Coupled mixed model for joint genetic analysis of complex disorders with two independently collected data sets.

ABSTRACT:

Background

In the last decade, Genome-wide Association studies (GWASs) have contributed to decoding the human genome by uncovering many genetic variations associated with various diseases. Many follow-up investigations involve joint analysis of multiple independently generated GWAS data sets. While most of the computational approaches developed for joint analysis are based on summary statistics, the joint analysis based on individual-level data with consideration of confounding factors remains to be a challenge.

Results

In this study, we propose a method, called Coupled Mixed Model (CMM), that enables a joint GWAS analysis on two independently collected sets of GWAS data with different phenotypes. The CMM method does not require the data sets to have the same phenotypes as i

SUBMITTER: Wang H 

PROVIDER: S-EPMC7866684 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature