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Identification of Differentially Expressed Subpathways using a Consensus Approach

The emergence of diseases and drug-induced perturbations are oftentimes the cause of biological pathway deregulations. Identifying differentially expressed subpathways in organism-level networks of signaling pathways can be a computationally intensive undertaking, due to their complexity. In this direction, we present a subpathway analysis method which refines organism-level networks via a two step-approach. The method first constructs a core-network of differentially expressed genes and subsequently includes a set of topologically significant non-differentially expressed genes, that both exhibit correlated expression levels with their neighbors and facilitate the signal propagation within the core-network. The refined network is then searched for differentially expressed subpathways using a plethora of subpathway identification methods and checked for enrichment in functional terms such as drugs and diseases. The approach assesses the differential expression of the subpathways using a consensus approach, by detecting even weak signals of differential expression, while accounting for correlations which arise in gene expression data.