Regenie.QRS: computationally efficient whole-genome quantile regression at biobank scale.

ABSTRACT: Genotype-phenotype associations can be context-dependent and dynamic in nature leading to heterogeneity of genetic effects across different parts of the phenotype distribution. Quantile regression, an alternative to linear regression for continuous phenotypes, is particularly well suited for detecting and characterizing heterogeneous genotype-phenotype associations. Here we propose a novel and computationally efficient whole-genome quantile regression technique, Regenie.QRS, for biobank-scale GWAS data with genetic structure. Our approach first estimates the polygenic effect, and then incorporates this effect as an offset in the non-mixed quantile regression model. Our simulations demonstrate robust control of type I error and higher power to detect heterogeneous associations relative to l

SUBMITTER: Wang F 

PROVIDER: S-EPMC12247936 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature