This is the development version of MSstatsPTM; for the stable release version, see MSstatsPTM.
Statistical Characterization of Post-translational ModificationsBioconductor version: Development (3.22)
MSstatsPTM provides general statistical methods for quantitative characterization of post-translational modifications (PTMs). Supports DDA, DIA, SRM, and tandem mass tag (TMT) labeling. Typically, the analysis involves the quantification of PTM sites (i.e., modified residues) and their corresponding proteins, as well as the integration of the quantification results. MSstatsPTM provides functions for summarization, estimation of PTM site abundance, and detection of changes in PTMs across experimental conditions.
Author: Devon Kohler [aut], Tsung-Heng Tsai [aut], Anthony Wu [aut, cre], Deril Raju [aut], Ting Huang [aut], Mateusz Staniak [aut], Meena Choi [aut], Olga Vitek [aut]
Maintainer: Anthony Wu <wu.anthon at northeastern.edu>
Citation (from within R, entercitation("MSstatsPTM")): 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("MSstatsPTM")
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("MSstatsPTM")Follow Installation instructions to use this package in your R session.
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