aurora: a machine learning gwas tool for analyzing microbial habitat adaptation

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Abstract

A primary goal of microbial genome-wide association studies is identifying genomic variants associated with a particular habitat. Existing tools fail to identify known causal variants if the analyzed trait shaped the phylogeny. Furthermore, due to inclusion of allochthonous strains or metadata errors, the stated sources of strains in public databases are often incorrect, and strains may not be adapted to the habitat from which they were isolated. We describe a new tool, aurora, that identifies autochthonous strains and the genes associated with habitats while acknowledging the potential role of the habitat adaptation trait in shaping phylogeny.

Original languageEnglish
Article number66
JournalGenome Biology
Volume26
Issue number1
DOIs
Publication statusPublished - Dec 2025

Keywords

  • Allochthonous
  • Autochthonous
  • GWAS
  • Habitat adaptation
  • Lactiplantibacillus plantarum
  • Limosilactobacillus reuteri
  • Machine learning
  • Microbial GWAS
  • Mycobacterium paratuberculosis
  • Salmonella Typhimurium

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