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

Read more on our website!

On our website https://msberends.github.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.

Contact Us

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: