YuliyaLab/ProteoMM: Multi-Dataset Model-based Differential Expression Proteomics Analysis Platform

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).

Getting started

Package details

AuthorYuliya V Karpievitch, Tim Stuart and Sufyaan Mohamed
Bioconductor views DifferentialExpression ImmunoOncology MassSpectrometry Normalization Proteomics
MaintainerYuliya V Karpievitch <yuliya.k@gmail.com>
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
YuliyaLab/ProteoMM documentation built on April 19, 2022, 8:12 a.m.