<metaproperty="og:title"content="Transform to microorganism ID — as.mo"/>
<metaproperty="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 Bacteria, Fungi and Protozoa (see Source), so 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. You could also select a genus and species column, zie Examples."/>
<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 <em>Bacteria</em>, <em>Fungi</em> and <em>Protozoa</em> (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>
<td><p>a character vector or a <code>data.frame</code> with one or two columns</p></td>
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<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>
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<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>
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<th>allow_uncertain</th>
<td><p>a logical 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>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</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>"p aer"</code> will return the ID of <em>Pseudomonas aeruginosa</em> and not <em>Pasteurella aerogenes</em></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 <strong>non</strong>-pathogenic microorganisms.</p>
<p>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. 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_STRPTC_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>"D. spartina"</code>. This is the abbreviation of an old taxonomic name: <em>Didymosphaeria spartinae</em> (the last "e" was missing from the input). This fungus was renamed to <em>Leptosphaeria obiones</em>, so a warning will be thrown that this result (<code>F_LPTSP_OBI</code>) needs review.</p></li>
<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. <ahref='https://dx.doi.org/10.1084/jem.57.4.571'>https://dx.doi.org/10.1084/jem.57.4.571</a></p>
<p>[3] Integrated Taxonomic Information System (ITIS). Retrieved September 2018. <ahref='http://www.itis.gov'>http://www.itis.gov</a></p>
This package contains the <strong>complete microbial taxonomic data</strong> (with all nine taxonomic ranks - from kingdom to subspecies) from the publicly available Integrated Taxonomic Information System (ITIS, <ahref='https://www.itis.gov'>https://www.itis.gov</a>).</p>
<p>All ~20,000 (sub)species from <strong>the taxonomic kingdoms Bacteria, Fungi and Protozoa are included in this package</strong>, as well as all their ~2,500 previously accepted names known to ITIS. Furthermore, the responsible authors and year of publication are available. This allows users to use authoritative taxonomic information for their data analysis on any microorganism, not only human pathogens. It also helps to quickly determine the Gram stain of bacteria, since ITIS honours the taxonomic branching order of bacterial phyla according to Cavalier-Smith (2002), which defines that all bacteria are classified into either subkingdom Negibacteria or subkingdom Posibacteria.</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> with ITIS content 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_STRPTC_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_STRPTC_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>
