Quantifying Metagenomic Strain Associations from Microbiomes with Anpan.

ABSTRACT: Genetic and genomic variation among microbial strains can dramatically influence their phenotypes and environmental impact, including on human health. However, inferential methods for quantifying these differences have been lacking. Strain-level metagenomic profiling data has several features that make traditional statistical methods challenging to use, including high dimensionality, extreme variation among samples, and complex phylogenetic relatedness. We present Anpan, a set of quantitative methods addressing three key challenges in microbiome strain epidemiology. First, adaptive filtering designed to interrogate microbial strain gene carriage is combined with linear models to identify strain-specific genetic elements associated with host health outcomes and other phenotypes. Second, phy

SUBMITTER: Ghazi AR 

PROVIDER: S-EPMC11741421 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature