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(v0.7.1.9081) bug_drug fixes

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dr. M.S. (Matthijs) Berends
2019-09-23 13:53:50 +02:00
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docs/reference/as.mo.html
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</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">0.7.1.9079</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9081</span>
</span>
</div>
@ -305,41 +305,35 @@ A microorganism ID from this package (class: <code>mo</code>) typically looks li
<p><strong>Self-learning algoritm</strong> <br />
The <code>as.mo()</code> function gains experience from previously determined microorganism IDs and learns from it. This drastically improves both speed and reliability. Use <code>clear_mo_history()</code> to reset the algorithms. Only experience from your current <code>AMR</code> package version is used. This is done because in the future the taxonomic tree (which is included in this package) may change for any organism and it consequently has to rebuild its knowledge.</p>
<p>Usually, any guess after the first try runs 80-95% faster than the first try.</p>
<p><strong>Intelligent rules</strong> <br />
This function uses intelligent rules to help getting fast and logical results. It tries to find matches in this order:</p><ul>
<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>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>Taxonomic kingdom: it first searches in Bacteria, then Fungi, then Protozoa, then Archaea, then others</p></li>
<li><p>Breakdown of input values: from here it starts to breakdown input values to find possible matches</p></li>
<p>This resets with every update of this <code>AMR</code> package since results are saved to your local package library folder.</p>
<p><strong>Intelligent rules</strong> <br />
The <code>as.mo()</code> function uses several coercion rules for fast and logical results. It assesses the input matching criteria in the following order:</p><ul>
<li><p>Human pathogenic prevalence: the function starts with more prevalent microorganisms, followed by less prevalent ones;</p></li>
<li><p>Taxonomic kingdom: the function starts with determining Bacteria, then Fungi, then Protozoa, then others;</p></li>
<li><p>Breakdown of input values to identify 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 />
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, previously accepted (but now invalid) taxonomic names and misspelled input</p></li>
<li><p>(uncertainty level 2): It removed parts between brackets, 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 tries any part of the name</p></li>
<p>This will lead to the effect that e.g. <code>"E. coli"</code> (a highly prevalent microorganism found in humans) will return the microbial ID of <em>Escherichia coli</em> and not <em>Entamoeba coli</em> (a less prevalent microorganism in humans), although the latter would alphabetically come first. In addition, the <code>as.mo()</code> function can differentiate four levels of uncertainty to guess valid results:</p>
<ul>
<li><p>Uncertainty level 0: no additional rules are applied;</p></li>
<li><p>Uncertainty level 1: allow previously accepted (but now invalid) taxonomic names and minor spelling errors;</p></li>
<li><p>Uncertainty level 2: allow all of level 1, strip values between brackets, inverse the words of the input, strip off text elements from the end keeping at least two elements;</p></li>
<li><p>Uncertainty level 3: allow all of level 1 and 2, strip off text elements from the end, allow any part of a taxonomic name.</p></li>
</ul>
<p>You can also use e.g. <code>as.mo(..., allow_uncertain = 1)</code> to only allow up to level 1 uncertainty.</p>
<p>Examples:</p><ul>
<p>This leads to e.g.:</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_GRPB</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>
<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_AURS</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_GNRR</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 data.frame with all values that could be coerced based on an old, previously accepted taxonomic name.</p>
<p>The level of uncertainty can be set using the argument <code>allow_uncertain</code>. The default is <code>allow_uncertain = TRUE</code>, which is equal to uncertainty level 2. Using <code>allow_uncertain = FALSE</code> is equal to uncertainty level 0 and will skip all rules. You can also use e.g. <code>as.mo(..., allow_uncertain = 1)</code> to only allow up to level 1 uncertainty.</p>
<p>Use <code>mo_failures()</code> to get a vector with all values that could not be coerced to a valid value. <br />
Use <code>mo_uncertainties()</code> to get a <code>data.frame</code> with all values that were coerced to a valid value, but with uncertainty. <br />
Use <code>mo_renamed()</code> to get a <code>data.frame</code> 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 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>
<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 positives and Gram negatives, like all Enterobacteriaceae and e.g. <em>Pseudomonas</em> and <em>Legionella</em>.</p>
<p>Group 2 contains probably less pathogenic microorganisms; all other members of phyla that were found in humans in the Northern Netherlands between 2001 and 2018.</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 <code><a href='microorganisms.html'>microorganisms</a></code> and <code><a href='microorganisms.old.html'>microorganisms.old</a></code> 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>Pseudomonas</em> and <em>Legionella</em> and all species within the order Enterobacteriales.</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>.</p>
<p>Group 3 (least prevalent microorganisms) consists of all other microorganisms.</p>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>