Discordance between different bioinformatic methods for identifying resistance genes from short-read genomic data, with a focus on <i>Escherichia coli</i>.

ABSTRACT: Several bioinformatics genotyping algorithms are now commonly used to characterize antimicrobial resistance (AMR) gene profiles in whole-genome sequencing (WGS) data, with a view to understanding AMR epidemiology and developing resistance prediction workflows using WGS in clinical settings. Accurately evaluating AMR in Enterobacterales, particularly Escherichia coli, is of major importance, because this is a common pathogen. However, robust comparisons of different genotyping approaches on relevant simulated and large real-life WGS datasets are lacking. Here, we used both simulated datasets and a large set of real E. coli WGS data (n=1818 isolates) to systematically investigate genotyping methods in greater detail. Simulated constructs and real sequences were processed

SUBMITTER: Davies TJ 

PROVIDER: S-EPMC10763500 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature