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<meta property="og:description" content="Use this function to determine a valid microorganism ID (mo). Determination is done using Artificial Intelligence (AI) and the complete taxonomic kingdoms Archaea, Bacteria, Protozoa, Viruses and most microbial species from the kingdom Fungi (see Source), so the input can be almost anything: a full name (like &quot;Staphylococcus aureus&quot;), an abbreviated name (like &quot;S. aureus&quot;), an abbreviation known in the field (like &quot;MRSA&quot;), or just a genus. You could also select a genus and species column, zie Examples." />
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<h1>Transform to microorganism ID</h1>
<div class="hidden name"><code>as.mo.Rd</code></div>
</div>
<div class="ref-description">
<p>Use this function to determine a valid microorganism ID (<code>mo</code>). Determination is done using Artificial Intelligence (AI) and the complete taxonomic kingdoms Archaea, Bacteria, Protozoa, Viruses and most microbial species from the kingdom Fungi (see Source), so the input can be almost anything: a full name (like <code>"Staphylococcus aureus"</code>), an abbreviated name (like <code>"S. aureus"</code>), an abbreviation known in the field (like <code>"MRSA"</code>), or just a genus. You could also <code>select</code> a genus and species column, zie Examples.</p>
</div>
<pre class="usage"><span class='fu'>as.mo</span>(<span class='no'>x</span>, <span class='kw'>Becker</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>Lancefield</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>allow_uncertain</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
<span class='kw'>reference_df</span> <span class='kw'>=</span> <span class='fu'><a href='mo_source.html'>get_mo_source</a></span>())
<span class='fu'>is.mo</span>(<span class='no'>x</span>)
<span class='fu'>mo_failures</span>()
<span class='fu'>mo_uncertainties</span>()
<span class='fu'>mo_renamed</span>()</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>x</th>
<td><p>a character vector or a <code>data.frame</code> with one or two columns</p></td>
</tr>
<tr>
<th>Becker</th>
<td><p>a logical to indicate whether <em>Staphylococci</em> should be categorised into Coagulase Negative <em>Staphylococci</em> ("CoNS") and Coagulase Positive <em>Staphylococci</em> ("CoPS") instead of their own species, according to Karsten Becker <em>et al.</em> [1].</p>
<p>This excludes <em>Staphylococcus aureus</em> at default, use <code>Becker = "all"</code> to also categorise <em>S. aureus</em> as "CoPS".</p></td>
</tr>
<tr>
<th>Lancefield</th>
<td><p>a logical to indicate whether beta-haemolytic <em>Streptococci</em> should be categorised into Lancefield groups instead of their own species, according to Rebecca C. Lancefield [2]. These <em>Streptococci</em> will be categorised in their first group, e.g. <em>Streptococcus dysgalactiae</em> will be group C, although officially it was also categorised into groups G and L.</p>
<p>This excludes <em>Enterococci</em> at default (who are in group D), use <code>Lancefield = "all"</code> to also categorise all <em>Enterococci</em> as group D.</p></td>
</tr>
<tr>
<th>allow_uncertain</th>
<td><p>a logical to indicate whether the input should be checked for less possible results, see Details</p></td>
</tr>
<tr>
<th>reference_df</th>
<td><p>a <code>data.frame</code> to use for extra reference when translating <code>x</code> to a valid <code>mo</code>. See <code><a href='mo_source.html'>set_mo_source</a></code> and <code><a href='mo_source.html'>get_mo_source</a></code> to automate the usage of your own codes (e.g. used in your analysis or organisation).</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>Character (vector) with class <code>"mo"</code>. Unknown values will return <code>NA</code>.</p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>A microbial ID from this package (class: <code>mo</code>) typically looks like these examples:<br /></p><pre>
Code Full name
--------------- --------------------------------------
B_KLBSL Klebsiella
B_KLBSL_PNE Klebsiella pneumoniae
B_KLBSL_PNE_RHI Klebsiella pneumoniae rhinoscleromatis
| | | |
| | | |
| | | ----&gt; subspecies, a 3-4 letter acronym
| | ----&gt; species, a 3-4 letter acronym
| ----&gt; genus, a 5-7 letter acronym, mostly without vowels
----&gt; taxonomic kingdom: A (Archaea), AN (Animalia), B (Bacteria), C (Chromista),
F (Fungi), P (Protozoa), PL (Plantae) or V (Viruses)
</pre>
<p>Values that cannot be coered will be considered 'unknown' and have an MO code <code>UNKNOWN</code>.</p>
<p>Use the <code><a href='mo_property.html'>mo_property</a></code> functions to get properties based on the returned code, see Examples.</p>
<p><strong>Artificial Intelligence</strong> <br />
This function uses Artificial Intelligence (AI) to help getting fast and logical results. It tries to find matches in this order:</p><ul>
<li><p>Taxonomic kingdom: it first searches in Bacteria, then Fungi, then Protozoa</p></li>
<li><p>Human pathogenic prevalence: it first searches in more prevalent microorganisms, then less prevalent ones (see section <em>Microbial prevalence of pathogens in humans</em>)</p></li>
<li><p>Valid MO codes and full names: it first searches in already valid MO code and known genus/species combinations</p></li>
<li><p>Breakdown of input values: from here it starts to breakdown input values to find possible matches</p></li>
</ul>
<p>A couple of effects because of these rules:</p><ul>
<li><p><code>"E. coli"</code> will return the ID of <em>Escherichia coli</em> and not <em>Entamoeba coli</em>, although the latter would alphabetically come first</p></li>
<li><p><code>"H. influenzae"</code> will return the ID of <em>Haemophilus influenzae</em> and not <em>Haematobacter influenzae</em> for the same reason</p></li>
<li><p>Something like <code>"stau"</code> or <code>"S aur"</code> will return the ID of <em>Staphylococcus aureus</em> and not <em>Staphylococcus auricularis</em></p></li>
</ul><p>This means that looking up human pathogenic microorganisms takes less time than looking up human non-pathogenic microorganisms.</p>
<p><strong>Uncertain results</strong> <br />
When using <code>allow_uncertain = TRUE</code> (which is the default setting), it will use additional rules if all previous AI rules failed to get valid results. These are:</p><ul>
<li><p>It tries to look for previously accepted (but now invalid) taxonomic names</p></li>
<li><p>It strips off values between brackets and the brackets itself, and re-evaluates the input with all previous rules</p></li>
<li><p>It strips off words from the end one by one and re-evaluates the input with all previous rules</p></li>
<li><p>It strips off words from the start one by one and re-evaluates the input with all previous rules</p></li>
<li><p>It tries to look for some manual changes which are not (yet) published to the Catalogue of Life (like <em>Propionibacterium</em> being <em>Cutibacterium</em>)</p></li>
</ul>
<p>Examples:</p><ul>
<li><p><code>"Streptococcus group B (known as S. agalactiae)"</code>. The text between brackets will be removed and a warning will be thrown that the result <em>Streptococcus group B</em> (<code>B_STRPT_GRB</code>) needs review.</p></li>
<li><p><code>"S. aureus - please mind: MRSA"</code>. The last word will be stripped, after which the function will try to find a match. If it does not, the second last word will be stripped, etc. Again, a warning will be thrown that the result <em>Staphylococcus aureus</em> (<code>B_STPHY_AUR</code>) needs review.</p></li>
<li><p><code>"Fluoroquinolone-resistant Neisseria gonorrhoeae"</code>. The first word will be stripped, after which the function will try to find a match. A warning will be thrown that the result <em>Neisseria gonorrhoeae</em> (<code>B_NESSR_GON</code>) needs review.</p></li>
</ul>
<p>Use <code>mo_failures()</code> to get a vector with all values that could not be coerced to a valid value.</p>
<p>Use <code>mo_uncertainties()</code> to get a data.frame with all values that were coerced to a valid value, but with uncertainty.</p>
<p>Use <code>mo_renamed()</code> to get a vector with all values that could be coerced based on an old, previously accepted taxonomic name.</p>
<p><strong>Microbial prevalence of pathogens in humans</strong> <br />
The artificial intelligence takes into account microbial prevalence of pathogens in humans. It uses three groups and every (sub)species is in the group it matches first. These groups are:</p><ul>
<li><p>1 (most prevalent): class is Gammaproteobacteria <strong>or</strong> genus is one of: <em>Enterococcus</em>, <em>Staphylococcus</em>, <em>Streptococcus</em>.</p></li>
<li><p>2: phylum is one of: Proteobacteria, Firmicutes, Actinobacteria, Sarcomastigophora <strong>or</strong> genus is one of: <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>, <em>Ureaplasma</em>.</p></li>
<li><p>3 (least prevalent): all others.</p></li>
</ul>
<p>Group 1 contains all common Gram negatives, like all Enterobacteriaceae and e.g. <em>Pseudomonas</em> and <em>Legionella</em>.</p>
<p>Group 2 probably contains all other microbial pathogens ever found in humans.</p>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<p>[1] Becker K <em>et al.</em> <strong>Coagulase-Negative Staphylococci</strong>. 2014. Clin Microbiol Rev. 27(4): 870–926. <a href='https://dx.doi.org/10.1128/CMR.00109-13'>https://dx.doi.org/10.1128/CMR.00109-13</a></p>
<p>[2] Lancefield RC <strong>A serological differentiation of human and other groups of hemolytic streptococci</strong>. 1933. J Exp Med. 57(4): 571–95. <a href='https://dx.doi.org/10.1084/jem.57.4.571'>https://dx.doi.org/10.1084/jem.57.4.571</a></p>
<p>[3] Catalogue of Life: Annual Checklist (public online taxonomic database), <a href='www.catalogueoflife.org'>www.catalogueoflife.org</a> (check included annual version with <code><a href='catalogue_of_life_version.html'>catalogue_of_life_version</a>()</code>).</p>
<h2 class="hasAnchor" id="catalogue-of-life"><a class="anchor" href="#catalogue-of-life"></a>Catalogue of Life</h2>
<p><img src='figures/logo_col.png' height=40px style=margin-bottom:5px /> <br />
This package contains the complete taxonomic tree of almost all microorganisms (~60,000 species) from the authoritative and comprehensive Catalogue of Life (<a href='http://www.catalogueoflife.org'>http://www.catalogueoflife.org</a>). The Catalogue of Life is the most comprehensive and authoritative global index of species currently available.</p>
<p><a href='catalogue_of_life.html'>Click here</a> for more information about the included taxa. The Catalogue of Life releases updates annually; check which version was included in this package with <code><a href='catalogue_of_life_version.html'>catalogue_of_life_version</a>()</code>.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a comprehensive tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='microorganisms.html'>microorganisms</a></code> for the <code>data.frame</code> that is being used to determine ID's. <br />
The <code><a href='mo_property.html'>mo_property</a></code> functions (like <code><a href='mo_property.html'>mo_genus</a></code>, <code><a href='mo_property.html'>mo_gramstain</a></code>) to get properties based on the returned code.</p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<span class='co'># These examples all return "B_STPHY_AUR", the ID of S. aureus:</span>
<span class='fu'>as.mo</span>(<span class='st'>"stau"</span>)
<span class='fu'>as.mo</span>(<span class='st'>"STAU"</span>)
<span class='fu'>as.mo</span>(<span class='st'>"staaur"</span>)
<span class='fu'>as.mo</span>(<span class='st'>"S. aureus"</span>)
<span class='fu'>as.mo</span>(<span class='st'>"S aureus"</span>)
<span class='fu'>as.mo</span>(<span class='st'>"Staphylococcus aureus"</span>)
<span class='fu'>as.mo</span>(<span class='st'>"Staphylococcus aureus (MRSA)"</span>)
<span class='fu'>as.mo</span>(<span class='st'>"MRSA"</span>) <span class='co'># Methicillin Resistant S. aureus</span>
<span class='fu'>as.mo</span>(<span class='st'>"VISA"</span>) <span class='co'># Vancomycin Intermediate S. aureus</span>
<span class='fu'>as.mo</span>(<span class='st'>"VRSA"</span>) <span class='co'># Vancomycin Resistant S. aureus</span>
<span class='fu'>as.mo</span>(<span class='st'>"Streptococcus group A"</span>)
<span class='fu'>as.mo</span>(<span class='st'>"GAS"</span>) <span class='co'># Group A Streptococci</span>
<span class='fu'>as.mo</span>(<span class='st'>"GBS"</span>) <span class='co'># Group B Streptococci</span>
<span class='fu'>as.mo</span>(<span class='st'>"S. epidermidis"</span>) <span class='co'># will remain species: B_STPHY_EPI</span>
<span class='fu'>as.mo</span>(<span class='st'>"S. epidermidis"</span>, <span class='kw'>Becker</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) <span class='co'># will not remain species: B_STPHY_CNS</span>
<span class='fu'>as.mo</span>(<span class='st'>"S. pyogenes"</span>) <span class='co'># will remain species: B_STRPT_PYO</span>
<span class='fu'>as.mo</span>(<span class='st'>"S. pyogenes"</span>, <span class='kw'>Lancefield</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) <span class='co'># will not remain species: B_STRPT_GRA</span>
<span class='co'># Use mo_* functions to get a specific property based on `mo`</span>
<span class='no'>Ecoli</span> <span class='kw'>&lt;-</span> <span class='fu'>as.mo</span>(<span class='st'>"E. coli"</span>) <span class='co'># returns `B_ESCHR_COL`</span>
<span class='fu'><a href='mo_property.html'>mo_genus</a></span>(<span class='no'>Ecoli</span>) <span class='co'># returns "Escherichia"</span>
<span class='fu'><a href='mo_property.html'>mo_gramstain</a></span>(<span class='no'>Ecoli</span>) <span class='co'># returns "Gram negative"</span>
<span class='co'># but it uses as.mo internally too, so you could also just use:</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='co'># }</span><span class='co'># NOT RUN {</span>
<span class='no'>df</span>$<span class='no'>mo</span> <span class='kw'>&lt;-</span> <span class='fu'>as.mo</span>(<span class='no'>df</span>$<span class='no'>microorganism_name</span>)
<span class='co'># the select function of tidyverse is also supported:</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
<span class='no'>df</span>$<span class='no'>mo</span> <span class='kw'>&lt;-</span> <span class='no'>df</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>microorganism_name</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>as.mo</span>()
<span class='co'># and can even contain 2 columns, which is convenient for genus/species combinations:</span>
<span class='no'>df</span>$<span class='no'>mo</span> <span class='kw'>&lt;-</span> <span class='no'>df</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>genus</span>, <span class='no'>species</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>as.mo</span>()
<span class='co'># although this works easier and does the same:</span>
<span class='no'>df</span> <span class='kw'>&lt;-</span> <span class='no'>df</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='kw'>mo</span> <span class='kw'>=</span> <span class='fu'>as.mo</span>(<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/paste'>paste</a></span>(<span class='no'>genus</span>, <span class='no'>species</span>)))
<span class='co'># }</span></pre>
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