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Article Dans Une Revue Journal of Open Source Software Année : 2023

Baargin: a Nextflow workflow for the automatic analysis of bacterial genomics data with a focus on Antimicrobial Resistance

Juliette Hayer
Jacques Dainat
Ella Marcy
Anne-Laure Bañuls

Résumé

The emergence and development of Antimicrobial Resistance (AMR) is a global health problem, that could cause about 10 million deaths yearly by 2050 (Thompson, 2022). The study of the genomes of these (multi)resistant bacterial strains is of high importance to understand emergence and circulation of the resistance. In the past couple of decades, high throughput sequencing technologies have seriously improved and it has become more affordable to sequence the full genomes of hundreds of bacterial strains at a time. As a counterpart, these experiments produce large amount of data that needs to be analysed by various bioinformatics methods and tools for reconstructing the genomes and therefore identify their specific features and the genetic determinants of the AMR. For automating the bioinformatics analysis of multiple strains, we have developed a Nextflow (DI Tommaso et al., 2017) workflow called baargin (Bacterial Assembly and Antimicrobial Resistance Genes detection In Nextflow) https://github.com/ jhayer/baargin. It enables to conduct sequencing reads quality control, genome assembly and annotation, Multi-Locus Sequence Typing and plasmid identification, as well as antimicrobial resistance determinants detection, and pangenome analysis. The use of Nextflow, a workflow management system, makes our workflow portable, flexible, and able to conduct reproducible analyses
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Dates et versions

hal-04273434 , version 1 (19-01-2024)

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Juliette Hayer, Jacques Dainat, Ella Marcy, Anne-Laure Bañuls. Baargin: a Nextflow workflow for the automatic analysis of bacterial genomics data with a focus on Antimicrobial Resistance. Journal of Open Source Software, 2023, 8 (90), pp.5397. ⟨10.21105/joss.05397⟩. ⟨hal-04273434⟩
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