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.

DEsubs is a network-based systems biology R package that extracts disease-perturbed subpathways within a pathway network as recorded by RNA-seq experiments. It contains an extensive and customized framework with a broad range of operation modes at all stages of the subpathway analysis, enabling so a case-specific approach. The operation modes include pathway network construction and processing, subpathway extraction, visualization and enrichment analysis with regard to various biological and pharmacological features. Its capabilities render DEsubs a tool-guide for both the modeler and experimentalist for the identification of more robust systems-level drug targets and biomarkers for complex diseases. AVAILABILITY AND IMPLEMENTATION: DEsubs is implemented as an R package following Bioconductor guidelines: http://bioconductor.org/packages/DEsubs/ CONTACT: [email protected] information: Supplementary data are available at Bioinformatics online.

MOTIVATION: In the era of network medicine and the rapid growth of paired time series mRNA/microRNA expression experiments, there is an urgent need for pathway enrichment analysis methods able to capture the time- and condition-specific 'active parts' of the biological circuitry as well as the microRNA impact. Current methods ignore the multiple dynamical 'themes'-in the form of enriched biologically relevant microRNA-mediated subpathways-that determine the functionality of signaling networks across time. RESULTS: To address these challenges, we developed time-vaRying enriCHment integrOmics Subpathway aNalysis tOol (CHRONOS) by integrating time series mRNA/microRNA expression data with KEGG pathway maps and microRNA-target interactions. Specifically, microRNA-mediated subpathway topologies are extracted and evaluated based on the temporal transition and the fold change activity of the linked genes/microRNAs. Further, we provide measures that capture the structural and functional features of subpathways in relation to the complete organism pathway atlas. Our application to synthetic and real data shows that CHRONOS outperforms current subpathway-based methods into unraveling the inherent dynamic properties of pathways. AVAILABILITY AND IMPLEMENTATION: CHRONOS is freely available at http://biosignal.med.upatras.gr/chronos/ CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.