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<a class="navbar-brand me-2" href="https://msberends.github.io/AMR/index.html">AMR (for R)</a>
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index.html
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news/index.html
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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@@ -159,18 +159,18 @@
</div>
<div class="section level2">
<h2 class="pkg-version" data-toc-text="2.1.1.9058" id="amr-2119058">AMR 2.1.1.9058<a class="anchor" aria-label="anchor" href="#amr-2119058"></a></h2>
<h2 class="pkg-version" data-toc-text="2.1.1.9059" id="amr-2119059">AMR 2.1.1.9059<a class="anchor" aria-label="anchor" href="#amr-2119059"></a></h2>
<p><em>(this beta version will eventually become v3.0. We’re happy to reach a new major milestone soon, which will be all about the new One Health support! Install this beta using <a href="https://msberends.github.io/AMR/#latest-development-version">the instructions here</a>.)</em></p>
<div class="section level5">
<h5 id="a-new-milestone-one-health-support--human--veterinary--environmental-2-1-1-9058">A New Milestone: One Health Support (= Human + Veterinary + Environmental)<a class="anchor" aria-label="anchor" href="#a-new-milestone-one-health-support--human--veterinary--environmental-2-1-1-9058"></a></h5>
<h5 id="a-new-milestone-amr-v30-with-one-health-support--human--veterinary--environmental-2-1-1-9059">A New Milestone: AMR v3.0 with One Health Support (= Human + Veterinary + Environmental)<a class="anchor" aria-label="anchor" href="#a-new-milestone-amr-v30-with-one-health-support--human--veterinary--environmental-2-1-1-9059"></a></h5>
<p>This package now supports not only tools for AMR data analysis in clinical settings, but also for veterinary and environmental microbiology. This was made possible through a collaboration with the <a href="https://www.upei.ca/avc" class="external-link">University of Prince Edward Island</a>, Canada. To celebrate this great improvement of the package, we also updated the package logo to reflect this change.</p>
</div>
<div class="section level3">
<h3 id="breaking-2-1-1-9058">Breaking<a class="anchor" aria-label="anchor" href="#breaking-2-1-1-9058"></a></h3>
<h3 id="breaking-2-1-1-9059">Breaking<a class="anchor" aria-label="anchor" href="#breaking-2-1-1-9059"></a></h3>
<ul><li>Removed all functions and references that used the deprecated <code>rsi</code> class, which were all replaced with their <code>sir</code> equivalents over a year ago</li>
</ul></div>
<div class="section level3">
<h3 id="new-2-1-1-9058">New<a class="anchor" aria-label="anchor" href="#new-2-1-1-9058"></a></h3>
<h3 id="new-2-1-1-9059">New<a class="anchor" aria-label="anchor" href="#new-2-1-1-9059"></a></h3>
<ul><li>One Health implementation
<ul><li>Function <code><a href="../reference/as.sir.html">as.sir()</a></code> now has extensive support for animal breakpoints from CLSI. Use <code>breakpoint_type = "animal"</code> and set the <code>host</code> argument to a variable that contains animal species names.</li>
<li>The <code>clinical_breakpoints</code> data set contains all these breakpoints, and can be downloaded on our <a href="https://msberends.github.io/AMR/articles/datasets.html">download page</a>.</li>
@@ -180,15 +180,15 @@
<li>
<code><a href="../reference/ab_property.html">ab_url()</a></code> now supports retrieving the WHOCC url of their ATCvet pages</li>
</ul></li>
<li>EUCAST 2024 and CLSI 2024 are now supported, by adding all of their over 4,000 clinical breakpoints to the <code>clinical_breakpoints</code> data set for usage in <code><a href="../reference/as.sir.html">as.sir()</a></code>. EUCAST 2024 (v14.0) is now the new default guideline for all MIC and disks diffusion interpretations.</li>
<li>EUCAST 2024 and CLSI 2024 are now supported, by adding all of their over 4,000 new clinical breakpoints to the <code>clinical_breakpoints</code> data set for usage in <code><a href="../reference/as.sir.html">as.sir()</a></code>. EUCAST 2024 (v14.0) is now the new default guideline for all MIC and disks diffusion interpretations.</li>
<li>
<code><a href="../reference/as.sir.html">as.sir()</a></code> now brings additional factor levels: “NI” for non-interpretable and “SDD” for susceptible dose-dependent. Users can now set their own criteria (using regular expressions) as to what should be considered S, I, R, SDD, and NI. Also, to get quantitative values, <code><a href="https://rdrr.io/r/base/double.html" class="external-link">as.double()</a></code> or a <code>sir</code> object will return 1 for S, 2 for SDD/I, and 3 for R (NI will become <code>NA</code>). Other functions using <code>sir</code> classes (e.g., <code><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary()</a></code>) are updated to reflect the change to contain NI and SDD.</li>
