GREGOR: evaluating global enrichment of trait-associated variants in epigenomic features using a systematic, data-driven approach

Bioinformatics. 2015 Aug 15;31(16):2601-6. doi: 10.1093/bioinformatics/btv201. Epub 2015 Apr 16.


Motivation: The majority of variation identified by genome wide association studies falls in non-coding genomic regions and is hypothesized to impact regulatory elements that modulate gene expression. Here we present a statistically rigorous software tool GREGOR (Genomic Regulatory Elements and Gwas Overlap algoRithm) for evaluating enrichment of any set of genetic variants with any set of regulatory features. Using variants from five phenotypes, we describe a data-driven approach to determine the tissue and cell types most relevant to a trait of interest and to identify the subset of regulatory features likely impacted by these variants. Last, we experimentally evaluate six predicted functional variants at six lipid-associated loci and demonstrate significant evidence for allele-specific impact on expression levels. GREGOR systematically evaluates enrichment of genetic variation with the vast collection of regulatory data available to explore novel biological mechanisms of disease and guide us toward the functional variant at trait-associated loci.

Availability and implementation: GREGOR, including source code, documentation, examples, and executables, is available at


Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms*
  • Epigenomics*
  • Genetic Variation / genetics*
  • Genome-Wide Association Study*
  • Genomics / methods
  • Humans
  • Organ Specificity
  • Phenotype
  • Programming Languages
  • Quantitative Trait Loci*
  • Regulatory Sequences, Nucleic Acid / genetics*
  • Software*