SPA_GRM: effectively controlling for sample relatedness in large-scale genome-wide association studies of longitudinal traits.

ABSTRACT: Sample relatedness is a major confounder in genome-wide association studies (GWAS), potentially leading to inflated type I error rates if not appropriately controlled. A common strategy is to incorporate a random effect related to genetic relatedness matrix (GRM) into regression models. However, this approach is challenging for large-scale GWAS of complex traits, such as longitudinal traits. Here we propose a scalable and accurate analysis framework, SPA_GRM, which controls for sample relatedness via a precise approximation of the joint distribution of genotypes. SPA_GRM can utilize GRM-free models and thus is applicable to various trait types and statistical methods, including linear mixed models and generalized estimation equations for longitudinal traits. A hybrid st

SUBMITTER: Xu H 

PROVIDER: S-EPMC11803118 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature