Package: plgem
Title: Detect differential expression in microarray and proteomics
        datasets with the Power Law Global Error Model (PLGEM)
Version: 1.48.0
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
Depends: R (>= 2.10)
License: GPL-2
URL: http://www.genopolis.it
biocViews: Microarray, DifferentialExpression, Proteomics,
        GeneExpression, MassSpectrometry
NeedsCompilation: no
Packaged: 2017-04-24 23:20:35 UTC; biocbuild
Built: R 3.4.0; ; 2017-04-25 06:17:22 UTC; windows
