ReactomeGSA

ReactomeGSA performs multi-omics gene set and pathway analysis using Reactome's online analysis service, with support for comparative analysis across datasets and species.

Key Features:

• Multi-omics support: ReactomeGSA supports quantitative pathway analysis methods for different omics data types including transcriptomics, proteomics, and scRNA-seq data.
• Comparative pathway analysis: ReactomeGSA processes different datasets simultaneously to enable comparative pathway analysis across different datasets and species.
• Cross-species mapping: Data from different species is automatically mapped to a common pathway space.
• Public data integration: ReactomeGSA integrates public data from EMBL-EBI's Expression Atlas, GEO RNA-seq Experiments Interactive Navigator (GREIN), and Single Cell ExpressionAtlas.
• Dataset search: ReactomeGSA includes a search function to find public datasets across supported resources.
• R/Bioconductor package: The ReactomeGSA R package provides programmatic access to the analysis service with explicit support for scRNA-seq data.
• Visualization integration: Retrieved results can be visualized using Reactome's web application.

Scientific Applications:

• Multi-omics pathway analysis: ReactomeGSA enables pathway analysis of experiments from different omics technologies.
• Cross-species comparative analysis: ReactomeGSA supports comparative pathway analysis across different species through automatic mapping to a common pathway space.
• Public data reuse: ReactomeGSA simplifies the reuse and direct integration of public datasets from Expression Atlas and GREIN resources.
• Cancer immunology research: ReactomeGSA can integrate large multi-omics datasets to derive novel biomedical insights, as demonstrated by characterization of B cell roles in anti-tumor immunity across TCGA transcriptomics and CPTAC proteomics studies.
• Single-cell pathway analysis: ReactomeGSA supports scRNA-seq data analysis to investigate cell-type-specific pathway activities, such as NFkappaB activation in tumor-associated plasma cells.

Methodology:

ReactomeGSA uses Reactome's online analysis service which performs gene set analysis using R packages including limma and edgeR.