Causal-TWAS: a new method for integrative analysis of expression QTLs and GWAS detects causal genes of complex traits
Xin He, PhD
Associate Professor | Department of Human Genetics
University of Chicago
WHEN: Wednesday, February 28, 2024, from 3:30 to 4:30 p.m.
WHERE: hybrid | 2001 McGill College Avenue, Rm 1201;
NOTE: Dr. He will be presenting from Chicago
Abstract
Genome-wide association studies (GWAS) have been successful in mapping associations of genetic variants with complex traits, but the causal variants and genes underlying these associations are often unknown. Researchers have often used expression Quantitative Trait Loci (eQTLs) data to nominate putative risk genes from GWAS. But existing methods for integrative analysis of eQTLs and GWAS are susceptible to false positive findings, due to pleiotropic effects of eQTLs. We developed a new method, causal-TWAS (cTWAS) to address this challlenge. It borrows ideas from statistical fine-mapping and allows us to adjust all pleiotropic effects. cTWAS showed calibrated false discovery rates in simulations, and its application on several common traits discovered novel candidate genes.
Speaker bio
Dr. Xin He is an Associate Professor at Department of Human Genetics, University of Chicago. Dr. He is interested in how genetic variations lead to phenotypic effects. His research focues on developing novel computational methods to detect risk genes of complex dieases and gain deeper insights into the disease mechanisms. His lab has published papers in leading journals such as Science, Nature Genetics and Nature Methods. Link: