NGSEA

NGSEA augments gene set enrichment analysis (GSEA) by incorporating functional network neighbor information to improve identification of pathway gene sets and drug-target associations from gene expression data.

Key Features:

• Network-augmented enrichment score: Augments the enrichment score calculation by considering individual genes and their neighboring connections within a functional network.
• DEG-aware interpretation: Addresses limitations of traditional GSEA by accounting for differentially expressed genes (DEGs) that are dysregulated via interactions with functional genes.
• Improved pathway detection: More accurately identifies pathway gene sets associated with specific gene expression phenotypes compared with conventional GSEA.
• Drug-target gene set analysis: Uses drug-target gene sets to retrieve known anti-cancer drugs from patient-derived gene expression data.
• Performance versus Connectivity Map: Demonstrated superior retrieval of relevant drugs compared to the Connectivity Map.
• Drug repurposing support: Enabled repurposing of FDA-approved drugs with experimental validation examples, including budesonide for colorectal cancer.

Scientific Applications:

• Pathway interpretation: Identification and prioritization of biological pathways associated with gene expression phenotypes.
• Functional gene set refinement: Distinguishing functional pathway members from genes dysregulated through network interactions.
• Drug discovery and repositioning: Retrieval and prioritization of anti-cancer drugs and repurposing candidates using drug-target gene sets.
• Comparative method evaluation: Benchmarking enrichment results against conventional GSEA and Connectivity Map outputs.

Methodology:

Augments the GSEA enrichment score by incorporating neighboring gene connections within a functional network and evaluates gene sets using drug-target gene sets on patient-derived gene expression data.