A Robust Association Test Leveraging Unknown Genetic Interactions: Application to Cystic Fibrosis Lung Disease.

ABSTRACT: For complex traits such as lung disease in Cystic Fibrosis (CF), Gene x Gene or Gene x Environment interactions can impact disease severity but these remain largely unknown. Unaccounted-for genetic interactions introduce a distributional shift in the quantitative trait across the genotypic groups. Joint location and scale tests, or full distributional differences across genotype groups can account for unknown genetic interactions and increase power for gene identification compared with the conventional association test. Here we propose a new joint location and scale test (JLS), a quantile regression-basd JLS (qJLS), that addresses previous limitations. Specifically, qJLS is free of distributional assumptions, thus applies to non-Gaussian traits; is as powerful as the existing JLS tests und

SUBMITTER: Kim S 

PROVIDER: S-EPMC12172146 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature