Welcome to the AMR package.
AMR is a free and open-source R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. It supports any table format, including WHONET/EARS-Net data.
We created this package for both academic research and routine analysis at the Faculty of Medical Sciences of the University of Groningen and the Medical Microbiology & Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG). This R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but not patent) purposes under the terms of the GNU General Public License version 2.0 (GPL-2), as published by the Free Software Foundation.
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
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, EARS-Net code, ATC code, PubChem code, defined daily dose or trade name)
Plotting antimicrobial resistance
Getting SNOMED codes of a microorganism, or get its name associated with a SNOMED code
Getting LOINC codes of an antibiotic, or get its name associated with 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
On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.
For suggestions, comments or questions, please contact us at:
Matthijs S. Berends
m.s.berends [at] umcg [dot] nl
University of Groningen
Department of Medical Microbiology
University Medical Center Groningen
Post Office Box 30001
9700 RB Groningen
The Netherlands
If you have found a bug, please file a new issue at:
https://gitlab.com/msberends/AMR/issues