Package: plgem Title: Detect differential expression in microarray and proteomics datasets with the Power Law Global Error Model (PLGEM) Version: 1.84.0 Author: Mattia Pelizzola and Norman Pavelka 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 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: Bioconductor 3.23 Date/Publication: 2026-04-28 12:31:01 UTC RemoteUrl: https://github.com/bioc/plgem RemoteRef: RELEASE_3_23 RemoteSha: 88242f4bec8754e68e655c6819c81661b4df2908 NeedsCompilation: no Packaged: 2026-07-03 06:04:21 UTC; root