@article{mbs:/content/journal/mgen/10.1099/mgen.0.000131, author = "Hunt, Martin and Mather, Alison E and Sánchez-Busó, Leonor and Page, Andrew J and Parkhill, Julian and Keane, Jacqueline A and Harris, Simon R", title = "ARIBA: rapid antimicrobial resistance genotyping directly from sequencing reads", journal= "Microbial Genomics", year = "2017", volume = "3", number = "10", pages = "", doi = "https://doi.org/10.1099/mgen.0.000131", url = "https://www.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.000131", publisher = "Microbiology Society", issn = "2057-5858", type = "Journal Article", keywords = "sequence typing", keywords = "genotyping", keywords = "bacteria", keywords = "antimicrobial resistance", keywords = "whole genome sequencing", eid = "e000131", abstract = "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.", }