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

Bioconductor version: Release (3.18)

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")):


To install this package, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


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

An introduction to PLGEM PDF R Script
Reference Manual PDF


biocViews DifferentialExpression, GeneExpression, ImmunoOncology, MassSpectrometry, Microarray, Proteomics, Software
Version 1.74.0
In Bioconductor since BioC 1.6 (R-2.1) or earlier (> 19 years)
License GPL-2
Depends R (>= 2.10)
Imports utils, Biobase(>= 2.5.5), MASS, methods
System Requirements
URL http://www.genopolis.it
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Follow Installation instructions to use this package in your R session.

Source Package plgem_1.74.0.tar.gz
Windows Binary plgem_1.74.0.zip
macOS Binary (x86_64) plgem_1.74.0.tgz
macOS Binary (arm64) plgem_1.74.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/plgem
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/plgem
Bioc Package Browser https://code.bioconductor.org/browse/plgem/
Package Short Url https://bioconductor.org/packages/plgem/
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