritirachium</em> or <em>Ureaplasma</em>. <strong>Group 3</strong> consists of all other microorganisms.</p>

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</tr>
<tr>
<th>add_intrinsic_resistance</th>
<td><p><em>(only useful when using a EUCAST guideline)</em> a logical to indicate whether intrinsic antibiotic resistance must also be considered for applicable bug-drug combinations, meaning that e.g. ampicillin will always return "R" in <em>Klebsiella</em> species. Determination is based on the <a href='intrinsic_resistant.html'>intrinsic_resistant</a> data set, that itself is based on <a href='https://www.eucast.org/expert_rules_and_intrinsic_resistance/'>'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2</a> from 2020.</p></td>
<td><p><em>(only useful when using a EUCAST guideline)</em> a logical to indicate whether intrinsic antibiotic resistance must also be considered for applicable bug-drug combinations, meaning that e.g. ampicillin will always return "R" in <em>Klebsiella</em> species. Determination is based on the <a href='intrinsic_resistant.html'>intrinsic_resistant</a> data set, that itself is based on <a href='https://www.eucast.org/expert_rules_and_intrinsic_resistance/'>'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2</a> (2020).</p></td>
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<tr>
<th>reference_data</th>

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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.5.0</span>
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<h1>Data set with treatment dosages as defined by EUCAST</h1>
<small class="dont-index">Source: <a href='https://github.com/msberends/AMR/blob/master/R/data.R'><code>R/data.R</code></a></small>
<div class="hidden name"><code>dosage.Rd</code></div>
</div>
<div class="ref-description">
<p>EUCAST breakpoints used in this package are based on the dosages in this data set. They can be retrieved with <code><a href='eucast_rules.html'>eucast_dosage()</a></code>.</p>
</div>
<pre class="usage"><span class='va'>dosage</span></pre>
<h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
<p>A <a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a> with 135 observations and 9 variables:</p><ul>
<li><p><code>ab</code><br /> Antibiotic ID as used in this package (such as <code>AMC</code>), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available</p></li>
<li><p><code>name</code><br /> Official name of the antimicrobial agent as used by WHONET/EARS-Net or the WHO</p></li>
<li><p><code>type</code><br /> Type of the dosage, either "high_dosage", "standard_dosage" or "uncomplicated_uti"</p></li>
<li><p><code>dose</code><br /> Dose, such as "2 g" or "25 mg/kg"</p></li>
<li><p><code>dose_times</code><br /> Dose, such as "2 g" or "25 mg/kg"</p></li>
<li><p><code>administration</code><br /> Route of administration, either "im", "iv" or "oral"</p></li>
<li><p><code>notes</code><br /> Additional dosage notes</p></li>
<li><p><code>original_txt</code><br /> Original text in the PDF file of EUCAST</p></li>
<li><p><code>eucast_version</code><br /> Version number of the EUCAST Clinical Breakpoints guideline to which these dosages apply</p></li>
</ul>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p><a href='https://www.eucast.org/clinical_breakpoints/'>'EUCAST Clinical Breakpoint Tables' v11.0</a> (2021) are based on the dosages in this data set.</p>
<h2 class="hasAnchor" id="reference-data-publicly-available"><a class="anchor" href="#reference-data-publicly-available"></a>Reference data publicly available</h2>
<p>All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find <a href='https://msberends.github.io/AMR/articles/datasets.html'>all download links on our website</a>, which is automatically updated with every code change.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.github.io/AMR/'>https://msberends.github.io/AMR/</a> you can find <a href='https://msberends.github.io/AMR/articles/AMR.html'>a comprehensive tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.github.io/AMR/reference/'>complete documentation of all functions</a> and <a href='https://msberends.github.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>. As we would like to better understand the backgrounds and needs of our users, please <a href='https://msberends.github.io/AMR/survey.html'>participate in our survey</a>!</p>
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<p>Developed by <a href='https://www.rug.nl/staff/m.s.berends/'>Matthijs S. Berends</a>, <a href='https://www.rug.nl/staff/c.f.luz/'>Christian F. Luz</a>, <a href='https://www.rug.nl/staff/a.w.friedrich/'>Alexander W. Friedrich</a>, <a href='https://www.rug.nl/staff/b.sinha/'>Bhanu N. M. Sinha</a>, <a href='https://www.rug.nl/staff/c.j.albers/'>Casper J. Albers</a>, <a href='https://www.rug.nl/staff/c.glasner/'>Corinna Glasner</a>.</p>
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21
docs/reference/eucast_rules.html
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@ -49,7 +49,7 @@
<script src="../extra.js"></script>
<meta property="og:title" content="Apply EUCAST rules — eucast_rules" />
<meta property="og:description" content="Apply rules for clinical breakpoints and intrinsic resistance as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, https://eucast.org), see Source.
<meta property="og:description" content="Apply rules for clinical breakpoints and intrinsic resistance as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, https://eucast.org), see Source. Use eucast_dosage() to get advised dosages of a certain bug-drug combination, which is based on the dosage data set.
To improve the interpretation of the antibiogram before EUCAST rules are applied, some non-EUCAST rules can applied at default, see Details." />
<meta property="og:image" content="https://msberends.github.io/AMR/logo.png" />
@ -240,7 +240,7 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
</div>
<div class="ref-description">
