GOrilla

GOrilla identifies enriched Gene Ontology (GO) terms in ranked gene lists to detect functional enrichment without requiring predefined target or background gene sets.

Key Features:

• Ranked List Analysis: Accepts inherently ordered gene lists such as those ranked by expression level or differential expression for enrichment testing.
• No Predefined Target/Background Sets: Detects enriched GO terms from the ranked list itself without separate target and background gene sets.
• Statistical Rigor (mHG): Uses a threshold statistical approach grounded in the minimum Hypergeometric (mHG) distribution to compute exact p-values for observed GO term enrichments.
• Multiple Testing Control: Addresses multiple testing issues through its exact mHG-based framework without relying on simulations.
• Efficiency: Computes enrichment for thousands of genes and GO terms with rapid performance.
• Visualization: Presents enrichment results as a hierarchical structure that reflects relationships among enriched GO terms.

Scientific Applications:

• Gene expression profiling: Identifies GO terms enriched among genes ranked by expression levels.
• Differential expression analysis: Finds functional categories enriched in genes ranked by differential expression metrics.
• Functional enrichment of ordered genomic data: Applies to any study where genomic entities are naturally represented as ranked lists.

Methodology:

GOrilla applies a threshold statistical approach based on a complete theoretical characterization of the minimum Hypergeometric (mHG) distribution to compute exact p-values for GO term enrichment and to address multiple testing without simulations.