PLEIO: a method to map and interpret pleiotropic loci with GWAS summary statistics.

ABSTRACT: Identifying and interpreting pleiotropic loci is essential to understanding the shared etiology among diseases and complex traits. A common approach to mapping pleiotropic loci is to meta-analyze GWAS summary statistics across multiple traits. However, this strategy does not account for the complex genetic architectures of traits, such as genetic correlations and heritabilities. Furthermore, the interpretation is challenging because phenotypes often have different characteristics and units. We propose PLEIO (Pleiotropic Locus Exploration and Interpretation using Optimal test), a summary-statistic-based framework to map and interpret pleiotropic loci in a joint analysis of multiple diseases and complex traits. Our method maximizes power by systematically accounting for genetic correlations

SUBMITTER: Lee CH 

PROVIDER: S-EPMC7820744 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature