ArticleMicrobial genomics2025
microGWAS: a computational pipeline to perform large-scale bacterial genome-wide association studies.
Article in Microbial genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Recent advancements in artificial intelligence applications for the mitigation of antimicrobial resistance: challenges and opportunities.JAC-antimicrobial resistance · 2026Review
- Skin Infection Pathogenicity Associated with a Canine Microbiome Resident: Polygenic Architecture of Virulence Factors inAntibiotics (Basel, Switzerland) · 2026Article
- BaGPipe: an automated, reproducible, and flexible pipeline for bacterial genome-wide association studies.BMC microbiology · 2026Article
- Genomics for antimicrobial resistance-progress and future directions.Antimicrobial agents and chemotherapy · 2025Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Identifying genetic variants associated with bacterial phenotypes, such as virulence, host preference and antimicrobial resistance, has great potential for a better understanding of the mechanisms involved in these traits. The availability of large collections of bacterial genomes has made genome-wide association studies (GWAS) a common approach for this purpose. The need to employ multiple software tools for data pre- and postprocessing limits the application of these methods by experienced bioinformaticians. To address this issue, we have developed a pipeline to perform bacterial GWAS from a set of assemblies and annotations, with multiple phenotypes as targets. The associations are run using five sets of genetic variants: unitigs, gene presence/absence, rare variants (i.e. gene burden test), gene-cluster-specific
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