ProteoMM
This is the released version of ProteoMM; for the devel version, see ProteoMM.
Multi-Dataset Model-based Differential Expression Proteomics Analysis Platform
Bioconductor version: Release (3.23)
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")):
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M (2015). "Orchestrating high-throughput genomic analysis with Bioconductor." Nature Methods, 12(2), 115–121. doi:10.1038/nmeth.3252.
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JYH, Zhang J (2004). "Bioconductor: open software development for computational biology and bioinformatics." Genome Biology, 5(10), R80. doi:10.1186/gb-2004-5-10-r80.
Installation
To install this package, start R (version "4.6") 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.
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 | 1.30.0 |
| In Bioconductor since | BioC 3.8 (R-3.5) (8 years) |
| License | MIT |
| Depends | R (>= 3.5) |
| Imports | gdata, biomaRt, ggplot2, ggrepel, gtools, stats, matrixStats, graphics |
| System Requirements | |
| URL |
See More
| Suggests | BiocStyle, knitr, rmarkdown |
| Linking To | |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | mi4p |
| Links To Me | |
| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | ProteoMM_1.30.0.tar.gz |
| Windows Binary (x86_64) | ProteoMM_1.30.0.zip |
| macOS Binary (big-sur-x86_64) | ProteoMM_1.30.0.tgz |
| macOS Binary (sonoma-arm64) | ProteoMM_1.30.0.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 |