Network-assisted analysis of GWAS data identifies a functionally-relevant gene module for childhood-onset asthma.

ABSTRACT: The number of genetic factors associated with asthma remains limited. To identify new genes with an undetected individual effect but collectively influencing asthma risk, we conducted a network-assisted analysis that integrates outcomes of genome-wide association studies (GWAS) and protein-protein interaction networks. We used two GWAS datasets, each consisting of the results of a meta-analysis of nine childhood-onset asthma GWASs (5,924 and 6,043 subjects, respectively). We developed a novel method to compute gene-level P-values (fastCGP), and proposed a parallel dense-module search and cross-selection strategy to identify an asthma-associated gene module. We identified a module of 91 genes with a significant joint effect on childhood-onset asthma (P < 10^-5). This module contai

SUBMITTER: Liu Y 

PROVIDER: S-EPMC5430538 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature