--- 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