<p>Apply rules for clinical breakpoints and intrinsic resistance as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, <a href='https://eucast.org'>https://eucast.org</a>), see <em>Source</em>.</p>
<p>Apply rules for clinical breakpoints and intrinsic resistance as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, <a href='https://eucast.org'>https://eucast.org</a>), see <em>Source</em>. Use <code>eucast_dosage()</code> to get advised dosages of a certain bug-drug combination, which is based on the <a href='dosage.html'>dosage</a> data set.</p>
<p>To improve the interpretation of the antibiogram before EUCAST rules are applied, some non-EUCAST rules can applied at default, see Details.</p>
</div>
@ -254,7 +254,9 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
version_expertrules <span class='op'>=</span> <span class='fl'>3.2</span>,
ampc_cephalosporin_resistance <span class='op'>=</span> <span class='cn'>NA</span>,
<span class='va'>...</span>
<span class='op'>)</span></pre>
<span class='op'>)</span>
<span class='fu'>eucast_dosage</span><span class='op'>(</span><span class='va'>ab</span>, administration <span class='op'>=</span> <span class='st'>"iv"</span>, version_breakpoints <span class='op'>=</span> <span class='fl'>11</span><span class='op'>)</span></pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
@ -281,7 +283,7 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
</tr>
<tr>
<th>version_breakpoints</th>
<td><p>the version number to use for the EUCAST Clinical Breakpoints guideline. Currently supported: 10.0.</p></td>
<td><p>the version number to use for the EUCAST Clinical Breakpoints guideline. Currently supported: 11.0, 10.0.</p></td>
</tr>
<tr>
<th>version_expertrules</th>
@ -295,6 +297,14 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
<th>...</th>
<td><p>column name of an antibiotic, please see section <em>Antibiotics</em> below</p></td>
</tr>
<tr>
<th>ab</th>
<td><p>any (vector of) text that can be coerced to a valid antibiotic code with <code><a href='as.ab.html'>as.ab()</a></code></p></td>
</tr>
<tr>
<th>administration</th>
<td><p>route of administration, either "im", "iv" or "oral"</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
@ -307,6 +317,7 @@ Leclercq et al. <strong>EUCAST expert rules in antimicrobial susceptibility test
<li><p>EUCAST Intrinsic Resistance and Unusual Phenotypes. Version 3.2, 2020. <a href='https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/2020/Intrinsic_Resistance_and_Unusual_Phenotypes_Tables_v3.2_20200225.pdf'>(link)</a></p></li>
<li><p>EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 9.0, 2019. <a href='https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_9.0_Breakpoint_Tables.xlsx'>(link)</a></p></li>
<li><p>EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 10.0, 2020. <a href='https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_10.0_Breakpoint_Tables.xlsx'>(link)</a></p></li>
<li><p>EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 11.0, 2021. <a href='https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_11.0_Breakpoint_Tables.xlsx'>(link)</a></p></li>
</ul>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
@ -393,6 +404,8 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
<span class='co'># containing all details about the transformations:</span>
<span class='va'>c</span> <span class='op'>&lt;-</span> <span class='fu'>eucast_rules</span><span class='op'>(</span><span class='va'>a</span>, verbose <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
<span class='co'># }</span>
<span class='fu'>eucast_dosage</span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"tobra"</span>, <span class='st'>"genta"</span>, <span class='st'>"cipro"</span><span class='op'>)</span>, <span class='st'>"iv"</span><span class='op'>)</span>
</pre>
</div>
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3
docs/reference/filter_ab_class.html
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@ -343,10 +343,11 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
<span class='fu'>filter_aminoglycosides</span><span class='op'>(</span><span class='st'>"R"</span>, <span class='st'>"all"</span><span class='op'>)</span> <span class='op'>%&gt;%</span>
<span class='fu'>filter_fluoroquinolones</span><span class='op'>(</span><span class='st'>"R"</span>, <span class='st'>"all"</span><span class='op'>)</span>
<span class='co'># with dplyr 1.0.0 and higher (that adds 'across()'), this is equal:</span>
<span class='co'># with dplyr 1.0.0 and higher (that adds 'across()'), this is all equal:</span>
<span class='co'># (though the row names on the first are more correct)</span>
<span class='va'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_carbapenems</span><span class='op'>(</span><span class='st'>"R"</span>, <span class='st'>"all"</span><span class='op'>)</span>
<span class='va'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span><span class='op'>(</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/across.html'>across</a></span><span class='op'>(</span><span class='fu'><a href='antibiotic_class_selectors.html'>carbapenems</a></span><span class='op'>(</span><span class='op'>)</span>, <span class='op'>~</span><span class='va'>.</span> <span class='op'>==</span> <span class='st'>"R"</span><span class='op'>)</span><span class='op'>)</span>
<span class='va'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span><span class='op'>(</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/across.html'>across</a></span><span class='op'>(</span><span class='fu'><a href='antibiotic_class_selectors.html'>carbapenems</a></span><span class='op'>(</span><span class='op'>)</span>, <span class='kw'>function</span><span class='op'>(</span><span class='va'>x</span><span class='op'>)</span> <span class='va'>x</span> <span class='op'>==</span> <span class='st'>"R"</span><span class='op'>)</span><span class='op'>)</span>
<span class='op'>}</span>
<span class='co'># }</span>
</pre>

