ReactomeGSA: new features to simplify public data reuse

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• ReactomeGSA is a leading multi-omics pathway analysis platform within the Reactome knowledgebase.
• It supports quantitative pathway analysis for diverse 'omics data types and comparative analysis across datasets and species.

Purpose of the Study:

• To present a major update of ReactomeGSA, simplifying public data integration and reuse.
• To enhance the platform's capabilities for comparative pathway analysis using publicly available datasets.

Main Methods:

• Developed the `grein_loader` Python application to fetch experiments from the GREIN resource.
• Integrated support for EMBL-EBI's Expression Atlas and GEO RNA-seq Experiments Interactive Navigator.
• Implemented a novel search function for public datasets across supported resources.
• Completely redeveloped the ReactomeGSA web frontend and R/Bioconductor package.

Main Results:

• Enabled direct fetching and integration of public datasets from GREIN, Expression Atlas, and GEO.
• Introduced a unified search interface for discovering public datasets.
• Simplified the user experience through a redeveloped web frontend and R package.
• Facilitated easier comparative pathway analysis across multiple datasets and species.

Conclusions:

• The updated ReactomeGSA platform significantly enhances the accessibility and usability of public multi-omics data for pathway analysis.
• The new features streamline comparative pathway analysis, promoting broader scientific discovery.
• The platform is readily available through a web interface, R/Bioconductor package, and Python application.