Name
Title | ||
|---|---|---|
Visually integrating and exploring high throughput Phenome-Wide Association Study (PheWAS) results using PheWAS-View. |
Abstract | ||
|---|---|---|
Phenome-Wide Association Studies (PheWAS) can be used to investigate the association between single nucleotide polymorphisms (SNPs) and a wide spectrum of phenotypes. This is a complementary approach to Genome Wide Association studies (GWAS) that calculate the association between hundreds of thousands of SNPs and one or a limited range of phenotypes. The extensive exploration of the association between phenotypic structure and genotypic variation through PheWAS produces a set of complex and comprehensive results. Integral to fully inspecting, analysing, and interpreting PheWAS results is visualization of the data. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1186/1756-0381-5-5 | BioData mining |
Keywords | Field | DocType |
PheWAS, Phenome-Wide Association Study, Visualization | Data mining,Computer science,Genome-wide association study,Phenome,Genetic association,Single-nucleotide polymorphism,Bioinformatics | Journal |
Volume | Issue | ISSN |
5 | 1 | 1756-0381 |
Citations | PageRank | References |
7 | 0.89 | 1 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sarah A. Pendergrass | 1 | 42 | 9.20 |
| Scott M. Dudek | 2 | 206 | 26.27 |
| Dana C. Crawford | 3 | 137 | 14.54 |
| Marylyn D. Ritchie | 4 | 692 | 86.79 |