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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

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...

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Detalles Bibliográficos
Autores principales: Burren, Oliver S., Guo, Hui, Wallace, Chris
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4296156/
https://www.ncbi.nlm.nih.gov/pubmed/25170024
http://dx.doi.org/10.1093/bioinformatics/btu571
Descripción
Sumario: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). Contact: chris.wallace@cimr.cam.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.