Published in
Oxford University Press (OUP), Bioinformatics, 23(30), p. 3342-3348
DOI: 10.1093/bioinformatics/btu571
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- ORCID
- Oxford University Press (OUP) | PDF
- [www.ncbi.nlm.nih.gov] | PDF
- [www.manchester.ac.uk]
- [arxiv.org] | PDF
- [arxiv.org] | PDF
- [europepmc.org] | PDF
- [www.researchgate.net]
- [www.ncbi.nlm.nih.gov] | PDF
- [www.repository.cam.ac.uk] | PDF
Tools
VSEAMS: A pipeline for variant set enrichment analysis using summary GWAS data identifies IKZF3, BATF and ESRRA as key transcription factors in type 1 diabetes
,
Hui Guo ,
Chris Wallace,
Guo H Wallace C. Burren Os
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Abstract
Motivation: Genome-wide association studies (GWAS) have identified many loci implicated in disease susceptibility. Integration of GWAS summary statistics (p values) and functional genomic datasets should help to elucidate mechanisms. Results: We describe the extension of a previously described non-parametric method to test whether GWAS signals are enriched in functionally defined loci to a situation where only GWAS p values are available. The approach is implemented in VSEAMS, a freely available software pipeline. We use VSEAMS to integrate functional gene sets defined via transcription factor knock down experiments with GWAS results for type 1 diabetes and find variant set enrichment in gene sets associated with IKZF3, BATF and ESRRA. IKZF3 lies in a known T1D susceptibility region, whilst BATF and ESRRA overlap other immune disease susceptibility regions, validating our approach and suggesting novel avenues of research for type 1 diabetes. Availability and implementation: VSEAMS is available for download http://github.com/ollyburren/vseams.