Two-sample tests on a graph

Bioconductor version: 2.9

DEGraph implements recent hypothesis testing methods which directly assess whether a particular gene network is differentially expressed between two conditions. This is to be contrasted with the more classical two-step approaches which first test individual genes, then test gene sets for enrichment in differentially expressed genes. These recent methods take into account the topology of the network to yield more powerful detection procedures. DEGraph provides methods to easily test all KEGG pathways for differential expression on any gene expression data set and tools to visualize the results.

Author: Laurent Jacob, Pierre Neuvial and Sandrine Dudoit

Maintainer: Laurent Jacob <laurent.jacob at>

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PDF R Script DEGraph: differential expression testing for gene networks
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biocViews Microarray, Bioinformatics, DifferentialExpression, GraphsAndNetworks
Depends R (>= 2.10.0), R.utils
Imports graph, KEGGgraph, lattice, mvtnorm, R.methodsS3, RBGL, Rgraphviz, rrcov, NCIgraph
Suggests corpcor, fields, graph, KEGGgraph, lattice, marray, RBGL, rrcov, Rgraphviz, NCIgraph
System Requirements
License GPL-3
Depends On Me
Imports Me
Suggests Me graphite
Version 1.6.0
Since Bioconductor 2.7 (R-2.12)

Package Downloads

Package Source DEGraph_1.6.0.tar.gz
Windows Binary (32- & 64-bit)
MacOS 10.5 (Leopard) binary DEGraph_1.6.0.tgz
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