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(v1.3.0.9035) mdro() for EUCAST 3.2, examples cleanup

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dr. M.S. (Matthijs) Berends
2020-09-29 23:35:46 +02:00
parent 68e6e1e329
commit 4e0374af29
94 changed files with 1143 additions and 1165 deletions
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6
docs/reference/age_groups.html
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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">1.3.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9035</span>
</span>
</div>
@ -315,7 +315,7 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
<span class='co'># same:</span>
<span class='fu'>age_groups</span>(<span class='kw'>ages</span>, <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='fl'>1</span>, <span class='fl'>2</span>, <span class='fl'>4</span>, <span class='fl'>6</span>, <span class='fl'>13</span>, <span class='fl'>17</span>))
<span class='co'>if</span> (<span class='fl'>FALSE</span>) {
<span class='co'># \donttest{</span>
<span class='co'># resistance of ciprofloxacine per age group</span>
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='kw'><a href='https://dplyr.tidyverse.org'>dplyr</a></span>)
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
@ -324,7 +324,7 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(age_group = <span class='fu'>age_groups</span>(<span class='kw'>age</span>)) <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='kw'>age_group</span>, <span class='kw'>CIP</span>) <span class='op'>%&gt;%</span>
<span class='fu'><a href='ggplot_rsi.html'>ggplot_rsi</a></span>(x = <span class='st'>"age_group"</span>, minimum = <span class='fl'>0</span>)
}
<span class='co'># }</span>
</pre>
</div>
<div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">

14
docs/reference/antibiotic_class_selectors.html
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@ -50,7 +50,7 @@
<meta property="og:title" content="Antibiotic class selectors — antibiotic_class_selectors" />
<meta property="og:description" content="Use these selection helpers inside any function that allows Tidyverse selection helpers, like dplyr::select() or tidyr::pivot_longer(). They help to select the columns of antibiotics that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations." />
<meta property="og:image" content="https://msberends.github.io/AMR/logo.svg" />
<meta property="og:image" content="https://msberends.github.io/AMR/logo.png" />
@ -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">1.3.0.9015</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9035</span>
</span>
</div>
@ -298,8 +298,7 @@
<div class='dont-index'><p><code><a href='filter_ab_class.html'>filter_ab_class()</a></code> for the <code><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter()</a></code> equivalent.</p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'>if</span> (<span class='fl'>FALSE</span>) {
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='kw'><a href='https://dplyr.tidyverse.org'>dplyr</a></span>)
<pre class="examples"><span class='co'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='st'><a href='https://dplyr.tidyverse.org'>"dplyr"</a></span>)) {
<span class='co'># this will select columns 'IPM' (imipenem) and 'MEM' (meropenem):</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
@ -322,11 +321,12 @@
<span class='fu'><a href='https://rdrr.io/r/base/format.html'>format</a></span>()
<span class='fu'><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a></span>(irrelevant = <span class='st'>"value"</span>,
<span class='fu'><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a></span>(some_column = <span class='st'>"some_value"</span>,
J01CA01 = <span class='st'>"S"</span>) <span class='op'>%&gt;%</span> <span class='co'># ATC code of ampicillin</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='fu'>penicillins</span>()) <span class='co'># the 'J01CA01' column will be selected</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='fu'>penicillins</span>()) <span class='co'># only the 'J01CA01' column will be selected</span>
}</pre>
}
</pre>
</div>
<div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
<nav id="toc" data-toggle="toc" class="sticky-top">

11
docs/reference/as.disk.html
View File

@ -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">1.3.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9035</span>
</span>
</div>
@ -282,7 +282,7 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
<div class='dont-index'><p><code><a href='as.rsi.html'>as.rsi()</a></code></p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'>if</span> (<span class='fl'>FALSE</span>) {
<pre class="examples"><span class='co'># \donttest{</span>
<span class='co'># transform existing disk zones to the `disk` class</span>
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='kw'><a href='https://dplyr.tidyverse.org'>dplyr</a></span>)
<span class='kw'>df</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a></span>(microorganism = <span class='st'>"E. coli"</span>,
@ -290,8 +290,9 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
CIP = <span class='fl'>14</span>,
GEN = <span class='fl'>18</span>,
TOB = <span class='fl'>16</span>)
<span class='kw'>df</span> <span class='op'>&lt;-</span> <span class='kw'>df</span> <span class='op'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate_all.html'>mutate_at</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='kw'>AMP</span><span class='op'>:</span><span class='kw'>TOB</span>), <span class='kw'>as.disk</span>)
<span class='kw'>df</span>
<span class='kw'>df</span>[, <span class='fl'>2</span><span class='op'>:</span><span class='fl'>5</span>] <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span>(<span class='kw'>df</span>[, <span class='fl'>2</span><span class='op'>:</span><span class='fl'>5</span>], <span class='kw'>as.disk</span>)
<span class='co'># same with dplyr:</span>
<span class='co'># df %&gt;% mutate(across(AMP:TOB, as.disk))</span>
<span class='co'># interpret disk values, see ?as.rsi</span>
<span class='fu'><a href='as.rsi.html'>as.rsi</a></span>(x = <span class='fu'>as.disk</span>(<span class='fl'>18</span>),
@ -300,7 +301,7 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
guideline = <span class='st'>"EUCAST"</span>)
<span class='fu'><a href='as.rsi.html'>as.rsi</a></span>(<span class='kw'>df</span>)
}
<span class='co'># }</span>
</pre>
</div>
<div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">

40
docs/reference/as.mo.html
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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">1.3.0.9034</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9035</span>
</span>
</div>
@ -361,10 +361,7 @@
<h3>Microbial prevalence of pathogens in humans</h3>
<p>The intelligent rules consider the prevalence of microorganisms in humans grouped into three groups, which is available as the <code>prevalence</code> columns in the <a href='microorganisms.html'>microorganisms</a> and <a href='microorganisms.old.html'>microorganisms.old</a> data sets. The grouping into prevalence groups is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence.</p>
<p>Group 1 (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>Klebsiella</em>, <em>Pseudomonas</em> and <em>Legionella</em>.</p>
<p>Group 2 consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is <em>Aspergillus</em>, <em>Bacteroides</em>, <em>Candida</em>, <em>Capnocytophaga</em>, <em>Chryseobacterium</em>, <em>Cryptococcus</em>, <em>Elisabethkingia</em>, <em>Flavobacterium</em>, <em>Fusobacterium</em>, <em>Giardia</em>, <em>Leptotrichia</em>, <em>Mycoplasma</em>, <em>Prevotella</em>, <em>Rhodotorula</em>, <em>Treponema</em>, <em>Trichophyton</em> or <em>Ureaplasma</em>. This group consequently contains all less common and rare human pathogens.</p>
<p>Group 3 (least prevalent microorganisms) consists of all other microorganisms. This group contains microorganisms most probably not found in humans.</p>
<p>The intelligent rules consider the prevalence of microorganisms in humans grouped into three groups, which is available as the <code>prevalence</code> columns in the <a href='microorganisms.html'>microorganisms</a> and <a href='microorganisms.old.html'>microorganisms.old</a> data sets. The grouping into human pathogenic prevalence is explained in the section <em>Matching score for microorganisms</em> below.</p>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
@ -392,15 +389,15 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
<p>$$m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \operatorname{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}$$</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) as found in <code><a href='microorganisms.html'>microorganisms$fullname</a></code>;</p></li>
<li><p>\(l_{n}\) is the length of \(n\);</p></li>
<li><p>\(\operatorname{lev}\) is the <a href='https://en.wikipedia.org/wiki/Levenshtein_distance'>Levenshtein distance function</a>;</p></li>
<li><p>\(p_{n}\) is the human pathogenic prevalence of \(n\), categorised into group \(1\), \(2\) and \(3\) (see <em>Details</em> in <code>?as.mo</code>), meaning that \(p = \{1, 2 , 3\}\);</p></li>
<li><p>\(k_{n}\) is the kingdom index of \(n\), set as follows: Bacteria = \(1\), Fungi = \(2\), Protozoa = \(3\), Archaea = \(4\), and all others = \(5\), meaning that \(k = \{1, 2 , 3, 4, 5\}\).</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>
</ul>
<p>This means that the user input <code>x = "E. coli"</code> gets for <em>Escherichia coli</em> a matching score of 68.8% and for <em>Entamoeba coli</em> a matching score of 7.9%.</p>
<p>All matches are sorted descending on their matching score and for all user input values, the top match will be returned.</p>
<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>
<p>All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., <code>"E. coli"</code> will return the microbial ID of <em>Escherichia coli</em> (\(m = 0.688\), a highly prevalent microorganism found in humans) and not <em>Entamoeba coli</em> (\(m = 0.079\), a less prevalent microorganism in humans), although the latter would alphabetically come first.</p>
<h2 class="hasAnchor" id="catalogue-of-life"><a class="anchor" href="#catalogue-of-life"></a>Catalogue of Life</h2>
@ -459,26 +456,7 @@ This package contains the complete taxonomic tree of almost all microorganisms (
<span class='co'># All mo_* functions use as.mo() internally too (see ?mo_property):</span>
<span class='fu'><a href='mo_property.html'>mo_genus</a></span>(<span class='st'>"E. coli"</span>) <span class='co'># returns "Escherichia"</span>
<span class='fu'><a href='mo_property.html'>mo_gramstain</a></span>(<span class='st'>"E. coli"</span>) <span class='co'># returns "Gram negative"</span>
<span class='co'># }</span>
<span class='co'>if</span> (<span class='fl'>FALSE</span>) {
<span class='kw'>df</span><span class='op'>$</span><span class='kw'>mo</span> <span class='op'>&lt;-</span> <span class='fu'>as.mo</span>(<span class='kw'>df</span><span class='op'>$</span><span class='kw'>microorganism_name</span>)
<span class='co'># the select function of the Tidyverse is also supported:</span>
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='kw'><a href='https://dplyr.tidyverse.org'>dplyr</a></span>)
<span class='kw'>df</span><span class='op'>$</span><span class='kw'>mo</span> <span class='op'>&lt;-</span> <span class='kw'>df</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='kw'>microorganism_name</span>) <span class='op'>%&gt;%</span>
<span class='fu'>as.mo</span>()
<span class='co'># and can even contain 2 columns, which is convenient</span>
<span class='co'># for genus/species combinations:</span>
<span class='kw'>df</span><span class='op'>$</span><span class='kw'>mo</span> <span class='op'>&lt;-</span> <span class='kw'>df</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='kw'>genus</span>, <span class='kw'>species</span>) <span class='op'>%&gt;%</span>
<span class='fu'>as.mo</span>()
<span class='co'># although this works easier and does the same:</span>
<span class='kw'>df</span> <span class='op'>&lt;-</span> <span class='kw'>df</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(mo = <span class='fu'>as.mo</span>(<span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste</a></span>(<span class='kw'>genus</span>, <span class='kw'>species</span>)))
}
</pre>
</div>
<div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">

