Welcome to the AMR package.

Details

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 microorganisms, since it contains almost all 60,000 microbial (sub)species from the Catalogue of Life

  • Calculating antimicrobial resistance

  • Calculating empirical susceptibility of both mono therapy and combination therapy

  • 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, ATC code, defined daily dose or trade name)

  • Plotting antimicrobial resistance

  • Determining first isolates to be used for AMR analysis

  • Applying EUCAST expert rules (not the translation from MIC to RSI values)

  • Determining multi-drug resistant organisms (MDRO)

  • Descriptive statistics: frequency tables, kurtosis and skewness

Authors

Matthijs S. Berends[1,2] Christian F. Luz[1], Erwin E.A. Hassing[2], Corinna Glasner[1], Alex W. Friedrich[1], Bhanu N.M. Sinha[1]

[1] Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands - rug.nl umcg.nl
[2] Certe Medical Diagnostics & Advice, Groningen, the Netherlands - certe.nl

Read more on our website!

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.

Contact us

For suggestions, comments or questions, please contact us at:

Matthijs S. Berends
m.s.berends [at] umcg [dot] nl
Department of Medical Microbiology, University of Groningen
University Medical Center Groningen
Post Office Box 30001
9700 RB Groningen

If you have found a bug, please file a new issue at:
https://gitlab.com/msberends/AMR/issues