xSyn

xSyn identifies three-way interactions among gene expression profiles in cancer to detect cases where a third gene modulates the co-expression clustering of two other genes.

Key Features:

• 3-Way Interaction Identification: Detects scenarios where two genes' expression values are clustered contingent on a third gene's expression level.
• Optimization Procedure: Applies an optimization procedure combining UPGMA (Unweighted Pair Group Method with Arithmetic Mean) hierarchical clustering and synergy analysis to detect non-linear interactions.
• Cancer Gene Expression Focus: Tailored to analyze cancer gene expression datasets to reveal oncology-specific interaction patterns.

Scientific Applications:

• Regulatory network analysis: Reveals multi-gene regulatory relationships within cancer gene co-expression networks.
• Detection of non-linear interactions: Identifies interactions that are not apparent from correlation coefficients or linear regression models.
• Target and biomarker prioritization: Prioritizes gene combinations that may represent potential therapeutic targets or biomarkers in cancer research.

Methodology:

Constructs gene co-expression networks from cancer expression data, uses UPGMA for hierarchical clustering, and applies synergy analysis within an optimization procedure to identify three-way interactions not captured by linear models.