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Multi-Dataset Model-based Differential Expression Proteomics Analysis Platform

Bioconductor version: Release (3.19)

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 “A 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>

Citation (from within R, enter citation("ProteoMM")):


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Multi-Dataset Model-based Differential Expression Proteomics Platform HTML R Script
Reference Manual PDF


biocViews DifferentialExpression, ImmunoOncology, MassSpectrometry, Normalization, Proteomics, Software
Version 1.22.0
In Bioconductor since BioC 3.8 (R-3.5) (5.5 years)
License MIT
Depends R (>= 3.5)
Imports gdata, biomaRt, ggplot2, ggrepel, gtools, stats, matrixStats, graphics
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Source Package ProteoMM_1.22.0.tar.gz
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