To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("http://bioc.ism.ac.jp/biocLite.R")
biocLite("acde")

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

acde

 

   

Artificial Components Detection of Differentially Expressed Genes

Bioconductor version: Release (3.5)

This package provides a multivariate inferential analysis method for detecting differentially expressed genes in gene expression data. It uses artificial components, close to the data's principal components but with an exact interpretation in terms of differential genetic expression, to identify differentially expressed genes while controlling the false discovery rate (FDR). The methods on this package are described in the vignette or in the article 'Multivariate Method for Inferential Identification of Differentially Expressed Genes in Gene Expression Experiments' by J. P. Acosta, L. Lopez-Kleine and S. Restrepo (2015, pending publication).

Author: Juan Pablo Acosta, Liliana Lopez-Kleine

Maintainer: Juan Pablo Acosta <jpacostar at unal.edu.co>

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

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("http://bioc.ism.ac.jp/biocLite.R")
biocLite("acde")

Documentation

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

browseVignettes("acde")

 

PDF R Script Identification of Differentially Expressed Genes with Artificial Components
PDF   Reference Manual
Text   NEWS

Details

biocViews DifferentialExpression, GeneExpression, Microarray, PrincipalComponent, Software, TimeCourse, mRNAMicroarray
Version 1.6.0
In Bioconductor since BioC 3.2 (R-3.2) (1.5 years)
License GPL-3
Depends R (>= 3.3), boot (>= 1.3)
Imports stats, graphics
LinkingTo
Suggests BiocGenerics, RUnit
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 acde_1.6.0.tar.gz
Windows Binary acde_1.6.0.zip
Mac OS X 10.11 (El Capitan) acde_1.6.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/acde/tree/release-3.5
Package Short Url http://bioconductor.org/packages/acde/
Package Downloads Report Download Stats

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