plgem
Detect differential expression in microarray and proteomics datasets with the Power Law Global Error Model (PLGEM)
Bioconductor version: 3.24 · Package version: 1.85.0
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.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("plgem") Details
| Maintainer | Norman Pavelka <normanpavelka@gmail.com> |
| Author | Mattia Pelizzola <mattia.pelizzola@gmail.com> and Norman Pavelka <normanpavelka@gmail.com> |
| License | GPL-2 |
| URL | http://www.genopolis.it |
| Downloads rank | 702 |
| Source branch | devel |
| biocViews | DifferentialExpression, GeneExpression, ImmunoOncology, MassSpectrometry, Microarray, Proteomics, Software |
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | plgem_1.85.0.tar.gz |
| Windows binary (x86_64) | plgem_1.85.0.zip |
| macOS binary (arm64) | plgem_1.85.0.tgz |
| macOS binary (x86_64) | plgem_1.85.0.tgz |
Reverse dependencies
Imports Me (1): INSPEcT