ProteoMM
This is the development version of ProteoMM; for the stable release version, see ProteoMM.
Multi-Dataset Model-based Differential Expression Proteomics Analysis Platform
Bioconductor version: Development (3.18)
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 gmail.com>
citation("ProteoMM")):
Installation
To install this package, start R (version "4.3") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("ProteoMM")For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("ProteoMM")| Multi-Dataset Model-based Differential Expression Proteomics Platform | HTML | R Script |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | DifferentialExpression, ImmunoOncology, MassSpectrometry, Normalization, Proteomics, Software |
| Version | 1.19.0 |
| In Bioconductor since | BioC 3.8 (R-3.5) (5 years) |
| License | MIT |
| Depends | R (>= 3.5) |
| Imports | gdata, biomaRt, ggplot2, ggrepel, gtools, stats, matrixStats, graphics |
| Linking To | |
| Suggests | BiocStyle, knitr, rmarkdown |
| System Requirements | |
| Enhances | |
| URL |
See More
| Depends On Me | |
| Imports Me | |
| Suggests Me | mi4p |
| Links To Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | ProteoMM_1.19.0.tar.gz |
| Windows Binary | ProteoMM_1.19.0.zip |
| macOS Binary (x86_64) | ProteoMM_1.19.0.tgz |
| macOS Binary (arm64) | ProteoMM_1.19.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/ProteoMM |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/ProteoMM |
| Bioc Package Browser | https://code.bioconductor.org/browse/ProteoMM/ |
| Package Short Url | https://bioconductor.org/packages/ProteoMM/ |
| Package Downloads Report | Download Stats |