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Antimicrobial resistance (AMR) is one of the major threats to human and animal health worldwide, yet few high-throughput tools exist to analyse and predict the resistance of a bacterial isolate from sequencing data. Here we present a new tool, ARIBA, that identifies AMR-associated genes and single nucleotide polymorphisms directly from short reads, and generates detailed and customizable output. The accuracy and advantages of ARIBA over other tools are demonstrated on three datasets from Gram-positive and Gram-negative bacteria, with ARIBA outperforming existing methods.

Original publication

DOI

10.1099/mgen.0.000131

Type

Journal

Microbial genomics

Publication Date

10/2017

Volume

3

Addresses

1​Infection Genomics, Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA, UK.

Keywords

Animals, Humans, Neisseria gonorrhoeae, Shigella sonnei, Enterococcus faecium, Genomics, Drug Resistance, Microbial, Software, Infections