This is the development version of MSstatsTMT; for the stable release version, see MSstatsTMT.
Protein Significance Analysis in shotgun mass spectrometry-based proteomic experiments with tandem mass tag (TMT) labelingBioconductor version: Development (3.22)
The package provides statistical tools for detecting differentially abundant proteins in shotgun mass spectrometry-based proteomic experiments with tandem mass tag (TMT) labeling. It provides multiple functionalities, including aata visualization, protein quantification and normalization, and statistical modeling and inference. Furthermore, it is inter-operable with other data processing tools, such as Proteome Discoverer, MaxQuant, OpenMS and SpectroMine.
Author: Devon Kohler [aut, cre], Ting Huang [aut], Meena Choi [aut], Mateusz Staniak [aut], Tony Wu [aut], Deril Raju [aut], Sicheng Hao [aut], Olga Vitek [aut]
Maintainer: Devon Kohler <kohler.d at northeastern.edu>
Citation (from within R, entercitation("MSstatsTMT")): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("MSstatsTMT")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("MSstatsTMT")Follow Installation instructions to use this package in your R session.
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