Efficient and accurate framework for genome-wide gene-environment interaction analysis in large-scale biobanks.

ABSTRACT: Gene-environment interaction (G×E) analysis elucidates the interplay between genetic and environmental factors. Genome-wide association studies (GWAS) have expanded to encompass complex traits like time-to-event and ordinal traits, which provide richer phenotypic information. However, most existing scalable approaches focus only on quantitative or binary traits. Here we propose SPAGxE_CCT, a scalable and accurate framework for diverse trait types. SPAGxE_CCT fits a genotype-independent model and employs a hybrid strategy including saddlepoint approximation (SPA) for accurate p value calculation, especially for low-frequency variants and unbalanced phenotypic distributions. We extend SPAGxE_CCT to SPAGxEmix_CCT, which accounts for population stratific

SUBMITTER: Ma Y 

PROVIDER: S-EPMC11955004 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature