GWAS3D: Detecting human regulatory variants by integrative analysis of genome-wide associations, chromosome interactions and histone modifications

Nucleic Acids Res. 2013 Jul;41(Web Server issue):W150-8. doi: 10.1093/nar/gkt456. Epub 2013 May 30.


Interpreting the genetic variants located in the regulatory regions, such as enhancers and promoters, is an indispensable step to understand molecular mechanism of complex traits. Recent studies show that genetic variants detected by genome-wide association study (GWAS) are significantly enriched in the regulatory regions. Therefore, detecting, annotating and prioritizing of genetic variants affecting gene regulation are critical to our understanding of genotype-phenotype relationships. Here, we developed a web server GWAS3D to systematically analyze the genetic variants that could affect regulatory elements, by integrating annotations from cell type-specific chromatin states, epigenetic modifications, sequence motifs and cross-species conservation. The regulatory elements are inferred from the genome-wide chromosome interaction data, chromatin marks in 16 different cell types and 73 regulatory factors motifs from the Encyclopedia of DNA Element project. Furthermore, we used these function elements, as well as risk haplotype, binding affinity, conservation and P-values reported from the original GWAS to reprioritize the genetic variants. Using studies from low-density lipoprotein cholesterol, we demonstrated that our reprioritizing approach was effective and cell type specific. In conclusion, GWAS3D provides a comprehensive annotation and visualization tool to help users interpreting their results. The web server is freely available at

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Chromosomes, Human / metabolism
  • Disease / genetics
  • Genetic Variation*
  • Genome-Wide Association Study
  • Histones / metabolism
  • Humans
  • Internet
  • Molecular Sequence Annotation
  • Nucleotide Motifs
  • Regulatory Elements, Transcriptional*
  • Software*
  • Transcription Factors / metabolism


  • Histones
  • Transcription Factors