Package: MSstatsTMT
Title: Protein Significance Analysis in shotgun mass spectrometry-based
        proteomic experiments with tandem mass tag (TMT) labeling
Version: 2.6.1
Date: 2023-02-18
Description: 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.
Authors@R: c(person("Ting", "Huang", email = "thuang0703@gmail.com", role=c("aut","cre")),
	person("Meena", "Choi", email = "mnchoi67@gmail.com", role="aut"),
	person("Mateusz", "Staniak", email = "mtst@mstaniak.pl", role = "aut"),
	person("Sicheng", "Hao", email = "hao.sic@husky.neu.edu", role = "aut"),
	person("Olga", "Vitek", email = "o.vitek@northeastern.edu", role = "aut"))
License: Artistic-2.0
Depends: R (>= 4.2)
Imports: limma, lme4, lmerTest, methods, data.table, stats, utils,
        ggplot2, grDevices, graphics, MSstats, MSstatsConvert,
        checkmate
Suggests: BiocStyle, knitr, rmarkdown, testthat
VignetteBuilder: knitr
biocViews: ImmunoOncology, MassSpectrometry, Proteomics, Software
Encoding: UTF-8
LazyData: true
URL: http://msstats.org/msstatstmt/
BugReports: https://groups.google.com/forum/#!forum/msstats
RoxygenNote: 7.2.3
git_url: https://git.bioconductor.org/packages/MSstatsTMT
git_branch: RELEASE_3_16
git_last_commit: a8aa9bc
git_last_commit_date: 2023-02-26
Date/Publication: 2023-02-27
NeedsCompilation: no
Packaged: 2023-02-27 22:19:01 UTC; biocbuild
Author: Ting Huang [aut, cre],
  Meena Choi [aut],
  Mateusz Staniak [aut],
  Sicheng Hao [aut],
  Olga Vitek [aut]
Maintainer: Ting Huang <thuang0703@gmail.com>
