NetDecoder Protocol for Building Context-Specific Protein Interaction Networks from Transcriptomic Data Using Information Flow Modeling.

Differential expression analysis is a commonly used technique for determining potential therapeutic targets, but it overlooks the complexity of gene networks across biological pathways. Often, highly expressed genes do not necessarily explain the properties of a biological phenotype. NetDecoder, a network biology tool that integrates transcriptomic data with protein-protein interaction (PPI) networks to model context-specific information flow, gene utility, and key edges and differentially utilized gene networks, was developed to address this limitation of differential expression analysis. This protocol is a beginner-friendly, step-by-step guide to using NetDecoder, with comprehensive guidelines spanning data preprocessing, NetDecoder execution, and analysis of outputs. The workflow includes software configuration, network construction, and flow-based modeling analysis to quantify gene (node) and gene-gene interaction (edge-level) differences between biological conditions. The resulting outputs include key targets and routers, differential flow subnetworks, and edge flow distributions, enabling identification of key regulatory genes and pathways associated with specific biological states. After following the outlined steps, researchers will be able to conduct independent research to uncover phenotypic gene flow across phenotypes using transcriptomic data and curated PPI networks.