  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.
