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arXiv · 1404.4482

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

Oliver S Burren·Hui Guo·Chris Wallace
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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.

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Oliver S Burren, Hui Guo, Chris Wallace. 2014-04-17. 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. https://doi.org/10.1093/bioinformatics%2Fbtu571

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