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(v1.3.0) remove vignettes from CRAN

new-mo-algorithm v1.3.0
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commit
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  1. 9
      .Rbuildignore
  2. 2
      docs/articles/index.html
  3. 256
      docs/articles/welcome_to_AMR.html
  4. 15
      docs/articles/welcome_to_AMR_files/accessible-code-block-0.0.1/empty-anchor.js
  5. 3
      docs/pkgdown.yml
  6. 3
      docs/sitemap.xml
  7. 56
      vignettes/welcome_to_AMR.Rmd

9
.Rbuildignore

@ -21,4 +21,11 @@ @@ -21,4 +21,11 @@
^public$
^data-raw$
^\.lintr$
^vignettes$
^vignettes/AMR.Rmd$
^vignettes/benchmarks.Rmd$
^vignettes/EUCAST.Rmd$
^vignettes/MDR.Rmd$
^vignettes/PCA.Rmd$
^vignettes/resistance_predict.Rmd$
^vignettes/SPSS.Rmd$
^vignettes/WHONET.Rmd$

2
docs/articles/index.html

@ -249,6 +249,8 @@ @@ -249,6 +249,8 @@
<dd></dt>
<dt><a href="resistance_predict.html">How to predict antimicrobial resistance</a></dt>
<dd></dt>
<dt><a href="welcome_to_AMR.html">Welcome to the AMR package</a></dt>
<dd></dt>
</dl>
</div>
</div>

