Name
Abstract | ||
|---|---|---|
Summary: Extracting biological insight from microarray data is important but challenging. Here we describe TAPPA, a java-based tool, for identification of phenotype-associated genetic pathways utilizing the pathway topological measures. This is achieved by first calculating a Pathway Connectivity Index (PCI) for each pathway, followed by evaluating its correlation to the phenotypic variation. Our PCI definition not only efficiently captures the contributions from genes that show subtle but consistent changes in expression, but also naturally overweighs the hub genes that interact with a large number of other genes in the pathway. TAPPA also allows evaluation of sub-modules within a pathway and their association to phenotypes. Availability: TAPPA and data for Figure 1 are freely available from http://watson.mcgee.mcw.edu:8080/similar to sgao Contact: sgao@mcw.edu Supplementary information: Supplementary data are available at Bioinformatics online. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1093/bioinformatics/btm460 | BIOINFORMATICS |
Keywords | Field | DocType |
associate editor: olga troyanskaya,genetics,indexation,microarray data | Topology,Gene,Phenotype,Biology,Proteome,Microarray analysis techniques,Bioinformatics,Genetics,Topological index,Gene expression profiling | Journal |
Volume | Issue | ISSN |
23 | 22 | 1367-4803 |
Citations | PageRank | References |
12 | 0.78 | 3 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shouguo Gao | 1 | 50 | 2.65 |
| Xujing Wang | 2 | 90 | 8.54 |