PathJam

PathJam integrates human pathway annotations from public databases such as Reactome, KEGG, and Biocarta and performs statistical enrichment analysis to identify pathway associations for input gene lists, producing outputs compatible with GSEA and accessible via a RESTful API.

Key Features:

• Comprehensive Integration: PathJam consolidates human pathway annotations from Reactome, KEGG, Biocarta and other public sources into a unified dataset.
• Statistical Enrichment Analysis: PathJam applies statistical methods to perform enrichment analysis and identify pathways significantly associated with user-provided gene lists.
• Interactive Visualizations: The platform provides graphs that visually link genes to their associated pathways for interactive exploration.
• Data Export Options: PathJam generates downloadable result files in formats intended for compatibility with downstream bioinformatics workflows.
• GSEA Compatibility: PathJam produces output files that are compatible with Gene Set Enrichment Analysis (GSEA).
• Standardized API: PathJam exposes a RESTful API for programmatic access to integrated pathway data and results.

Scientific Applications:

• Pathway annotation and enrichment: Integration and enrichment analysis of pathway annotations to interpret gene lists.
• Disease mechanism analysis: Elucidation of pathways and processes implicated in human disease mechanisms.
• Genomics and systems biology: Use of integrated pathway data to support genomics and systems-level analyses.
• Personalized medicine: Application of pathway-level insights to research areas relevant to personalized medicine.

Methodology:

Integration of diverse pathway databases into a cohesive analytical framework, application of statistical enrichment analyses to user gene lists, generation of interactive graphs linking genes to pathways, and provision of downloadable outputs alongside a RESTful API.