To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("edge")

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

edge

   

Extraction of Differential Gene Expression

Bioconductor version: 3.2

The edge package implements methods for carrying out differential expression analyses of genome-wide gene expression studies. Significance testing using the optimal discovery procedure and generalized likelihood ratio tests (equivalent to F-tests and t-tests) are implemented for general study designs. Special functions are available to facilitate the analysis of common study designs, including time course experiments. Other packages such as snm, sva, and qvalue are integrated in edge to provide a wide range of tools for gene expression analysis.

Author: John D. Storey, Jeffrey T. Leek and Andrew J. Bass

Maintainer: John D. Storey <jstorey at princeton.edu>, Andrew J. Bass <ajbass at princeton.edu>

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

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("edge")

Documentation

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

browseVignettes("edge")

 

PDF edge Package
PDF   Reference Manual
Text   NEWS
Text   LICENSE

Details

biocViews DataImport, DifferentialExpression, GeneExpression, MultipleComparison, Regression, Software, TimeCourse
Version 2.2.1
In Bioconductor since BioC 3.1 (R-3.2) (1 year)
License MIT + file LICENSE
Depends R (>= 3.1.0), Biobase
Imports methods, splines, sva, snm, jackstraw, qvalue(>= 1.99.0), MASS
LinkingTo
Suggests testthat, knitr, ggplot2, reshape2
SystemRequirements
Enhances
URL https://github.com/jdstorey/edge
BugReports https://github.com/jdstorey/edge/issues
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Package Source edge_2.2.1.tar.gz
Windows Binary edge_2.2.1.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) edge_2.2.0.tgz
Mac OS X 10.9 (Mavericks) edge_2.2.1.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/edge/tree/release-3.2
Package Short Url http://bioconductor.org/packages/edge/
Package Downloads Report Download Stats

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