A New, Free, and Independent Method for Standardised, Reproducible and Reliable Analyses of Antimicrobial Resistance Data

Open Research objectives / Practices

The AMR package for R was licensed under the GNU General Public License v2.0 (GPL-2). The source code is available on GitHub (https://github.com/msberends/AMR) and the University of Groningen Gitea server (https://git.web.rug.nl/P281424/AMR).

A technical manuscript was preprinted at bioRxiv (https://www.biorxiv.org/content/10.1101/810622v4) and was formally accepted by the open science Journal of Statistical Software (https://www.jstatsoft.org).

Among other open data sets, the AMR package contains the complete microbial taxonomy, which was made publicly available by the authoritative Catalogue of Life (https://www.catalogueoflife.org).

Introduction

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 AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.

Motivation

Open Research practises allow us to collaboratively work with the users of our new software method, which is also shown by the issues raised at our repository by others (https://github.com/msberends/AMR/issues). This has tremendously improved the quality of the provided method.

We were also contacted by users worldwide directly, which in several brought new collaborations for the project, which also continuously make public (https://msberends.github.io/AMR/authors.html)

Lessons learned

Open science and especially open-source software are still not as common as we like. Creating open-source methods is something we should have communicated more extensively about to our PhD supervisors, as they have found it hard to grasp or comprehend the extendibility and outreach that new open method can yield. Our method has been used in over 160 countries in only 2 years. Not something very uncommon for newly released open-source software (especially R packages), but it is quite uncommon in current common research practise. We should have invested more on this topic in our direct communications.

URLs, references and further information

• Website of the method: https://msberends.github.io/AMR/

• Repository of the method: https://github.com/msberends/AMR

• Official R channel of the method: https://cran.r-project.org/package=AMR