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. 2015 Aug 1;31(15):2591-4.
doi: 10.1093/bioinformatics/btv150. Epub 2015 Mar 24.

EW_dmGWAS: edge-weighted dense module search for genome-wide association studies and gene expression profiles

Quan Wang  1 , Hui Yu  1 , Zhongming Zhao  2 , Peilin Jia  3
Affiliations

EW_dmGWAS: edge-weighted dense module search for genome-wide association studies and gene expression profiles

Quan Wang et al. Bioinformatics. .

Abstract

We previously developed dmGWAS to search for dense modules in a human protein-protein interaction (PPI) network; it has since become a popular tool for network-assisted analysis of genome-wide association studies (GWAS). dmGWAS weights nodes by using GWAS signals. Here, we introduce an upgraded algorithm, EW_dmGWAS, to boost GWAS signals in a node- and edge-weighted PPI network. In EW_dmGWAS, we utilize condition-specific gene expression profiles for edge weights. Specifically, differential gene co-expression is used to infer the edge weights. We applied EW_dmGWAS to two diseases and compared it with other relevant methods. The results suggest that EW_dmGWAS is more powerful in detecting disease-associated signals.

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