GGEA

GGEA integrates directed gene regulatory networks to improve detection and interpretation of enriched gene sets by accounting for activation- and inhibition-driven correlations among gene members.

Key Features:

• Pairwise Regulation Concordance: Evaluates alignment between pairwise regulatory relationships and observed expression changes in regulator–target gene pairs.
• Regulator-Driven Expression Attribution: Identifies gene sets in which a substantial fraction of differential expression can be attributed to nearby regulators such as transcription factors.
• Incorporation of Directed Activation and Repression: Explicitly models directed inducing (activation) and repressing (inhibition) interactions to capture correlation patterns within gene sets.
• Improved Concordance Between Expression and Regulatory Interactions: Improves concordance between observed differential expression patterns and known regulatory interactions.
• Detection of Consistently Enriched Gene Sets: Prioritizes gene sets whose correlated expression patterns coherently reflect directed regulatory relationships, increasing sensitivity to consistent enrichment.

Scientific Applications:

• Regulatory network–aware gene set enrichment: Interprets gene expression datasets by integrating directed regulatory interactions to detect enriched gene sets that reflect underlying activation or inhibition.
• Human pathway and tumor analysis: Applied to human regulatory pathways and shown to detect specific regulatory processes altered in tumors of the central nervous system.

Methodology:

Aligns differential expression with directed regulatory interactions by assessing pairwise regulation concordance and attributing expression changes to nearby regulators (e.g., transcription factors), considering inducing and repressing relationships.