256
docs/articles/welcome_to_AMR.html

@ -0,0 +1,256 @@ @@ -0,0 +1,256 @@
<!DOCTYPE html>
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<title>Welcome to the AMR package • AMR (for R)</title>
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<script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet">
<script src="../extra.js"></script><meta property="og:title" content="Welcome to the AMR package">
<meta property="og:description" content="AMR">
<meta property="og:image" content="https://msberends.github.io/AMR/logo.svg">
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<![endif]-->
</head>
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<header><div class="navbar navbar-default navbar-fixed-top" role="navigation">
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<span class="icon-bar"></span>
<span class="icon-bar"></span>
</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</span>
</span>
</div>
<div id="navbar" class="navbar-collapse collapse">
<ul class="nav navbar-nav">
<li>
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<span class="fa fa-home"></span>
Home
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How to
<span class="caret"></span>
</a>
<ul class="dropdown-menu" role="menu">
<li>
<a href="../articles/AMR.html">
<span class="fa fa-directions"></span>
Conduct AMR analysis
</a>
</li>
<li>
<a href="../articles/resistance_predict.html">
<span class="fa fa-dice"></span>
Predict antimicrobial resistance
</a>
</li>
<li>
<a href="../articles/PCA.html">
<span class="fa fa-compress"></span>
Conduct principal component analysis for AMR
</a>
</li>
<li>
<a href="../articles/MDR.html">
<span class="fa fa-skull-crossbones"></span>
Determine multi-drug resistance (MDR)
</a>
</li>
<li>
<a href="../articles/WHONET.html">
<span class="fa fa-globe-americas"></span>
Work with WHONET data
</a>
</li>
<li>
<a href="../articles/SPSS.html">
<span class="fa fa-file-upload"></span>
Import data from SPSS/SAS/Stata
</a>
</li>
<li>
<a href="../articles/EUCAST.html">
<span class="fa fa-exchange-alt"></span>
Apply EUCAST rules
</a>
</li>
<li>
<a href="../reference/mo_property.html">
<span class="fa fa-bug"></span>
Get properties of a microorganism
</a>
</li>
<li>
<a href="../reference/ab_property.html">
<span class="fa fa-capsules"></span>
Get properties of an antibiotic
</a>
</li>
<li>
<a href="../articles/benchmarks.html">
<span class="fa fa-shipping-fast"></span>
Other: benchmarks
</a>
</li>
</ul>
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Manual
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Authors
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Changelog
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Survey
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</header><script src="welcome_to_AMR_files/accessible-code-block-0.0.1/empty-anchor.js"></script><div class="row">
<div class="col-md-9 contents">
<div class="page-header toc-ignore">
<h1 data-toc-skip>Welcome to the AMR package</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">31 July 2020</h4>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/welcome_to_AMR.Rmd"><code>vignettes/welcome_to_AMR.Rmd</code></a></small>
<div class="hidden name"><code>welcome_to_AMR.Rmd</code></div>
</div>
<div id="welcome-to-the-amr-package" class="section level1">
<h1 class="hasAnchor">
<a href="#welcome-to-the-amr-package" class="anchor"></a>Welcome to the AMR package</h1>
<p><code>AMR</code> is a free, open-source and independent R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. <strong>Our aim is to provide a standard</strong> for clean and reproducible antimicrobial resistance data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.</p>
<p>After installing this package, R knows <strong>~70,000 distinct microbial species</strong> and all <strong>~550 antibiotic, antimycotic and antiviral drugs</strong> by name and code (including ATC, EARS-NET, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data.</p>
<p>This package is fully independent of any other R package and works on Windows, macOS and Linux with all versions of R since R-3.0.0 (April 2013). <strong>It was designed to work in any setting, including those with very limited resources</strong>. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice and University Medical Center Groningen. This R package is actively maintained (see Changelog) and is free software (see Copyright).</p>
<p>Since its first public release in early 2018, this package has been downloaded from more than 100 countries.</p>
<div id="usage-examples" class="section level2">
<h2 class="hasAnchor">
<a href="#usage-examples" class="anchor"></a>Usage examples</h2>
<p>This package can be used for:</p>
<ul>
<li>Reference for the taxonomy of microorganisms, since the package contains all microbial (sub)species from the Catalogue of Life and List of Prokaryotic names with Standing in Nomenclature</li>
<li>Interpreting raw MIC and disk diffusion values, based on the latest CLSI or EUCAST guidelines</li>
<li>Retrieving antimicrobial drug names, doses and forms of administration from clinical health care records</li>
<li>Determining first isolates to be used for AMR analysis</li>
<li>Calculating antimicrobial resistance</li>
<li>Determining multi-drug resistance (MDR) / multi-drug resistant organisms (MDRO)</li>
<li>Calculating (empirical) susceptibility of both mono therapy and combination therapies</li>
<li>Predicting future antimicrobial resistance using regression models</li>
<li>Getting properties for any microorganism (like Gram stain, species, genus or family)</li>
<li>Getting properties for any antibiotic (like name, code of EARS-Net/ATC/LOINC/PubChem, defined daily dose or trade name)</li>
<li>Plotting antimicrobial resistance</li>
<li>Applying EUCAST expert rules</li>
<li>Getting SNOMED codes of a microorganism, or getting properties of a microorganism based on a SNOMED code</li>
<li>Getting LOINC codes of an antibiotic, or getting properties of an antibiotic based on a LOINC code</li>
<li>Machine reading the EUCAST and CLSI guidelines from 2011-2020 to translate MIC values and disk diffusion diameters to R/SI</li>
<li>Principal component analysis for AMR</li>
</ul>
</div>
</div>
</div>
<div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
<nav id="toc" data-toggle="toc"><h2 data-toc-skip>Contents</h2>
</nav>
</div>
</div>
<footer><div class="copyright">
<p>Developed by <a href="https://www.rug.nl/staff/m.s.berends/">Matthijs S. Berends</a>, <a href="https://www.rug.nl/staff/c.f.luz/">Christian F. Luz</a>, <a href="https://www.rug.nl/staff/a.w.friedrich/">Alexander W. Friedrich</a>, <a href="https://www.rug.nl/staff/b.sinha/">Bhanu N. M. Sinha</a>, <a href="https://www.rug.nl/staff/c.j.albers/">Casper J. Albers</a>, <a href="https://www.rug.nl/staff/c.glasner/">Corinna Glasner</a>.</p>
</div>
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<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.1.</p>
</div>
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</html>

15
docs/articles/welcome_to_AMR_files/accessible-code-block-0.0.1/empty-anchor.js

