MSstatsShiny: A GUI for Versatile, Scalable, and Reproducible Statistical Analyses of Quantitative Proteomic...

Area of Science:

• Proteomics
• Bioinformatics
• Computational Biology

Background:

• Liquid chromatography-mass spectrometry (LC-MS/MS) is key for protein identification and quantification.
• Analyzing protein abundance changes requires complex statistical methods, often in R.
• Existing tools like MSstats present a barrier for users with limited programming skills.

Purpose of the Study:

• To develop an accessible graphical user interface (GUI) for advanced proteomics statistical analysis.
• To integrate MSstats, MSstatsTMT, and MSstatsPTM into a user-friendly platform.
• To facilitate reproducible research by automating analysis and script generation.

Main Methods:

• Developed MSstatsShiny, an R-Shiny GUI.
• Integrated MSstats, MSstatsTMT, and MSstatsPTM functionalities.
• Designed a point-and-click pipeline for various proteomics experimental types (label-free, TMT-based, DDA, DIA).

Main Results:

• MSstatsShiny enables analysis of relative changes in peptides, proteins, and post-translational modifications (PTMs).
• The GUI supports diverse proteomics data acquisition strategies.
• Analysis pipelines are reproducible, with saved user selections and generated R scripts.

Conclusions:

• MSstatsShiny enhances accessibility to sophisticated proteomics statistical analyses.
• The platform supports reproducible research through automated analysis and script generation.
• MSstatsShiny can be installed locally or accessed via a cloud platform.