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
| Maintainer | Anthony Wu <wu.anthon@northeastern.edu> |
| 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] |
| License | Artistic-2.0 |
| URL | https://vitek-lab.github.io/MSstatsPTM/ |
| Bug Reports | https://github.com/Vitek-Lab/MSstatsPTM/issues |
| Downloads rank | 453 |
| Source branch | RELEASE_3_23 |
| biocViews | DifferentialExpression, ImmunoOncology, MassSpectrometry, Normalization, OneChannel, Proteomics, QualityControl, Software, TwoChannel |
Documentation
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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