2
docs/reference/first_isolate.html
View File

@ -285,7 +285,7 @@
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>x</th>
<td><p>a <a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a> containing isolates. Can be left blank when used inside <code>dplyr</code> verbs, such as <code><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter()</a></code>, <code><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate()</a></code> and <code><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarise()</a></code>.</p></td>
<td><p>a <a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a> containing isolates. Can be left blank for automatic determination.</p></td>
</tr>
<tr>
<th>col_date</th>

90
docs/reference/index.html
View File

@ -81,7 +81,7 @@
</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">1.5.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.5.0.9000</span>
</span>
</div>
@ -263,6 +263,48 @@
<td><p>The <code>AMR</code> Package</p></td>
</tr><tr>
<td>
<p><code><a href="example_isolates.html">example_isolates</a></code> </p>
</td>
<td><p>Data set with 2,000 example isolates</p></td>
</tr><tr>
<td>
<p><code><a href="microorganisms.html">microorganisms</a></code> </p>
</td>
<td><p>Data set with 67,151 microorganisms</p></td>
</tr><tr>
<td>
<p><code><a href="microorganisms.codes.html">microorganisms.codes</a></code> </p>
</td>
<td><p>Data set with 5,580 common microorganism codes</p></td>
</tr><tr>
<td>
<p><code><a href="microorganisms.old.html">microorganisms.old</a></code> </p>
</td>
<td><p>Data set with previously accepted taxonomic names</p></td>
</tr><tr>
<td>
<p><code><a href="antibiotics.html">antibiotics</a></code> <code><a href="antibiotics.html">antivirals</a></code> </p>
</td>
<td><p>Data sets with 558 antimicrobials</p></td>
</tr><tr>
<td>
<p><code><a href="intrinsic_resistant.html">intrinsic_resistant</a></code> </p>
</td>
<td><p>Data set with bacterial intrinsic resistance</p></td>
</tr><tr>
<td>
<p><code><a href="dosage.html">dosage</a></code> </p>
</td>
<td><p>Data set with treatment dosages as defined by EUCAST</p></td>
</tr><tr>
<td>
<p><code><a href="catalogue_of_life.html">catalogue_of_life</a></code> </p>
</td>
@ -287,30 +329,6 @@
<td><p>Lifecycles of functions in the <code>AMR</code> package</p></td>
</tr><tr>
<td>
<p><code><a href="microorganisms.html">microorganisms</a></code> </p>
</td>
<td><p>Data set with 67,151 microorganisms</p></td>
</tr><tr>
<td>
<p><code><a href="antibiotics.html">antibiotics</a></code> <code><a href="antibiotics.html">antivirals</a></code> </p>
</td>
<td><p>Data sets with 557 antimicrobials</p></td>
</tr><tr>
<td>
<p><code><a href="intrinsic_resistant.html">intrinsic_resistant</a></code> </p>
</td>
<td><p>Data set with bacterial intrinsic resistance</p></td>
</tr><tr>
<td>
<p><code><a href="example_isolates.html">example_isolates</a></code> </p>
</td>
<td><p>Data set with 2,000 example isolates</p></td>
</tr><tr>
<td>
<p><code><a href="example_isolates_unclean.html">example_isolates_unclean</a></code> </p>
</td>
@ -323,18 +341,6 @@
<td><p>Data set for R/SI interpretation</p></td>
</tr><tr>
<td>
<p><code><a href="microorganisms.codes.html">microorganisms.codes</a></code> </p>
</td>
<td><p>Data set with 5,583 common microorganism codes</p></td>
</tr><tr>
<td>
<p><code><a href="microorganisms.old.html">microorganisms.old</a></code> </p>
</td>
<td><p>Data set with previously accepted taxonomic names</p></td>
</tr><tr>
<td>
<p><code><a href="WHONET.html">WHONET</a></code> </p>
</td>
@ -361,7 +367,7 @@
</tr><tr>
<td>
<p><code><a href="mo_property.html">mo_name()</a></code> <code><a href="mo_property.html">mo_fullname()</a></code> <code><a href="mo_property.html">mo_shortname()</a></code> <code><a href="mo_property.html">mo_subspecies()</a></code> <code><a href="mo_property.html">mo_species()</a></code> <code><a href="mo_property.html">mo_genus()</a></code> <code><a href="mo_property.html">mo_family()</a></code> <code><a href="mo_property.html">mo_order()</a></code> <code><a href="mo_property.html">mo_class()</a></code> <code><a href="mo_property.html">mo_phylum()</a></code> <code><a href="mo_property.html">mo_kingdom()</a></code> <code><a href="mo_property.html">mo_domain()</a></code> <code><a href="mo_property.html">mo_type()</a></code> <code><a href="mo_property.html">mo_gramstain()</a></code> <code><a href="mo_property.html">mo_is_gram_negative()</a></code> <code><a href="mo_property.html">mo_is_gram_positive()</a></code> <code><a href="mo_property.html">mo_is_intrinsic_resistant()</a></code> <code><a href="mo_property.html">mo_snomed()</a></code> <code><a href="mo_property.html">mo_ref()</a></code> <code><a href="mo_property.html">mo_authors()</a></code> <code><a href="mo_property.html">mo_year()</a></code> <code><a href="mo_property.html">mo_rank()</a></code> <code><a href="mo_property.html">mo_taxonomy()</a></code> <code><a href="mo_property.html">mo_synonyms()</a></code> <code><a href="mo_property.html">mo_info()</a></code> <code><a href="mo_property.html">mo_url()</a></code> <code><a href="mo_property.html">mo_property()</a></code> </p>
<p><code><a href="mo_property.html">mo_name()</a></code> <code><a href="mo_property.html">mo_fullname()</a></code> <code><a href="mo_property.html">mo_shortname()</a></code> <code><a href="mo_property.html">mo_subspecies()</a></code> <code><a href="mo_property.html">mo_species()</a></code> <code><a href="mo_property.html">mo_genus()</a></code> <code><a href="mo_property.html">mo_family()</a></code> <code><a href="mo_property.html">mo_order()</a></code> <code><a href="mo_property.html">mo_class()</a></code> <code><a href="mo_property.html">mo_phylum()</a></code> <code><a href="mo_property.html">mo_kingdom()</a></code> <code><a href="mo_property.html">mo_domain()</a></code> <code><a href="mo_property.html">mo_type()</a></code> <code><a href="mo_property.html">mo_gramstain()</a></code> <code><a href="mo_property.html">mo_is_gram_negative()</a></code> <code><a href="mo_property.html">mo_is_gram_positive()</a></code> <code><a href="mo_property.html">mo_is_yeast()</a></code> <code><a href="mo_property.html">mo_is_intrinsic_resistant()</a></code> <code><a href="mo_property.html">mo_snomed()</a></code> <code><a href="mo_property.html">mo_ref()</a></code> <code><a href="mo_property.html">mo_authors()</a></code> <code><a href="mo_property.html">mo_year()</a></code> <code><a href="mo_property.html">mo_rank()</a></code> <code><a href="mo_property.html">mo_taxonomy()</a></code> <code><a href="mo_property.html">mo_synonyms()</a></code> <code><a href="mo_property.html">mo_info()</a></code> <code><a href="mo_property.html">mo_url()</a></code> <code><a href="mo_property.html">mo_property()</a></code> </p>
</td>
<td><p>Get properties of a microorganism</p></td>
</tr><tr>
@ -441,7 +447,7 @@
</tr><tr>
<td>
<p><code><a href="eucast_rules.html">eucast_rules()</a></code> </p>
<p><code><a href="eucast_rules.html">eucast_rules()</a></code> <code><a href="eucast_rules.html">eucast_dosage()</a></code> </p>
</td>
<td><p>Apply EUCAST rules</p></td>
</tr><tr>
@ -450,6 +456,12 @@
<p><code><a href="plot.html">plot(<i>&lt;disk&gt;</i>)</a></code> <code><a href="plot.html">plot(<i>&lt;mic&gt;</i>)</a></code> <code><a href="plot.html">barplot(<i>&lt;mic&gt;</i>)</a></code> <code><a href="plot.html">plot(<i>&lt;rsi&gt;</i>)</a></code> <code><a href="plot.html">barplot(<i>&lt;rsi&gt;</i>)</a></code> </p>
</td>
<td><p>Plotting for classes <code>rsi</code>, <code>mic</code> and <code>disk</code></p></td>
</tr><tr>
<td>
<p><code><a href="isolate_identifier.html">isolate_identifier()</a></code> </p>
</td>
<td><p>Create identifier of an isolate</p></td>
</tr>
</tbody><tbody>
<tr>

