Hayer Juliette, Dainat Jacques, Marcy E., Banuls Anne-Laure. (2023). Baargin : a Nextflow workflow for the automatic analysis of bacterial genomics data with a focus on Antimicrobial Resistance. Journal of Open Source Software, 8 (90), 5397 [5 p.]. ISSN 2475-9066.
Titre du document
Baargin : a Nextflow workflow for the automatic analysis of bacterial genomics data with a focus on Antimicrobial Resistance
Année de publication
2023
Type de document
Article
Auteurs
Hayer Juliette, Dainat Jacques, Marcy E., Banuls Anne-Laure
Source
Journal of Open Source Software, 2023,
8 (90), 5397 [5 p.] ISSN 2475-9066
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.
