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COMUNET: A tool to explore and visualize intercellular communication.

Bioinformatics 36, 4296-4300 (2020)
Verlagsversion Forschungsdaten DOI
Open Access Gold (Paid Option)
Creative Commons Lizenzvertrag
MOTIVATION: Intercellular communication plays an essential role in multicellular organisms and several algorithms to analyze it from single-cell transcriptional data have been recently published, but the results are often hard to visualize and interpret. RESULTS: We developed Cell cOmmunication exploration with MUltiplex NETworks (COMUNET), a tool that streamlines the interpretation of the results from cell-cell communication analyses. COMUNET uses multiplex networks to represent and cluster all potential communication patterns between cell types. The algorithm also enables the search for specific patterns of communication and can perform comparative analysis between two biological conditions. To exemplify its use, here we apply COMUNET to investigate cell communication patterns in single-cell transcriptomic datasets from mouse embryos and from an acute myeloid leukemia patient at diagnosis and after treatment. AVAILABILITY AND IMPLEMENTATION: Our algorithm is implemented in an R package available from https://github.com/ScialdoneLab/COMUNET, along with all the code to perform the analyses reported here. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
ISSN (print) / ISBN 1367-4803
Zeitschrift Bioinformatics
Quellenangaben Band: 36, Heft: 15, Seiten: 4296-4300 Artikelnummer: , Supplement: ,
Verlag Oxford University Press
Verlagsort Oxford