Bioc2026 Registration Open!

MSstatsPTM

Statistical Characterization of Post-translational Modifications

Bioconductor version: 3.23 · Package version: 2.14.0

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.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("MSstatsPTM")

Details

MaintainerAnthony Wu <wu.anthon@northeastern.edu>
AuthorDevon 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]
LicenseArtistic-2.0
URLhttps://vitek-lab.github.io/MSstatsPTM/
Bug Reportshttps://github.com/Vitek-Lab/MSstatsPTM/issues
Downloads rank453
Source branchRELEASE_3_23
biocViewsDifferentialExpression, ImmunoOncology, MassSpectrometry, Normalization, OneChannel, Proteomics, QualityControl, Software, TwoChannel

Documentation

Download

Dependencies

Depends: R (>= 4.3)

Imports: dplyr, gridExtra, stringr, stats, ggplot2, stringi, grDevices, MSstatsTMT, MSstatsConvert (>= 1.19.1), MSstats, data.table, Rcpp, Biostrings, checkmate, ggrepel, plotly, htmltools, rlang

LinkingTo: Rcpp

Suggests: knitr, rmarkdown, tinytest, covr, mockery, arrow, testthat (>= 3.0.0)

Reverse dependencies

Imports Me (2): MSstatsLiP, MSstatsShiny