Package: plgem
Title: Detect differential expression in microarray and proteomics
        datasets with the Power Law Global Error Model (PLGEM)
Version: 1.54.1
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
Depends: R (>= 2.10)
License: GPL-2
URL: http://www.genopolis.it
biocViews: ImmunoOncology, Microarray, DifferentialExpression,
        Proteomics, GeneExpression, MassSpectrometry
git_url: https://git.bioconductor.org/packages/plgem
git_branch: RELEASE_3_8
git_last_commit: 7c5b73c
git_last_commit_date: 2019-01-04
Date/Publication: 2019-01-04
NeedsCompilation: no
Packaged: 2019-01-05 01:48:20 UTC; biocbuild
Built: R 3.5.2; ; 2019-01-05 12:30:52 UTC; windows
