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PMID: 18854360 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't

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

Bioinformatics (Oxford, England) ·Vol. 24 ·No. 23 ·2008-12-01 ·Pages 2784-5

Holden M, Deng S, Wojnowski L, Kulle B

Abstract

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.

MeSH Terms
Genome Genome-Wide Association Study/methods Polymorphism, Single Nucleotide/genetics Software
Authors & Affiliations
4 authors, click to expand affiliations / ORCID
Holden Marit
Norwegian Computing Center, Oslo, Norway, Department of Pharmacology, University of Mainz, Mainz, Germany.
Deng Shiwei
Wojnowski Leszek
Kulle Bettina
Article Info
Journal
Bioinformatics (Oxford, England)
Abbr.
Bioinformatics
ISSN
1367-4811
Published
2008-12-01
Epub
2008-00-14
Pages
2784-5
Language
English
Region
England
NLM ID
9808944
Subset
IM
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