Package: plgem
Title: Detect differential expression in microarray and proteomics
        datasets with the Power Law Global Error Model (PLGEM)
Version: 1.85.0
Author: Mattia Pelizzola <mattia.pelizzola@gmail.com> and Norman
        Pavelka <normanpavelka@gmail.com>
Description: 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.
Maintainer: Norman Pavelka <normanpavelka@gmail.com>
Imports: utils, Biobase (>= 2.5.5), MASS, methods
Depends: R (>= 2.10)
License: GPL-2
URL: http://www.genopolis.it
biocViews: ImmunoOncology, Microarray, DifferentialExpression,
        Proteomics, GeneExpression, MassSpectrometry
Repository: https://bioc.r-universe.dev
Date/Publication: 2026-04-28 12:31:01 UTC
RemoteUrl: https://github.com/bioc/plgem
RemoteRef: HEAD
RemoteSha: 01627314fc19651d8ce05de8585e2a2e8f695957
NeedsCompilation: no
Packaged: 2026-07-19 05:08:23 UTC; root