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ProteoMM

Multi-Dataset Model-based Differential Expression Proteomics Analysis Platform

Bioconductor version: 3.23 · Package version: 1.30.0

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).

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("ProteoMM")

Details

MaintainerYuliya V Karpievitch <yuliya.k@gmail.com>
AuthorYuliya V Karpievitch, Tim Stuart and Sufyaan Mohamed
LicenseMIT
Downloads rank446
Source branchRELEASE_3_23
biocViewsDifferentialExpression, ImmunoOncology, MassSpectrometry, Normalization, Proteomics, Software

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packageProteoMM_1.30.0.tar.gz
Windows binary (x86_64)ProteoMM_1.30.0.zip
macOS binary (arm64)ProteoMM_1.30.0.tgz
macOS binary (x86_64)ProteoMM_1.30.0.tgz
Dependencies

Depends: R (>= 3.5)

Imports: gdata, biomaRt, ggplot2, ggrepel, gtools, stats, matrixStats, graphics

Suggests: BiocStyle, knitr, rmarkdown

Reverse dependencies

Suggests Me (1): mi4p