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  1. 4
      DESCRIPTION
  2. 4
      NEWS.md
  3. 2
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  22. 4
      docs/404.html
  23. 4
      docs/LICENSE-text.html
  24. 11
      docs/articles/EUCAST.html
  25. 67
      docs/articles/MDR.html
  26. 11
      docs/articles/PCA.html
  27. 15
      docs/articles/SPSS.html
  28. 11
      docs/articles/WHONET.html
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      docs/articles/index.html
  33. 11
      docs/articles/resistance_predict.html
  34. 11
      docs/articles/welcome_to_AMR.html
  35. 4
      docs/authors.html
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  37. 6
      docs/index.html
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      docs/news/index.html
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      docs/pkgdown.yml
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      docs/reference/as.rsi.html
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      docs/reference/index.html
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  44. 2
      index.md
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      pkgdown/extra.css
  46. 2
      vignettes/EUCAST.Rmd
  47. 2
      vignettes/MDR.Rmd
  48. 2
      vignettes/PCA.Rmd
  49. 4
      vignettes/SPSS.Rmd
  50. 2
      vignettes/WHONET.Rmd
  51. 32
      vignettes/benchmarks.Rmd
  52. 127
      vignettes/datasets.Rmd
  53. 2
      vignettes/resistance_predict.Rmd
  54. 2
      vignettes/welcome_to_AMR.Rmd

4
DESCRIPTION

@ -1,6 +1,6 @@ @@ -1,6 +1,6 @@
Package: AMR
Version: 1.3.0.9004
Date: 2020-08-16
Version: 1.3.0.9005
Date: 2020-08-17
Title: Antimicrobial Resistance Analysis
Authors@R: c(
person(role = c("aut", "cre"),

4
NEWS.md

@ -1,5 +1,5 @@ @@ -1,5 +1,5 @@
# AMR 1.3.0.9004
## <small>Last updated: 16 August 2020</small>
# AMR 1.3.0.9005
## <small>Last updated: 17 August 2020</small>
### New
* Data set `intrinsic_resistant`. This data set contains all bug-drug combinations where the 'bug' is intrinsic resistant to the 'drug' according to the latest EUCAST insights. It contains just two columns: `microorganism` and `antibiotic`.

2
_pkgdown.yml

@ -44,7 +44,7 @@ navbar: @@ -44,7 +44,7 @@ navbar:
- text: "Predict antimicrobial resistance"
icon: "fa-dice"
href: "articles/resistance_predict.html"
- text: "Download our free data sets"
- text: "Download our reference data sets for own use"
icon: "fa-database"
href: "articles/datasets.html"
- text: "Conduct principal component analysis for AMR"

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7
data-raw/internals.R

@ -89,6 +89,13 @@ haven::write_sav(mo, "data-raw/microorganisms.sav") @@ -89,6 +89,13 @@ haven::write_sav(mo, "data-raw/microorganisms.sav")
haven::write_dta(mo, "data-raw/microorganisms.dta")
openxlsx::write.xlsx(mo, "data-raw/microorganisms.xlsx")
saveRDS(microorganisms.old, "data-raw/microorganisms.old.rds", version = 2)
write.table(microorganisms.old, "data-raw/microorganisms.old.txt", sep = "\t", na = "", row.names = FALSE)
haven::write_sas(microorganisms.old, "data-raw/microorganisms.old.sas")
haven::write_sav(microorganisms.old, "data-raw/microorganisms.old.sav")
haven::write_dta(microorganisms.old, "data-raw/microorganisms.old.dta")
openxlsx::write.xlsx(microorganisms.old, "data-raw/microorganisms.old.xlsx")
ab <- dplyr::mutate_if(antibiotics, ~!is.numeric(.), as.character)
saveRDS(ab, "data-raw/antibiotics.rds", version = 2)
write.table(ab, "data-raw/antibiotics.txt", sep = "\t", na = "", row.names = FALSE)

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4
docs/404.html

@ -81,7 +81,7 @@ @@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="https://msberends.github.io/AMR/index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9004</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9005</span>
</span>
</div>
@ -121,7 +121,7 @@ @@ -121,7 +121,7 @@
<a href="articles/datasets.html">
<span class="fa fa-database"></span>
Download our free data sets
Download our reference data sets for own use
</a>
</li>
<li>

4
docs/LICENSE-text.html

@ -81,7 +81,7 @@ @@ -81,7 +81,7 @@
</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">1.3.0.9004</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9005</span>
</span>
</div>
@ -121,7 +121,7 @@ @@ -121,7 +121,7 @@
<a href="articles/datasets.html">
<span class="fa fa-database"></span>
Download our free data sets
Download our reference data sets for own use
</a>
</li>
<li>

11
docs/articles/EUCAST.html

@ -39,7 +39,7 @@ @@ -39,7 +39,7 @@
</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">1.3.0.9002</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9005</span>
</span>
</div>
@ -75,6 +75,13 @@ @@ -75,6 +75,13 @@
Predict antimicrobial resistance
</a>
</li>
<li>
<a href="../articles/datasets.html">
<span class="fa fa-database"></span>
Download our reference data sets for own use
</a>
</li>
<li>
<a href="../articles/PCA.html">
<span class="fa fa-compress"></span>
@ -184,9 +191,7 @@ @@ -184,9 +191,7 @@
<div class="col-md-9 contents">
<div class="page-header toc-ignore">
<h1 data-toc-skip>How to apply EUCAST rules</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">14 August 2020</h4>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/EUCAST.Rmd"><code>vignettes/EUCAST.Rmd</code></a></small>
<div class="hidden name"><code>EUCAST.Rmd</code></div>

