EGSEA

EGSEA performs ensemble gene set enrichment analysis by aggregating results from multiple gene set enrichment (GSE) algorithms to prioritize biologically relevant gene sets in RNA-sequencing data.

Key Features:

• Ensemble Approach: Combines results from twelve distinct GSE algorithms to calculate collective gene set scores and produce a consensus ranking.
• Extensive Gene Set Database: Includes approximately 25,000 gene sets compiled from sixteen collections.
• Visualization Capabilities: Provides multiple visualization options to examine gene sets at varying levels of granularity.
• Performance Validation: Tested on simulated datasets and real human and mouse datasets and reported to outperform individual GSE methods in identifying biologically relevant gene sets.
• Biological Interpretation: Facilitates extrapolation of biological functions and potential disease involvement from lists of differentially regulated genes.

Scientific Applications:

• RNA-sequencing analysis: Prioritizing and interpreting gene set-level changes in RNA-sequencing differential expression studies.
• Comparative and functional genomics: Comparing gene set results across multiple experimental conditions for comparative and functional genomics investigations.
• Pathway and regulatory mechanism discovery: Uncovering gene functions, regulatory mechanisms, and disease-associated pathways from differential expression data.

Methodology:

Aggregates outputs from twelve GSE algorithms to compute collective gene set scores and form a consensus ranking of biologically significant gene sets.