DOI: 10.18129/B9.bioc.MSstatsPTM  

This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see MSstatsPTM.

Statistical Characterization of Post-translational Modifications

Bioconductor version: 3.17

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, cre], Tsung-Heng Tsai [aut], Ting Huang [aut], Mateusz Staniak [aut], Meena Choi [aut], Olga Vitek [aut]

Maintainer: Devon Kohler <kohler.d at>

Citation (from within R, enter citation("MSstatsPTM")):


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HTML R Script MSstatsPTM LabelFree Workflow
HTML R Script MSstatsPTM TMT Workflow
PDF   Reference Manual


biocViews DifferentialExpression, ImmunoOncology, MassSpectrometry, Normalization, OneChannel, Proteomics, QualityControl, Software, TwoChannel
Version 2.2.4
In Bioconductor since BioC 3.12 (R-4.0) (3 years)
License Artistic-2.0
Depends R (>= 4.2)
Imports dplyr, gridExtra, stringr, stats, ggplot2, stringi, grDevices, MSstatsTMT, MSstatsConvert, MSstats, data.table, Rcpp, Biostrings, checkmate, ggrepel
LinkingTo Rcpp
Suggests knitr, rmarkdown, tinytest, covr
Depends On Me
Imports Me MSstatsLiP, MSstatsShiny
Suggests Me
Links To Me
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