RCy3: Network biology using Cytoscape from within R

Area of Science:

• Bioinformatics
• Computational Biology
• Network Biology

Background:

• Cytoscape is a widely used platform for network visualization and analysis.
• Seamless integration between R and Cytoscape is crucial for advanced network biology workflows.
• Existing tools may lack comprehensive features or ease of use for complex analyses.

Purpose of the Study:

• To introduce RCy3, a redesigned R package for Cytoscape automation.
• To enhance the integration of R programming with Cytoscape's full feature set.
• To streamline the development and usage of network biology workflows.

Main Methods:

• RCy3 leverages Cytoscape's REST API for seamless communication.
• The package includes over 100 new functions, with a focus on data overlay.
• Bi-directional conversion with igraph and graph packages ensures interoperability.

Main Results:

• Over 40 Cytoscape apps now support automation via RCy3.
• Hundreds of additional operations are accessible through these integrated apps.
• Demonstrated use cases include public database integration, enrichment analysis, and shortest path algorithms.

Conclusions:

• RCy3 significantly enhances network biology research by bridging R and Cytoscape.
• It enables bioinformaticians to create reproducible and complex network analysis workflows.
• The package facilitates the integration of Cytoscape functionalities with custom R analyses.