netGOR

netGOR integrates network interactions and gene-set overlaps to compute combined pathway enrichment scores that improve detection of enriched pathways for small gene sets.

Key Features:

• Integrated Scoring Framework: Combines network interactions and gene-set overlaps into a single score to provide a comprehensive assessment of pathway enrichment.
• Adaptive Resampling Based on Network Degrees: Resamples genes according to their network degrees to account for varying gene connectivity in enrichment analysis.
• Benchmark Performance: Demonstrated superior performance in identifying relevant gene-sets compared to existing tools, especially when analyzing limited numbers of genes.
• Comprehensive Output: Returns a data frame of gene-sets with associated p-values and q-values from netGO+, FET, and optionally netGO, and includes scores for network interactions and overlaps.

Scientific Applications:

• Gene expression analysis: Integrates network topology with gene-set statistics to assess pathway enrichment in gene expression datasets.
• Genome-wide association studies (GWAS): Interprets GWAS-associated gene lists by combining network information with pathway enrichment to identify disease-relevant biological processes.

Methodology:

Combines network interactions and gene-set overlaps into a single score, performs adaptive resampling of genes by network degree, computes p-values and q-values using netGO+, FET, and optionally netGO, and returns results as a data frame.