This is the released version of ProteoMM; for the devel version, see ProteoMM.
Multi-Dataset Model-based Differential Expression Proteomics Analysis PlatformBioconductor version: Release (3.21)
ProteoMM is a statistical method to perform model-based peptide-level differential expression analysis of single or multiple datasets. For multiple datasets ProteoMM produces a single fold change and p-value for each protein across multiple datasets. ProteoMM provides functionality for normalization, missing value imputation and differential expression. Model-based peptide-level imputation and differential expression analysis component of package follows the analysis described in âA statistical framework for protein quantitation in bottom-up MS based proteomics" (Karpievitch et al. Bioinformatics 2009). EigenMS normalisation is implemented as described in "Normalization of peak intensities in bottom-up MS-based proteomics using singular value decomposition." (Karpievitch et al. Bioinformatics 2009).
Author: Yuliya V Karpievitch, Tim Stuart and Sufyaan Mohamed
Maintainer: Yuliya V Karpievitch <yuliya.k at gmail.com>
Citation (from within R, entercitation("ProteoMM")): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("ProteoMM")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("ProteoMM")Follow Installation instructions to use this package in your R session.
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