plgem

DOI: 10.18129/B9.bioc.plgem    

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

Bioconductor version: Release (3.6)

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>

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

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("plgem")

Documentation

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

browseVignettes("plgem")

 

PDF R Script An introduction to PLGEM
PDF   Reference Manual
Text   NEWS

Details

biocViews DifferentialExpression, GeneExpression, MassSpectrometry, Microarray, Proteomics, Software
Version 1.50.0
In Bioconductor since BioC 1.6 (R-2.1) or earlier (> 13 years)
License GPL-2
Depends R (>= 2.10)
Imports utils, Biobase(>= 2.5.5), MASS
LinkingTo
Suggests
SystemRequirements
Enhances
URL http://www.genopolis.it
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Source Package plgem_1.50.0.tar.gz
Windows Binary plgem_1.50.0.zip
Mac OS X 10.11 (El Capitan) plgem_1.50.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/plgem
Package Short Url http://bioconductor.org/packages/plgem/
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