91
docs/reference/as.rsi.html
View File

@ -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">1.3.0.9032</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9035</span>
</span>
</div>
@ -424,34 +424,6 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
NIT = <span class='fu'><a href='as.mic.html'>as.mic</a></span>(<span class='fl'>32</span>))
<span class='fu'>as.rsi</span>(<span class='kw'>df</span>)
<span class='co'>if</span> (<span class='fl'>FALSE</span>) {
<span class='co'># the dplyr way</span>
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='kw'><a href='https://dplyr.tidyverse.org'>dplyr</a></span>)
<span class='kw'>df</span> <span class='op'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate_all.html'>mutate_if</a></span>(<span class='kw'>is.mic</span>, <span class='kw'>as.rsi</span>)
<span class='kw'>df</span> <span class='op'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate_all.html'>mutate_if</a></span>(<span class='fu'>function</span>(<span class='kw'>x</span>) <span class='fu'><a href='as.mic.html'>is.mic</a></span>(<span class='kw'>x</span>) <span class='op'>|</span> <span class='fu'><a href='as.disk.html'>is.disk</a></span>(<span class='kw'>x</span>), <span class='kw'>as.rsi</span>)
<span class='kw'>df</span> <span class='op'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/across.html'>across</a></span>(<span class='fu'>where</span>(<span class='kw'>is.mic</span>), <span class='kw'>as.rsi</span>))
<span class='kw'>df</span> <span class='op'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate_all.html'>mutate_at</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='kw'>AMP</span><span class='op'>:</span><span class='kw'>TOB</span>), <span class='kw'>as.rsi</span>)
<span class='kw'>df</span> <span class='op'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/across.html'>across</a></span>(<span class='kw'>AMP</span><span class='op'>:</span><span class='kw'>TOB</span>), <span class='kw'>as.rsi</span>)
<span class='kw'>df</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate_all.html'>mutate_at</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='kw'>AMP</span><span class='op'>:</span><span class='kw'>TOB</span>), <span class='kw'>as.rsi</span>, mo = <span class='st'>"E. coli"</span>)
<span class='co'># to include information about urinary tract infections (UTI)</span>
<span class='fu'><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a></span>(mo = <span class='st'>"E. coli"</span>,
NIT = <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"&lt;= 2"</span>, <span class='fl'>32</span>),
from_the_bladder = <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='fl'>TRUE</span>, <span class='fl'>FALSE</span>)) <span class='op'>%&gt;%</span>
<span class='fu'>as.rsi</span>(uti = <span class='st'>"from_the_bladder"</span>)
<span class='fu'><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a></span>(mo = <span class='st'>"E. coli"</span>,
NIT = <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"&lt;= 2"</span>, <span class='fl'>32</span>),
specimen = <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"urine"</span>, <span class='st'>"blood"</span>)) <span class='op'>%&gt;%</span>
<span class='fu'>as.rsi</span>() <span class='co'># automatically determines urine isolates</span>
<span class='kw'>df</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate_all.html'>mutate_at</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='kw'>AMP</span><span class='op'>:</span><span class='kw'>NIT</span>), <span class='kw'>as.rsi</span>, mo = <span class='st'>"E. coli"</span>, uti = <span class='fl'>TRUE</span>)
}
<span class='co'># for single values</span>
<span class='fu'>as.rsi</span>(x = <span class='fu'><a href='as.mic.html'>as.mic</a></span>(<span class='fl'>2</span>),
mo = <span class='fu'><a href='as.mo.html'>as.mo</a></span>(<span class='st'>"S. pneumoniae"</span>),
@ -463,6 +435,32 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
ab = <span class='st'>"ampicillin"</span>, <span class='co'># and `ab` with as.ab()</span>
guideline = <span class='st'>"EUCAST"</span>)
<span class='co'># \donttest{</span>
<span class='co'># the dplyr way</span>
<span class='co'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='st'><a href='https://dplyr.tidyverse.org'>"dplyr"</a></span>)) {
<span class='kw'>df</span> <span class='op'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate_all.html'>mutate_if</a></span>(<span class='kw'>is.mic</span>, <span class='kw'>as.rsi</span>)
<span class='kw'>df</span> <span class='op'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate_all.html'>mutate_if</a></span>(<span class='fu'>function</span>(<span class='kw'>x</span>) <span class='fu'><a href='as.mic.html'>is.mic</a></span>(<span class='kw'>x</span>) <span class='op'>|</span> <span class='fu'><a href='as.disk.html'>is.disk</a></span>(<span class='kw'>x</span>), <span class='kw'>as.rsi</span>)
<span class='kw'>df</span> <span class='op'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/across.html'>across</a></span>(<span class='fu'>where</span>(<span class='kw'>is.mic</span>), <span class='kw'>as.rsi</span>))
<span class='kw'>df</span> <span class='op'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate_all.html'>mutate_at</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='kw'>AMP</span><span class='op'>:</span><span class='kw'>TOB</span>), <span class='kw'>as.rsi</span>)
<span class='kw'>df</span> <span class='op'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/across.html'>across</a></span>(<span class='kw'>AMP</span><span class='op'>:</span><span class='kw'>TOB</span>), <span class='kw'>as.rsi</span>)
<span class='kw'>df</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate_all.html'>mutate_at</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='kw'>AMP</span><span class='op'>:</span><span class='kw'>TOB</span>), <span class='kw'>as.rsi</span>, mo = <span class='st'>"E. coli"</span>)
<span class='co'># to include information about urinary tract infections (UTI)</span>
<span class='fu'><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a></span>(mo = <span class='st'>"E. coli"</span>,
NIT = <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"&lt;= 2"</span>, <span class='fl'>32</span>),
from_the_bladder = <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='fl'>TRUE</span>, <span class='fl'>FALSE</span>)) <span class='op'>%&gt;%</span>
<span class='fu'>as.rsi</span>(uti = <span class='st'>"from_the_bladder"</span>)
<span class='fu'><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a></span>(mo = <span class='st'>"E. coli"</span>,
NIT = <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"&lt;= 2"</span>, <span class='fl'>32</span>),
specimen = <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"urine"</span>, <span class='st'>"blood"</span>)) <span class='op'>%&gt;%</span>
<span class='fu'>as.rsi</span>() <span class='co'># automatically determines urine isolates</span>
<span class='kw'>df</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate_all.html'>mutate_at</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='kw'>AMP</span><span class='op'>:</span><span class='kw'>NIT</span>), <span class='kw'>as.rsi</span>, mo = <span class='st'>"E. coli"</span>, uti = <span class='fl'>TRUE</span>)
}
<span class='co'># For CLEANING existing R/SI values ------------------------------------</span>
@ -473,26 +471,23 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
<span class='fu'><a href='plot.html'>plot</a></span>(<span class='kw'>rsi_data</span>) <span class='co'># for percentages</span>
<span class='fu'><a href='https://rdrr.io/r/graphics/barplot.html'>barplot</a></span>(<span class='kw'>rsi_data</span>) <span class='co'># for frequencies</span>
<span class='co'>if</span> (<span class='fl'>FALSE</span>) {
