To install this package, start R and enter:

## try http:// if https:// URLs are not supported

In most cases, you don't need to download the package archive at all.



This is the development version of gCMAP; for the stable release version, see gCMAP.

Tools for Connectivity Map-like analyses

Bioconductor version: Development (3.6)

The gCMAP package provides a toolkit for comparing differential gene expression profiles through gene set enrichment analysis. Starting from normalized microarray or RNA-seq gene expression values (stored in lists of ExpressionSet and CountDataSet objects) the package performs differential expression analysis using the limma or DESeq packages. Supplying a simple list of gene identifiers, global differential expression profiles or data from complete experiments as input, users can use a unified set of several well-known gene set enrichment analysis methods to retrieve experiments with similar changes in gene expression. To take into account the directionality of gene expression changes, gCMAPQuery introduces the SignedGeneSet class, directly extending GeneSet from the GSEABase package. To increase performance of large queries, multiple gene sets are stored as sparse incidence matrices within CMAPCollection eSets. gCMAP offers implementations of 1. Fisher's exact test (Fisher, J R Stat Soc, 1922) 2. The "connectivity map" method (Lamb et al, Science, 2006) 3. Parametric and non-parametric t-statistic summaries (Jiang & Gentleman, Bioinformatics, 2007) and 4. Wilcoxon / Mann-Whitney rank sum statistics (Wilcoxon, Biometrics Bulletin, 1945) as well as wrappers for the 5. camera (Wu & Smyth, Nucleic Acid Res, 2012) 6. mroast and romer (Wu et al, Bioinformatics, 2010) functions from the limma package and 7. wraps the gsea method from the mgsa package (Bauer et al, NAR, 2010). All methods return CMAPResult objects, an S4 class inheriting from AnnotatedDataFrame, containing enrichment statistics as well as annotation data and providing simple high-level summary plots.

Author: Thomas Sandmann <sandmann.t at>, Richard Bourgon <bourgon.richard at> and Sarah Kummerfeld <kummerfeld.sarah at>

Maintainer: Thomas Sandmann <sandmann.t at>

Citation (from within R, enter citation("gCMAP")):


To install this package, start R and enter:

## try http:// if https:// URLs are not supported


To view documentation for the version of this package installed in your system, start R and enter:



PDF R Script Creating reference datasets
PDF R Script gCMAP classes and methods
PDF   Reference Manual
Text   NEWS


biocViews Annotation, Microarray, Pathways, Software
Version 1.21.0
In Bioconductor since BioC 2.11 (R-2.15) (5 years)
License Artistic-2.0
Depends GSEABase, limma(>= 3.20.0)
Imports Biobase, methods, GSEAlm, Category, Matrix (>= 1.0.9), parallel, annotate, genefilter, AnnotationDbi, DESeq, grDevices, graphics, stats, utils, bigmemory, bigmemoryExtras(>= 1.1.2)
Suggests BiocGenerics, KEGG.db, reactome.db, RUnit, GO.db, mgsa
Depends On Me gCMAPWeb
Imports Me
Suggests Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Package Source gCMAP_1.21.0.tar.gz
Windows Binary
Mac OS X 10.11 (El Capitan) gCMAP_1.21.0.tgz
Source Repository git clone
Package Short Url
Package Downloads Report Download Stats

Documentation »


R / CRAN packages and documentation

Support »

Please read the posting guide. Post questions about Bioconductor to one of the following locations: