Coupled mixed model for joint genetic analysis of complex disorders with two independently collected data sets
Year: 2021
Type: article
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 it aims to infer the unknown phenotypes using a set of multivariate sparse mixed models. Moreover, CMM addresses the confounding variables due to population stratification, family structures, and cryptic relatedness, as well as those arising during data collection such as batch effects that frequently appear in joint genetic studies. We evaluate the performance of CMM using simulation experiments. In real data analysis, we illustrate the utility of CMM by an application to evaluating common genetic associations for Alzheimer's disease and substance use disorder using datasets independently collected for the two complex human disorders. Comparison of the results with those from previous experiments and analyses supports the utility of our method and provides new insights into the diseases. The software is available at https://github.com/HaohanWang/CMM .
Source: BMC Bioinformatics
Institutions: Carnegie Mellon University, University of Pittsburgh
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,490
Awards: G104586243, Sample-specific Models for Molecular Portraits of Diseases in Precision Medicine, G2189010064, G2423387114, G2835601961, G29951154, G3216574877, G4119534169, G4475667458, G5324093878, EFFECTS OF TRAUMATIC BRAIN INJURY (TBI) AND POST TRAUMATIC STRESS DISORDER (PTSD) ON ALZHEIMER'S DISEASE (AD) IN VETERANS USING IMAGING AND BIOMARKERS IN THE AD NEUROIMAGING INITIATIVE (ADNI)", NIDA Center of Excellence OF Computational Drug Abuse Research (CDAR), Alzheimer's Disease Neuroimaging Initiative, G5850682332, Time/Space-Varying Networks of Molecular Interactions: A New Paradigm for Studyin, G764699806, G8895907669, G9000039018, G9000074849, G9000122335
OpenAlex ID: W3129100339