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DrugVsDisease
Comparison of disease and drug profiles using Gene set Enrichment Analysis
Bioconductor version: 3.0
This package generates ranked lists of differential gene expression for either disease or drug profiles. Input data can be downloaded from Array Express or GEO, or from local CEL files. Ranked lists of differential expression and associated p-values are calculated using Limma. Enrichment scores (Subramanian et al. PNAS 2005) are calculated to a reference set of default drug or disease profiles, or a set of custom data supplied by the user. Network visualisation of significant scores are output in Cytoscape format.
Author: C. Pacini
Maintainer: j. Saez-Rodriguez <saezrodriguez at ebi.ac.uk>
Citation (from within R,
enter citation("DrugVsDisease")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("DrugVsDisease")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("DrugVsDisease")
| R Script | DrugVsDisease | |
| Reference Manual |
Details
| biocViews | Clustering, GeneExpression, Microarray, Software |
| Version | 2.6.0 |
| In Bioconductor since | BioC 2.12 (R-3.0) |
| License | GPL-3 |
| Depends | R (>= 2.10), affy, limma, biomaRt, ArrayExpress, GEOquery, DrugVsDiseasedata, cMap2data, qvalue |
| Imports | annotate, hgu133a.db, hgu133a2.db, hgu133plus2.db, RUnit, BiocGenerics, xtable |
| LinkingTo | |
| Suggests | |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | DrugVsDisease_2.6.0.tar.gz |
| Windows Binary | DrugVsDisease_2.6.0.zip |
| Mac OS X 10.6 (Snow Leopard) | DrugVsDisease_2.6.0.tgz |
| Mac OS X 10.9 (Mavericks) | DrugVsDisease_2.6.0.tgz |
| Browse/checkout source | (username/password: readonly) |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Counting Reads for Differential Expression (parathyroideSE vignette)
- Annotation
- Annotating Variants
- Annotating Ranges
- Flow Cytometry and other assays
- Candidate Binding Sites for Known Transcription Factors
- Cloud-enabled cis-eQTL search and annotation
- RNA-Seq workflow: gene-level exploratory analysis and differential expression
- Changing genomic coordinate systems with rtracklayer::liftOver
- Mass spectrometry and proteomics data analysis
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