CoGAPS
Coordinated Gene Activity in Pattern Sets
Bioconductor version: 2.7
Coordinated Gene Activity in Pattern Sets (CoGAPS) infers biological processes which are active in individual gene sets from corresponding microarray measurements. CoGAPS achieves this inference by combining a MCMC matrix decomposition algorithm (GAPS) with a novel statistic inferring activity on gene sets.
Author: Elana J. Fertig
Maintainer: Elana J. Fertig <ejfertig at jhmi.edu>, Michael F. Ochs <mfo at jhu.edu>
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("CoGAPS")
To cite this package in a publication, start R and enter:
citation("CoGAPS")
Documentation
| R Script | GAPS/CoGAPS Users Manual | |
| Reference Manual |
Details
| biocViews | GeneExpression, Microarray, Bioinformatics |
| Depends | R (>= 2.9.0), rjags(>= 2.1.0), R.utils (>= 1.2.4) |
| Imports | graphics, grDevices, methods, stats, utils |
| Suggests | |
| System Requirements | GAPS-JAGS (==1.0.2) |
| License | GPL (== 2) |
| URL | http://www.cancerbiostats.onc.jhmi.edu/cogaps.cfm |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Version | 1.0.0 |
| Since | Bioconductor 2.7 (R-2.12) |
Package Downloads
| Package Source | CoGAPS_1.0.0.tar.gz |
| Windows Binary | |
| MacOS 10.5 (Leopard) binary | |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Annotation
- Variants
- Flow Cytometry and other assays
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