CorDiffViz

CorDiffViz estimates and visualizes differential correlation networks across multiple omics datasets to characterize condition-specific changes in biomolecular interactions.

Key Features:

• Multi-Omics Integration: Constructs cross-correlation networks between two distinct omics datasets to enable integrative analyses.
• Multiple Correlation Measures and Inference Methods: Supports analysis using a variety of correlation measures and statistical inference methods for estimating correlations.
• Differential Correlation Visualization: Produces visual representations of differential correlation networks to highlight changes in molecular interactions between states.
• Condition Comparison: Enables comparison between correlation networks within a single condition and differential correlations across two conditions.

Scientific Applications:

• Network Comparison: Characterizes differences between omics networks under varying conditions to reveal condition-specific interaction changes.
• Disease Mechanism Elucidation: Identifies changes in biomolecular interactions that may underlie disease initiation and progression.
• Biomarker and Therapeutic Target Discovery: Highlights differential interactions that can point to candidate biomarkers or therapeutic targets.

Methodology:

Estimates differential correlations and constructs cross-correlation networks between two omics datasets using multiple correlation measures and inference methods.