factDesign

Factorial designed microarray experiment analysis

Bioconductor version: Release (3.20)

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 (version "4.4") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("factDesign")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

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

browseVignettes("factDesign")

factDesign	PDF	R Script
Reference Manual	PDF

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	DifferentialExpression, Microarray, Software
Version	1.82.0
In Bioconductor since	BioC 1.6 (R-2.1) or earlier (> 19.5 years)
License	LGPL
Depends	Biobase(>= 2.5.5)
Imports	stats
System Requirements
URL

Suggests	affy, genefilter, multtest
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Build Report	Build Report

Package Archives

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

Source Package	factDesign_1.82.0.tar.gz
Windows Binary (x86_64)	factDesign_1.82.0.zip
macOS Binary (x86_64)	factDesign_1.82.0.tgz
macOS Binary (arm64)	factDesign_1.81.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/factDesign
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/factDesign
Bioc Package Browser	https://code.bioconductor.org/browse/factDesign/
Package Short Url	https://bioconductor.org/packages/factDesign/
Package Downloads Report	Download Stats