2
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@ -255,7 +255,7 @@
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>The repository of this <code>AMR</code> package contains a file comprising this exact data set: <a href='https://github.com/msberends/AMR/blob/master/data-raw/intrinsic_resistant.txt'>https://github.com/msberends/AMR/blob/master/data-raw/intrinsic_resistant.txt</a>. This file <strong>allows for machine reading EUCAST guidelines about intrinsic resistance</strong>, which is almost impossible with the Excel and PDF files distributed by EUCAST. The file is updated automatically.</p>
<p>This data set is based on <a href='https://www.eucast.org/expert_rules_and_intrinsic_resistance/'>'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2</a> from 2020.</p>
<p>This data set is based on <a href='https://www.eucast.org/expert_rules_and_intrinsic_resistance/'>'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2</a> (2020).</p>
<h2 class="hasAnchor" id="reference-data-publicly-available"><a class="anchor" href="#reference-data-publicly-available"></a>Reference data publicly available</h2>

313
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@ -0,0 +1,313 @@
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<meta property="og:description" content="This function will paste the microorganism code with all antimicrobial results into one string for each row in a data set. This is useful to compare isolates, e.g. between institutions or regions, when there is no genotyping available." />
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<div class="page-header">
<h1>Create identifier of an isolate</h1>
<small class="dont-index">Source: <a href='https://github.com/msberends/AMR/blob/master/R/isolate_identifier.R'><code>R/isolate_identifier.R</code></a></small>
<div class="hidden name"><code>isolate_identifier.Rd</code></div>
</div>
<div class="ref-description">
<p>This function will paste the microorganism code with all antimicrobial results into one string for each row in a data set. This is useful to compare isolates, e.g. between institutions or regions, when there is no genotyping available.</p>
</div>
<pre class="usage"><span class='fu'>isolate_identifier</span><span class='op'>(</span><span class='va'>x</span>, col_mo <span class='op'>=</span> <span class='cn'>NULL</span>, cols_ab <span class='op'>=</span> <span class='cn'>NULL</span><span class='op'>)</span></pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>x</th>
<td><p>data with antibiotic columns, such as <code>amox</code>, <code>AMX</code> and <code>AMC</code></p></td>
</tr>
<tr>
<th>col_mo</th>
<td><p>column name of the IDs of the microorganisms (see <code><a href='as.mo.html'>as.mo()</a></code>), defaults to the first column of class <code><a href='as.mo.html'>mo</a></code>. Values will be coerced using <code><a href='as.mo.html'>as.mo()</a></code>.</p></td>
</tr>
<tr>
<th>cols_ab</th>
<td><p>a character vector of column names of <code>x</code>, or (a combination with) an <a href='[ab_class()]'>antibiotic selector function</a>, such as <code><a href='antibiotic_class_selectors.html'>carbapenems()</a></code> and <code>aminoglysides()</code></p></td>
</tr>
</table>
<h2 class="hasAnchor" id="maturing-lifecycle"><a class="anchor" href="#maturing-lifecycle"></a>Maturing lifecycle</h2>
<p><img src='figures/lifecycle_maturing.svg' style=margin-bottom:5px /> <br />
The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>maturing</strong>. The unlying code of a maturing function has been roughed out, but finer details might still change. Since this function needs wider usage and more extensive testing, you are very welcome <a href='https://github.com/msberends/AMR/issues'>to suggest changes at our repository</a> or <a href='AMR.html'>write us an email (see section 'Contact Us')</a>.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.github.io/AMR/'>https://msberends.github.io/AMR/</a> you can find <a href='https://msberends.github.io/AMR/articles/AMR.html'>a comprehensive tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.github.io/AMR/reference/'>complete documentation of all functions</a> and <a href='https://msberends.github.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>. As we would like to better understand the backgrounds and needs of our users, please <a href='https://msberends.github.io/AMR/survey.html'>participate in our survey</a>!</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># automatic selection of microorganism and antibiotics (i.e., all &lt;rsi&gt; columns, see ?as.rsi)</span>
<span class='va'>x</span> <span class='op'>&lt;-</span> <span class='fu'>isolate_identifier</span><span class='op'>(</span><span class='va'>example_isolates</span><span class='op'>)</span>
<span class='co'># ignore microorganism codes, only use antimicrobial results</span>
<span class='va'>x</span> <span class='op'>&lt;-</span> <span class='fu'>isolate_identifier</span><span class='op'>(</span><span class='va'>example_isolates</span>, col_mo <span class='op'>=</span> <span class='cn'>FALSE</span>, cols_ab <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"AMX"</span>, <span class='st'>"TZP"</span>, <span class='st'>"GEN"</span>, <span class='st'>"TOB"</span><span class='op'>)</span><span class='op'>)</span>
<span class='co'># select antibiotics from certain antibiotic classes</span>
<span class='va'>x</span> <span class='op'>&lt;-</span> <span class='fu'>isolate_identifier</span><span class='op'>(</span><span class='va'>example_isolates</span>, cols_ab <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='fu'><a href='antibiotic_class_selectors.html'>carbapenems</a></span><span class='op'>(</span><span class='op'>)</span>, <span class='fu'><a href='antibiotic_class_selectors.html'>aminoglycosides</a></span><span class='op'>(</span><span class='op'>)</span><span class='op'>)</span><span class='op'>)</span>
</pre>
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<p>Developed by <a href='https://www.rug.nl/staff/m.s.berends/'>Matthijs S. Berends</a>, <a href='https://www.rug.nl/staff/c.f.luz/'>Christian F. Luz</a>, <a href='https://www.rug.nl/staff/a.w.friedrich/'>Alexander W. Friedrich</a>, <a href='https://www.rug.nl/staff/b.sinha/'>Bhanu N. M. Sinha</a>, <a href='https://www.rug.nl/staff/c.j.albers/'>Casper J. Albers</a>, <a href='https://www.rug.nl/staff/c.glasner/'>Corinna Glasner</a>.</p>
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@ -268,7 +268,7 @@
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>x</th>
<td><p>a <a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a> with antibiotics columns, like <code>AMX</code> or <code>amox</code>. Can be left blank when used inside <code>dplyr</code> verbs, such as <code><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter()</a></code>, <code><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate()</a></code> and <code><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarise()</a></code>.</p></td>
<td><p>a <a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a> with antibiotics columns, like <code>AMX</code> or <code>amox</code>. Can be left blank for automatic determination.</p></td>
</tr>
<tr>
<th>guideline</th>