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='kw'><a href='https://dplyr.tidyverse.org'>dplyr</a></span>)
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate_all.html'>mutate_at</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='kw'>PEN</span><span class='op'>:</span><span class='kw'>RIF</span>), <span class='kw'>as.rsi</span>)
<span class='co'># same: </span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'>as.rsi</span>(<span class='kw'>PEN</span><span class='op'>:</span><span class='kw'>RIF</span>)
<span class='co'># fastest way to transform all columns with already valid AMR results to class `rsi`:</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate_all.html'>mutate_if</a></span>(<span class='kw'>is.rsi.eligible</span>, <span class='kw'>as.rsi</span>)
<span class='co'># note: from dplyr 1.0.0 on, this will be: </span>
<span class='co'># example_isolates %&gt;%</span>
<span class='co'># mutate(across(is.rsi.eligible, as.rsi))</span>
<span class='co'># default threshold of `is.rsi.eligible` is 5%.</span>
<span class='fu'>is.rsi.eligible</span>(<span class='kw'>WHONET</span><span class='op'>$</span><span class='kw'>`First name`</span>) <span class='co'># fails, &gt;80% is invalid</span>
<span class='fu'>is.rsi.eligible</span>(<span class='kw'>WHONET</span><span class='op'>$</span><span class='kw'>`First name`</span>, threshold = <span class='fl'>0.99</span>) <span class='co'># succeeds</span>
<span class='co'># the dplyr way</span>
<span class='co'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='st'><a href='https://dplyr.tidyverse.org'>"dplyr"</a></span>)) {
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate_all.html'>mutate_at</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='kw'>PEN</span><span class='op'>:</span><span class='kw'>RIF</span>), <span class='kw'>as.rsi</span>)
<span class='co'># same: </span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'>as.rsi</span>(<span class='kw'>PEN</span><span class='op'>:</span><span class='kw'>RIF</span>)
<span class='co'># fastest way to transform all columns with already valid AMR results to class `rsi`:</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate_all.html'>mutate_if</a></span>(<span class='kw'>is.rsi.eligible</span>, <span class='kw'>as.rsi</span>)
<span class='co'># note: from dplyr 1.0.0 on, this will be: </span>
<span class='co'># example_isolates %&gt;%</span>
<span class='co'># mutate(across(is.rsi.eligible, as.rsi))</span>
}
<span class='co'># }</span>
</pre>
</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">1.3.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9035</span>
</span>
</div>
@ -327,18 +327,15 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
<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> (which reads a lot easier than here in R) 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'>if</span> (<span class='fl'>FALSE</span>) {
<pre class="examples"><span class='co'># \donttest{</span>
<span class='co'># oral DDD (Defined Daily Dose) of amoxicillin</span>
<span class='fu'>atc_online_property</span>(<span class='st'>"J01CA04"</span>, <span class='st'>"DDD"</span>, <span class='st'>"O"</span>)
<span class='co'># parenteral DDD (Defined Daily Dose) of amoxicillin</span>
<span class='fu'>atc_online_property</span>(<span class='st'>"J01CA04"</span>, <span class='st'>"DDD"</span>, <span class='st'>"P"</span>)
<span class='fu'>atc_online_property</span>(<span class='st'>"J01CA04"</span>, property = <span class='st'>"groups"</span>) <span class='co'># search hierarchical groups of amoxicillin</span>
<span class='co'># [1] "ANTIINFECTIVES FOR SYSTEMIC USE"</span>
<span class='co'># [2] "ANTIBACTERIALS FOR SYSTEMIC USE"</span>
<span class='co'># [3] "BETA-LACTAM ANTIBACTERIALS, PENICILLINS"</span>
<span class='co'># [4] "Penicillins with extended spectrum"</span>
}
<span class='co'># }</span>
</pre>
</div>
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19
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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">1.3.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9035</span>
</span>
</div>
@ -279,18 +279,11 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='fu'>availability</span>(<span class='kw'>example_isolates</span>)
<span class='co'>if</span> (<span class='fl'>FALSE</span>) {
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='kw'><a href='https://dplyr.tidyverse.org'>dplyr</a></span>)
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>availability</span>()
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select_all.html'>select_if</a></span>(<span class='kw'>is.rsi</span>) <span class='op'>%&gt;%</span>
<span class='fu'>availability</span>()
<span class='kw'>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='kw'>mo</span> <span class='op'>==</span> <span class='fu'><a href='as.mo.html'>as.mo</a></span>(<span class='st'>"E. coli"</span>)) <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select_all.html'>select_if</a></span>(<span class='kw'>is.rsi</span>) <span class='op'>%&gt;%</span>
<span class='fu'>availability</span>()
<span class='co'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='st'><a href='https://dplyr.tidyverse.org'>"dplyr"</a></span>)) {
<span class='kw'>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='kw'>mo</span> <span class='op'>==</span> <span class='fu'><a href='as.mo.html'>as.mo</a></span>(<span class='st'>"E. coli"</span>)) <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select_all.html'>select_if</a></span>(<span class='kw'>is.rsi</span>) <span class='op'>%&gt;%</span>
<span class='fu'>availability</span>()
}
</pre>
</div>

16
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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">1.3.0.9028</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9035</span>
</span>
</div>
@ -304,7 +304,7 @@
</tr>
<tr>
<th>remove_intrinsic_resistant</th>
<td><p>logical to indicate that rows with 100% resistance for all tested antimicrobials must be removed from the table</p></td>
<td><p>logical to indicate that rows and columns with 100% resistance for all tested antimicrobials must be removed from the table</p></td>
</tr>
<tr>
<th>decimal.mark</th>
@ -348,13 +348,13 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
<span class='fu'><a href='https://rdrr.io/r/base/format.html'>format</a></span>(<span class='kw'>x</span>, translate_ab = <span class='st'>"name (atc)"</span>)
<span class='co'># Use FUN to change to transformation of microorganism codes</span>
<span class='kw'>x</span> <span class='op'>&lt;-</span> <span class='fu'>bug_drug_combinations</span>(<span class='kw'>example_isolates</span>,
FUN = <span class='kw'>mo_gramstain</span>)
<span class='fu'>bug_drug_combinations</span>(<span class='kw'>example_isolates</span>,
FUN = <span class='kw'>mo_gramstain</span>)
<span class='kw'>x</span> <span class='op'>&lt;-</span> <span class='fu'>bug_drug_combinations</span>(<span class='kw'>example_isolates</span>,
FUN = <span class='fu'>function</span>(<span class='kw'>x</span>) <span class='fu'><a href='https://rdrr.io/r/base/ifelse.html'>ifelse</a></span>(<span class='kw'>x</span> <span class='op'>==</span> <span class='fu'><a href='as.mo.html'>as.mo</a></span>(<span class='st'>"E. coli"</span>),
<span class='st'>"E. coli"</span>,
<span class='st'>"Others"</span>))
<span class='fu'>bug_drug_combinations</span>(<span class='kw'>example_isolates</span>,
FUN = <span class='fu'>function</span>(<span class='kw'>x</span>) <span class='fu'><a href='https://rdrr.io/r/base/ifelse.html'>ifelse</a></span>(<span class='kw'>x</span> <span class='op'>==</span> <span class='fu'><a href='as.mo.html'>as.mo</a></span>(<span class='st'>"E. coli"</span>),
<span class='st'>"E. coli"</span>,
<span class='st'>"Others"</span>))
<span class='co'># }</span>
</pre>
</div>

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@ -50,7 +50,7 @@
<meta property="og:title" content="Filter isolates on result in antimicrobial class — filter_ab_class" />
<meta property="og:description" content="Filter isolates on results in specific antimicrobial classes. This makes it easy to filter on isolates that were tested for e.g. any aminoglycoside, or to filter on carbapenem-resistant isolates without the need to specify the drugs." />
<meta property="og:image" content="https://msberends.github.io/AMR/logo.svg" />
<meta property="og:image" content="https://msberends.github.io/AMR/logo.png" />
@ -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">1.3.0.9015</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9035</span>
</span>
</div>
@ -310,41 +310,45 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
<div class='dont-index'><p><code><a href='antibiotic_class_selectors.html'>antibiotic_class_selectors()</a></code> for the <code><a href='https://dplyr.tidyverse.org/reference/select.html'>select()</a></code> equivalent.</p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'>if</span> (<span class='fl'>FALSE</span>) {
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='kw'><a href='https://dplyr.tidyverse.org'>dplyr</a></span>)
<pre class="examples"><span class='fu'>filter_aminoglycosides</span>(<span class='kw'>example_isolates</span>)
<span class='co'># filter on isolates that have any result for any aminoglycoside</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_ab_class</span>(<span class='st'>"aminoglycoside"</span>)
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_aminoglycosides</span>()
<span class='co'># \donttest{</span>
<span class='co'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='st'><a href='https://dplyr.tidyverse.org'>"dplyr"</a></span>)) {
<span class='co'># this is essentially the same as (but without determination of column names):</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter_all.html'>filter_at</a></span>(.vars = <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"GEN"</span>, <span class='st'>"TOB"</span>, <span class='st'>"AMK"</span>, <span class='st'>"KAN"</span>)),
.vars_predicate = <span class='fu'><a href='https://dplyr.tidyverse.org/reference/all_vars.html'>any_vars</a></span>(<span class='kw'>.</span> <span class='op'>%in%</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"S"</span>, <span class='st'>"I"</span>, <span class='st'>"R"</span>)))
<span class='co'># filter on isolates that have any result for any aminoglycoside</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_aminoglycosides</span>()
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_ab_class</span>(<span class='st'>"aminoglycoside"</span>)
<span class='co'># this is essentially the same as (but without determination of column names):</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter_all.html'>filter_at</a></span>(.vars = <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"GEN"</span>, <span class='st'>"TOB"</span>, <span class='st'>"AMK"</span>, <span class='st'>"KAN"</span>)),
.vars_predicate = <span class='fu'><a href='https://dplyr.tidyverse.org/reference/all_vars.html'>any_vars</a></span>(<span class='kw'>.</span> <span class='op'>%in%</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"S"</span>, <span class='st'>"I"</span>, <span class='st'>"R"</span>)))
<span class='co'># filter on isolates that show resistance to ANY aminoglycoside</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_aminoglycosides</span>(<span class='st'>"R"</span>, <span class='st'>"any"</span>)
<span class='co'># filter on isolates that show resistance to ALL aminoglycosides</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_aminoglycosides</span>(<span class='st'>"R"</span>, <span class='st'>"all"</span>)
<span class='co'># filter on isolates that show resistance to</span>
<span class='co'># any aminoglycoside and any fluoroquinolone</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'>filter_aminoglycosides</span>(<span class='st'>"R"</span>) <span class='op'>%&gt;%</span>
<span class='fu'>filter_fluoroquinolones</span>(<span class='st'>"R"</span>)
<span class='co'># filter on isolates that show resistance to</span>
<span class='co'># all aminoglycosides and all fluoroquinolones</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'>filter_aminoglycosides</span>(<span class='st'>"R"</span>, <span class='st'>"all"</span>) <span class='op'>%&gt;%</span>
<span class='fu'>filter_fluoroquinolones</span>(<span class='st'>"R"</span>, <span class='st'>"all"</span>)
<span class='co'># with dplyr 1.0.0 and higher (that adds 'across()'), this is equal:</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_carbapenems</span>(<span class='st'>"R"</span>, <span class='st'>"all"</span>)
<span class='kw'>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='fu'><a href='https://dplyr.tidyverse.org/reference/across.html'>across</a></span>(<span class='fu'><a href='antibiotic_class_selectors.html'>carbapenems</a></span>(), <span class='op'>~</span><span class='kw'>.</span> <span class='op'>==</span> <span class='st'>"R"</span>))
}</pre>
<span class='co'># filter on isolates that show resistance to ANY aminoglycoside</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_aminoglycosides</span>(<span class='st'>"R"</span>, <span class='st'>"any"</span>)
<span class='co'># filter on isolates that show resistance to ALL aminoglycosides</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_aminoglycosides</span>(<span class='st'>"R"</span>, <span class='st'>"all"</span>)
<span class='co'># filter on isolates that show resistance to</span>
<span class='co'># any aminoglycoside and any fluoroquinolone</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'>filter_aminoglycosides</span>(<span class='st'>"R"</span>) <span class='op'>%&gt;%</span>
<span class='fu'>filter_fluoroquinolones</span>(<span class='st'>"R"</span>)
<span class='co'># filter on isolates that show resistance to</span>
<span class='co'># all aminoglycosides and all fluoroquinolones</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'>filter_aminoglycosides</span>(<span class='st'>"R"</span>, <span class='st'>"all"</span>) <span class='op'>%&gt;%</span>
<span class='fu'>filter_fluoroquinolones</span>(<span class='st'>"R"</span>, <span class='st'>"all"</span>)
<span class='co'># with dplyr 1.0.0 and higher (that adds 'across()'), this is equal:</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>filter_carbapenems</span>(<span class='st'>"R"</span>, <span class='st'>"all"</span>)
<span class='kw'>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='fu'><a href='https://dplyr.tidyverse.org/reference/across.html'>across</a></span>(<span class='fu'><a href='antibiotic_class_selectors.html'>carbapenems</a></span>(), <span class='op'>~</span><span class='kw'>.</span> <span class='op'>==</span> <span class='st'>"R"</span>))
}
<span class='co'># }</span>
</pre>
</div>
<div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
<nav id="toc" data-toggle="toc" class="sticky-top">

90
docs/reference/first_isolate.html
View File

@ -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">1.3.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9035</span>
</span>
</div>
@ -369,15 +369,16 @@
<p><strong>WHY THIS IS SO IMPORTANT</strong> <br />
To conduct an analysis of antimicrobial resistance, you should only include the first isolate of every patient per episode <a href='https://www.ncbi.nlm.nih.gov/pubmed/17304462'>(ref)</a>. If you would not do this, you could easily get an overestimate or underestimate of the resistance of an antibiotic. Imagine that a patient was admitted with an MRSA and that it was found in 5 different blood cultures the following week. The resistance percentage of oxacillin of all <em>S. aureus</em> isolates would be overestimated, because you included this MRSA more than once. It would be <a href='https://en.wikipedia.org/wiki/Selection_bias'>selection bias</a>.</p>
<p>All isolates with a microbial ID of <code>NA</code> will be excluded as first isolate.</p>
<p>The functions <code>filter_first_isolate()</code> and <code>filter_first_weighted_isolate()</code> are helper functions to quickly filter on first isolates. The function <code>filter_first_isolate()</code> is essentially equal to one of:</p><pre> <span class='kw'>x</span> <span class='op'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='fu'>first_isolate</span>(<span class='kw'>.</span>, <span class='kw'>...</span>))
<p>The functions <code>filter_first_isolate()</code> and <code>filter_first_weighted_isolate()</code> are helper functions to quickly filter on first isolates. The function <code>filter_first_isolate()</code> is essentially equal to either:</p><pre> <span class='kw'>x</span>[<span class='fu'>first_isolate</span>(<span class='kw'>x</span>, <span class='kw'>...</span>), ]
<span class='kw'>x</span> <span class='op'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='fu'>first_isolate</span>(<span class='kw'>x</span>, <span class='kw'>...</span>))
</pre>
<p>The function <code>filter_first_weighted_isolate()</code> is essentially equal to:</p><pre> <span class='kw'>x</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(keyab = <span class='fu'><a href='key_antibiotics.html'>key_antibiotics</a></span>(<span class='kw'>.</span>)) <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(only_weighted_firsts = <span class='fu'>first_isolate</span>(<span class='kw'>x</span>,
col_keyantibiotics = <span class='st'>"keyab"</span>, <span class='kw'>...</span>)) <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='kw'>only_weighted_firsts</span> <span class='op'>==</span> <span class='fl'>TRUE</span>) <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='op'>-</span><span class='kw'>only_weighted_firsts</span>, <span class='op'>-</span><span class='kw'>keyab</span>)
<p>The function <code>filter_first_weighted_isolate()</code> is essentially equal to:</p><pre> <span class='kw'>x</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(keyab = <span class='fu'><a href='key_antibiotics.html'>key_antibiotics</a></span>(<span class='kw'>.</span>)) <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(only_weighted_firsts = <span class='fu'>first_isolate</span>(<span class='kw'>x</span>,
col_keyantibiotics = <span class='st'>"keyab"</span>, <span class='kw'>...</span>)) <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='kw'>only_weighted_firsts</span> <span class='op'>==</span> <span class='fl'>TRUE</span>) <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='op'>-</span><span class='kw'>only_weighted_firsts</span>, <span class='op'>-</span><span class='kw'>keyab</span>)
</pre>
<h2 class="hasAnchor" id="key-antibiotics"><a class="anchor" href="#key-antibiotics"></a>Key antibiotics</h2>
@ -411,50 +412,41 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
<pre class="examples"><span class='co'># `example_isolates` is a dataset available in the AMR package.</span>
<span class='co'># See ?example_isolates.</span>
<span class='co'>if</span> (<span class='fl'>FALSE</span>) {
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='kw'><a href='https://dplyr.tidyverse.org'>dplyr</a></span>)
<span class='co'># Filter on first isolates:</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(first_isolate = <span class='fu'>first_isolate</span>(<span class='kw'>.</span>)) <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='kw'>first_isolate</span> <span class='op'>==</span> <span class='fl'>TRUE</span>)
<span class='co'># basic filtering on first isolates</span>
<span class='kw'>example_isolates</span>[<span class='fu'>first_isolate</span>(<span class='kw'>example_isolates</span>), ]
<span class='co'># Now let's see if first isolates matter:</span>
<span class='kw'>A</span> <span class='op'>&lt;-</span> <span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='kw'>hospital_id</span>) <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></span>(count = <span class='fu'><a href='count.html'>n_rsi</a></span>(<span class='kw'>GEN</span>), <span class='co'># gentamicin availability</span>
resistance = <span class='fu'><a href='proportion.html'>resistance</a></span>(<span class='kw'>GEN</span>)) <span class='co'># gentamicin resistance</span>
<span class='kw'>B</span> <span class='op'>&lt;-</span> <span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'>filter_first_weighted_isolate</span>() <span class='op'>%&gt;%</span> <span class='co'># the 1st isolate filter</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='kw'>hospital_id</span>) <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></span>(count = <span class='fu'><a href='count.html'>n_rsi</a></span>(<span class='kw'>GEN</span>), <span class='co'># gentamicin availability</span>
resistance = <span class='fu'><a href='proportion.html'>resistance</a></span>(<span class='kw'>GEN</span>)) <span class='co'># gentamicin resistance</span>
<span class='co'># Have a look at A and B.</span>
<span class='co'># B is more reliable because every isolate is counted only once.</span>
<span class='co'># Gentamicin resistance in hospital D appears to be 3.7% higher than</span>
<span class='co'># when you (erroneously) would have used all isolates for analysis.</span>
<span class='co'>## OTHER EXAMPLES:</span>
<span class='co'># Short-hand versions:</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'>filter_first_isolate</span>()
<span class='co'># \donttest{</span>
<span class='co'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='st'><a href='https://dplyr.tidyverse.org'>"dplyr"</a></span>)) {
<span class='co'># Filter on first isolates:</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(first_isolate = <span class='fu'>first_isolate</span>(<span class='kw'>.</span>)) <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='kw'>first_isolate</span> <span class='op'>==</span> <span class='fl'>TRUE</span>)
<span class='co'># Short-hand versions:</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'>filter_first_isolate</span>()
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'>filter_first_weighted_isolate</span>()
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'>filter_first_weighted_isolate</span>()
<span class='co'># set key antibiotics to a new variable</span>
<span class='kw'>x</span><span class='op'>$</span><span class='kw'>keyab</span> <span class='op'>&lt;-</span> <span class='fu'><a href='key_antibiotics.html'>key_antibiotics</a></span>(<span class='kw'>x</span>)
<span class='kw'>x</span><span class='op'>$</span><span class='kw'>first_isolate</span> <span class='op'>&lt;-</span> <span class='fu'>first_isolate</span>(<span class='kw'>x</span>)
<span class='kw'>x</span><span class='op'>$</span><span class='kw'>first_isolate_weighed</span> <span class='op'>&lt;-</span> <span class='fu'>first_isolate</span>(<span class='kw'>x</span>, col_keyantibiotics = <span class='st'>'keyab'</span>)
<span class='kw'>x</span><span class='op'>$</span><span class='kw'>first_blood_isolate</span> <span class='op'>&lt;-</span> <span class='fu'>first_isolate</span>(<span class='kw'>x</span>, specimen_group = <span class='st'>"Blood"</span>)
<span class='co'># Now let's see if first isolates matter:</span>
<span class='kw'>A</span> <span class='op'>&lt;-</span> <span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='kw'>hospital_id</span>) <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></span>(count = <span class='fu'><a href='count.html'>n_rsi</a></span>(<span class='kw'>GEN</span>), <span class='co'># gentamicin availability</span>
resistance = <span class='fu'><a href='proportion.html'>resistance</a></span>(<span class='kw'>GEN</span>)) <span class='co'># gentamicin resistance</span>
<span class='kw'>B</span> <span class='op'>&lt;-</span> <span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'>filter_first_weighted_isolate</span>() <span class='op'>%&gt;%</span> <span class='co'># the 1st isolate filter</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='kw'>hospital_id</span>) <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></span>(count = <span class='fu'><a href='count.html'>n_rsi</a></span>(<span class='kw'>GEN</span>), <span class='co'># gentamicin availability</span>
resistance = <span class='fu'><a href='proportion.html'>resistance</a></span>(<span class='kw'>GEN</span>)) <span class='co'># gentamicin resistance</span>
<span class='co'># Have a look at A and B.</span>
<span class='co'># B is more reliable because every isolate is counted only once.</span>
<span class='co'># Gentamicin resistance in hospital D appears to be 3.7% higher than</span>
<span class='co'># when you (erroneously) would have used all isolates for analysis.</span>
}
<span class='co'># }</span>
</pre>
</div>
<div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">

10
docs/reference/ggplot_pca.html
View File

@ -50,7 +50,7 @@
<meta property="og:title" content="PCA biplot with ggplot2 — ggplot_pca" />
<meta property="og:description" content="Produces a ggplot2 variant of a so-called biplot for PCA (principal component analysis), but is more flexible and more appealing than the base R biplot() function." />
<meta property="og:image" content="https://msberends.github.io/AMR/logo.svg" />
<meta property="og:image" content="https://msberends.github.io/AMR/logo.png" />
@ -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">1.3.0.9015</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9035</span>
</span>
</div>
@ -395,8 +395,7 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>maturing<
<span class='co'># See ?example_isolates.</span>
<span class='co'># See ?pca for more info about Principal Component Analysis (PCA).</span>
<span class='co'>if</span> (<span class='fl'>FALSE</span>) {
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='kw'><a href='https://dplyr.tidyverse.org'>dplyr</a></span>)
<span class='co'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='st'><a href='https://dplyr.tidyverse.org'>"dplyr"</a></span>)) {
<span class='kw'>pca_model</span> <span class='op'>&lt;-</span> <span class='kw'>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='fu'><a href='mo_property.html'>mo_genus</a></span>(<span class='kw'>mo</span>) <span class='op'>==</span> <span class='st'>"Staphylococcus"</span>) <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(species = <span class='fu'><a href='mo_property.html'>mo_shortname</a></span>(<span class='kw'>mo</span>)) <span class='op'>%&gt;%</span>
@ -414,7 +413,8 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>maturing<
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/scale_viridis.html'>scale_colour_viridis_d</a></span>() <span class='op'>+</span>
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/labs.html'>labs</a></span>(title = <span class='st'>"Title here"</span>)
}
}</pre>
}
</pre>
</div>
<div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
<nav id="toc" data-toggle="toc" class="sticky-top">

11
docs/reference/ggplot_rsi.html
View File

@ -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">1.3.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9035</span>
</span>
</div>
@ -467,14 +467,14 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>maturing<
}
<span class='co'>if</span> (<span class='fl'>FALSE</span>) {
<span class='co'># \donttest{</span>
<span class='co'># resistance of ciprofloxacine per age group</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(first_isolate = <span class='fu'><a href='first_isolate.html'>first_isolate</a></span>(<span class='kw'>.</span>)) <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='kw'>first_isolate</span> <span class='op'>==</span> <span class='fl'>TRUE</span>,
<span class='kw'>mo</span> <span class='op'>==</span> <span class='fu'><a href='as.mo.html'>as.mo</a></span>(<span class='st'>"E. coli"</span>)) <span class='op'>%&gt;%</span>
<span class='co'># `age_group` is also a function of this package:</span>
<span class='co'># `age_groups` is also a function of this AMR package:</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(age_group = <span class='fu'><a href='age_groups.html'>age_groups</a></span>(<span class='kw'>age</span>)) <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='kw'>age_group</span>,
<span class='kw'>CIP</span>) <span class='op'>%&gt;%</span>
@ -483,7 +483,8 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>maturing<
<span class='co'># for colourblind mode, use divergent colours from the viridis package:</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='kw'>AMX</span>, <span class='kw'>NIT</span>, <span class='kw'>FOS</span>, <span class='kw'>TMP</span>, <span class='kw'>CIP</span>) <span class='op'>%&gt;%</span>
<span class='fu'>ggplot_rsi</span>() <span class='op'>+</span> <span class='fu'><a href='https://ggplot2.tidyverse.org/reference/scale_viridis.html'>scale_fill_viridis_d</a></span>()
<span class='fu'>ggplot_rsi</span>() <span class='op'>+</span>
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/scale_viridis.html'>scale_fill_viridis_d</a></span>()
<span class='co'># a shorter version which also adjusts data label colours:</span>
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='kw'>AMX</span>, <span class='kw'>NIT</span>, <span class='kw'>FOS</span>, <span class='kw'>TMP</span>, <span class='kw'>CIP</span>) <span class='op'>%&gt;%</span>
@ -500,7 +501,7 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>maturing<
title = <span class='st'>"AMR of Anti-UTI Drugs Per Hospital"</span>,
x.title = <span class='st'>"Hospital"</span>,
datalabels = <span class='fl'>FALSE</span>)
}
<span class='co'># }</span>
</pre>
</div>
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21
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@ -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">1.3.0.9034</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9035</span>
</span>
</div>
@ -634,25 +634,6 @@
</td>
<td><p>Symbol of a p-value</p></td>
</tr>
</tbody><tbody>
<tr>
<th colspan="2">
<h2 id="section-other-deprecated-functions" class="hasAnchor"><a href="#section-other-deprecated-functions" class="anchor"></a>Other: deprecated functions</h2>
<p class="section-desc"><p>These functions are deprecated, meaning that they will still work but show a warning with every use and will be removed in a future version.</p></p>
</th>
</tr>
</tbody><tbody>
<tr>
<td>
<p><code><a href="AMR-deprecated.html">portion_R()</a></code> <code><a href="AMR-deprecated.html">portion_IR()</a></code> <code><a href="AMR-deprecated.html">portion_I()</a></code> <code><a href="AMR-deprecated.html">portion_SI()</a></code> <code><a href="AMR-deprecated.html">portion_S()</a></code> <code><a href="AMR-deprecated.html">portion_df()</a></code> </p>
</td>
<td><p>Deprecated functions</p></td>
</tr>
</tbody>
</table>
</div>

31
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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">1.3.0.9032</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9035</span>
</span>
</div>
@ -296,20 +296,23 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
<pre class="examples"><span class='fu'>left_join_microorganisms</span>(<span class='fu'><a href='as.mo.html'>as.mo</a></span>(<span class='st'>"K. pneumoniae"</span>))
<span class='fu'>left_join_microorganisms</span>(<span class='st'>"B_KLBSL_PNE"</span>)
<span class='co'>if</span> (<span class='fl'>FALSE</span>) {
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='kw'><a href='https://dplyr.tidyverse.org'>dplyr</a></span>)
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span> <span class='fu'>left_join_microorganisms</span>()
<span class='kw'>df</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a></span>(date = <span class='fu'><a href='https://rdrr.io/r/base/seq.html'>seq</a></span>(from = <span class='fu'><a href='https://rdrr.io/r/base/as.Date.html'>as.Date</a></span>(<span class='st'>"2018-01-01"</span>),
to = <span class='fu'><a href='https://rdrr.io/r/base/as.Date.html'>as.Date</a></span>(<span class='st'>"2018-01-07"</span>),
by = <span class='fl'>1</span>),
bacteria = <span class='fu'><a href='as.mo.html'>as.mo</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"S. aureus"</span>, <span class='st'>"MRSA"</span>, <span class='st'>"MSSA"</span>, <span class='st'>"STAAUR"</span>,
<span class='st'>"E. coli"</span>, <span class='st'>"E. coli"</span>, <span class='st'>"E. coli"</span>)),
stringsAsFactors = <span class='fl'>FALSE</span>)
<span class='fu'><a href='https://rdrr.io/r/base/colnames.html'>colnames</a></span>(<span class='kw'>df</span>)
<span class='kw'>df_joined</span> <span class='op'>&lt;-</span> <span class='fu'>left_join_microorganisms</span>(<span class='kw'>df</span>, <span class='st'>"bacteria"</span>)
<span class='fu'><a href='https://rdrr.io/r/base/colnames.html'>colnames</a></span>(<span class='kw'>df_joined</span>)
<span class='co'># \donttest{</span>
<span class='co'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='st'><a href='https://dplyr.tidyverse.org'>"dplyr"</a></span>)) {
<span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'>left_join_microorganisms</span>() <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://rdrr.io/r/base/colnames.html'>colnames</a></span>()
<span class='kw'>df</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a></span>(date = <span class='fu'><a href='https://rdrr.io/r/base/seq.html'>seq</a></span>(from = <span class='fu'><a href='https://rdrr.io/r/base/as.Date.html'>as.Date</a></span>(<span class='st'>"2018-01-01"</span>),
to = <span class='fu'><a href='https://rdrr.io/r/base/as.Date.html'>as.Date</a></span>(<span class='st'>"2018-01-07"</span>),
by = <span class='fl'>1</span>),
bacteria = <span class='fu'><a href='as.mo.html'>as.mo</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"S. aureus"</span>, <span class='st'>"MRSA"</span>, <span class='st'>"MSSA"</span>, <span class='st'>"STAAUR"</span>,
<span class='st'>"E. coli"</span>, <span class='st'>"E. coli"</span>, <span class='st'>"E. coli"</span>)),
stringsAsFactors = <span class='fl'>FALSE</span>)
<span class='fu'><a href='https://rdrr.io/r/base/colnames.html'>colnames</a></span>(<span class='kw'>df</span>)
<span class='kw'>df_joined</span> <span class='op'>&lt;-</span> <span class='fu'>left_join_microorganisms</span>(<span class='kw'>df</span>, <span class='st'>"bacteria"</span>)
<span class='fu'><a href='https://rdrr.io/r/base/colnames.html'>colnames</a></span>(<span class='kw'>df_joined</span>)
}
<span class='co'># }</span>
</pre>
</div>
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43
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@ -50,7 +50,7 @@
<meta property="og:title" content="Key antibiotics for first weighted isolates — key_antibiotics" />
<meta property="og:description" content="These function can be used to determine first isolates (see first_isolate()). Using key antibiotics to determine first isolates is more reliable than without key antibiotics. These selected isolates will then be called first weighted isolates." />
<meta property="og:image" content="https://msberends.github.io/AMR/logo.svg" />
<meta property="og:image" content="https://msberends.github.io/AMR/logo.png" />
@ -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">1.3.0.9015</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9035</span>
</span>
</div>
@ -395,32 +395,35 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
<pre class="examples"><span class='co'># `example_isolates` is a dataset available in the AMR package.</span>
<span class='co'># See ?example_isolates.</span>
<span class='co'>if</span> (<span class='fl'>FALSE</span>) {
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='kw'><a href='https://dplyr.tidyverse.org'>dplyr</a></span>)
<span class='co'># set key antibiotics to a new variable</span>
<span class='kw'>my_patients</span> <span class='op'>&lt;-</span> <span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(keyab = <span class='fu'>key_antibiotics</span>(<span class='kw'>.</span>)) <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(
<span class='co'># now calculate first isolates</span>
first_regular = <span class='fu'><a href='first_isolate.html'>first_isolate</a></span>(<span class='kw'>.</span>, col_keyantibiotics = <span class='fl'>FALSE</span>),
<span class='co'># and first WEIGHTED isolates</span>
first_weighted = <span class='fu'><a href='first_isolate.html'>first_isolate</a></span>(<span class='kw'>.</span>, col_keyantibiotics = <span class='st'>"keyab"</span>)
)
<span class='co'># Check the difference, in this data set it results in 7% more isolates:</span>
<span class='fu'><a href='https://rdrr.io/r/base/sum.html'>sum</a></span>(<span class='kw'>my_patients</span><span class='op'>$</span><span class='kw'>first_regular</span>, na.rm = <span class='fl'>TRUE</span>)
<span class='fu'><a href='https://rdrr.io/r/base/sum.html'>sum</a></span>(<span class='kw'>my_patients</span><span class='op'>$</span><span class='kw'>first_weighted</span>, na.rm = <span class='fl'>TRUE</span>)
}
<span class='co'># output of the `key_antibiotics` function could be like this:</span>
<span class='kw'>strainA</span> <span class='op'>&lt;-</span> <span class='st'>"SSSRR.S.R..S"</span>
<span class='kw'>strainB</span> <span class='op'>&lt;-</span> <span class='st'>"SSSIRSSSRSSS"</span>
<span class='co'># can those strings can be compared with:</span>
<span class='fu'>key_antibiotics_equal</span>(<span class='kw'>strainA</span>, <span class='kw'>strainB</span>)
<span class='co'># TRUE, because I is ignored (as well as missing values)</span>
<span class='fu'>key_antibiotics_equal</span>(<span class='kw'>strainA</span>, <span class='kw'>strainB</span>, ignore_I = <span class='fl'>FALSE</span>)
<span class='co'># FALSE, because I is not ignored and so the 4th value differs</span></pre>
<span class='co'># FALSE, because I is not ignored and so the 4th value differs</span>
<span class='co'># \donttest{</span>
<span class='co'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='st'><a href='https://dplyr.tidyverse.org'>"dplyr"</a></span>)) {
<span class='co'># set key antibiotics to a new variable</span>
<span class='kw'>my_patients</span> <span class='op'>&lt;-</span> <span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(keyab = <span class='fu'>key_antibiotics</span>(<span class='kw'>.</span>)) <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(
<span class='co'># now calculate first isolates</span>
first_regular = <span class='fu'><a href='first_isolate.html'>first_isolate</a></span>(<span class='kw'>.</span>, col_keyantibiotics = <span class='fl'>FALSE</span>),
<span class='co'># and first WEIGHTED isolates</span>
first_weighted = <span class='fu'><a href='first_isolate.html'>first_isolate</a></span>(<span class='kw'>.</span>, col_keyantibiotics = <span class='st'>"keyab"</span>)
)
<span class='co'># Check the difference, in this data set it results in 7% more isolates:</span>
<span class='fu'><a href='https://rdrr.io/r/base/sum.html'>sum</a></span>(<span class='kw'>my_patients</span><span class='op'>$</span><span class='kw'>first_regular</span>, na.rm = <span class='fl'>TRUE</span>)
<span class='fu'><a href='https://rdrr.io/r/base/sum.html'>sum</a></span>(<span class='kw'>my_patients</span><span class='op'>$</span><span class='kw'>first_weighted</span>, na.rm = <span class='fl'>TRUE</span>)
}
<span class='co'># }</span>
</pre>
</div>
<div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
<nav id="toc" data-toggle="toc" class="sticky-top">

