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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.
Package details |
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Author | Mattia Pelizzola <mattia.pelizzola@gmail.com> and Norman Pavelka <normanpavelka@gmail.com> |
Bioconductor views | DifferentialExpression GeneExpression ImmunoOncology MassSpectrometry Microarray Proteomics |
Maintainer | Norman Pavelka <normanpavelka@gmail.com> |
License | GPL-2 |
Version | 1.62.0 |
URL | http://www.genopolis.it |
Package repository | View on Bioconductor |
Installation |
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