To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("plgem")
    In most cases, you don't need to download the package archive at all.
Bioconductor version: 2.13
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.
Author: Mattia Pelizzola <mattia.pelizzola at gmail.com> and Norman Pavelka <normanpavelka at gmail.com>
Maintainer: Norman Pavelka <normanpavelka at gmail.com>
Citation (from within R,
      enter citation("plgem")):
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("plgem")
    To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("plgem")
    
| R Script | An introduction to PLGEM | |
| Reference Manual | ||
| Text | NEWS | 
| biocViews | DifferentialExpression, Microarray, Proteomics, Software | 
| Version | 1.34.0 | 
| In Bioconductor since | BioC 1.6 (R-2.1) or earlier | 
| License | GPL-2 | 
| Depends | R (>= 2.10), Biobase(>= 2.5.5), MASS | 
| Imports | utils | 
| Suggests | |
| System Requirements | |
| URL | http://www.genopolis.it | 
| Depends On Me | |
| Imports Me | |
| Suggests Me | 
Follow Installation instructions to use this package in your R session.
| Package Source | plgem_1.34.0.tar.gz | 
| Windows Binary | plgem_1.34.0.zip (32- & 64-bit) | 
| Mac OS X 10.6 (Snow Leopard) | plgem_1.34.0.tgz | 
| Browse/checkout source | (username/password: readonly) | 
| Package Downloads Report | Download Stats | 
 
  
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