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 <email@example.com> and Norman Pavelka <firstname.lastname@example.org>|
|Bioconductor views||DifferentialExpression GeneExpression ImmunoOncology MassSpectrometry Microarray Proteomics|
|Maintainer||Norman Pavelka <email@example.com>|
|Package repository||View on Bioconductor|
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