Protocol for the processing and downstream analysis of phosphoproteomic data with PhosR.

Area of Science:

• Proteomics
• Bioinformatics
• Computational Biology

Background:

• Phosphoproteomic data analysis demands sophisticated computational approaches.
• Existing methodologies may not offer comprehensive solutions for complex datasets.

Purpose of the Study:

• To introduce PhosR, a novel R package for the integrated analysis of phosphoproteomic data.
• To provide a user-friendly platform for essential data processing and advanced functional interpretation.

Main Methods:

• Development of a suite of R-based tools within the PhosR package.
• Implementation of data imputation and normalization techniques.
• Integration of functional analysis modules, including kinase activity inference and signalome construction.

Main Results:

• PhosR offers a comprehensive workflow for phosphoproteomic data.
• The package facilitates key analytical steps, from data preprocessing to biological interpretation.
• Enables the construction of signalome networks and inference of kinase activities.

Conclusions:

• PhosR significantly enhances the interpretation and discovery capabilities for large-scale phosphoproteomic studies.
• Provides a robust computational framework for researchers in the field.