A computational approach for identification of core modules from a co-expression network and GWAS data

STAR Protoc. 2021 Aug 21;2(3):100768. doi: 10.1016/j.xpro.2021.100768. eCollection 2021 Sep 17.

Abstract

This protocol describes the application of the "omnigenic" model of the genetic architecture of complex traits to identify novel "core" genes influencing a disease-associated phenotype. Core genes are hypothesized to directly regulate disease and may serve as therapeutic targets. This protocol leverages GWAS data, a co-expression network, and publicly available data, including the GTEx database and the International Mouse Phenotyping Consortium Database, to identify modules enriched for genes with "core-like" characteristics. For complete details on the use and execution of this protocol, please refer to Sabik et al. (2020).

Keywords: Bioinformatics; Genetics; Genomics; RNAseq; Systems biology.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Computational Biology / methods*
  • Gene Ontology
  • Gene Regulatory Networks*
  • Genome-Wide Association Study / methods*
  • Genome-Wide Association Study / statistics & numerical data
  • Linkage Disequilibrium
  • Mice
  • Phenotype
  • Polymorphism, Single Nucleotide
  • Sequence Analysis, RNA