Name
Title | ||
|---|---|---|
GSEA-SNP: applying gene set enrichment analysis to SNP data from genome-wide association studies. |
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. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1093/bioinformatics/btn516 | BIOINFORMATICS |
Keywords | Field | DocType |
genome wide association study | Genome,Association mapping,Phenotype,Biology,Tag SNP,Mechanism (biology),Genetic association,Single-nucleotide polymorphism,Bioinformatics,Genetics,SNP | Journal |
Volume | Issue | ISSN |
24 | 23 | 1367-4803 |
Citations | PageRank | References |
18 | 2.27 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marit Holden | 1 | 25 | 5.14 |
| Shiwei Deng | 2 | 18 | 2.27 |
| Leszek Wojnowski | 3 | 18 | 2.27 |
| Bettina Kulle | 4 | 18 | 2.27 |