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@ -6,7 +6,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Data set with 5,583 common microorganism codes — microorganisms.codes • AMR (for R)</title>
<title>Data set with 5,580 common microorganism codes — microorganisms.codes • AMR (for R)</title>
<!-- favicons -->
<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
@ -48,7 +48,7 @@
<link href="../extra.css" rel="stylesheet">
<script src="../extra.js"></script>
<meta property="og:title" content="Data set with 5,583 common microorganism codes — microorganisms.codes" />
<meta property="og:title" content="Data set with 5,580 common microorganism codes — microorganisms.codes" />
<meta property="og:description" content="A data set containing commonly used codes for microorganisms, from laboratory systems and WHONET. Define your own with set_mo_source(). They will all be searched when using as.mo() and consequently all the mo_* functions." />
<meta property="og:image" content="https://msberends.github.io/AMR/logo.png" />
@ -233,7 +233,7 @@
<div class="row">
<div class="col-md-9 contents">
<div class="page-header">
<h1>Data set with 5,583 common microorganism codes</h1>
<h1>Data set with 5,580 common microorganism codes</h1>
<small class="dont-index">Source: <a href='https://github.com/msberends/AMR/blob/master/R/data.R'><code>R/data.R</code></a></small>
<div class="hidden name"><code>microorganisms.codes.Rd</code></div>
</div>
@ -247,7 +247,7 @@
<h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
<p>A <a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a> with 5,583 observations and 2 variables:</p><ul>
<p>A <a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a> with 5,580 observations and 2 variables:</p><ul>
<li><p><code>code</code><br /> Commonly used code of a microorganism</p></li>
<li><p><code>mo</code><br /> ID of the microorganism in the <a href='microorganisms.html'>microorganisms</a> data set</p></li>
</ul>

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@ -266,7 +266,11 @@
<p>Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures, Germany, Prokaryotic Nomenclature Up-to-Date, <a href='https://www.dsmz.de/services/online-tools/prokaryotic-nomenclature-up-to-date'>https://www.dsmz.de/services/online-tools/prokaryotic-nomenclature-up-to-date</a> and <a href='https://lpsn.dsmz.de'>https://lpsn.dsmz.de</a> (check included version with <code><a href='catalogue_of_life_version.html'>catalogue_of_life_version()</a></code>).</p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>Manually added were:</p><ul>
<p>Please note that entries are only based on the Catalogue of Life and the LPSN (see below). Since these sources incorporate entries based on (recent) publications in the International Journal of Systematic and Evolutionary Microbiology (IJSEM), it can happen that the year of publication is sometimes later than one might expect.</p>
<p>For example, <em>Staphylococcus pettenkoferi</em> was newly named in Diagnostic Microbiology and Infectious Disease in 2002 (PMID 12106949), but it was not before 2007 that a publication in IJSEM followed (PMID 17625191). Consequently, the AMR package returns 2007 for <code><a href='mo_property.html'>mo_year("S. pettenkoferi")</a></code>.</p><h3 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Manually additions</h3>
<p>For convenience, some entries were added manually:</p><ul>
<li><p>11 entries of <em>Streptococcus</em> (beta-haemolytic: groups A, B, C, D, F, G, H, K and unspecified; other: viridans, milleri)</p></li>
<li><p>2 entries of <em>Staphylococcus</em> (coagulase-negative (CoNS) and coagulase-positive (CoPS))</p></li>
<li><p>3 entries of <em>Trichomonas</em> (<em>Trichomonas vaginalis</em>, and its family and genus)</p></li>
@ -276,6 +280,8 @@
<li><p>6 families under the Enterobacterales order, according to Adeolu <em>et al.</em> (2016, PMID 27620848), that are not (yet) in the Catalogue of Life</p></li>
<li><p>7,411 species from the DSMZ (Deutsche Sammlung von Mikroorganismen und Zellkulturen) since the DSMZ contain the latest taxonomic information based on recent publications</p></li>
</ul>
<h3 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Direct download</h3>

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@ -82,7 +82,7 @@
</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">1.5.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.5.0.9000</span>
</span>
</div>

