bioRxivSystems BiologyPreprint
CrosstalkNet: mining large-scale bipartite co-expression networks to characterize epi-stroma crosstalk
Venkata SK. ManemiD, George Alexandru AdamiD, Tina GruossoiD, Mathieu GigouxiD, Nicholas BertosiD, Morag ParkiD, Benjamin Haibe‐KainsiD
Abstract
BackgroundOver the last several years, we have witnessed the metamorphosis of network biology from being a mere representation of molecular interactions to models enabling inference of complex biological processes. Networks provide promising tools to elucidate intercellular interactions that contribute to the functioning of key biological pathways in a cell. However, the exploration of these large-scale networks remains a challenge due to their high-dimensionality.\n\nResultsCrosstalkNet is a user friendly, web-based network visualization tool to retrieve and mine interactions in large-scale bipartite co-expression networks. In this study, we discuss the use of gene co-expression networks to explore the rewiring of interactions between tumor epithelial and stromal cells. We show how CrosstalkNet can be used to efficiently visualize, mine, and interpret large co-expression networks representing the crosstalk occurring between the tumour and its microenvironment.\n\nConclusionCrosstalkNet serves as a tool to assist biologists and clinicians in exploring complex, large interaction graphs to obtain insights into the biological processes that govern the tumor epithelial-stromal crosstalk. A comprehensive tutorial along with case studies are provided with the application.\n\nAvailabilityThe web-based application is available at the following location: http://epistroma.pmgenomics.ca/app/. The code is open-source and freely available from http://github.com/bhklab/EpiStroma-webapp.\n\nContactbhaibeka@uhnresearch.ca
- assay: bulk RNA-seq
- research focus: cell-cell communication
- research focus: benchmarking
- research focus: database / resource
- research focus: software / tool
- approach: statistical model
- Citations
- 0
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