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COMUNET: A tool to explore and visualize intercellular communication.
Bioinformatics 36, 4296-4300 (2020)
Publ. Version/Full Text
Research data
DOI
PMC
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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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Bone-marrow; Cell
ISSN (print) / ISBN
1367-4803
Journal
Bioinformatics
Quellenangaben
Volume: 36,
Issue: 15,
Pages: 4296-4300
Publisher
Oxford University Press
Publishing Place
Oxford
Non-patent literature
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Reviewing status
Peer reviewed