Registration Open for Bioc2024 July 24-26


This is the development version of plgem; for the stable release version, see plgem.

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

Bioconductor version: Development (3.20)

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> and Norman Pavelka <normanpavelka at>

Maintainer: Norman Pavelka <normanpavelka at>

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


To install this package, start R (version "4.4") and enter:

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

# The following initializes usage of Bioc devel


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 1.77.0
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
See More
Linking To
Depends On Me
Imports Me INSPEcT
Suggests Me
Links To Me
Build Report Build Report

Package Archives

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

Source Package plgem_1.77.0.tar.gz
Windows Binary
macOS Binary (x86_64) plgem_1.77.0.tgz
macOS Binary (arm64) plgem_1.77.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
Bioc Package Browser
Package Short Url
Package Downloads Report Download Stats