<code><a href="../reference/as.sir.html">as.sir()</a></code> now brings additional factor levels: “NI” for non-interpretable and “SDD” for susceptible dose-dependent. Users can now set their own criteria (using regular expressions) as to what should be considered S, I, R, SDD, and NI. Also, to get quantitative values, <code><a href="https://rdrr.io/r/base/double.html" class="external-link">as.double()</a></code> on a <code>sir</code> object will return 1 for S, 2 for SDD/I, and 3 for R (NI will become <code>NA</code>). Other functions using <code>sir</code> classes (e.g., <code><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary()</a></code>) are updated to reflect the change to contain NI and SDD.</li>
<li>The function group <code>scale_*_mic()</code>, namely: <code><a href="../reference/plot.html">scale_x_mic()</a></code>, <code><a href="../reference/plot.html">scale_y_mic()</a></code>, <code><a href="../reference/plot.html">scale_colour_mic()</a></code> and <code><a href="../reference/plot.html">scale_fill_mic()</a></code>. They are advanced ggplot2 extensions to allow easy plotting of MIC values. They allow for manual range definition and plotting missing intermediate log2 levels.</li>
<li>Function <code><a href="../reference/as.mic.html">rescale_mic()</a></code>, which allows to rescale MIC values to a manually set range. This is the powerhouse behind the <code>scale_*_mic()</code> functions, but it can be used by users directly to e.g. compare equality in MIC distributions by rescaling them to the same range first.</li>
<li>Function <code><a href="../reference/mo_property.html">mo_group_members()</a></code> to retrieve the member microorganisms of a microorganism group. For example, <code>mo_group_members("Strep group C")</code> returns a vector of all microorganisms that are in that group.</li>
</ul></div>
<div class="section level3">
<h3 id="changed-2-1-1-9058">Changed<a class="anchor" aria-label="anchor" href="#changed-2-1-1-9058"></a></h3>
<h3 id="changed-2-1-1-9059">Changed<a class="anchor" aria-label="anchor" href="#changed-2-1-1-9059"></a></h3>
<ul><li>For SIR interpretation, it is now possible to use column names for argument <code>ab</code>, <code>mo</code>, and <code>uti</code>: <code>as.sir(..., ab = "column1", mo = "column2", uti = "column3")</code>. This greatly improves the flexibility for users.</li>
<li>Extended the antibiotic selectors with <code><a href="../reference/antibiotic_class_selectors.html">nitrofurans()</a></code> and <code><a href="../reference/antibiotic_class_selectors.html">rifamycins()</a></code>
</li>
@@ -221,7 +221,7 @@
<li>Intermediate log2 levels used for MIC plotting are now more common values instead of following a strict dilution range</li>
</ul></div>
<div class="section level3">
<h3 id="other-2-1-1-9058">Other<a class="anchor" aria-label="anchor" href="#other-2-1-1-9058"></a></h3>
<h3 id="other-2-1-1-9059">Other<a class="anchor" aria-label="anchor" href="#other-2-1-1-9059"></a></h3>
<ul><li>Added Jordan Stull, Matthew Saab, and Javier Sanchez as contributors, to thank them for their valuable input</li>
</ul></div>
</div>
pkgdown.yml
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resistance_predict: resistance_predict.html
welcome_to_AMR: welcome_to_AMR.html
WHONET: WHONET.html
last_built: 2024-06-17T20:22Z
last_built: 2024-06-17T20:29Z
urls:
reference: https://msberends.github.io/AMR/reference
article: https://msberends.github.io/AMR/articles
reference/AMR-options.html
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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reference/AMR.html
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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reference/WHOCC.html
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reference/ab_from_text.html
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reference/ab_property.html
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reference/add_custom_antimicrobials.html
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reference/add_custom_microorganisms.html
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reference/age.html
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reference/age_groups.html
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reference/antibiogram.html
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reference/antibiotic_class_selectors.html
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@@ -12,7 +12,7 @@ In short, if you have a column name that resembles an antimicrobial drug, it wil
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reference/antibiotics.html
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@@ -10,7 +10,7 @@
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@@ -10,7 +10,7 @@
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reference/as.sir.html
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@@ -24,7 +24,7 @@ All breakpoints used for interpretation are available in our clinical_breakpoint
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@@ -263,7 +263,7 @@ All breakpoints used for interpretation are available in our clinical_breakpoint
