[med-svn] [SCM] r-bioc-edger branch, master, updated. upstream/2.2.5-20-g11ea982

[Charles Plessy]

The following commit has been merged in the master branch:
commit 11ea98231f0d72515f71b17c4abd7d5d17da227f
Author: Charles Plessy <plessy at debian.org>
Date:   Thu Jun 2 14:52:04 2011 +0900

    Intend to package edgeR.
    
    URL: http://bugs.debian.org/628882

diff --git a/debian/changelog b/debian/changelog
index a79368c..79aadef 100644
--- a/debian/changelog
+++ b/debian/changelog
@@ -1,5 +1,5 @@
 r-bioc-edger (2.2.5-1) UNRELEASED; urgency=low
 
-  * Initial release (Closes: #nnnn)  <nnnn is the bug number of your ITP>
+  * Initial release (Closes: #628882)
 
  -- Charles Plessy <plessy at debian.org>  Fri, 15 Apr 2011 13:20:43 +0900
diff --git a/debian/control b/debian/control
index 65cc288..35db4f6 100644
--- a/debian/control
+++ b/debian/control
@@ -16,7 +16,9 @@ Architecture: all
 Depends: ${R:Depends}, r-bioc-biobase, r-bioc-limma, ${misc:Depends}
 Suggests: r-cran-mass
 Description: Empirical analysis of digital gene expression data in R
- Differential expression analysis of RNA-seq and digital gene expression
- profiles with biological replication. Uses empirical Bayes estimation and exact
- tests based on the negative binomial distribution. Also useful for differential
- signal analysis with other types of genome-scale count data.
+ Bioconductor package for differential expression analysis of whole
+ transcriptome sequencing (RNA-seq) and digital gene expression
+ profiles with biological replication. It uses empirical Bayes
+ estimation and exact tests based on the negative binomial
+ distribution. It is also useful for differential signal analysis with
+ other types of genome-scale count data.

-- 
empirical analysis of digital gene expression data in R