plgem

Detect differential expression in microarray and proteomics datasets with the Power Law Global Error Model (PLGEM)

Bioconductor version: Release (2.7)

The Power Law Global Error Model (PLGEM) has been shown to faithfully model the variance-versus-mean dependence that exists in a variety of genome-wide datasets, including microarray and proteomics data. The use of PLGEM has been shown to improve the detection of differentially expressed genes or proteins in these datasets.

Author: Mattia Pelizzola and Norman Pavelka

Maintainer: Norman Pavelka

To install this package, start R and enter:

source("http:///biocLite.R")
biocLite("plgem")    

Documentation

PDF

R Script

An introduction to PLGEM

Reference Manual

Details

biocViews	Microarray, DifferentialExpression, Proteomics
Depends	R, Biobase, MASS
Imports	utils
Suggests
System Requirements
License	GPL
URL	http://www.genopolis.it
Depends On Me
Imports Me
Suggests Me
Version	1.22.0

Package Downloads

Package Source	plgem_1.22.0.tar.gz
Windows Binary	plgem_1.22.0.zip (32- & 64-bit)
MacOS 10.5 (Leopard) binary	plgem_1.22.0.tgz
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