67
docs/articles/MDR.html

@ -39,7 +39,7 @@ @@ -39,7 +39,7 @@
</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">1.3.0.9002</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9005</span>
</span>
</div>
@ -75,6 +75,13 @@ @@ -75,6 +75,13 @@
Predict antimicrobial resistance
</a>
</li>
<li>
<a href="../articles/datasets.html">
<span class="fa fa-database"></span>
Download our reference data sets for own use
</a>
</li>
<li>
<a href="../articles/PCA.html">
<span class="fa fa-compress"></span>
@ -184,9 +191,7 @@ @@ -184,9 +191,7 @@
<div class="col-md-9 contents">
<div class="page-header toc-ignore">
<h1 data-toc-skip>How to determine multi-drug resistance (MDR)</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">14 August 2020</h4>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/MDR.Rmd"><code>vignettes/MDR.Rmd</code></a></small>
<div class="hidden name"><code>MDR.Rmd</code></div>
@ -315,19 +320,19 @@ Unique: 2</p> @@ -315,19 +320,19 @@ Unique: 2</p>
<div class="sourceCode" id="cb5"><pre class="downlit">
<span class="fu"><a href="https://rdrr.io/r/utils/head.html">head</a></span>(<span class="kw">my_TB_data</span>)
<span class="co"># rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin</span>
<span class="co"># 1 R R R R R S</span>
<span class="co"># 2 S R S I I S</span>
<span class="co"># 3 R R R S S S</span>
<span class="co"># 4 S I S R I S</span>
<span class="co"># 5 S R R R S R</span>
<span class="co"># 6 S S R S S R</span>
<span class="co"># 1 S S S S S R</span>
<span class="co"># 2 S R S R S S</span>
<span class="co"># 3 R S S S I R</span>
<span class="co"># 4 R S R S R R</span>
<span class="co"># 5 R S S R S R</span>
<span class="co"># 6 S R I S R S</span>
<span class="co"># kanamycin</span>
<span class="co"># 1 S</span>
<span class="co"># 2 I</span>
<span class="co"># 2 R</span>
<span class="co"># 3 R</span>
<span class="co"># 4 R</span>
<span class="co"># 5 S</span>
<span class="co"># 6 I</span>
<span class="co"># 4 S</span>
<span class="co"># 5 R</span>
<span class="co"># 6 R</span>
</pre></div>
<p>We can now add the interpretation of MDR-TB to our data set. You can use:</p>
<div class="sourceCode" id="cb6"><pre class="downlit">
@ -363,40 +368,40 @@ Unique: 5</p> @@ -363,40 +368,40 @@ Unique: 5</p>
<tr class="odd">
<td align="left">1</td>
<td align="left">Mono-resistant</td>
<td align="right">3241</td>
<td align="right">64.82%</td>
<td align="right">3241</td>
<td align="right">64.82%</td>
<td align="right">3203</td>
<td align="right">64.06%</td>
<td align="right">3203</td>
<td align="right">64.06%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">Negative</td>
<td align="right">642</td>
<td align="right">12.84%</td>
<td align="right">3883</td>
<td align="right">77.66%</td>
<td align="right">682</td>
<td align="right">13.64%</td>
<td align="right">3885</td>
<td align="right">77.70%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">Multi-drug-resistant</td>
<td align="right">595</td>
<td align="right">11.90%</td>
<td align="right">4478</td>
<td align="right">89.56%</td>
<td align="right">627</td>
<td align="right">12.54%</td>
<td align="right">4512</td>
<td align="right">90.24%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">Poly-resistant</td>
<td align="right">311</td>
<td align="right">6.22%</td>
<td align="right">4789</td>
<td align="right">95.78%</td>
<td align="right">268</td>
<td align="right">5.36%</td>
<td align="right">4780</td>
<td align="right">95.60%</td>
</tr>
<tr class="odd">
<td align="left">5</td>
<td align="left">Extensively drug-resistant</td>
<td align="right">211</td>
<td align="right">4.22%</td>
<td align="right">220</td>
<td align="right">4.40%</td>
<td align="right">5000</td>
<td align="right">100.00%</td>
</tr>

11
docs/articles/PCA.html

@ -39,7 +39,7 @@ @@ -39,7 +39,7 @@
</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">1.3.0.9002</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9005</span>
</span>
</div>
@ -75,6 +75,13 @@ @@ -75,6 +75,13 @@
Predict antimicrobial resistance
</a>
</li>
<li>
<a href="../articles/datasets.html">
<span class="fa fa-database"></span>
Download our reference data sets for own use
</a>
</li>
<li>
<a href="../articles/PCA.html">
<span class="fa fa-compress"></span>
@ -184,9 +191,7 @@ @@ -184,9 +191,7 @@
<div class="col-md-9 contents">
<div class="page-header toc-ignore">
<h1 data-toc-skip>How to conduct principal component analysis (PCA) for AMR</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">14 August 2020</h4>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/PCA.Rmd"><code>vignettes/PCA.Rmd</code></a></small>
<div class="hidden name"><code>PCA.Rmd</code></div>

15
docs/articles/SPSS.html

@ -39,7 +39,7 @@ @@ -39,7 +39,7 @@
</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">1.3.0.9002</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9005</span>
</span>
</div>
@ -75,6 +75,13 @@ @@ -75,6 +75,13 @@
Predict antimicrobial resistance
</a>
</li>
<li>
<a href="../articles/datasets.html">
<span class="fa fa-database"></span>
Download our reference data sets for own use
</a>
</li>
<li>
<a href="../articles/PCA.html">
<span class="fa fa-compress"></span>
@ -186,7 +193,7 @@ @@ -186,7 +193,7 @@
<h1 data-toc-skip>How to import data from SPSS / SAS / Stata</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">14 August 2020</h4>
<h4 class="date">17 August 2020</h4>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/SPSS.Rmd"><code>vignettes/SPSS.Rmd</code></a></small>
<div class="hidden name"><code>SPSS.Rmd</code></div>
@ -207,7 +214,7 @@ @@ -207,7 +214,7 @@
<ul>
<li>
<p><strong>R is highly modular.</strong></p>
<p>The <a href="https://cran.r-project.org/">official R network (CRAN)</a> features almost 14,000 packages at the time of writing, our <code>AMR</code> package being one of them. All these packages were peer-reviewed before publication. Aside from this official channel, there are also developers who choose not to submit to CRAN, but rather keep it on their own public repository, like GitHub. So there may even be a lot more than 14,000 packages out there.</p>
<p>The <a href="https://cran.r-project.org/">official R network (CRAN)</a> features more than 16,000 packages at the time of writing, our <code>AMR</code> package being one of them. All these packages were peer-reviewed before publication. Aside from this official channel, there are also developers who choose not to submit to CRAN, but rather keep it on their own public repository, like GitHub. So there may even be a lot more than 14,000 packages out there.</p>
<p>Bottom line is, you can really extend it yourself or ask somebody to do this for you. Take for example our <code>AMR</code> package. Among other things, it adds reliable reference data to R to help you with the data cleaning and analysis. SPSS, SAS and Stata will never know what a valid MIC value is or what the Gram stain of <em>E. coli</em> is. Or that all species of <em>Klebiella</em> are resistant to amoxicillin and that Floxapen<sup>®</sup> is a trade name of flucloxacillin. These facts and properties are often needed to clean existing data, which would be very inconvenient in a software package without reliable reference data. See below for a demonstration.</p>
</li>
<li>
@ -221,7 +228,7 @@ @@ -221,7 +228,7 @@
</li>
<li>
<p><strong>R has a huge community.</strong></p>
<p>Many R users just ask questions on websites like <a href="https://stackoverflow.com">StackOverflow.com</a>, the largest online community for programmers. At the time of writing, more than <a href="https://stackoverflow.com/questions/tagged/r?sort=votes">300,000 R-related questions</a> have already been asked on this platform (which covers questions and answers for any programming language). In my own experience, most questions are answered within a couple of minutes.</p>
<p>Many R users just ask questions on websites like <a href="https://stackoverflow.com">StackOverflow.com</a>, the largest online community for programmers. At the time of writing, more than <a href="https://stackoverflow.com/questions/tagged/r?sort=votes">360,000 R-related questions</a> have already been asked on this platform (which covers questions and answers for any programming language). In my own experience, most questions are answered within a couple of minutes.</p>
</li>
<li>
<p><strong>R understands any data type, including SPSS/SAS/Stata.</strong></p>

11
docs/articles/WHONET.html

@ -39,7 +39,7 @@ @@ -39,7 +39,7 @@
</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">1.3.0.9002</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9005</span>
</span>
</div>
@ -75,6 +75,13 @@ @@ -75,6 +75,13 @@
Predict antimicrobial resistance
</a>
</li>
<li>
<a href="../articles/datasets.html">
<span class="fa fa-database"></span>
Download our reference data sets for own use
</a>
</li>
<li>
<a href="../articles/PCA.html">
<span class="fa fa-compress"></span>
@ -184,9 +191,7 @@ @@ -184,9 +191,7 @@
<div class="col-md-9 contents">
<div class="page-header toc-ignore">
<h1 data-toc-skip>How to work with WHONET data</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">14 August 2020</h4>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/WHONET.Rmd"><code>vignettes/WHONET.Rmd</code></a></small>
<div class="hidden name"><code>WHONET.Rmd</code></div>

125
docs/articles/benchmarks.html

@ -39,7 +39,7 @@ @@ -39,7 +39,7 @@
</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">1.3.0.9002</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9005</span>
</span>
</div>
@ -75,6 +75,13 @@ @@ -75,6 +75,13 @@
Predict antimicrobial resistance
</a>
</li>
<li>
<a href="../articles/datasets.html">
<span class="fa fa-database"></span>
Download our reference data sets for own use
</a>
</li>
<li>
<a href="../articles/PCA.html">
<span class="fa fa-compress"></span>
@ -184,9 +191,7 @@ @@ -184,9 +191,7 @@
<div class="col-md-9 contents">
<div class="page-header toc-ignore">
<h1 data-toc-skip>Benchmarks</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">14 August 2020</h4>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/benchmarks.Rmd"><code>vignettes/benchmarks.Rmd</code></a></small>
<div class="hidden name"><code>benchmarks.Rmd</code></div>
@ -224,56 +229,30 @@ @@ -224,56 +229,30 @@
times = <span class="fl">10</span>)
<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span>(<span class="kw">S.aureus</span>, unit = <span class="st">"ms"</span>, signif = <span class="fl">2</span>)
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># as.mo("sau") 9.1 11.0 21 11 13 77 10</span>
<span class="co"># as.mo("stau") 180.0 180.0 190 180 190 210 10</span>
<span class="co"># as.mo("STAU") 170.0 170.0 190 180 210 210 10</span>
<span class="co"># as.mo("staaur") 8.7 12.0 18 12 14 47 10</span>
<span class="co"># as.mo("STAAUR") 9.9 10.0 12 12 12 13 10</span>
<span class="co"># as.mo("S. aureus") 13.0 15.0 29 28 43 47 10</span>
<span class="co"># as.mo("S aureus") 12.0 16.0 25 17 40 52 10</span>
<span class="co"># as.mo("Staphylococcus aureus") 9.1 9.7 14 11 11 44 10</span>
<span class="co"># as.mo("Staphylococcus aureus (MRSA)") 920.0 960.0 990 980 1000 1100 10</span>
<span class="co"># as.mo("Sthafilokkockus aaureuz") 430.0 440.0 460 460 460 510 10</span>
<span class="co"># as.mo("MRSA") 9.1 11.0 16 12 12 37 10</span>
<span class="co"># as.mo("VISA") 15.0 17.0 23 18 20 47 10</span>
<span class="co"># as.mo("VRSA") 15.0 17.0 27 19 44 50 10</span>
<span class="co"># as.mo(22242419) 140.0 140.0 150 150 160 170 10</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># as.mo("sau") 8.8 10.0 24 12 38 57 10</span>
<span class="co"># as.mo("stau") 170.0 170.0 180 170 190 210 10</span>
<span class="co"># as.mo("STAU") 160.0 170.0 180 170 200 220 10</span>
<span class="co"># as.mo("staaur") 9.6 10.0 13 11 12 36 10</span>
<span class="co"># as.mo("STAAUR") 10.0 10.0 25 12 34 80 10</span>
<span class="co"># as.mo("S. aureus") 14.0 15.0 21 15 18 47 10</span>
<span class="co"># as.mo("S aureus") 12.0 15.0 21 16 18 45 10</span>
<span class="co"># as.mo("Staphylococcus aureus") 8.9 9.4 15 11 12 37 10</span>
<span class="co"># as.mo("Staphylococcus aureus (MRSA)") 900.0 920.0 940 940 960 1000 10</span>
<span class="co"># as.mo("Sthafilokkockus aaureuz") 410.0 420.0 450 450 470 520 10</span>
<span class="co"># as.mo("MRSA") 8.8 10.0 16 11 12 38 10</span>
<span class="co"># as.mo("VISA") 13.0 16.0 27 19 41 47 10</span>
<span class="co"># as.mo("VRSA") 13.0 16.0 22 18 19 42 10</span>
<span class="co"># as.mo(22242419) 140.0 140.0 150 140 160 170 10</span>
</pre></div>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-4-1.png" width="562.5"></p>
<p>In the table above, all measurements are shown in milliseconds (thousands of seconds). A value of 5 milliseconds means it can determine 200 input values per second. It case of 100 milliseconds, this is only 10 input values per second.</p>
<p>To achieve this speed, the <code>as.mo</code> function also takes into account the prevalence of human pathogenic microorganisms. The downside of this is of course that less prevalent microorganisms will be determined less fast. See this example for the ID of <em>Methanosarcina semesiae</em> (<code>B_MTHNSR_SEMS</code>), a bug probably never found before in humans:</p>
<div class="sourceCode" id="cb3"><pre class="downlit">
<span class="kw">M.semesiae</span> <span class="op">&lt;-</span> <span class="fu">microbenchmark</span>(<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"metsem"</span>),
<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"METSEM"</span>),
<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"M. semesiae"</span>),
<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"M. semesiae"</span>),
<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"Methanosarcina semesiae"</span>),
times = <span class="fl">10</span>)
<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span>(<span class="kw">M.semesiae</span>, unit = <span class="st">"ms"</span>, signif = <span class="fl">4</span>)
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max</span>
<span class="co"># as.mo("metsem") 193.600 200.200 209.30 202.800 218.00 238.20</span>
<span class="co"># as.mo("METSEM") 186.500 193.500 208.40 202.600 228.90 244.80</span>
<span class="co"># as.mo("M. semesiae") 12.280 13.090 18.86 14.430 15.48 59.40</span>
<span class="co"># as.mo("M. semesiae") 14.060 14.520 20.98 16.420 17.56 46.18</span>
<span class="co"># as.mo("Methanosarcina semesiae") 8.065 9.203 12.65 9.715 10.65 39.96</span>
<span class="co"># neval</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
<span class="co"># 10</span>
</pre></div>
<p>Looking up arbitrary codes of less prevalent microorganisms costs the most time. Full names (like <em>Methanosarcina semesiae</em>) are always very fast and only take some thousands of seconds to coerce - they are the most probable input from most data sets.</p>
<p>In the figure below, we compare <em>Escherichia coli</em> (which is very common) with <em>Prevotella brevis</em> (which is moderately common) and with <em>Methanosarcina semesiae</em> (which is uncommon):</p>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-6-1.png" width="900"></p>
<p>Uncommon microorganisms take some more time than common microorganisms. To further improve performance, two important calculations take almost no time at all: <strong>repetitive results</strong> and <strong>already precalculated results</strong>.</p>
<p>To improve performance, two important calculations take almost no time at all: <strong>repetitive results</strong> and <strong>already precalculated results</strong>.</p>
<div id="repetitive-results" class="section level3">
<h3 class="hasAnchor">
<a href="#repetitive-results" class="anchor"></a>Repetitive results</h3>
<p>Repetitive results are unique values that are present more than once. Unique values will only be calculated once by <code><a href="../reference/as.mo.html">as.mo()</a></code>. We will use <code><a href="../reference/mo_property.html">mo_name()</a></code> for this test - a helper function that returns the full microbial name (genus, species and possibly subspecies) which uses <code><a href="../reference/as.mo.html">as.mo()</a></code> internally.</p>
