Journal Article

GSEA-SNP: applying gene set enrichment analysis to SNP data from genome-wide association studies

Marit Holden, Shiwei Deng, Leszek Wojnowski and Bettina Kulle

in Bioinformatics

Volume 24, issue 23, pages 2784-2785
Published in print December 2008 | ISSN: 1367-4803
Published online October 2008 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btn516
GSEA-SNP: applying gene set enrichment analysis to SNP data from genome-wide association studies

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The power of genome-wide SNP association studies is limited, among others, by the large number of false positive test results. To provide a remedy, we combined SNP association analysis with the pathway-driven gene set enrichment analysis (GSEA), recently developed to facilitate handling of genome-wide gene expression data. The resulting GSEA-SNP method rests on the assumption that SNPs underlying a disease phenotype are enriched in genes constituting a signaling pathway or those with a common regulation. Besides improving power for association mapping, GSEA-SNP may facilitate the identification of disease-associated SNPs and pathways, as well as the understanding of the underlying biological mechanisms. GSEA-SNP may also help to identify markers with weak effects, undetectable in association studies without pathway consideration. The program is freely available and can be downloaded from our website.

Contact: bkulle@medisin.uio.no

Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  1146 words. 

Subjects: Bioinformatics and Computational Biology

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