TY - JOUR T1 - AMR – An R Package for Working with Antimicrobial Resistance Data JF - bioRxiv DO - 10.1101/810622 SP - 810622 AU - Matthijs S. Berends AU - Christian F. Luz AU - Alexander W. Friedrich AU - Bhanu N.M. Sinha AU - Casper J. Albers AU - Corinna Glasner Y1 - 2019/01/01 UR - http://biorxiv.org/content/early/2019/11/08/810622.abstract N2 - Antimicrobial resistance is an increasing threat to global health. Evidence for this trend is generated in microbiological laboratories through testing microorganisms for resistance against antimicrobial agents. International standards and guidelines are in place for this process as well as for reporting data on (inter-)national levels. However, there is a gap in the availability of standardized and reproducible tools for working with laboratory data to produce the required reports. Of data coming from laboratory information systems, it is known that extensive efforts in data cleaning and validation are required. Furthermore, the global nature of antimicrobial resistance demands to incorporate international reference data in the analysis process.In this paper, we introduce the AMR package for R that aims at closing this gap by providing tools to simplify antimicrobial resistance data cleaning and analysis, while incorporating international guidelines and scientifically reliable reference data. The AMR package enables standardized and reproducible antimicrobial resistance analyses, including the application of evidence-based rules, determination of first isolates, translation of various codes for microorganisms and antimicrobial agents, determination of (multi-drug) resistant microorganisms, and calculation of antimicrobial resistance, prevalence and future trends. The AMR package works independently of any laboratory information system and provides several functions to integrate into international workflows (e.g. WHONET software by the World Health Organization). ER -