Majority of GWAS risk loci localize to the noncoding genomic region with gene regulatory signal, suggesting that most trait/disease casual SNPs exert their phenotypic effects by altering gene expression. GWAS4D systematically analyzes GWAS summary data and identify context-specific regulatory variants by integrating latest multidimensional functional genomics resources and our recently published algorithms.
By incorporating roadmap 127 tissue/cell type-specific epigenomes data, GWAS4D uses our previously developed joint likelihood framework to measure the regulatory probability of genetic variants in a context-dependent manner. It also estimates possiable altered TFBSs using large-scale motif collections and annotates non-coding variant with comprehensive functional predictions.
Connecting non-coding variant to their gene targets under particular chromatin organization is crucial to understand variant regulatory mechanism. GWAS4D uniformly processes Hi-C data and reports significant interactions at 5kb resolution across tissues/cell types of multiple human organs and different development stages. It also equips a highly interactive visualization function for variant-target interaction.