<metaproperty="og:description"content="Use this function to determine a valid microorganism ID (mo). Determination is done using intelligent rules and the complete taxonomic kingdoms Bacteria, Chromista, Protozoa, Archaea and most microbial species from the kingdom Fungi (see Source). The input can be almost anything: a full name (like "Staphylococcus aureus"), an abbreviated name (like "S. aureus"), an abbreviation known in the field (like "MRSA"), or just a genus. Please see Examples."/>
<p>Use this function to determine a valid microorganism ID (<code>mo</code>). Determination is done using intelligent rules and the complete taxonomic kingdoms Bacteria, Chromista, Protozoa, Archaea and most microbial species from the kingdom Fungi (see Source). 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. Please see Examples.</p>
<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> [1,2]. Note that this does not include species that were newly named after these publications, like <em>S. caeli</em>.</p>
<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 [3]. 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>
<td><p>a logical (<code>TRUE</code> or <code>FALSE</code>) or a value between 0 and 3 to indicate whether the input should be checked for less possible results, see Details</p></td>
<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><ahref='mo_source.html'>set_mo_source</a></code> and <code><ahref='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>
<p>The algorithm uses data from the Catalogue of Life (see below) and from one other source (see <code><ahref='microorganisms.html'>?microorganisms</a></code>).</p>
<li><p>Human pathogenic prevalence: it first searches in more prevalent microorganisms, then less prevalent ones (see <em>Microbial prevalence of pathogens in humans</em> below)</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>
The algorithm can additionally use three different levels of uncertainty to guess valid results. The default is <code>allow_uncertain = TRUE</code>, which is equal to uncertainty level 2. Using <code>allow_uncertain = FALSE</code> will skip all of these additional rules:</p><ul>
<li><p>(uncertainty level 1): It tries to look for only matching genera</p></li>
<li><p>(uncertainty level 1): It tries to look for previously accepted (but now invalid) taxonomic names</p></li>
<li><p>(uncertainty level 2): It strips off values between brackets and the brackets itself, and re-evaluates the input with all previous rules</p></li>
<li><p>(uncertainty level 2): It strips off words from the end one by one and re-evaluates the input with all previous rules</p></li>
<li><p>(uncertainty level 3): It strips off words from the start one by one and re-evaluates the input with all previous rules</p></li>
<li><p>(uncertainty level 3): It tries any part of the name</p></li>
<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>
The intelligent rules take into account microbial prevalence of pathogens in humans. It uses three groups and all (sub)species are in only one group. 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>
<p>Group 1 contains all common Gram positives and Gram negatives, like all Enterobacteriaceae and e.g. <em>Pseudomonas</em> and <em>Legionella</em>.</p>
<p>Group 2 probably contains less microbial pathogens; all other members of phyla that were found in humans in the Northern Netherlands between 2001 and 2018.</p>
<p>[2] Becker K <em>et al.</em><strong>Implications of identifying the recently defined members of the <em>S. aureus</em> complex, <em>S. argenteus</em> and <em>S. schweitzeri</em>: A position paper of members of the ESCMID Study Group for staphylococci and Staphylococcal Diseases (ESGS).</strong> 2019. Clin Microbiol Infect. <ahref='https://doi.org/10.1016/j.cmi.2019.02.028'>https://doi.org/10.1016/j.cmi.2019.02.028</a></p>
<p>[3] Lancefield RC <strong>A serological differentiation of human and other groups of hemolytic streptococci</strong>. 1933. J Exp Med. 57(4): 571–95. <ahref='https://dx.doi.org/10.1084/jem.57.4.571'>https://dx.doi.org/10.1084/jem.57.4.571</a></p>
<p>[4] Catalogue of Life: Annual Checklist (public online taxonomic database), <ahref='www.catalogueoflife.org'>www.catalogueoflife.org</a> (check included annual version with <code><ahref='catalogue_of_life_version.html'>catalogue_of_life_version</a>()</code>).</p>
This package contains the complete taxonomic tree of almost all microorganisms (~65,000 species) from the authoritative and comprehensive Catalogue of Life (<ahref='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><ahref='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><ahref='catalogue_of_life_version.html'>catalogue_of_life_version</a>()</code>.</p>
<p>On our website <ahref='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <ahref='https://msberends.gitlab.io/AMR/articles/AMR.html'>a comprehensive tutorial</a> about how to conduct AMR analysis, the <ahref='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <ahref='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<divclass='dont-index'><p><code><ahref='microorganisms.html'>microorganisms</a></code> for the <code>data.frame</code> that is being used to determine ID's. <br/>
The <code><ahref='mo_property.html'>mo_property</a></code> functions (like <code><ahref='mo_property.html'>mo_genus</a></code>, <code><ahref='mo_property.html'>mo_gramstain</a></code>) to get properties based on the returned code.</p></div>
<spanclass='fu'>as.mo</span>(<spanclass='st'>"S. epidermidis"</span>) <spanclass='co'># will remain species: B_STPHY_EPI</span>
<spanclass='fu'>as.mo</span>(<spanclass='st'>"S. epidermidis"</span>, <spanclass='kw'>Becker</span><spanclass='kw'>=</span><spanclass='fl'>TRUE</span>) <spanclass='co'># will not remain species: B_STPHY_CNS</span>
<spanclass='fu'>as.mo</span>(<spanclass='st'>"S. pyogenes"</span>) <spanclass='co'># will remain species: B_STRPT_PYO</span>
<spanclass='fu'>as.mo</span>(<spanclass='st'>"S. pyogenes"</span>, <spanclass='kw'>Lancefield</span><spanclass='kw'>=</span><spanclass='fl'>TRUE</span>) <spanclass='co'># will not remain species: B_STRPT_GRA</span>
<p>Developed by <ahref='https://www.rug.nl/staff/m.s.berends/'>Matthijs S. Berends</a>, <ahref='https://www.rug.nl/staff/c.f.luz/'>Christian F. Luz</a>, <ahref='https://www.rug.nl/staff/c.glasner/'>Corinna Glasner</a>, <ahref='https://www.rug.nl/staff/a.w.friedrich/'>Alex W. Friedrich</a>, <ahref='https://www.rug.nl/staff/b.sinha/'>Bhanu N. M. Sinha</a>.</p>
