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. © The Author 2008. Published by Oxford University Press. All rights reserved.
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CITATION STYLE
Holden, M., Deng, S., Wojnowski, L., & Kulle, B. (2008). GSEA-SNP: Applying gene set enrichment analysis to SNP data from genome-wide association studies. Bioinformatics, 24(23), 2784–2785. https://doi.org/10.1093/bioinformatics/btn516
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