updated package maintainer

DESCRIPTION

@@ -1,23 +1,24 @@
-Package: MSstatsTMT
-Title: Protein Significance Analysis in shotgun mass spectrometry-based proteomic experiments with tandem mass tag (TMT) labeling
-Version: 2.7.1
-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 = "[email protected]", role=c("aut","cre")),
-	person("Meena", "Choi", email = "[email protected]", role="aut"),
-	person("Mateusz", "Staniak", email = "[email protected]", role = "aut"),
-	person("Sicheng", "Hao", email = "[email protected]", role = "aut"),
-	person("Olga", "Vitek", email = "[email protected]", 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
+Package: MSstatsTMT
+Title: Protein Significance Analysis in shotgun mass spectrometry-based proteomic experiments with tandem mass tag (TMT) labeling
+Version: 2.7.2
+Date: 2024-04-23
+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("Devon", "Kohler", email = "[email protected]", role=c("aut","cre")),
+  person("Ting", "Huang", email = "[email protected]", role=c("aut")),
+	person("Meena", "Choi", email = "[email protected]", role="aut"),
+	person("Mateusz", "Staniak", email = "[email protected]", role = "aut"),
+	person("Sicheng", "Hao", email = "[email protected]", role = "aut"),
+	person("Olga", "Vitek", email = "[email protected]", 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