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

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.

Package details

AuthorMattia Pelizzola <mattia.pelizzola@gmail.com> and Norman Pavelka <normanpavelka@gmail.com>
Bioconductor views DifferentialExpression GeneExpression ImmunoOncology MassSpectrometry Microarray Proteomics
MaintainerNorman Pavelka <normanpavelka@gmail.com>
LicenseGPL-2
Version1.62.0
URL http://www.genopolis.it
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("plgem")

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plgem documentation built on Nov. 8, 2020, 5:31 p.m.