Package: plgem
Title: Detect differential expression in microarray and proteomics
        datasets with the Power Law Global Error Model (PLGEM)
Version: 1.83.0
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: 2025-10-29 13:56:13 UTC
RemoteUrl: https://github.com/bioc/plgem
RemoteRef: HEAD
RemoteSha: b4e2cd904f78e35454d591d571afd1e1930683d7
NeedsCompilation: no
Packaged: 2025-10-30 08:30:06 UTC; root
Built: R 4.6.0; ; 2025-10-30 08:31:28 UTC; windows