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@ -82,7 +82,7 @@
</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">1.5.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.5.0.9000</span>
</span>
</div>
@ -262,14 +262,14 @@
<p>With ambiguous user input in <code><a href='as.mo.html'>as.mo()</a></code> and all the <code><a href='mo_property.html'>mo_*</a></code> functions, the returned results are chosen based on their matching score using <code>mo_matching_score()</code>. This matching score \(m\), is calculated as:</p>
<p>$$m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}$$</p>
<p><img src='figures/mo_matching_score.png' width="300px" alt="mo matching score" /></p>
<p>where:</p><ul>
<li><p>\(x\) is the user input;</p></li>
<li><p>\(n\) is a taxonomic name (genus, species, and subspecies);</p></li>
<li><p>\(l_n\) is the length of \(n\);</p></li>
<li><p>lev is the <a href='https://en.wikipedia.org/wiki/Levenshtein_distance'>Levenshtein distance function</a>, which counts any insertion, deletion and substitution as 1 that is needed to change \(x\) into \(n\);</p></li>
<li><p>\(p_n\) is the human pathogenic prevalence group of \(n\), as described below;</p></li>
<li><p>\(k_n\) is the taxonomic kingdom of \(n\), set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.</p></li>
<li><p><i>x</i> is the user input;</p></li>
<li><p><i>n</i> is a taxonomic name (genus, species, and subspecies);</p></li>
<li><p><i>l<sub>n</sub></i> is the length of <i>n</i>;</p></li>
<li><p><i>lev</i> is the <a href="https://en.wikipedia.org/wiki/Levenshtein_distance">Levenshtein distance function</a>, which counts any insertion, deletion and substitution as 1 that is needed to change <i>x</i> into <i>n</i>;</p></li>
<li><p><i>p<sub>n</sub></i> is the human pathogenic prevalence group of <i>n</i>, as described below;</p></li>
<li><p><i>k<sub>n</sub></i> is the taxonomic kingdom of <i>n</i>, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.</p></li>
</ul>
<p>The grouping into human pathogenic prevalence (\(p\)) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. <strong>Group 1</strong> (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is <em>Enterococcus</em>, <em>Staphylococcus</em> or <em>Streptococcus</em>. This group consequently contains all common Gram-negative bacteria, such as <em>Pseudomonas</em> and <em>Legionella</em> and all species within the order Enterobacterales. <strong>Group 2</strong> consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is <em>Absidia</em>, <em>Acremonium</em>, <em>Actinotignum</em>, <em>Alternaria</em>, <em>Anaerosalibacter</em>, <em>Apophysomyces</em>, <em>Arachnia</em>, <em>Aspergillus</em>, <em>Aureobacterium</em>, <em>Aureobasidium</em>, <em>Bacteroides</em>, <em>Basidiobolus</em>, <em>Beauveria</em>, <em>Blastocystis</em>, <em>Branhamella</em>, <em>Calymmatobacterium</em>, <em>Candida</em>, <em>Capnocytophaga</em>, <em>Catabacter</em>, <em>Chaetomium</em>, <em>Chryseobacterium</em>, <em>Chryseomonas</em>, <em>Chrysonilia</em>, <em>Cladophialophora</em>, <em>Cladosporium</em>, <em>Conidiobolus</em>, <em>Cryptococcus</em>, <em>Curvularia</em>, <em>Exophiala</em>, <em>Exserohilum</em>, <em>Flavobacterium</em>, <em>Fonsecaea</em>, <em>Fusarium</em>, <em>Fusobacterium</em>, <em>Hendersonula</em>, <em>Hypomyces</em>, <em>Koserella</em>, <em>Lelliottia</em>, <em>Leptosphaeria</em>, <em>Leptotrichia</em>, <em>Malassezia</em>, <em>Malbranchea</em>, <em>Mortierella</em>, <em>Mucor</em>, <em>Mycocentrospora</em>, <em>Mycoplasma</em>, <em>Nectria</em>, <em>Ochroconis</em>, <em>Oidiodendron</em>, <em>Phoma</em>, <em>Piedraia</em>, <em>Pithomyces</em>, <em>Pityrosporum</em>, <em>Prevotella</em>,\<em>Pseudallescheria</em>, <em>Rhizomucor</em>, <em>Rhizopus</em>, <em>Rhodotorula</em>, <em>Scolecobasidium</em>, <em>Scopulariopsis</em>, <em>Scytalidium</em>,<em>Sporobolomyces</em>, <em>Stachybotrys</em>, <em>Stomatococcus</em>, <em>Treponema</em>, <em>Trichoderma</em>, <em>Trichophyton</em>, <em>Trichosporon</em>, <em>Tritirachium</em> or <em>Ureaplasma</em>. <strong>Group 3</strong> consists of all other microorganisms.</p>
@ -281,6 +281,16 @@
<p><img src='figures/lifecycle_stable.svg' style=margin-bottom:5px /> <br />
The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
<p>If the unlying code needs breaking changes, they will occur gradually. For example, a argument will be deprecated and first continue to work, but will emit an message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
<h2 class="hasAnchor" id="reference-data-publicly-available"><a class="anchor" href="#reference-data-publicly-available"></a>Reference data publicly available</h2>
<p>All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find <a href='https://msberends.github.io/AMR/articles/datasets.html'>all download links on our website</a>, which is automatically updated with every code change.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.github.io/AMR/'>https://msberends.github.io/AMR/</a> you can find <a href='https://msberends.github.io/AMR/articles/AMR.html'>a comprehensive tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.github.io/AMR/reference/'>complete documentation of all functions</a> and <a href='https://msberends.github.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>. As we would like to better understand the backgrounds and needs of our users, please <a href='https://msberends.github.io/AMR/survey.html'>participate in our survey</a>!</p>
<h2 class="hasAnchor" id="author"><a class="anchor" href="#author"></a>Author</h2>
<p>Matthijs S. Berends</p>

