plgem

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

Bioconductor version: 2.8

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 <mattia.pelizzola at gmail.com> and Norman Pavelka <normanpavelka at gmail.com>

Maintainer: Norman Pavelka <normanpavelka at gmail.com>

To install this package, start R and enter:

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

To cite this package in a publication, start R and enter:

    citation("plgem")

Documentation

PDF R Script An introduction to PLGEM
PDF   Reference Manual

Details

biocViews Microarray, DifferentialExpression, Proteomics
Depends R (>= 2.6.0), Biobase(>= 2.5.5), MASS
Imports utils
Suggests
System Requirements
License GPL-2
URL http://www.genopolis.it
Depends On Me
Imports Me
Suggests Me
Version 1.24.0
Since Bioconductor 1.6 (R-2.1) or earlier

Package Downloads

Package Source plgem_1.24.0.tar.gz
Windows Binary plgem_1.24.0.zip (32- & 64-bit)
MacOS 10.5 (Leopard) binary plgem_1.24.0.tgz
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