The Galaxy Platform for Reproducible Affinity Proteomic Mass Spectrometry Data Analysis

Area of Science:

• Proteomics
• Bioinformatics
• Computational Biology

Background:

• Affinity proteomics mass spectrometry (AP-MS) is crucial for studying protein-protein interactions (PPIs), protein complexes, and signaling networks.
• Managing large AP-MS datasets and integrating diverse software tools pose challenges for researchers lacking computational backgrounds.
• Manual data formatting and complex visualization can be error-prone and time-consuming in AP-MS analysis.

Purpose of the Study:

• To develop and present a Galaxy-based platform for simplifying AP-MS data analysis.
• To provide an accessible workflow for researchers with limited computational experience.
• To enable efficient processing, analysis, and visualization of AP-MS data.

Main Methods:

• Development of a Galaxy platform tailored for AP-MS data analysis.
• Integration of various software tools into a cohesive workflow.
• Utilization of sample data and a step-by-step workflow guide for user onboarding.

Main Results:

• Researchers can process raw mass spectrometry data (mzML format) through peak processing and database searching.
• The platform facilitates the assignment of protein interaction confidence scores.
• Interactive data visualization tools are integrated for exploring complex results.

Conclusions:

• The Galaxy-based platform democratizes AP-MS data analysis, making it accessible to biologists without computational expertise.
• This approach streamlines the characterization of protein complexes and signaling networks.
• The provided workflow and sample data accelerate the adoption of advanced proteomics analysis techniques.