From 791bb6d33f0a994814ff3775c389ee69d5ab7824 Mon Sep 17 00:00:00 2001 From: "Matthijs S. Berends" Date: Fri, 31 Jul 2020 11:39:56 +0200 Subject: [PATCH] (v1.3.0) remove vignettes from CRAN --- .Rbuildignore | 9 +- docs/articles/index.html | 2 + docs/articles/welcome_to_AMR.html | 256 ++++++++++++++++++ .../empty-anchor.js | 15 + docs/pkgdown.yml | 3 +- docs/sitemap.xml | 3 + vignettes/welcome_to_AMR.Rmd | 56 ++++ 7 files changed, 342 insertions(+), 2 deletions(-) create mode 100644 docs/articles/welcome_to_AMR.html create mode 100644 docs/articles/welcome_to_AMR_files/accessible-code-block-0.0.1/empty-anchor.js create mode 100644 vignettes/welcome_to_AMR.Rmd diff --git a/.Rbuildignore b/.Rbuildignore index b1c2ef1a..67cfd832 100755 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -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$ diff --git a/docs/articles/index.html b/docs/articles/index.html index be5e1ed2..a21603d9 100644 --- a/docs/articles/index.html +++ b/docs/articles/index.html @@ -249,6 +249,8 @@
How to predict antimicrobial resistance
+
Welcome to the AMR package
+
diff --git a/docs/articles/welcome_to_AMR.html b/docs/articles/welcome_to_AMR.html new file mode 100644 index 00000000..c1837ae5 --- /dev/null +++ b/docs/articles/welcome_to_AMR.html @@ -0,0 +1,256 @@ + + + + + + + +Welcome to the AMR package • AMR (for R) + + + + + + + + + + + + + + + + + + +
+
+ + + + +
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+

Welcome to the AMR package

+

Matthijs S. Berends

+ +

31 July 2020

+ + Source: vignettes/welcome_to_AMR.Rmd + + +
+ + + +
+

+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
    • +
+
+
+
+ + + +
+ + + + +
+ + + + + + diff --git a/docs/articles/welcome_to_AMR_files/accessible-code-block-0.0.1/empty-anchor.js b/docs/articles/welcome_to_AMR_files/accessible-code-block-0.0.1/empty-anchor.js new file mode 100644 index 00000000..ca349fd6 --- /dev/null +++ b/docs/articles/welcome_to_AMR_files/accessible-code-block-0.0.1/empty-anchor.js @@ -0,0 +1,15 @@ +// Hide empty 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'); + for (var j = 0; j < linkList.length; j++) { + if (linkList[j].innerHTML === "") { + linkList[j].setAttribute('aria-hidden', 'true'); + } + } + } +}); diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml index f5473010..f6e59365 100644 --- a/docs/pkgdown.yml +++ b/docs/pkgdown.yml @@ -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 diff --git a/docs/sitemap.xml b/docs/sitemap.xml index 732bf771..76b07fbd 100644 --- a/docs/sitemap.xml +++ b/docs/sitemap.xml @@ -171,4 +171,7 @@ https://msberends.github.io/AMR/articles/resistance_predict.html + + https://msberends.github.io/AMR/articles/welcome_to_AMR.html + diff --git a/vignettes/welcome_to_AMR.Rmd b/vignettes/welcome_to_AMR.Rmd new file mode 100644 index 00000000..8287bfc8 --- /dev/null +++ b/vignettes/welcome_to_AMR.Rmd @@ -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