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<meta property="og:description" content="This helper function is used by as.mo() to determine the most probable match of taxonomic records, based on user input." />
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<h1>Calculate the matching score for microorganisms</h1>
<small class="dont-index">Source: <a href='https://github.com/msberends/AMR/blob/master/R/mo_matching_score.R'><code>R/mo_matching_score.R</code></a></small>
<div class="hidden name"><code>mo_matching_score.Rd</code></div>
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<div class="ref-description">
<p>This helper function is used by <code><a href='as.mo.html'>as.mo()</a></code> to determine the most probable match of taxonomic records, based on user input.</p>
</div>
<pre class="usage"><span class='fu'>mo_matching_score</span>(<span class='kw'>x</span>, <span class='kw'>fullname</span>, uncertainty = <span class='fl'>1</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>Any user input value(s)</p></td>
</tr>
<tr>
<th>fullname</th>
<td><p>A full taxonomic name, that exists in <code><a href='microorganisms.html'>microorganisms$fullname</a></code></p></td>
</tr>
<tr>
<th>uncertainty</th>
<td><p>The level of uncertainty set in <code><a href='as.mo.html'>as.mo()</a></code>, see <code>allow_uncertain</code> in that function (here, it defaults to 1, but is automatically determined in <code><a href='as.mo.html'>as.mo()</a></code> based on the number of transformations needed to get to a result)</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>The matching score is based on four parameters:</p><ol>
<li><p>A human pathogenic prevalence \(P\), that is categorised into group 1, 2 and 3 (see <code><a href='as.mo.html'>as.mo()</a></code>);</p></li>
<li><p>A kingdom index \(K\) is set as follows: Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, and all others = 5;</p></li>
<li><p>The level of uncertainty \(U\) that is needed to get to a result (1 to 3, see <code><a href='as.mo.html'>as.mo()</a></code>);</p></li>
<li><p>The <a href='https://en.wikipedia.org/wiki/Levenshtein_distance'>Levenshtein distance</a> \(L\) is the distance between the user input and all taxonomic full names, with the text length of the user input being the maximum distance. A modified version of the Levenshtein distance \(L'\) based on the text length of the full name \(F\) is calculated as:</p></li>
</ol>
<p>$$L' = 1 - \frac{0.5L}{F}$$</p>
<p>The final matching score \(M\) is calculated as:
$$M = L' \times \frac{1}{P K U} = \frac{F - 0.5L}{F P K U}$$</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>()
</pre>
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