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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 extended a non-parametric SNP set enrichment method to test for enrichment of GWAS signals 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 identify enrichment of type 1 diabetes (T1D) GWAS associations near genes that are targets for the transcription factors IKZF3, BATF and ESRRA. IKZF3 lies in a known T1D susceptibility region, while BATF and ESRRA overlap other immune disease susceptibility regions, validating our approach and suggesting novel avenues of research for T1D.Availability and implementation
VSEAMS is available for download (http://github.com/ollyburren/vseams).
SUBMITTER: Burren OS
PROVIDER: S-EPMC4296156 | biostudies-literature | 2014 Dec
REPOSITORIES: biostudies-literature
Burren Oliver S OS Guo Hui H Wallace Chris C
Bioinformatics (Oxford, England) 20140827 23
<h4>Motivation</h4>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.<h4>Results</h4>We extended a non-parametric SNP set enrichment method to test for enrichment of GWAS signals in functionally defined loci to a situation where only GWAS P-values are available. The approach is implemented in VSEAMS, a freely available software ...[more]