Integrating eQTL data with GWAS summary statistics in pathway-based analysis with application to schizophrenia.

ABSTRACT: Many genetic variants affect complex traits through gene expression, which can be exploited to boost statistical power and enhance interpretation in genome-wide association studies (GWASs) as demonstrated by the transcriptome-wide association study (TWAS) approach. Furthermore, due to polygenic inheritance, a complex trait is often affected by multiple genes with similar functions as annotated in gene pathways. Here, we extend TWAS from gene-based analysis to pathway-based analysis: we integrate public pathway collections, expression quantitative trait locus (eQTL) data and GWAS summary association statistics (or GWAS individual-level data) to identify gene pathways associated with complex traits. The basic idea is to weight the SNPs of the genes in a pathway based on their estimated cis-e

SUBMITTER: Wu C 

PROVIDER: S-EPMC5851843 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature