P281424/AMR
1
0 Fork 0
mirror of https://github.com/msberends/AMR.git synced 2026-10-01 04:13:33 +02:00
Code Releases Activity

Built site for AMR@2.1.1.9112: e231352

Browse Source
This commit is contained in:
github-actions committed 2024-12-09 17:48:59 +00:00
1 parent 5def32a932
commit 350e6e4c50
4 files changed
+40 -38
Download Patch File Download Diff File Expand all files Collapse all files

No files matched your search

extra.js
+28 -26
View File
@@ -67,32 +67,34 @@ $(document).ready(function() {
// add country flags // add country flags
function country_flag(x) { function country_flag(x) {
if (typeof(x) != "undefined") { if (typeof(x) != "undefined") {
x = x.replace("Alex", '<img src="lang_de.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Alex'); const prefix = '<img src="lang_';
x = x.replace("Andrew", '<img src="lang_us.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Andrew'); const suffix = '.svg" style="height: 13px !important; border: 1px solid #cccccc; aspect-ratio: 1 / 0.6; object-fit: cover; vertical-align: initial !important;"> ';
x = x.replace("Anita", '<img src="lang_au.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Anita'); x = x.replace("Alex", prefix + "de" + suffix + "Alex");
x = x.replace("Annick", '<img src="lang_nl.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Annick'); x = x.replace("Andrew", prefix + "us" + suffix + "Andrew");
x = x.replace("Anthony", '<img src="lang_en.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Anthony'); x = x.replace("Anita", prefix + "au" + suffix + "Anita");
x = x.replace("Anton", '<img src="lang_uk.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Anton'); x = x.replace("Annick", prefix + "nl" + suffix + "Annick");
x = x.replace("Bart", '<img src="lang_nl.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Bart'); x = x.replace("Anthony", prefix + "en" + suffix + "Anthony");
x = x.replace("Bhanu", '<img src="lang_nl.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Bhanu'); x = x.replace("Anton", prefix + "uk" + suffix + "Anton");
x = x.replace("Casper", '<img src="lang_nl.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Casper'); x = x.replace("Bart", prefix + "nl" + suffix + "Bart");
x = x.replace("Christian", '<img src="lang_de.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Christian'); x = x.replace("Bhanu", prefix + "nl" + suffix + "Bhanu");
x = x.replace("Corinna", '<img src="lang_nl.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Corinna'); x = x.replace("Casper", prefix + "nl" + suffix + "Casper");
x = x.replace("Dennis", '<img src="lang_nl.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Dennis'); x = x.replace("Christian", prefix + "de" + suffix + "Christian");
x = x.replace("Dmytro", '<img src="lang_uk.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Dmytro'); x = x.replace("Corinna", prefix + "nl" + suffix + "Corinna");
x = x.replace("Eric", '<img src="lang_nl.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Eric'); x = x.replace("Dennis", prefix + "nl" + suffix + "Dennis");
x = x.replace("Erwin", '<img src="lang_nl.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Erwin'); x = x.replace("Dmytro", prefix + "uk" + suffix + "Dmytro");
x = x.replace("Gwen", '<img src="lang_en.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Gwen'); x = x.replace("Eric", prefix + "nl" + suffix + "Eric");
x = x.replace("Jason", '<img src="lang_ca.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Jason'); x = x.replace("Erwin", prefix + "nl" + suffix + "Erwin");
x = x.replace("Javier", '<img src="lang_ca.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Javier'); x = x.replace("Gwen", prefix + "en" + suffix + "Gwen");
x = x.replace("Jonas", '<img src="lang_de.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Jonas'); x = x.replace("Jason", prefix + "ca" + suffix + "Jason");
x = x.replace("Judith", '<img src="lang_nl.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Judith'); x = x.replace("Javier", prefix + "ca" + suffix + "Javier");
x = x.replace("Larisse", '<img src="lang_sa.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Larisse'); x = x.replace("Jonas", prefix + "de" + suffix + "Jonas");
x = x.replace("Matthew", '<img src="lang_ca.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Matthew'); x = x.replace("Judith", prefix + "nl" + suffix + "Judith");
x = x.replace("Matthijs", '<img src="lang_nl.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Matthijs'); x = x.replace("Larisse", prefix + "sa" + suffix + "Larisse");
x = x.replace("Peter", '<img src="lang_en.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Peter'); x = x.replace("Matthew", prefix + "ca" + suffix + "Matthew");
x = x.replace("Rogier", '<img src="lang_nl.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Rogier'); x = x.replace("Matthijs", prefix + "nl" + suffix + "Matthijs");
x = x.replace("Sofia", '<img src="lang_sv.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Sofia'); x = x.replace("Peter", prefix + "en" + suffix + "Peter");
x = x.replace("Rogier", prefix + "nl" + suffix + "Rogier");
x = x.replace("Sofia", prefix + "sv" + suffix + "Sofia");
} }
return(x); return(x);
} }
pkgdown.yml
+1 -1
View File
@@ -11,7 +11,7 @@ articles:
resistance_predict: resistance_predict.html resistance_predict: resistance_predict.html
welcome_to_AMR: welcome_to_AMR.html welcome_to_AMR: welcome_to_AMR.html
WHONET: WHONET.html WHONET: WHONET.html
last_built: 2024-12-09T13:46Z last_built: 2024-12-09T17:45Z
urls: urls:
reference: https://msberends.github.io/AMR/reference reference: https://msberends.github.io/AMR/reference
article: https://msberends.github.io/AMR/articles article: https://msberends.github.io/AMR/articles
reference/as.sir.html
+10 -10
View File
@@ -785,16 +785,16 @@ 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: 57 × 16</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 57 × 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> 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;">*</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> 2024-12-09 <span style="color: #949494;">13:47:36</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;"> 1</span> 2024-12-09 <span style="color: #949494;">17:46:26</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> 2024-12-09 <span style="color: #949494;">13:47:43</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;"> 2</span> 2024-12-09 <span style="color: #949494;">17:46:32</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> 2024-12-09 <span style="color: #949494;">13:47:43</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> 2024-12-09 <span style="color: #949494;">17:46:33</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> 2024-12-09 <span style="color: #949494;">13:47:44</span> 4 genta Escheri… cattle GEN B_ESCHR_COLI </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 2024-12-09 <span style="color: #949494;">17:46:33</span> 4 genta Escheri… cattle GEN B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 2024-12-09 <span style="color: #949494;">13:47:44</span> 4 genta Escheri… cattle GEN B_ESCHR_COLI </span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 2024-12-09 <span style="color: #949494;">17:46:34</span> 4 genta Escheri… cattle GEN B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 2024-12-09 <span style="color: #949494;">13:47:36</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;"> 6</span> 2024-12-09 <span style="color: #949494;">17:46:26</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> 2024-12-09 <span style="color: #949494;">13:47:43</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;"> 7</span> 2024-12-09 <span style="color: #949494;">17:46:32</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> 2024-12-09 <span style="color: #949494;">13:47:43</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> 2024-12-09 <span style="color: #949494;">17:46:33</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> 2024-12-09 <span style="color: #949494;">13:47:44</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;"> 9</span> 2024-12-09 <span style="color: #949494;">17:46:33</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> 2024-12-09 <span style="color: #949494;">13:47:44</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> 2024-12-09 <span style="color: #949494;">17:46:34</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 47 more rows</span></span> <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 47 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;"># 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> <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>
search.json
+1 -1
View File
@@ -1 +1 @@
[{"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 24 Jun 2024. 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\") #> ClLine truncated [{"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 24 Jun 2024. 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\") #> ClLine truncated