Leveraging gene co-expression patterns to infer trait-relevant tissues in genome-wide association studies.

ABSTRACT: Genome-wide association studies (GWASs) have identified many SNPs associated with various common diseases. Understanding the biological functions of these identified SNP associations requires identifying disease/trait relevant tissues or cell types. Here, we develop a network method, CoCoNet, to facilitate the identification of trait-relevant tissues or cell types. Different from existing approaches, CoCoNet incorporates tissue-specific gene co-expression networks constructed from either bulk or single cell RNA sequencing (RNAseq) studies with GWAS data for trait-tissue inference. In particular, CoCoNet relies on a covariance regression network model to express gene-level effect measurements for the given GWAS trait as a function of the tissue-specific co-expression adjacency matrix. With

SUBMITTER: Shang L 

PROVIDER: S-EPMC7192514 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature