PCxN

PCxN quantifies coexpression relationships among canonical pathways to elucidate functional interplay and pathway-level associations.

Key Features:

• Systematic Quantification: Quantifies coexpression across 1,330 canonical pathways from the Molecular Signatures Database (MSigDB) using a curated collection of 3,207 microarrays derived from 72 normal human tissues to estimate correlations between pathways.
• Shared Gene Consideration: Accounts for the presence of shared genes between pathway annotations to distinguish significant pathway correlations from simple gene-set overlap.
• Novel Insights into Disease Mechanisms: Applied to an Alzheimer's Disease (AD) case study to retrieve pathways significantly correlated with an expert-curated AD gene list and enriched for genes independently linked to AD.
• Complementary Analysis: Complements gene set enrichment by revealing relationships between enriched pathways and identifying additional highly correlated pathways, highlighting clusters involved in cell adhesion, oxidative stress, and connections to extracellular matrix pathways.

Scientific Applications:

• Complex Disease Research: Enables investigation of complex diseases such as Alzheimer's Disease by uncovering novel pathway relationships and mechanisms associated with curated disease gene lists.
• Pathway Interaction Analysis: Provides a framework for exploring global pathway interactions and interdependencies across canonical pathways from MSigDB.

Methodology:

Estimates pathway–pathway correlations via coexpression analysis applied to 3,207 curated microarrays from 72 normal human tissues, incorporates MSigDB pathway annotations for 1,330 canonical pathways, and accounts for shared genes between pathway annotations when establishing significant correlations.