PCAN

PCAN links genotypes with phenotypes by integrating known gene-phenotype associations into molecular signaling networks to prioritize and biologically interpret genes associated with disease traits.

Key Features:

• Semantic Similarity Assessment: Assesses consensus semantic similarity of phenotypes in a candidate gene's signaling neighborhood.
• Integration with Molecular Networks: Integrates high-quality protein interactions from STRING and pathway annotations from Metabase to define signaling neighborhoods.
• Statistical Significance: Detects significant phenotype consensus (p < 0.05) in approximately 67% of analyzed OMIM disease-gene associations.
• Case Study Application: Applied to Joubert Syndrome to identify significant phenotype consensus and interrogate discriminatory traits among mechanistically related genes.
• Mechanistic Deconvolution: Facilitates mechanistic deconvolution of diverse phenotypes by prioritizing genes within signaling networks.

Scientific Applications:

• Gene Prioritization: Prioritizing candidate genes most likely involved in specific phenotypes.
• Mechanistic Insights: Deconvoluting complex phenotypic presentations to reveal underlying genetic mechanisms.
• Target Discovery: Linking genetic variations to disease phenotypes to support discovery of potential therapeutic targets.

Methodology:

PCAN assesses phenotype consensus within a candidate gene's signaling neighborhood using semantic similarity measures and high-quality interaction data from STRING together with pathway information from Metabase.