CoExpNetViz

CoExpNetViz constructs comparative co-expression networks to identify conserved gene co-expression patterns across multiple plant species using published and unpublished gene expression data.

Key Features:

• User-defined query genes: Accepts a set of bait genes as the basis for constructing co-expression networks.
• Multi-species analysis: Constructs co-expression networks across multiple species by leveraging cross-species orthology to identify conserved patterns.
• Co-expression calculation: Computes co-expression values using mutual information and Pearson correlation coefficients across input datasets.
• Network output for Cytoscape: Generates output files formatted for visualization as network graphs in Cytoscape.
• Supports published and unpublished expression data: Integrates both published and unpublished gene expression datasets for comparative analysis.

Scientific Applications:

• Functional genomics: Infers gene function and regulatory relationships from conserved co-expression patterns.
• Comparative transcriptomics in plants: Identifies conserved genetic modules across closely related plant species, including modules implicated in stress responses.
• Non-model organism analysis: Enables inclusion of unpublished data to extend comparative studies beyond model systems for functional gene discovery.

Methodology:

Three-step algorithm: (1) compute co-expression values for each bait gene using mutual information and Pearson correlation coefficients across input datasets; (2) group non-bait (target) genes based on cross-species orthology; (3) generate output files for visualization in Cytoscape.