PhosPiR

PhosPiR automates phosphoproteomic analysis of mass spectrometry (MS) datasets using integrated R packages to produce phosphosite annotation, statistical comparisons, enrichment analyses, proteome-wide kinase activity mapping, substrate mapping, and network hub identification.

Key Features:

• R package integration: Integrates multiple R packages into a unified pipeline for analysis of phosphoproteomic MS data.
• Integration with databases and knowledge resources: Connects to existing databases and knowledge resources for phosphosite annotation and functional context.
• Automated workflow: Performs data clean-up, provides a dataset overview, executes multiple statistical testing procedures, conducts differential expression analysis, and generates phosphosite annotation.
• Cross-species translation: Supports translation of phosphosites and protein identifiers across species for comparative analyses.
• Multilevel enrichment analyses: Performs pathway and process enrichment analyses at multiple levels to identify significant biological signatures.
• Proteome-wide kinase activity mapping: Infers kinase activities across the proteome to characterize signalling networks.
• Substrate mapping: Maps kinase substrates to phosphosites to identify putative kinase–substrate relationships.
• Network hub analysis: Identifies network hubs and key nodes within protein and phosphosite interaction networks.
• Graphical outputs: Generates heatmaps, box plots, volcano plots, and circos plots for visualization of results.

Scientific Applications:

• Proteome-wide data mining: Enables large-scale extraction of phosphorylation-based signals to investigate pathophysiological mechanisms from phosphoproteomic MS data.
• Disease biology: Supports identification of dysregulated phosphorylation events and signalling pathways relevant to disease mechanisms.
• Drug discovery: Facilitates identification of kinase targets, substrate networks, and signalling nodes relevant to therapeutic development.
• Comparative and evolutionary studies: Supports cross-species translation to enable comparative phosphoproteomics and evolutionary analyses.
• Signalling network characterization: Integrates kinase activity mapping, substrate mapping, and network hub analysis to characterize cellular signalling networks.

Methodology:

Accepts mass spectrometry (MS) phosphoproteomic data and uses integrated R packages to perform data clean-up, dataset overview, statistical testing, differential expression analysis, phosphosite annotation, enrichment analyses, kinase activity mapping, substrate mapping, network hub analysis, and generation of heatmaps, box plots, volcano plots, and circos plots.