Majority of GWAS risk loci, as well as those loci with moderate effect size, 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. An increasing number of studies have shown that associated variants for a particular trait/disease are significantly enriched in certain chromatin states of relevant tissues/cell types. Therefore, integrating genome-wide association signals with coordinated epigenomic profiles in a particular tissue/cell type provides a promising direction to fine-map casual regulatory variants. In addition, connecting regulatory variant to their gene targets is difficult and poorly predicted by computational methods, especially under dynamic cellular environment. However, recent international genome projects, like ENCODE and 4D Nucleome project, continuously generate genome-wide chromosome conformation capture data (including Hi-C, ChIA-PET, etc.) on widespread tissues/cell types and different development stages, which provides great opportunities to study the effect of regulatory variant at spatiotemporal level.

GWAS4D (http://mulinlab.tmu.edu.cn/gwas4d) is designed to systematically analyze GWAS summary data and identify context-specific regulatory variants by integrating latest multidimensional functional genomics resources and our recently published algorithms. In general, the web server introduces following six major features: (1) prioritizes the regulatory variant by cepip (Li MJ et.al. Genome Biology. 2017); (2) incorporates 127 tissue/cell type-specific epigenomes data; (3) integrates and refines TF motifs from eight public resources for 1480 transcriptional regulators; (4) uniformly processes Hi-C data and calls significant interactions at 5kb resolution across 45 tissues/cell types, links variant to its target regions; (5) annotates non-coding variant with comprehensive functional annotations; (6) equips a highly interactive visualization function for variant-target interaction.

GWAS4D was developed by mulinlab@Research Center of Basic Medical Sciences, Tianjin Medical University. If you have questions or suggestions to this platform, please contact us through mulin0424.liATgmail.com.

Please cite our work from: Huang D, Yi X, Zhang S, Zheng Z, Wang P, Xuan C, Sham PC, Wang J, Li MJ*. GWAS4D: Multidimensional analysis of context-specific regulatory variant for human complex diseases and traits. Nucleic Acids Res. 2018; gky407

Updates:
news: 15/09/2018 GWAS4D now supports to download annotation information of all prioritized variants in corresponding table page.
18/04/2018 GWAS4D now can estimate likely causal tissue/cell type upon input GWAS significant signals of particular disease.
13/04/2018 GWAS4D now can support user-defined tissue/cell-type specific epigenome data (narrow peak) and chromosome interaction data.
10/04/2018 Add annotations download function for each prioritized SNV.
14/02/2018 Add CistromeDB human TF ChIP-seq annotation and FANTOM CAT CAGE annotation.
08/02/2018 Update 15 HiC interaction data from GEO.
30/12/2017 GWAS4D now can directly link variant to epilogos, HaploReg v4.1, RegulomeDB v1.1, rSNPBase v3.1 and 3DSNP v1.0.
24/12/2017 First release of GWAS4D.