<li><p><strong>CLSI M100: Performance Standard for Antimicrobial Susceptibility Testing</strong>, 2011-2024, <em>Clinical and Laboratory Standards Institute</em> (CLSI). <a href="https://clsi.org/standards/products/microbiology/documents/m100/" class="external-link">https://clsi.org/standards/products/microbiology/documents/m100/</a>.</p></li>
<li><p><strong>CLSI VET01: Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals</strong>, 2019-2024, <em>Clinical and Laboratory Standards Institute</em> (CLSI). <a href="https://clsi.org/standards/products/veterinary-medicine/documents/vet01//" class="external-link">https://clsi.org/standards/products/veterinary-medicine/documents/vet01//</a>.</p></li>
<li><p><strong>EUCAST Breakpoint tables for interpretation of MICs and zone diameters</strong>, 2011-2024, <em>European Committee on Antimicrobial Susceptibility Testing</em> (EUCAST). <a href="https://www.eucast.org/clinical_breakpoints" class="external-link">https://www.eucast.org/clinical_breakpoints</a>.</p></li>
<li><p><strong>WHONET</strong> as a source for machine-reading clinical breakpoints ((read more here)https://msberends.github.io/AMR/reference/clinical_breakpoints.html#imported-from-whonet), 1989-2024, <em>WHO Collaborating Centre for Surveillance of Antimicrobial Resistance</em>. <a href="https://whonet.org/" class="external-link">https://whonet.org/</a>.</p></li>
<li><p><strong>WHONET</strong> as a source for machine-reading the clinical breakpoints (<a href="https://msberends.github.io/AMR/reference/clinical_breakpoints.html#imported-from-whonet">read more here</a>), 1989-2024, <em>WHO Collaborating Centre for Surveillance of Antimicrobial Resistance</em>. <a href="https://whonet.org/" class="external-link">https://whonet.org/</a>.</p></li>
</ul></div>
<div class="section level2">
<h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
@@ -866,16 +866,16 @@ A microorganism is categorised as "Resistant" when there is a high likelihood of
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 59 × 16</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> datetime index ab_given mo_given host_given ab mo </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">*</span> <span style="color: #949494; font-style: italic;">&lt;dttm&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;ab&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 2024-06-17 <span style="color: #949494;">20:23:28</span> 4 AMX B_STRPT… human AMX B_STRPT_PNMN </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 2024-06-17 <span style="color: #949494;">20:23:34</span> 4 genta Escheri… human GEN B_[ORD]_ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> 2024-06-17 <span style="color: #949494;">20:23:35</span> 4 genta Escheri… human GEN B_[ORD]_ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 2024-06-17 <span style="color: #949494;">20:23:35</span> 4 genta Escheri… cattle GEN B_[ORD]_ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 2024-06-17 <span style="color: #949494;">20:23:35</span> 4 genta Escheri… cattle GEN B_[ORD]_ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 2024-06-17 <span style="color: #949494;">20:23:28</span> 3 AMX B_STRPT… human AMX B_STRPT_PNMN </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> 2024-06-17 <span style="color: #949494;">20:23:34</span> 3 tobra Escheri… human TOB B_[ORD]_ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> 2024-06-17 <span style="color: #949494;">20:23:35</span> 3 tobra Escheri… human TOB B_[ORD]_ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 2024-06-17 <span style="color: #949494;">20:23:35</span> 3 tobra Escheri… horses TOB B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 2024-06-17 <span style="color: #949494;">20:23:35</span> 3 tobra Escheri… horses TOB B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 2024-06-17 <span style="color: #949494;">20:30:05</span> 4 AMX B_STRPT… human AMX B_STRPT_PNMN </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 2024-06-17 <span style="color: #949494;">20:30:11</span> 4 genta Escheri… human GEN B_[ORD]_ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> 2024-06-17 <span style="color: #949494;">20:30:11</span> 4 genta Escheri… human GEN B_[ORD]_ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 2024-06-17 <span style="color: #949494;">20:30:12</span> 4 genta Escheri… cattle GEN B_[ORD]_ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 2024-06-17 <span style="color: #949494;">20:30:12</span> 4 genta Escheri… cattle GEN B_[ORD]_ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 2024-06-17 <span style="color: #949494;">20:30:05</span> 3 AMX B_STRPT… human AMX B_STRPT_PNMN </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> 2024-06-17 <span style="color: #949494;">20:30:11</span> 3 tobra Escheri… human TOB B_[ORD]_ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> 2024-06-17 <span style="color: #949494;">20:30:11</span> 3 tobra Escheri… human TOB B_[ORD]_ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 2024-06-17 <span style="color: #949494;">20:30:12</span> 3 tobra Escheri… horses TOB B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 2024-06-17 <span style="color: #949494;">20:30:12</span> 3 tobra Escheri… horses TOB B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 49 more rows</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 9 more variables: host &lt;chr&gt;, method &lt;chr&gt;, input &lt;dbl&gt;, outcome &lt;sir&gt;,</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># notes &lt;chr&gt;, guideline &lt;chr&gt;, ref_table &lt;chr&gt;, uti &lt;lgl&gt;,</span></span>
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@@ -12,7 +12,7 @@ count_resistant() should be used to count resistant isolates, count_susceptible(
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[{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"How to conduct AMR data analysis","text":"Conducting AMR data analysis unfortunately requires -depth knowledge different scientific fields, makes hard right. least, requires: Good questions (always start !) reliable data thorough understanding (clinical) epidemiology, understand clinical epidemiological relevance possible bias results thorough understanding (clinical) microbiology/infectious diseases, understand microorganisms causal infections implications pharmaceutical treatment, well understanding intrinsic acquired microbial resistance Experience data analysis microbiological tests results, understand determination limitations MIC values interpretations SIR values Availability biological taxonomy microorganisms probably normalisation factors pharmaceuticals, defined daily doses (DDD) Available (inter-)national guidelines, profound methods apply course, instantly provide knowledge experience. AMR package, aimed providing (1) tools simplify antimicrobial resistance data cleaning, transformation analysis, (2) methods easily incorporate international guidelines (3) scientifically reliable reference data, including requirements mentioned . AMR package enables standardised reproducible AMR data analysis, application evidence-based rules, determination first isolates, translation various codes microorganisms antimicrobial agents, determination (multi-drug) resistant microorganisms, calculation antimicrobial resistance, prevalence future trends.","code":""},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"preparation","dir":"Articles","previous_headings":"","what":"Preparation","title":"How to conduct AMR data analysis","text":"tutorial, create fake demonstration data work . can skip Cleaning data already data ready. start analysis, try make structure data generally look like :","code":""},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"needed-r-packages","dir":"Articles","previous_headings":"Preparation","what":"Needed R packages","title":"How to conduct AMR data analysis","text":"many uses R, need additional packages AMR data analysis. package works closely together tidyverse packages dplyr ggplot2 RStudio. tidyverse tremendously improves way conduct data science - allows natural way writing syntaxes creating beautiful plots R. also use cleaner package, can used cleaning data creating frequency tables. AMR package contains data set example_isolates_unclean, might look data users extracted laboratory systems: AMR data analysis, like microorganism column contain valid, --date taxonomy, antibiotic columns cleaned SIR values well.","code":"library(dplyr) library(ggplot2) library(AMR) # (if not yet installed, install with:) # install.packages(c(\"dplyr\", \"ggplot2\", \"AMR\")) example_isolates_unclean #> # A tibble: 3,000 × 8 #> patient_id hospital date bacteria AMX AMC CIP GEN #> <chr> <chr> <date> <chr> <chr> <chr> <chr> <chr> #> 1 J3 A 2012-11-21 E. coli R I S S #> 2 R7 A 2018-04-03 K. pneumoniae R I S S #> 3 P3 A 2014-09-19 E. coli R S S S #> 4 P10 A 2015-12-10 E. coli S I S S #> 5 B7 A 2015-03-02 E. coli S S S S #> 6 W3 A 2018-03-31 S. aureus R S R S #> 7 J8 A 2016-06-14 E. coli R S S S #> 8 M3 A 2015-10-25 E. coli R S S S #> 9 J3 A 2019-06-19 E. coli S S S S #> 10 G6 A 2015-04-27 S. aureus S S S S #> # ℹ 2,990 more rows # we will use 'our_data' as the data set name for this tutorial our_data <- example_isolates_unclean"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"taxonomy-of-microorganisms","dir":"Articles","previous_headings":"Preparation","what":"Taxonomy of microorganisms","title":"How to conduct AMR data analysis","text":".mo(), users can transform arbitrary microorganism names codes current taxonomy. AMR package contains --date taxonomic data. specific, currently included data retrieved 11 Dec 2022. codes AMR packages come .mo() short, still human readable. importantly, .mo() supports kinds input: first character codes denote taxonomic kingdom, Bacteria (B), Fungi (F), Protozoa (P). AMR package also contain functions directly retrieve taxonomic properties, name, genus, species, family, order, even Gram-stain. start mo_ use .mo() internally, still arbitrary user input can used: Now can thus clean data: Apparently, uncertainty translation taxonomic codes. Let’s check : ’s good.","code":"as.mo(\"Klebsiella pneumoniae\") #> Class 'mo' #> [1] B_KLBSL_PNMN as.mo(\"K. pneumoniae\") #> ClaLine truncated
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