Discover novel disease-associated genes based on regulatory networks of long-range chromatin interactions.

ABSTRACT: Identifying genes and non-coding genetic variants that are genetically associated with complex diseases and the underlying mechanisms is one of the most important questions in functional genomics. Due to the limited statistical power and the lack of mechanistic modeling, traditional genome-wide association studies (GWAS) is restricted to fully address this question. Based on multi-omics data integration, cell-type specific regulatory networks can be built to improve GWAS analysis. In this study, we developed a new computational infrastructure, APRIL, to incorporate 3D chromatin interactions into regulatory network construction, which can extend the networks to include long-range cis-regulatory links between non-coding GWAS SNPs and target genes. Combinatorial transcription factors that co-

SUBMITTER: Wang H 

PROVIDER: S-EPMC8026483 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature