factDesign

DOI: 10.18129/B9.bioc.factDesign    

Factorial designed microarray experiment analysis

Bioconductor version: Release (3.15)

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 "4.2") 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")

 

PDF R Script factDesign
PDF   Reference Manual

Details

biocViews DifferentialExpression, Microarray, Software
Version 1.72.0
In Bioconductor since BioC 1.6 (R-2.1) or earlier (> 17.5 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
Links To Me
Build Report  

Package Archives

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

Source Package factDesign_1.72.0.tar.gz
Windows Binary factDesign_1.72.0.zip (64-bit only)
macOS Binary (x86_64) factDesign_1.72.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/factDesign
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/factDesign
Package Short Url https://bioconductor.org/packages/factDesign/
Package Downloads Report Download Stats

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