Tissue-specific network-based genome wide study of amygdala imaging phenotypes to identify functional interaction modules.

ABSTRACT:

Motivation

Network-based genome-wide association studies (GWAS) aim to identify functional modules from biological networks that are enriched by top GWAS findings. Although gene functions are relevant to tissue context, most existing methods analyze tissue-free networks without reflecting phenotypic specificity.

Results

We propose a novel module identification framework for imaging genetic studies using the tissue-specific functional interaction network. Our method includes three steps: (i) re-prioritize imaging GWAS findings by applying machine learning methods to incorporate network topological information and enhance the connectivity among top genes; (ii) detect densely connected modules based on interactions among top re-prioritized genes; and (iii) identify phenotype-re

SUBMITTER: Yao X 

PROVIDER: S-EPMC6410887 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature