POUTINE

POUTINE implements a homoplasy-counting approach to detect genotype-phenotype associations in genome-wide association studies, improving identification of causal variants in microbial genomes where linkage disequilibrium and clonality confound allele-counting methods.

Key Features:

• Homoplasy-Based Approach: Leverages homoplastic mutations rather than allele identity-by-state to identify convergent variants associated with phenotypes.
• Reduction of False Positives: Mitigates false-positive associations arising from linkage disequilibrium in weakly recombining or clonal populations.
• Clarity in Causal Variant Identification: Helps distinguish likely causal variants from background linked variation by focusing on recurrent, independent mutation events.

Scientific Applications:

• Microbial GWAS: Applied to genome-wide association studies of microbes where strong clonality and weak recombination obscure classical allele-counting signals.
• Mycobacterium tuberculosis antibiotic-resistance studies: Has been used on M. tuberculosis genome datasets and antibiotic-resistance phenotypes to reveal association signals against background noise.

Methodology:

POUTINE identifies and counts homoplastic mutations to detect genotype-phenotype associations, shifting analysis away from allele-counting approaches that are confounded by linkage disequilibrium.