Accurate genetic and environmental covariance estimation with composite likelihood in genome-wide association studies.

ABSTRACT: Genetic and environmental covariances between pairs of complex traits are important quantitative measurements that characterize their shared genetic and environmental architectures. Accurate estimation of genetic and environmental covariances in genome-wide association studies (GWASs) can help us identify common genetic and environmental factors associated with both traits and facilitate the investigation of their causal relationship. Genetic and environmental covariances are often modeled through multivariate linear mixed models. Existing algorithms for covariance estimation include the traditional restricted maximum likelihood (REML) method and the recent method of moments (MoM). Compared to REML, MoM approaches are computationally efficient and require only GWAS summary statistics. Howe

SUBMITTER: Gao B 

PROVIDER: S-EPMC7808654 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature