To install this package, start R and enter:

## try http if https is not available
source("https://bioconductor.org/biocLite.R")
biocLite("factDesign")

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

factDesign

Factorial designed microarray experiment analysis

Bioconductor version: 3.1

This package provides a set of tools for analyzing data from a factorial designed microarray experiment, or any microarray experiment for which a linear model is appropriate. The functions can be used to evaluate tests of contrast of biological interest and perform single outlier detection.

Author: Denise Scholtens

Maintainer: Denise Scholtens <dscholtens at northwestern.edu>

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

Installation

To install this package, start R and enter:

## try http if https is not available
source("https://bioconductor.org/biocLite.R")
biocLite("factDesign")

Documentation

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

browseVignettes("factDesign")

 

PDF R Script factDesign
PDF   Reference Manual

Details

biocViews DifferentialExpression, Microarray, Software
Version 1.44.0
In Bioconductor since BioC 1.6 (R-2.1) or earlier (> 10.5 years)
License LGPL
Depends Biobase(>= 2.5.5)
Imports stats
LinkingTo
Suggests affy, genefilter, multtest
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Package Source factDesign_1.44.0.tar.gz
Windows Binary factDesign_1.44.0.zip
Mac OS X 10.6 (Snow Leopard) factDesign_1.44.0.tgz
Mac OS X 10.9 (Mavericks) factDesign_1.44.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/factDesign/tree/release-3.1
Package Short Url http://bioconductor.org/packages/factDesign/
Package Downloads Report Download Stats

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