A clustering linear combination method for multiple phenotype association studies based on GWAS summary statistics.

ABSTRACT: There is strong evidence showing that joint analysis of multiple phenotypes in genome-wide association studies (GWAS) can increase statistical power when detecting the association between genetic variants and human complex diseases. We previously developed the Clustering Linear Combination (CLC) method and a computationally efficient CLC (ceCLC) method to test the association between multiple phenotypes and a genetic variant, which perform very well. However, both of these methods require individual-level genotypes and phenotypes that are often not easily accessible. In this research, we develop a novel method called sCLC for association studies of multiple phenotypes and a genetic variant based on GWAS summary statistics. We use the LD score regression to estimate the correlation matrix a

SUBMITTER: Wang M 

PROVIDER: S-EPMC9975197 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature