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Supplementary Video S6 from CrosstalkNet: A Visualization Tool for Differential Co-expression Networks and Communities

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posted on 2024-07-23, 18:00 authored by Venkata Manem, George Alexandru Adam, Tina Gruosso, Mathieu Gigoux, Nicholas Bertos, Morag Park, Benjamin Haibe-Kains

This video presents on how to upload communities of the co-expression network files, visualize them and download all the interactions in each community in a CSV format.

Funding

National Institutes of Health

Cancer Research Society

Canadian Institutes of Health Research

Princess Margaret Cancer

Natural Sciences and Engineering Research Council of Canada

Ministry of Economic Development, Innovation

Ministry of Research & Innovation of Ontario,

Stand Up To Cancer Canada—Canadian Cancer Society Breast Cancer Dream Team Research

Government of Ontario

American Association for Cancer Research International—Canada

History

ARTICLE ABSTRACT

Variations in physiological conditions can rewire molecular interactions between biological compartments, which can yield novel insights into gain or loss of interactions specific to perturbations of interest. Networks are a promising tool to elucidate intercellular interactions, yet exploration of these large-scale networks remains a challenge due to their high dimensionality. To retrieve and mine interactions, we developed CrosstalkNet, a user friendly, web-based network visualization tool that provides a statistical framework to infer condition-specific interactions coupled with a community detection algorithm for bipartite graphs to identify significantly dense subnetworks. As a case study, we used CrosstalkNet to mine a set of 54 and 22 gene-expression profiles from breast tumor and normal samples, respectively, with epithelial and stromal compartments extracted via laser microdissection. We show how CrosstalkNet can be used to explore large-scale co-expression networks and to obtain insights into the biological processes that govern cross-talk between different tumor compartments.Significance: This web application enables researchers to mine complex networks and to decipher novel biological processes in tumor epithelial-stroma cross-talk as well as in other studies of intercompartmental interactions. Cancer Res; 78(8); 2140–3. ©2018 AACR.

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