====== DEGraph software home page ======

===== Overview =====

  * **Title**: Two-sample tests on a graph
  * **Language**: ''R''
  * **Description**: 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.
  * **Authors**: [[http://lbbe.univ-lyon1.fr/-Jacob-Laurent-.html|Laurent Jacob]] and [[members:pneuvial:welcome|Pierre Neuvial]]
  * **Maintainer**: [[http://lbbe.univ-lyon1.fr/-Jacob-Laurent-.html|Laurent Jacob]]
  * **Availability**: get [[http://www.bioconductor.org/packages/release/bioc/html/DEGraph.html|DEGraph]] from Bioconductor
  * **References**: Jacob, L., Neuvial, P., & Dudoit, S. (2012). [[https://projecteuclid.org/euclid.aoas/1339419608|More power via graph-structured tests for differential expression of gene networks]]. //The Annals of Applied Statistics//, 6(2), 561-600.

=====  Installation =====

To install this package, start ''R'' and enter:

<code>
## try http if https is not available
source("https://bioconductor.org/biocLite.R")
biocLite("DEGraph")
</code>

=====  Documentation =====

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

<code>
browseVignettes("DEGraph")
</code>