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@ -82,7 +82,7 @@
</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">1.5.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.5.0.9000</span>
</span>
</div>
@ -274,6 +274,8 @@
<span class='fu'>mo_is_gram_positive</span><span class='op'>(</span><span class='va'>x</span>, language <span class='op'>=</span> <span class='fu'><a href='translate.html'>get_locale</a></span><span class='op'>(</span><span class='op'>)</span>, <span class='va'>...</span><span class='op'>)</span>
<span class='fu'>mo_is_yeast</span><span class='op'>(</span><span class='va'>x</span>, language <span class='op'>=</span> <span class='fu'><a href='translate.html'>get_locale</a></span><span class='op'>(</span><span class='op'>)</span>, <span class='va'>...</span><span class='op'>)</span>
<span class='fu'>mo_is_intrinsic_resistant</span><span class='op'>(</span><span class='va'>x</span>, <span class='va'>ab</span>, language <span class='op'>=</span> <span class='fu'><a href='translate.html'>get_locale</a></span><span class='op'>(</span><span class='op'>)</span>, <span class='va'>...</span><span class='op'>)</span>
<span class='fu'>mo_snomed</span><span class='op'>(</span><span class='va'>x</span>, language <span class='op'>=</span> <span class='fu'><a href='translate.html'>get_locale</a></span><span class='op'>(</span><span class='op'>)</span>, <span class='va'>...</span><span class='op'>)</span>
@ -301,7 +303,7 @@
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>x</th>
<td><p>any character (vector) that can be coerced to a valid microorganism code with <code><a href='as.mo.html'>as.mo()</a></code>. Can be left blank for auto-guessing the column containing microorganism codes when used inside <code>dplyr</code> verbs, such as <code><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter()</a></code>, <code><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate()</a></code> and <code><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarise()</a></code>, please see <em>Examples</em>.</p></td>
<td><p>any character (vector) that can be coerced to a valid microorganism code with <code><a href='as.mo.html'>as.mo()</a></code>. Can be left blank for auto-guessing the column containing microorganism codes if used in a data set, please see <em>Examples</em>.</p></td>
</tr>
<tr>
<th>language</th>
@ -347,7 +349,8 @@
<p>The short name - <code>mo_shortname()</code> - almost always returns the first character of the genus and the full species, like <code>"E. coli"</code>. Exceptions are abbreviations of staphylococci (such as <em>"CoNS"</em>, Coagulase-Negative Staphylococci) and beta-haemolytic streptococci (such as <em>"GBS"</em>, Group B Streptococci). Please bear in mind that e.g. <em>E. coli</em> could mean <em>Escherichia coli</em> (kingdom of Bacteria) as well as <em>Entamoeba coli</em> (kingdom of Protozoa). Returning to the full name will be done using <code><a href='as.mo.html'>as.mo()</a></code> internally, giving priority to bacteria and human pathogens, i.e. <code>"E. coli"</code> will be considered <em>Escherichia coli</em>. In other words, <code>mo_fullname(mo_shortname("Entamoeba coli"))</code> returns <code>"Escherichia coli"</code>.</p>
<p>Since the top-level of the taxonomy is sometimes referred to as 'kingdom' and sometimes as 'domain', the functions <code>mo_kingdom()</code> and <code>mo_domain()</code> return the exact same results.</p>
<p>The Gram stain - <code>mo_gramstain()</code> - will be determined based on the taxonomic kingdom and phylum. According to Cavalier-Smith (2002, <a href='https://pubmed.ncbi.nlm.nih.gov/11837318'>PMID 11837318</a>), who defined subkingdoms Negibacteria and Posibacteria, only these phyla are Posibacteria: Actinobacteria, Chloroflexi, Firmicutes and Tenericutes. These bacteria are considered Gram-positive - all other bacteria are considered Gram-negative. Species outside the kingdom of Bacteria will return a value <code>NA</code>. Functions <code>mo_is_gram_negative()</code> and <code>mo_is_gram_positive()</code> always return <code>TRUE</code> or <code>FALSE</code> (except when the input is <code>NA</code> or the MO code is <code>UNKNOWN</code>), thus always return <code>FALSE</code> for species outside the taxonomic kingdom of Bacteria.</p>
<p>Intrinsic resistance - <code>mo_is_intrinsic_resistant()</code> - will be determined based on the <a href='intrinsic_resistant.html'>intrinsic_resistant</a> data set, which is based on <a href='https://www.eucast.org/expert_rules_and_intrinsic_resistance/'>'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2</a> from 2020. The <code>mo_is_intrinsic_resistant()</code> can be vectorised over arguments <code>x</code> (input for microorganisms) and over <code>ab</code> (input for antibiotics).</p>
<p>Determination of yeasts - <code>mo_is_yeast()</code> - will be based on the taxonomic phylum, class and order. Budding yeasts are true fungi of the phylum Ascomycetes, class Saccharomycetes (also called Hemiascomycetes). The true yeasts are separated into one main order Saccharomycetales. For all microorganisms that are in one of those two groups, the function will return <code>TRUE</code>. It returns <code>FALSE</code> for all other taxonomic entries.</p>
<p>Intrinsic resistance - <code>mo_is_intrinsic_resistant()</code> - will be determined based on the <a href='intrinsic_resistant.html'>intrinsic_resistant</a> data set, which is based on <a href='https://www.eucast.org/expert_rules_and_intrinsic_resistance/'>'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2</a> (2020). The <code>mo_is_intrinsic_resistant()</code> can be vectorised over arguments <code>x</code> (input for microorganisms) and over <code>ab</code> (input for antibiotics).</p>
<p>All output will be <a href='translate.html'>translate</a>d where possible.</p>
<p>The function <code>mo_url()</code> will return the direct URL to the online database entry, which also shows the scientific reference of the concerned species.</p>
<h2 class="hasAnchor" id="stable-lifecycle"><a class="anchor" href="#stable-lifecycle"></a>Stable lifecycle</h2>
@ -362,14 +365,14 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
<p>With ambiguous user input in <code><a href='as.mo.html'>as.mo()</a></code> and all the <code>mo_*</code> functions, the returned results are chosen based on their matching score using <code><a href='mo_matching_score.html'>mo_matching_score()</a></code>. This matching score \(m\), is calculated as:</p>
<p>$$m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}$$</p>
<p><img src='figures/mo_matching_score.png' width="300px" alt="mo matching score" /></p>
<p>where:</p><ul>
<li><p>\(x\) is the user input;</p></li>
<li><p>\(n\) is a taxonomic name (genus, species, and subspecies);</p></li>
<li><p>\(l_n\) is the length of \(n\);</p></li>
<li><p>lev is the <a href='https://en.wikipedia.org/wiki/Levenshtein_distance'>Levenshtein distance function</a>, which counts any insertion, deletion and substitution as 1 that is needed to change \(x\) into \(n\);</p></li>
<li><p>\(p_n\) is the human pathogenic prevalence group of \(n\), as described below;</p></li>
<li><p>\(k_n\) is the taxonomic kingdom of \(n\), set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.</p></li>
<li><p><i>x</i> is the user input;</p></li>
<li><p><i>n</i> is a taxonomic name (genus, species, and subspecies);</p></li>
<li><p><i>l<sub>n</sub></i> is the length of <i>n</i>;</p></li>
<li><p><i>lev</i> is the <a href="https://en.wikipedia.org/wiki/Levenshtein_distance">Levenshtein distance function</a>, which counts any insertion, deletion and substitution as 1 that is needed to change <i>x</i> into <i>n</i>;</p></li>
<li><p><i>p<sub>n</sub></i> is the human pathogenic prevalence group of <i>n</i>, as described below;</p></li>
<li><p><i>k<sub>n</sub></i> is the taxonomic kingdom of <i>n</i>, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.</p></li>
</ul>
<p>The grouping into human pathogenic prevalence (\(p\)) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. <strong>Group 1</strong> (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is <em>Enterococcus</em>, <em>Staphylococcus</em> or <em>Streptococcus</em>. This group consequently contains all common Gram-negative bacteria, such as <em>Pseudomonas</em> and <em>Legionella</em> and all species within the order Enterobacterales. <strong>Group 2</strong> consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is <em>Absidia</em>, <em>Acremonium</em>, <em>Actinotignum</em>, <em>Alternaria</em>, <em>Anaerosalibacter</em>, <em>Apophysomyces</em>, <em>Arachnia</em>, <em>Aspergillus</em>, <em>Aureobacterium</em>, <em>Aureobasidium</em>, <em>Bacteroides</em>, <em>Basidiobolus</em>, <em>Beauveria</em>, <em>Blastocystis</em>, <em>Branhamella</em>, <em>Calymmatobacterium</em>, <em>Candida</em>, <em>Capnocytophaga</em>, <em>Catabacter</em>, <em>Chaetomium</em>, <em>Chryseobacterium</em>, <em>Chryseomonas</em>, <em>Chrysonilia</em>, <em>Cladophialophora</em>, <em>Cladosporium</em>, <em>Conidiobolus</em>, <em>Cryptococcus</em>, <em>Curvularia</em>, <em>Exophiala</em>, <em>Exserohilum</em>, <em>Flavobacterium</em>, <em>Fonsecaea</em>, <em>Fusarium</em>, <em>Fusobacterium</em>, <em>Hendersonula</em>, <em>Hypomyces</em>, <em>Koserella</em>, <em>Lelliottia</em>, <em>Leptosphaeria</em>, <em>Leptotrichia</em>, <em>Malassezia</em>, <em>Malbranchea</em>, <em>Mortierella</em>, <em>Mucor</em>, <em>Mycocentrospora</em>, <em>Mycoplasma</em>, <em>Nectria</em>, <em>Ochroconis</em>, <em>Oidiodendron</em>, <em>Phoma</em>, <em>Piedraia</em>, <em>Pithomyces</em>, <em>Pityrosporum</em>, <em>Prevotella</em>,\<em>Pseudallescheria</em>, <em>Rhizomucor</em>, <em>Rhizopus</em>, <em>Rhodotorula</em>, <em>Scolecobasidium</em>, <em>Scopulariopsis</em>, <em>Scytalidium</em>,<em>Sporobolomyces</em>, <em>Stachybotrys</em>, <em>Stomatococcus</em>, <em>Treponema</em>, <em>Trichoderma</em>, <em>Trichophyton</em>, <em>Trichosporon</em>, <em>Tritirachium</em> or <em>Ureaplasma</em>. <strong>Group 3</strong> consists of all other microorganisms.</p>
@ -488,6 +491,8 @@ This package contains the complete taxonomic tree of almost all microorganisms (
<span class='co'># other --------------------------------------------------------------------</span>
<span class='fu'>mo_is_yeast</span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"Candida"</span>, <span class='st'>"E. coli"</span><span class='op'>)</span><span class='op'>)</span> <span class='co'># TRUE, FALSE</span>
<span class='co'># gram stains and intrinsic resistance can also be used as a filter in dplyr verbs</span>
<span class='kw'>if</span> <span class='op'>(</span><span class='kw'><a href='https://rdrr.io/r/base/library.html'>require</a></span><span class='op'>(</span><span class='st'><a href='https://dplyr.tidyverse.org'>"dplyr"</a></span><span class='op'>)</span><span class='op'>)</span> <span class='op'>{</span>
<span class='va'>example_isolates</span> <span class='op'>%&gt;%</span>

2
docs/reference/resistance_predict.html
View File

@ -287,7 +287,7 @@
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>x</th>
<td><p>a <a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a> containing isolates. Can be left blank when used inside <code>dplyr</code> verbs, such as <code><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter()</a></code>, <code><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate()</a></code> and <code><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarise()</a></code>.</p></td>
<td><p>a <a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a> containing isolates. Can be left blank for automatic determination.</p></td>
</tr>
<tr>
<th>col_ab</th>