PathExt

PathExt identifies differentially active paths in omics-integrated biological networks to reveal context-specific gene interactions and processes that are not captured by differential expression (DEG) analysis.

Key Features:

• Path-Based Analysis: Identifies differentially active paths when control samples are available or the most active paths in their absence, capturing network-level activity beyond DEGs.
• TopNet Construction: Constructs a TopNet sub-network composed of significant paths that forms a well-connected graph encapsulating essential genes and processes relevant to the studied context.
• Single Sample Capability: Extracts characteristic genes and pathways from a single transcriptomic sample.
• Control-Free Analysis: Operates without an appropriate control group by prioritizing most active paths when controls are unavailable.

Scientific Applications:

• Mycobacterium tuberculosis drug response: Characterized M.tb responses to exposure from 18 antibacterial drugs using one transcriptomic sample per drug exposure.
• GTEx tissue analysis: Analyzed GTEx transcriptomic data across 39 human tissues to identify tissue-relevant genes and processes.

Methodology:

PathExt integrates omics data into a network model and identifies differentially active or most active paths, focusing on paths rather than individual gene expression to derive TopNet sub-networks.