<div class="sourceCode" id="cb4"><pre class="downlit">
<div class="sourceCode" id="cb3"><pre class="downlit">
<span class="co"># take all MO codes from the example_isolates data set</span>
<span class="kw">x</span> <span class="op">&lt;-</span> <span class="kw">example_isolates</span><span class="op">$</span><span class="kw">mo</span> <span class="op">%&gt;%</span>
<span class="co"># keep only the unique ones</span>
@ -299,28 +278,28 @@ @@ -299,28 +278,28 @@
<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span>(<span class="kw">run_it</span>, unit = <span class="st">"ms"</span>, signif = <span class="fl">3</span>)
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># mo_name(x) 1920 1940 2010 1990 2060 2120 10</span>
<span class="co"># mo_name(x) 1810 1850 1980 1940 2130 2230 10</span>
</pre></div>
<p>So transforming 500,000 values (!!) of 50 unique values only takes 1.99 seconds. You only lose time on your unique input values.</p>
<p>So transforming 500,000 values (!!) of 50 unique values only takes 1.94 seconds. You only lose time on your unique input values.</p>
</div>
<div id="precalculated-results" class="section level3">
<h3 class="hasAnchor">
<a href="#precalculated-results" class="anchor"></a>Precalculated results</h3>
<p>What about precalculated results? If the input is an already precalculated result of a helper function like <code><a href="../reference/mo_property.html">mo_name()</a></code>, it almost doesn’t take any time at all (see ‘C’ below):</p>
<div class="sourceCode" id="cb5"><pre class="downlit">
<div class="sourceCode" id="cb4"><pre class="downlit">
<span class="kw">run_it</span> <span class="op">&lt;-</span> <span class="fu">microbenchmark</span>(A = <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"B_STPHY_AURS"</span>),
B = <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"S. aureus"</span>),
C = <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"Staphylococcus aureus"</span>),
times = <span class="fl">10</span>)
<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span>(<span class="kw">run_it</span>, unit = <span class="st">"ms"</span>, signif = <span class="fl">3</span>)
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># A 5.90 6.16 6.93 7.24 7.43 7.89 10</span>
<span class="co"># B 11.40 12.00 16.20 13.20 14.20 45.20 10</span>
<span class="co"># C 1.05 1.07 1.18 1.13 1.28 1.40 10</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># A 5.080 5.220 5.81 5.66 6.46 7.16 10</span>
<span class="co"># B 10.000 10.200 14.40 10.60 11.30 49.00 10</span>
<span class="co"># C 0.862 0.875 1.04 1.05 1.14 1.40 10</span>
</pre></div>
<p>So going from <code><a href="../reference/mo_property.html">mo_name("Staphylococcus aureus")</a></code> to <code>"Staphylococcus aureus"</code> takes 0.0011 seconds - it doesn’t even start calculating <em>if the result would be the same as the expected resulting value</em>. That goes for all helper functions:</p>
<div class="sourceCode" id="cb6"><pre class="downlit">
<p>So going from <code><a href="../reference/mo_property.html">mo_name("Staphylococcus aureus")</a></code> to <code>"Staphylococcus aureus"</code> takes 0.001 seconds - it doesn’t even start calculating <em>if the result would be the same as the expected resulting value</em>. That goes for all helper functions:</p>
<div class="sourceCode" id="cb5"><pre class="downlit">
<span class="kw">run_it</span> <span class="op">&lt;-</span> <span class="fu">microbenchmark</span>(A = <span class="fu"><a href="../reference/mo_property.html">mo_species</a></span>(<span class="st">"aureus"</span>),
B = <span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span>(<span class="st">"Staphylococcus"</span>),
C = <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"Staphylococcus aureus"</span>),
@ -332,15 +311,15 @@ @@ -332,15 +311,15 @@
times = <span class="fl">10</span>)
<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span>(<span class="kw">run_it</span>, unit = <span class="st">"ms"</span>, signif = <span class="fl">3</span>)
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># A 0.976 0.993 1.13 1.07 1.29 1.34 10</span>
<span class="co"># B 1.000 1.060 1.13 1.07 1.15 1.40 10</span>
<span class="co"># C 0.927 1.030 1.08 1.06 1.11 1.35 10</span>
<span class="co"># D 0.896 0.983 1.11 1.08 1.27 1.41 10</span>
<span class="co"># E 0.866 1.020 1.10 1.07 1.23 1.37 10</span>
<span class="co"># F 0.967 0.993 1.16 1.05 1.32 1.61 10</span>
<span class="co"># G 0.855 1.020 1.07 1.07 1.17 1.31 10</span>
<span class="co"># H 0.966 1.010 1.12 1.06 1.19 1.36 10</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># A 0.869 0.889 0.951 0.904 1.010 1.19 10</span>
<span class="co"># B 0.837 0.873 0.977 0.937 1.010 1.36 10</span>
<span class="co"># C 0.869 0.874 1.020 0.921 1.130 1.40 10</span>
<span class="co"># D 0.829 0.858 0.898 0.862 0.873 1.21 10</span>
<span class="co"># E 0.862 0.870 0.983 0.918 1.050 1.36 10</span>
<span class="co"># F 0.841 0.850 0.915 0.867 0.907 1.24 10</span>
<span class="co"># G 0.842 0.851 0.940 0.898 1.000 1.16 10</span>
<span class="co"># H 0.854 0.864 1.030 0.920 1.170 1.60 10</span>
</pre></div>
<p>Of course, when running <code><a href="../reference/mo_property.html">mo_phylum("Firmicutes")</a></code> the function has zero knowledge about the actual microorganism, namely <em>S. aureus</em>. But since the result would be <code>"Firmicutes"</code> anyway, there is no point in calculating the result. And because this package ‘knows’ all phyla of all known bacteria (according to the Catalogue of Life), it can just return the initial value immediately.</p>
</div>
@ -348,7 +327,7 @@ @@ -348,7 +327,7 @@
<h3 class="hasAnchor">
<a href="#results-in-other-languages" class="anchor"></a>Results in other languages</h3>
<p>When the system language is non-English and supported by this <code>AMR</code> package, some functions will have a translated result. This almost does’t take extra time:</p>
<div class="sourceCode" id="cb7"><pre class="downlit">
<div class="sourceCode" id="cb6"><pre class="downlit">
<span class="fu"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"CoNS"</span>, language = <span class="st">"en"</span>) <span class="co"># or just mo_name("CoNS") on an English system</span>
<span class="co"># [1] "Coagulase-negative Staphylococcus (CoNS)"</span>
@ -368,14 +347,14 @@ @@ -368,14 +347,14 @@
times = <span class="fl">100</span>)
<span class="fu"><a href="https://rdrr.io/r/base/print.html">print</a></span>(<span class="kw">run_it</span>, unit = <span class="st">"ms"</span>, signif = <span class="fl">4</span>)
<span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># en 13.09 14.02 18.36 14.59 16.22 61.92 100</span>
<span class="co"># de 14.00 14.83 18.06 15.48 16.85 56.01 100</span>
<span class="co"># nl 17.71 18.99 24.79 20.09 22.22 58.50 100</span>
<span class="co"># es 13.99 15.02 20.94 15.88 16.70 141.90 100</span>
<span class="co"># it 13.68 14.97 19.02 15.52 16.72 50.26 100</span>
<span class="co"># fr 13.96 15.05 20.63 15.72 17.14 52.71 100</span>
<span class="co"># pt 14.13 14.86 19.81 15.69 17.46 53.89 100</span>
<span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># en 10.72 11.54 15.34 12.76 13.82 44.53 100</span>
<span class="co"># de 11.47 12.77 17.24 13.60 14.78 55.48 100</span>
<span class="co"># nl 14.58 15.91 19.06 16.96 18.46 46.24 100</span>
<span class="co"># es 11.24 11.96 16.86 13.17 14.70 50.05 100</span>
<span class="co"># it 11.35 12.42 17.79 13.52 16.28 50.31 100</span>
<span class="co"># fr 11.41 12.29 17.08 13.43 15.44 53.91 100</span>
<span class="co"># pt 11.34 12.06 16.23 13.25 14.80 51.96 100</span>
</pre></div>
<p>Currently supported are German, Dutch, Spanish, Italian, French and Portuguese.</p>
</div>

