The DisGeNET cytoscape app: Exploring and visualizing disease genomics data.

Area of Science:

• Bioinformatics
• Computational Biology
• Systems Biology

Background:

• Genomic variant exploration has identified numerous disease-associated loci.
• Network-based approaches are crucial for understanding disease molecular mechanisms.
• Abundant omics data and interactomics information fuel these approaches.

Purpose of the Study:

• To introduce the DisGeNET Cytoscape App, integrating DisGeNET's knowledge platform with Cytoscape.
• To provide tools for querying, analyzing, and visualizing gene-disease and variant-disease associations.
• To support reproducible and scalable analysis workflows using DisGeNET data.

Main Methods:

• Integration of the DisGeNET database with the Cytoscape platform.
• Development of functions for network visualization and analysis of gene/variant-disease associations.
• Implementation of Cytoscape Automation and a REST API for programmatic access.

Main Results:

• The DisGeNET Cytoscape App enables comprehensive analysis of genomic and disease data.
• Novel features include variant-disease network analysis and disease enrichment analysis.
• The app supports annotation of external networks and facilitates reproducible research.

Conclusions:

• The DisGeNET Cytoscape App enhances the analysis of complex disease-associated genomic data.
• It provides a powerful, integrated platform for researchers studying gene-disease relationships.
• The app's features promote scalable and reproducible bioinformatics workflows.