Overview

We developed a novel approach to annotating functional regulatory regions that integrates sequence information (e.g., position weight matrices) with DNaseI footprinting data to predict the impact of a sequence change on TF binding. We identified over 3 million regulatory variants predicted to affect active regulatory regions for a panel of TFs in over 650 cell-types.

Moyerbrailean GA, Kalita CA, Harvey CT, Wen X, Luca F, Pique-Regi R. (2016) Which Genetics Variants in DNase-Seq Footprints Are More Likely to Alter Binding? PLoS Genet 12(2): e1005875. doi: 10.1371/journal.pgen.1005875

USCS Browser Hub

We have provided annotations as a brower hub to facilitate viewing of the data. There are two tracks: 1) regulatory variants, and 2) regulatory footprints.

Launch UCSC browser with hub (new window)

Data

CentiSNPs Compendium

For each transcription factor motif we summarized all SNPs in footprints accross all ENCODE and Roadmap Epigenome (see README in the link below for more details)

• Compendium by TF motif (for each motif file)

Regulatory Regions

The footprint annotation data is also available as bed files, separated both by cell-type and TF motif. Each file is formatted as bed9+ files, with four additional data fields: SNP position, 1KG reference allele, 1KG alternate allele, prior log ratio for binding of the reference allele, and the prior LR for binding of the alternate allele. For TFBS without a polymorphism, the SNP position is listed as "0" and the prior LR for the reference allele is repeated.

• Files by cell-type (for each cell-tpe, all motifs are reported)
• Files by TF motif (for each motif file, all tissues are reported)

Supplemental Files

The supplemental excel files associated with the above publications can be downloaded here:

• Tables
• Code

Additional Files

• Set of 1KG SNPs used
• Annotations for DAP as used in DAP (Wen et al. 2016, PLoS Genetics) and TORUS

Acknowledgements

• The NIH and AHA, for funding supporting this research
• The ENCODE Project and the Roadmap Epigenmics Project, for their DNase-seq data
• Joe Pickrell for his assistance with fgwas
• Wayne State University High Performance Computing Grid
• Members of the Luca and Pique labs for helpful discussions.

Links to related resources

• The QuASAR package - Quantitative Allele-Specific Analysis of Reads
• The QuASAR publication
• The CENTIPEDE software package
• The ENCODE Data Coordination Center at UCSC
• The Roadmap Epigenomics Data Repository

Contact Information

For questions related to the hub or the data, please contact:

• Roger Pique-Regi: rpique@wayne.edu
• Francesca Luca: fluca@wayne.edu