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@ -5,7 +5,7 @@ @@ -5,7 +5,7 @@
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<title>Data sets for download / own use • AMR (for R)</title>
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9004</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9005</span>
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@ -79,7 +79,7 @@ @@ -79,7 +79,7 @@
<a href="../articles/datasets.html">
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Download our free data sets
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@ -190,7 +190,7 @@ @@ -190,7 +190,7 @@
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<div class="col-md-9 contents">
<div class="page-header toc-ignore">
<h1 data-toc-skip>Data sets for download</h1>
<h1 data-toc-skip>Data sets for download / own use</h1>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/datasets.Rmd"><code>vignettes/datasets.Rmd</code></a></small>
@ -200,16 +200,18 @@ @@ -200,16 +200,18 @@
<p>This package contains a lot of reference data sets that are all reliable, up-to-date and free to download. You can even use them outside of R, for example to train your laboratory information system (LIS) about intrinsic resistance!</p>
<p>We included them in our <code>AMR</code> package, but also automatically ‘mirror’ them to our public repository in different software formats. On this page, we explain how to download them and how the structure of the data sets look like. The tab separated files <strong>allow for machine reading taxonomic data and EUCAST and CLSI interpretation guidelines</strong>, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI.</p>
<p><em>Note: Years and dates of updates mentioned on this page, are from on <code>AMR</code> package version 1.3.0.9004, online released on 16 August 2020. <strong>If you are reading this page from within R, please <a href="https://msberends.github.io/AMR/articles/datasets.html">visit our website</a> for the latest update.</strong></em></p>
<div id="microorganisms" class="section level2">
<p>This package contains a lot of reference data sets that are all reliable, up-to-date and free to download. You can even use them outside of R, for example to teach your laboratory information system (LIS) about intrinsic resistance!</p>
<p>We included them in our <code>AMR</code> package, but also automatically ‘mirror’ them to our public repository in different software formats. On this page, we explain how to download them and how the structure of the data sets look like. The tab separated files <strong>allow for machine reading taxonomic data and EUCAST and CLSI interpretation guidelines</strong>, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. We also offer all data sets in formats for R, SPSS, SAS, Stata and Excel.</p>
<p><em>Note: Years and dates of updates mentioned on this page, are from on <code>AMR</code> package version 1.3.0.9005, online released on 17 August 2020. <strong>If you are reading this page from within R, please <a href="https://msberends.github.io/AMR/articles/datasets.html">visit our website</a> for the latest update.</strong></em></p>
<div id="microorganisms-currently-accepted-names" class="section level2">
<h2 class="hasAnchor">
<a href="#microorganisms" class="anchor"></a>Microorganisms</h2>
<a href="#microorganisms-currently-accepted-names" class="anchor"></a>Microorganisms (currently accepted names)</h2>
<p>This data set is in R available as <code>microorganisms</code>, after you load the <code>AMR</code> package.</p>
<div id="source" class="section level4">
<h4 class="hasAnchor">
<a href="#source" class="anchor"></a>Source</h4>
<p>It was last updated on 28 July 2020 20:52:40 CEST.</p>
<p>Direct download links:<br><a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.rds">R file (.rds)</a>, 2.7 MB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.xlsx">Excel workbook (.xlsx)</a>, 6.1 MB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.sav">SPSS file (.sav)</a>, 28.2 MB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.sav">Stata file (.dta)</a>, 28.2 MB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.dta">SAS file (.sas)</a>, 25.2 MB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.txt">Tab separated file (.txt)</a>, 13.3 MB.</p>
<div id="source" class="section level3">
<h3 class="hasAnchor">
<a href="#source" class="anchor"></a>Source</h3>
<p>Our full taxonomy of microorganisms is based on the authoritative and comprehensive:</p>
<ul>
<li>
@ -218,12 +220,11 @@ @@ -218,12 +220,11 @@
<a href="https://lpsn.dsmz.de">List of Prokaryotic names with Standing in Nomenclature</a> (LPSN, included version: May 2020)</li>
</ul>
</div>
<div id="structure" class="section level4">
<h4 class="hasAnchor">
<a href="#structure" class="anchor"></a>Structure</h4>
<p>A data set with 67,151 rows and 16 columns, containing the following column names:</p>
<p><em>mo, fullname, kingdom, phylum, class, order, family, genus, species, subspecies, rank, ref, species_id, source, prevalence, snomed</em>.</p>
<p>Included per taxonomic kingdom:</p>
<div id="structure" class="section level3">
<h3 class="hasAnchor">
<a href="#structure" class="anchor"></a>Structure</h3>
<p>A data set with 67,151 rows and 16 columns, containing the following column names:<br><em>mo, fullname, kingdom, phylum, class, order, family, genus, species, subspecies, rank, ref, species_id, source, prevalence, snomed</em>.</p>
<p>Included (sub)species per taxonomic kingdom:</p>
<table class="table">
<thead><tr class="header">
<th align="center">Kingdom</th>
@ -256,23 +257,6 @@ @@ -256,23 +257,6 @@
</tr>
</tbody>
</table>
</div>
<div id="download" class="section level4">
<h4 class="hasAnchor">
<a href="#download" class="anchor"></a>Download</h4>
<p>Download the data set preferably in the software you use, so the data file already has the correct data structure. Below files were updated on 28 July 2020 20:52:40 CEST.</p>
<ul>
<li><p>R file (.rds): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.rds">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/microorganisms.rds">from GitLab</a> (file size: 2.7 MB)</p></li>
<li><p>Excel workbook (.xlsx): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.xlsx">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/microorganisms.xlsx">from GitLab</a> (file size: 6.1 MB)</p></li>
<li><p>SPSS file (.sav): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.sav">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/microorganisms.sav">from GitLab</a> (file size: 28.2 MB)</p></li>
<li><p>Stata file (.dta): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.sav">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/microorganisms.sav">from GitLab</a> (file size: 28.2 MB)</p></li>
<li><p>SAS file (.sas): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.dta">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/microorganisms.dta">from GitLab</a> (file size: 25.2 MB)</p></li>
<li><p>Tab separated file (.txt): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.txt">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/microorganisms.txt">from GitLab</a> (file size: 13.3 MB)</p></li>
</ul>
</div>
<div id="example" class="section level4">
<h4 class="hasAnchor">
<a href="#example" class="anchor"></a>Example</h4>
<p>Example rows when filtering on genus <em>Escherichia</em>:</p>
<table class="table">
<colgroup>
@ -424,13 +408,68 @@ @@ -424,13 +408,68 @@
</table>
</div>
</div>
<div id="microorganisms-previously-accepted-names" class="section level2">
<h2 class="hasAnchor">
<a href="#microorganisms-previously-accepted-names" class="anchor"></a>Microorganisms (previously accepted names)</h2>
<p>This data set is in R available as <code>microorganisms.old</code>, after you load the <code>AMR</code> package.</p>
<p>It was last updated on 28 May 2020 11:17:56 CEST.</p>
<p>Direct download links:<br><a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.old.rds">R file (.rds)</a>, 0.3 MB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.old.xlsx">Excel workbook (.xlsx)</a>, 0.4 MB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.old.sav">SPSS file (.sav)</a>, 1.9 MB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.old.sav">Stata file (.dta)</a>, 1.9 MB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.old.dta">SAS file (.sas)</a>, 1.8 MB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/microorganisms.old.txt">Tab separated file (.txt)</a>, 0.8 MB.</p>
<div id="source-1" class="section level3">
<h3 class="hasAnchor">
<a href="#source-1" class="anchor"></a>Source</h3>
<p>This data set contains old, previously accepted taxonomic names. The data sources are the same as the <code>microorganisms</code> data set:</p>
<ul>
<li>
<a href="http://www.catalogueoflife.org">Catalogue of Life</a> (included version: 2019)</li>
<li>
<a href="https://lpsn.dsmz.de">List of Prokaryotic names with Standing in Nomenclature</a> (LPSN, included version: May 2020)</li>
</ul>
</div>
<div id="structure-1" class="section level3">
<h3 class="hasAnchor">
<a href="#structure-1" class="anchor"></a>Structure</h3>
<p>A data set with 12,708 rows and 4 columns, containing the following column names:<br><em>fullname, fullname_new, ref, prevalence</em>.</p>
<p><strong>Note:</strong> remember that the ‘ref’ columns contains the scientific reference to the old taxonomic entries, i.e. of column <em>fullname</em>. For the scientific reference of the new names, i.e. of column <em>fullname_new</em>, see the <code>microorganisms</code> data set.</p>
<p>Example rows when filtering on <em>Escherichia</em>:</p>
<table class="table">
<thead><tr class="header">
<th align="center">fullname</th>
<th align="center">fullname_new</th>
<th align="center">ref</th>
<th align="center">prevalence</th>
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">Escherichia adecarboxylata</td>
<td align="center">Leclercia adecarboxylata</td>
<td align="center">Leclerc, 1962</td>
<td align="center">1</td>
</tr>
<tr class="even">
<td align="center">Escherichia blattae</td>
<td align="center">Shimwellia blattae</td>
<td align="center">Burgess et al., 1973</td>
<td align="center">1</td>
</tr>
<tr class="odd">
<td align="center">Escherichia vulneris</td>
<td align="center">Pseudescherichia vulneris</td>
<td align="center">Brenner et al., 1983</td>
<td align="center">1</td>
</tr>
</tbody>
</table>
</div>
</div>
<div id="antibiotic-agents" class="section level2">
<h2 class="hasAnchor">
<a href="#antibiotic-agents" class="anchor"></a>Antibiotic agents</h2>
<p>This data set is in R available as <code>antibiotics</code>, after you load the <code>AMR</code> package.</p>
<div id="source-1" class="section level4">
<h4 class="hasAnchor">
<a href="#source-1" class="anchor"></a>Source</h4>
<p>It was last updated on 31 July 2020 12:12:13 CEST.</p>
<p>Direct download links:<br><a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.rds">R file (.rds)</a>, 37 kB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.xlsx">Excel workbook (.xlsx)</a>, 65 kB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.sav">SPSS file (.sav)</a>, 1.3 MB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.sav">Stata file (.dta)</a>, 1.3 MB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.dta">SAS file (.sas)</a>, 0.3 MB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.txt">Tab separated file (.txt)</a>, 0.1 MB.</p>
<div id="source-2" class="section level3">
<h3 class="hasAnchor">
<a href="#source-2" class="anchor"></a>Source</h3>
<p>This data set contains all EARS-Net and ATC codes gathered from WHO and WHONET, and all compound IDs from PubChem. It also contains all brand names (synonyms) as found on PubChem and Defined Daily Doses (DDDs) for oral and parenteral administration.</p>
<ul>
<li>
@ -439,28 +478,10 @@ @@ -439,28 +478,10 @@
<li><a href="https://whonet.org">WHONET software 2019</a></li>
</ul>
</div>
<div id="structure-1" class="section level4">
<h4 class="hasAnchor">
<a href="#structure-1" class="anchor"></a>Structure</h4>
<p>A data set with 456 rows and 14 columns, containing the following column names:</p>
<p><em>ab, atc, cid, name, group, atc_group1, atc_group2, abbreviations, synonyms, oral_ddd, oral_units, iv_ddd, iv_units, loinc</em>.</p>
</div>
<div id="download-1" class="section level4">
<h4 class="hasAnchor">
<a href="#download-1" class="anchor"></a>Download</h4>
<p>Download the data set preferably in the software you use, so the data file already has the correct data structure. Below files were updated on 31 July 2020 12:12:13 CEST.</p>
<ul>
<li><p>R file (.rds): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.rds">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antibiotics.rds">from GitLab</a> (file size: 37.3 kB)</p></li>
<li><p>Excel workbook (.xlsx): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.xlsx">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antibiotics.xlsx">from GitLab</a> (file size: 64.5 kB)</p></li>
<li><p>SPSS file (.sav): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.sav">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antibiotics.sav">from GitLab</a> (file size: 1.3 MB)</p></li>
<li><p>Stata file (.dta): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.sav">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antibiotics.sav">from GitLab</a> (file size: 1.3 MB)</p></li>
<li><p>SAS file (.sas): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.dta">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antibiotics.dta">from GitLab</a> (file size: 321.8 kB)</p></li>
<li><p>Tab separated file (.txt): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antibiotics.txt">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antibiotics.txt">from GitLab</a> (file size: 146.1 kB)</p></li>
</ul>
</div>
<div id="example-1" class="section level4">
<h4 class="hasAnchor">
<a href="#example-1" class="anchor"></a>Example</h4>
<div id="structure-2" class="section level3">
<h3 class="hasAnchor">
<a href="#structure-2" class="anchor"></a>Structure</h3>
<p>A data set with 456 rows and 14 columns, containing the following column names:<br><em>ab, atc, cid, name, group, atc_group1, atc_group2, abbreviations, synonyms, oral_ddd, oral_units, iv_ddd, iv_units, loinc</em>.</p>
<p>Example rows:</p>
<table class="table">
<colgroup>
@ -600,9 +621,11 @@ @@ -600,9 +621,11 @@
<h2 class="hasAnchor">
<a href="#antiviral-agents" class="anchor"></a>Antiviral agents</h2>
<p>This data set is in R available as <code>antivirals</code>, after you load the <code>AMR</code> package.</p>
<div id="source-2" class="section level4">
<h4 class="hasAnchor">
<a href="#source-2" class="anchor"></a>Source</h4>
<p>It was last updated on 23 November 2019 19:03:43 CET.</p>
<p>Direct download links:<br><a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.rds">R file (.rds)</a>, 5 kB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.xlsx">Excel workbook (.xlsx)</a>, 14 kB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.sav">SPSS file (.sav)</a>, 68 kB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.sav">Stata file (.dta)</a>, 68 kB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.dta">SAS file (.sas)</a>, 67 kB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.txt">Tab separated file (.txt)</a>, 16 kB.</p>
<div id="source-3" class="section level3">
<h3 class="hasAnchor">
<a href="#source-3" class="anchor"></a>Source</h3>
<p>This data set contains all ATC codes gathered from WHO and all compound IDs from PubChem. It also contains all brand names (synonyms) as found on PubChem and Defined Daily Doses (DDDs) for oral and parenteral administration.</p>
<ul>
<li>
@ -610,28 +633,10 @@ @@ -610,28 +633,10 @@
<li><a href="https://pubchem.ncbi.nlm.nih.gov">PubChem by the US National Library of Medicine</a></li>
</ul>
</div>
<div id="structure-2" class="section level4">
<h4 class="hasAnchor">
<a href="#structure-2" class="anchor"></a>Structure</h4>
<p>A data set with 102 rows and 9 columns, containing the following column names:</p>
<p><em>atc, cid, name, atc_group, synonyms, oral_ddd, oral_units, iv_ddd, iv_units</em>.</p>
</div>
<div id="download-2" class="section level4">
<h4 class="hasAnchor">
<a href="#download-2" class="anchor"></a>Download</h4>
<p>Download the data set preferably in the software you use, so the data file already has the correct data structure. Below files were updated on 23 November 2019 19:03:43 CET.</p>
<ul>
<li><p>R file (.rds): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.rds">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antivirals.rds">from GitLab</a> (file size: 4.6 kB)</p></li>
<li><p>Excel workbook (.xlsx): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.xlsx">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antivirals.xlsx">from GitLab</a> (file size: 13.6 kB)</p></li>
<li><p>SPSS file (.sav): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.sav">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antivirals.sav">from GitLab</a> (file size: 67.7 kB)</p></li>
<li><p>Stata file (.dta): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.sav">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antivirals.sav">from GitLab</a> (file size: 67.7 kB)</p></li>
<li><p>SAS file (.sas): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.dta">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antivirals.dta">from GitLab</a> (file size: 67.2 kB)</p></li>
<li><p>Tab separated file (.txt): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/antivirals.txt">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/antivirals.txt">from GitLab</a> (file size: 16.2 kB)</p></li>
</ul>
</div>
<div id="example-2" class="section level4">
<h4 class="hasAnchor">
<a href="#example-2" class="anchor"></a>Example</h4>
<div id="structure-3" class="section level3">
<h3 class="hasAnchor">
<a href="#structure-3" class="anchor"></a>Structure</h3>
<p>A data set with 102 rows and 9 columns, containing the following column names:<br><em>atc, cid, name, atc_group, synonyms, oral_ddd, oral_units, iv_ddd, iv_units</em>.</p>
<p>Example rows:</p>
<table class="table">
<colgroup>
@ -731,35 +736,19 @@ @@ -731,35 +736,19 @@
<h2 class="hasAnchor">
<a href="#intrinsic-bacterial-resistance" class="anchor"></a>Intrinsic bacterial resistance</h2>
<p>This data set is in R available as <code>intrinsic_resistant</code>, after you load the <code>AMR</code> package.</p>
<div id="source-3" class="section level4">
<h4 class="hasAnchor">
<a href="#source-3" class="anchor"></a>Source</h4>
<p>It was last updated on 14 August 2020 14:18:20 CEST.</p>
<p>Direct download links:<br><a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.rds">R file (.rds)</a>, 97 kB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.xlsx">Excel workbook (.xlsx)</a>, 0.5 MB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.sav">SPSS file (.sav)</a>, 4.2 MB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.sav">Stata file (.dta)</a>, 4.2 MB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.dta">SAS file (.sas)</a>, 3.7 MB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.txt">Tab separated file (.txt)</a>, 1.8 MB.</p>
<div id="source-4" class="section level3">
<h3 class="hasAnchor">
<a href="#source-4" class="anchor"></a>Source</h3>
<p>This data set contains all defined intrinsic resistance by EUCAST of all bug-drug combinations.</p>
<p>The data set is based on ‘EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes’, version 3.1, 2016.</p>
</div>
<div id="structure-3" class="section level4">
<h4 class="hasAnchor">
<a href="#structure-3" class="anchor"></a>Structure</h4>
<p>A data set with 49,462 rows and 2 columns, containing the following column names:</p>
<p><em>microorganism, antibiotic</em>.</p>
</div>
<div id="download-3" class="section level4">
<h4 class="hasAnchor">
<a href="#download-3" class="anchor"></a>Download</h4>
<p>Download the data set preferably in the software you use, so the data file already has the correct data structure. Below files were updated on 14 August 2020 14:18:20 CEST.</p>
<ul>
<li><p>R file (.rds): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.rds">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/intrinsic_resistant.rds">from GitLab</a> (file size: 96.6 kB)</p></li>
<li><p>Excel workbook (.xlsx): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.xlsx">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/intrinsic_resistant.xlsx">from GitLab</a> (file size: 0.5 MB)</p></li>
<li><p>SPSS file (.sav): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.sav">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/intrinsic_resistant.sav">from GitLab</a> (file size: 4.2 MB)</p></li>
<li><p>Stata file (.dta): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.sav">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/intrinsic_resistant.sav">from GitLab</a> (file size: 4.2 MB)</p></li>
<li><p>SAS file (.sas): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.dta">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/intrinsic_resistant.dta">from GitLab</a> (file size: 3.7 MB)</p></li>
<li><p>Tab separated file (.txt): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/intrinsic_resistant.txt">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/intrinsic_resistant.txt">from GitLab</a> (file size: 1.8 MB)</p></li>
</ul>
</div>
<div id="example-3" class="section level4">
<h4 class="hasAnchor">
<a href="#example-3" class="anchor"></a>Example</h4>
<p>Example rows:</p>
<div id="structure-4" class="section level3">
<h3 class="hasAnchor">
<a href="#structure-4" class="anchor"></a>Structure</h3>
<p>A data set with 49,462 rows and 2 columns, containing the following column names:<br><em>microorganism, antibiotic</em>.</p>
<p>Example rows when filtering on <em>Klebsiella</em>:</p>
<table class="table">
<thead><tr class="header">
<th align="center">microorganism</th>
@ -798,33 +787,17 @@ @@ -798,33 +787,17 @@
<h2 class="hasAnchor">
<a href="#interpretation-from-mic-values-disk-diameters-to-rsi" class="anchor"></a>Interpretation from MIC values / disk diameters to R/SI</h2>
<p>This data set is in R available as <code>rsi_translation</code>, after you load the <code>AMR</code> package.</p>
<div id="source-4" class="section level4">
<h4 class="hasAnchor">
<a href="#source-4" class="anchor"></a>Source</h4>
<p>It was last updated on 29 July 2020 13:12:34 CEST.</p>
<p>Direct download links:<br><a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.rds">R file (.rds)</a>, 55 kB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.xlsx">Excel workbook (.xlsx)</a>, 0.6 MB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.sav">SPSS file (.sav)</a>, 3.4 MB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.sav">Stata file (.dta)</a>, 3.4 MB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.dta">SAS file (.sas)</a>, 3 MB – <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.txt">Tab separated file (.txt)</a>, 1.5 MB.</p>
<div id="source-5" class="section level3">
<h3 class="hasAnchor">
<a href="#source-5" class="anchor"></a>Source</h3>
<p>This data set contains interpretation rules for MIC values and disk diffusion diameters. Included guidelines are CLSI (2010-2019) and EUCAST (2011-2020).</p>
</div>
<div id="structure-4" class="section level4">
<h4 class="hasAnchor">
<a href="#structure-4" class="anchor"></a>Structure</h4>
<p>A data set with 18,650 rows and 10 columns, containing the following column names:</p>
<p><em>guideline, method, site, mo, ab, ref_tbl, disk_dose, breakpoint_S, breakpoint_R, uti</em>.</p>
</div>
<div id="download-4" class="section level4">
<h4 class="hasAnchor">
<a href="#download-4" class="anchor"></a>Download</h4>
<p>Download the data set preferably in the software you use, so the data file already has the correct data structure. Below files were updated on 29 July 2020 13:12:34 CEST.</p>
<ul>
<li><p>R file (.rds): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.rds">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/rsi_translation.rds">from GitLab</a> (file size: 55.1 kB)</p></li>
<li><p>Excel workbook (.xlsx): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.xlsx">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/rsi_translation.xlsx">from GitLab</a> (file size: 0.6 MB)</p></li>
<li><p>SPSS file (.sav): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.sav">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/rsi_translation.sav">from GitLab</a> (file size: 3.4 MB)</p></li>
<li><p>Stata file (.dta): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.sav">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/rsi_translation.sav">from GitLab</a> (file size: 3.4 MB)</p></li>
<li><p>SAS file (.sas): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.dta">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/rsi_translation.dta">from GitLab</a> (file size: 3 MB)</p></li>
<li><p>Tab separated file (.txt): <a href="https://github.com/msberends/AMR/raw/master/data-raw/../data-raw/rsi_translation.txt">from GitHub</a>, <a href="https://gitlab.com/msberends/AMR/-/raw/master/data-raw/../data-raw/rsi_translation.txt">from GitLab</a> (file size: 1.5 MB)</p></li>
</ul>
</div>
<div id="example-4" class="section level4">
<h4 class="hasAnchor">
<a href="#example-4" class="anchor"></a>Example</h4>
<div id="structure-5" class="section level3">
<h3 class="hasAnchor">
<a href="#structure-5" class="anchor"></a>Structure</h3>
<p>A data set with 18,650 rows and 10 columns, containing the following column names:<br><em>guideline, method, site, mo, ab, ref_tbl, disk_dose, breakpoint_S, breakpoint_R, uti</em>.</p>
<p>Example rows:</p>
<table class="table">
<colgroup>

6
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