Journal
NUCLEIC ACIDS RESEARCH
Volume 46, Issue W1, Pages W114-W120Publisher
OXFORD UNIV PRESS
DOI: 10.1093/nar/gky407
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Funding
- National Natural Science Foundation of China [31701143]
- Talent Excellence Program from Tianjin Medical University
- Tianjin Medical University
- Thousand Youth Talents Plan of Tianjin
- Discipline Development Fund from Tianjin Medical University
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Genome-wide association studies have generated over thousands of susceptibility loci for many human complex traits, and yet formost of these associations the true causal variants remain unknown. Tissue/cell type-specific prediction and prioritization of noncoding regulatory variants will facilitate the identification of causal variants and underlying pathogenic mechanisms for particular complex diseases and traits. By leveraging recent large-scale functional genomics/epigenomics data, we develop an intuitive web server, GWAS4D (http://mulinlab.tmu.edu.cn/gwas4d or http://mulinlab.org/gwas4d), that systematically evaluates GWAS signals and identifies context-specific regulatory variants. The updated web server includes six major features: (i) updates the regulatory variant prioritization method with our new algorithm; (ii) incorporates 127 tissue/cell type-specific epigenomes data; (iii) integrates motifs of 1480 transcriptional regulators from 13 public resources; (iv) uniformly processes Hi-C data and generates significant interactions at 5 kb resolution across 60 tissues/cell types; (v) adds comprehensive non-coding variant functional annotations; (vi) equips a highly interactive visualization function for SNP-target interaction. Using a GWAS fine-mapped set for 161 coronary artery disease risk loci, we demonstrate that GWAS4D is able to efficiently prioritize disease-causal regulatory variants.
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