11
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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">1.3.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9035</span>
</span>
</div>
@ -313,11 +313,12 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
<span class='co'>#&gt; TRUE TRUE TRUE</span>
<span class='co'># get isolates whose name start with 'Ent' or 'ent'</span>
<span class='co'>if</span> (<span class='fl'>FALSE</span>) {
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='kw'><a href='https://dplyr.tidyverse.org'>dplyr</a></span>)
<span class='kw'>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='fu'><a href='mo_property.html'>mo_name</a></span>(<span class='kw'>mo</span>) <span class='op'>%like%</span> <span class='st'>"^ent"</span>)
<span class='co'># \donttest{</span>
<span class='co'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='st'><a href='https://dplyr.tidyverse.org'>"dplyr"</a></span>)) {
<span class='kw'>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='fu'><a href='mo_property.html'>mo_name</a></span>(<span class='kw'>mo</span>) <span class='op'>%like%</span> <span class='st'>"^ent"</span>)
}
<span class='co'># }</span>
</pre>
</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">1.3.0.9034</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9035</span>
</span>
</div>
@ -265,21 +265,22 @@
<p>$$m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \operatorname{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}$$</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) as found in <code><a href='microorganisms.html'>microorganisms$fullname</a></code>;</p></li>
<li><p>\(l_{n}\) is the length of \(n\);</p></li>
<li><p>\(\operatorname{lev}\) is the <a href='https://en.wikipedia.org/wiki/Levenshtein_distance'>Levenshtein distance function</a>;</p></li>
<li><p>\(p_{n}\) is the human pathogenic prevalence of \(n\), categorised into group \(1\), \(2\) and \(3\) (see <em>Details</em> in <code><a href='as.mo.html'>?as.mo</a></code>), meaning that \(p = \{1, 2 , 3\}\);</p></li>
<li><p>\(k_{n}\) is the kingdom index of \(n\), set as follows: Bacteria = \(1\), Fungi = \(2\), Protozoa = \(3\), Archaea = \(4\), and all others = \(5\), meaning that \(k = \{1, 2 , 3, 4, 5\}\).</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>
</ul>
<p>This means that the user input <code>x = "E. coli"</code> gets for <em>Escherichia coli</em> a matching score of 68.8% and for <em>Entamoeba coli</em> a matching score of 7.9%.</p>
<p>All matches are sorted descending on their matching score and for all user input values, the top match will be returned.</p>
<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>
<p>All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., <code>"E. coli"</code> will return the microbial ID of <em>Escherichia coli</em> (\(m = 0.688\), a highly prevalent microorganism found in humans) and not <em>Entamoeba coli</em> (\(m = 0.079\), a less prevalent microorganism in humans), although the latter would alphabetically come first.</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='fu'><a href='as.mo.html'>as.mo</a></span>(<span class='st'>"E. coli"</span>)
<span class='fu'><a href='as.mo.html'>mo_uncertainties</a></span>()
<span class='fu'>mo_matching_score</span>(<span class='st'>"E. coli"</span>, <span class='st'>"Escherichia coli"</span>)
<span class='fu'>mo_matching_score</span>(x = <span class='st'>"E. coli"</span>,
n = <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"Escherichia coli"</span>, <span class='st'>"Entamoeba coli"</span>))
</pre>
</div>
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16
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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">1.3.0.9034</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9035</span>
</span>
</div>
@ -354,15 +354,15 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
<p>$$m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \operatorname{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}$$</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) as found in <code><a href='microorganisms.html'>microorganisms$fullname</a></code>;</p></li>
<li><p>\(l_{n}\) is the length of \(n\);</p></li>
<li><p>\(\operatorname{lev}\) is the <a href='https://en.wikipedia.org/wiki/Levenshtein_distance'>Levenshtein distance function</a>;</p></li>
<li><p>\(p_{n}\) is the human pathogenic prevalence of \(n\), categorised into group \(1\), \(2\) and \(3\) (see <em>Details</em> in <code><a href='as.mo.html'>?as.mo</a></code>), meaning that \(p = \{1, 2 , 3\}\);</p></li>
<li><p>\(k_{n}\) is the kingdom index of \(n\), set as follows: Bacteria = \(1\), Fungi = \(2\), Protozoa = \(3\), Archaea = \(4\), and all others = \(5\), meaning that \(k = \{1, 2 , 3, 4, 5\}\).</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>
</ul>
<p>This means that the user input <code>x = "E. coli"</code> gets for <em>Escherichia coli</em> a matching score of 68.8% and for <em>Entamoeba coli</em> a matching score of 7.9%.</p>
<p>All matches are sorted descending on their matching score and for all user input values, the top match will be returned.</p>
<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>
<p>All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., <code>"E. coli"</code> will return the microbial ID of <em>Escherichia coli</em> (\(m = 0.688\), a highly prevalent microorganism found in humans) and not <em>Entamoeba coli</em> (\(m = 0.079\), a less prevalent microorganism in humans), although the latter would alphabetically come first.</p>
<h2 class="hasAnchor" id="catalogue-of-life"><a class="anchor" href="#catalogue-of-life"></a>Catalogue of Life</h2>

7
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@ -50,7 +50,7 @@
<meta property="og:title" content="Symbol of a p-value — p_symbol" />
<meta property="og:description" content="Return the symbol related to the p-value: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1. Values above p = 1 will return NA." />
<meta property="og:image" content="https://msberends.github.io/AMR/logo.svg" />
<meta property="og:image" content="https://msberends.github.io/AMR/logo.png" />
@ -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">1.3.0.9015</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9035</span>
</span>
</div>
@ -260,6 +260,9 @@
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>Text</p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p><strong>NOTE</strong>: this function will be moved to the <code>cleaner</code> package when a new version is being published on CRAN.</p>
<h2 class="hasAnchor" id="questioning-lifecycle"><a class="anchor" href="#questioning-lifecycle"></a>Questioning lifecycle</h2>

41
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@ -50,7 +50,7 @@
<meta property="og:title" content="Principal Component Analysis (for AMR) — pca" />
<meta property="og:description" content="Performs a principal component analysis (PCA) based on a data set with automatic determination for afterwards plotting the groups and labels, and automatic filtering on only suitable (i.e. non-empty and numeric) variables." />
<meta property="og:image" content="https://msberends.github.io/AMR/logo.svg" />
<meta property="og:image" content="https://msberends.github.io/AMR/logo.png" />
@ -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">1.3.0.9015</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9035</span>
</span>
</div>
@ -322,23 +322,26 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>maturing<
<pre class="examples"><span class='co'># `example_isolates` is a dataset available in the AMR package.</span>
<span class='co'># See ?example_isolates.</span>
<span class='co'>if</span> (<span class='fl'>FALSE</span>) {
<span class='co'># calculate the resistance per group first</span>
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='kw'><a href='https://dplyr.tidyverse.org'>dplyr</a></span>)
<span class='kw'>resistance_data</span> <span class='op'>&lt;-</span> <span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(order = <span class='fu'><a href='mo_property.html'>mo_order</a></span>(<span class='kw'>mo</span>), <span class='co'># group on anything, like order</span>
genus = <span class='fu'><a href='mo_property.html'>mo_genus</a></span>(<span class='kw'>mo</span>)) <span class='op'>%&gt;%</span> <span class='co'># and genus as we do here</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/summarise_all.html'>summarise_if</a></span>(<span class='kw'>is.rsi</span>, <span class='kw'>resistance</span>) <span class='co'># then get resistance of all drugs</span>
<span class='co'># now conduct PCA for certain antimicrobial agents</span>
<span class='kw'>pca_result</span> <span class='op'>&lt;-</span> <span class='kw'>resistance_data</span> <span class='op'>%&gt;%</span>
<span class='fu'>pca</span>(<span class='kw'>AMC</span>, <span class='kw'>CXM</span>, <span class='kw'>CTX</span>, <span class='kw'>CAZ</span>, <span class='kw'>GEN</span>, <span class='kw'>TOB</span>, <span class='kw'>TMP</span>, <span class='kw'>SXT</span>)
<span class='kw'>pca_result</span>
<span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span>(<span class='kw'>pca_result</span>)
<span class='fu'><a href='https://rdrr.io/r/stats/biplot.html'>biplot</a></span>(<span class='kw'>pca_result</span>)
<span class='fu'><a href='ggplot_pca.html'>ggplot_pca</a></span>(<span class='kw'>pca_result</span>) <span class='co'># a new and convenient plot function</span>
}</pre>
<span class='co'># \donttest{</span>
<span class='co'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='st'><a href='https://dplyr.tidyverse.org'>"dplyr"</a></span>)) {
<span class='co'># calculate the resistance per group first </span>
<span class='kw'>resistance_data</span> <span class='op'>&lt;-</span> <span class='kw'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(order = <span class='fu'><a href='mo_property.html'>mo_order</a></span>(<span class='kw'>mo</span>), <span class='co'># group on anything, like order</span>
genus = <span class='fu'><a href='mo_property.html'>mo_genus</a></span>(<span class='kw'>mo</span>)) <span class='op'>%&gt;%</span> <span class='co'># and genus as we do here</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/summarise_all.html'>summarise_if</a></span>(<span class='kw'>is.rsi</span>, <span class='kw'>resistance</span>) <span class='co'># then get resistance of all drugs</span>
<span class='co'># now conduct PCA for certain antimicrobial agents</span>
<span class='kw'>pca_result</span> <span class='op'>&lt;-</span> <span class='kw'>resistance_data</span> <span class='op'>%&gt;%</span>
<span class='fu'>pca</span>(<span class='kw'>AMC</span>, <span class='kw'>CXM</span>, <span class='kw'>CTX</span>, <span class='kw'>CAZ</span>, <span class='kw'>GEN</span>, <span class='kw'>TOB</span>, <span class='kw'>TMP</span>, <span class='kw'>SXT</span>)
<span class='kw'>pca_result</span>
<span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span>(<span class='kw'>pca_result</span>)
<span class='fu'><a href='https://rdrr.io/r/stats/biplot.html'>biplot</a></span>(<span class='kw'>pca_result</span>)
<span class='fu'><a href='ggplot_pca.html'>ggplot_pca</a></span>(<span class='kw'>pca_result</span>) <span class='co'># a new and convenient plot function</span>
}
<span class='co'># }</span>
</pre>
</div>
<div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
<nav id="toc" data-toggle="toc" class="sticky-top">

11
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@ -83,7 +83,7 @@ resistance() should be used to calculate resistance, susceptibility() should be
</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">1.3.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9035</span>
</span>
</div>
@ -464,15 +464,6 @@ A microorganism is categorised as <em>Susceptible, Increased exposure</em> when
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='kw'>hospital_id</span>) <span class='op'>%&gt;%</span>
<span class='fu'>proportion_df</span>(translate = <span class='fl'>FALSE</span>)
}
<span class='co'>if</span> (<span class='fl'>FALSE</span>) {
<span class='co'># calculate current empiric combination therapy of Helicobacter gastritis:</span>
<span class='kw'>my_table</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='kw'>first_isolate</span> <span class='op'>==</span> <span class='fl'>TRUE</span>,
<span class='kw'>genus</span> <span class='op'>==</span> <span class='st'>"Helicobacter"</span>) <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></span>(p = <span class='fu'>susceptibility</span>(<span class='kw'>AMX</span>, <span class='kw'>MTR</span>), <span class='co'># amoxicillin with metronidazole</span>
n = <span class='fu'><a href='count.html'>count_all</a></span>(<span class='kw'>AMX</span>, <span class='kw'>MTR</span>))
}
</pre>
</div>
<div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">

6
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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">1.3.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9035</span>
</span>
</div>
@ -418,9 +418,7 @@ A microorganism is categorised as <em>Susceptible, Increased exposure</em> when
}
<span class='co'># create nice plots with ggplot2 yourself</span>
<span class='co'>if</span> (<span class='fl'>FALSE</span>) {
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='kw'><a href='https://dplyr.tidyverse.org'>dplyr</a></span>)
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='kw'><a href='http://ggplot2.tidyverse.org'>ggplot2</a></span>)
<span class='co'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='st'><a href='https://dplyr.tidyverse.org'>"dplyr"</a></span>) <span class='op'>&amp;</span> <span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='st'><a href='http://ggplot2.tidyverse.org'>"ggplot2"</a></span>)) {
<span class='kw'>data</span> <span class='op'>&lt;-</span> <span class='kw'>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='kw'>mo</span> <span class='op'>==</span> <span class='fu'><a href='as.mo.html'>as.mo</a></span>(<span class='st'>"E. coli"</span>)) <span class='op'>%&gt;%</span>