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// Hide empty <a> tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) -->
// v0.0.1
// Written by JooYoung Seo (jooyoung@psu.edu) and Atsushi Yasumoto on June 1st, 2020.
document.addEventListener('DOMContentLoaded', function() {
const codeList = document.getElementsByClassName("sourceCode");
for (var i = 0; i < codeList.length; i++) {
var linkList = codeList[i].getElementsByTagName('a');
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if (linkList[j].innerHTML === "") {
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3
docs/pkgdown.yml

@ -10,7 +10,8 @@ articles: @@ -10,7 +10,8 @@ articles:
WHONET: WHONET.html
benchmarks: benchmarks.html
resistance_predict: resistance_predict.html
last_built: 2020-07-31T08:49Z
welcome_to_AMR: welcome_to_AMR.html
last_built: 2020-07-31T09:39Z
urls:
reference: https://msberends.github.io/AMR/reference
article: https://msberends.github.io/AMR/articles

3
docs/sitemap.xml

@ -171,4 +171,7 @@ @@ -171,4 +171,7 @@
<url>
<loc>https://msberends.github.io/AMR/articles/resistance_predict.html</loc>
</url>
<url>
<loc>https://msberends.github.io/AMR/articles/welcome_to_AMR.html</loc>
</url>
</urlset>

56
vignettes/welcome_to_AMR.Rmd vendored

@ -0,0 +1,56 @@ @@ -0,0 +1,56 @@
---
title: "Welcome to the AMR package"
author: "Matthijs S. Berends"
date: '`r format(Sys.Date(), "%d %B %Y")`'
output:
rmarkdown::html_vignette:
toc: true
toc_depth: 3
vignette: >
%\VignetteIndexEntry{Welcome to the AMR package}
%\VignetteEncoding{UTF-8}
%\VignetteEngine{knitr::rmarkdown}
editor_options:
chunk_output_type: console
---
```{r setup, include = FALSE, results = 'markup'}
knitr::opts_chunk$set(
warning = FALSE,
collapse = TRUE,
comment = "#",
fig.width = 7.5,
fig.height = 5
)
```
# Welcome to the AMR package
`AMR` is a free, open-source and independent R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. **Our aim is to provide a standard** for clean and reproducible antimicrobial resistance data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.
After installing this package, R knows **~70,000 distinct microbial species** and all **~550 antibiotic, antimycotic and antiviral drugs** by name and code (including ATC, EARS-NET, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data.
This package is fully independent of any other R package and works on Windows, macOS and Linux with all versions of R since R-3.0.0 (April 2013). **It was designed to work in any setting, including those with very limited resources**. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice and University Medical Center Groningen. This R package is actively maintained (see Changelog) and is free software (see Copyright).
Since its first public release in early 2018, this package has been downloaded from more than 100 countries.
## Usage examples
This package can be used for:
* Reference for the taxonomy of microorganisms, since the package contains all microbial (sub)species from the Catalogue of Life and List of Prokaryotic names with Standing in Nomenclature
* Interpreting raw MIC and disk diffusion values, based on the latest CLSI or EUCAST guidelines
* Retrieving antimicrobial drug names, doses and forms of administration from clinical health care records
* Determining first isolates to be used for AMR analysis
* Calculating antimicrobial resistance
* Determining multi-drug resistance (MDR) / multi-drug resistant organisms (MDRO)
* Calculating (empirical) susceptibility of both mono therapy and combination therapies
* Predicting future antimicrobial resistance using regression models
* Getting properties for any microorganism (like Gram stain, species, genus or family)
* Getting properties for any antibiotic (like name, code of EARS-Net/ATC/LOINC/PubChem, defined daily dose or trade name)
* Plotting antimicrobial resistance
* Applying EUCAST expert rules
* Getting SNOMED codes of a microorganism, or getting properties of a microorganism based on a SNOMED code
* Getting LOINC codes of an antibiotic, or getting properties of an antibiotic based on a LOINC code
* Machine reading the EUCAST and CLSI guidelines from 2011-2020 to translate MIC values and disk diffusion diameters to R/SI
* Principal component analysis for AMR
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