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New avenues for systematically inferring cell-cell communication: through single-cell transcriptomics data

For multicellular organisms, cell-cell communication is essential to numerous biological processes. Drawing upon the latest development of single-cell RNA-sequencing (scRNA-seq), high-resolution transcriptomic data have deepened our understanding of cellular phenotype heterogeneity and composition o...

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Autores principales: Shao, Xin, Lu, Xiaoyan, Liao, Jie, Chen, Huajun, Fan, Xiaohui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Higher Education Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7719148/
https://www.ncbi.nlm.nih.gov/pubmed/32435978
http://dx.doi.org/10.1007/s13238-020-00727-5
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author Shao, Xin
Lu, Xiaoyan
Liao, Jie
Chen, Huajun
Fan, Xiaohui
author_facet Shao, Xin
Lu, Xiaoyan
Liao, Jie
Chen, Huajun
Fan, Xiaohui
author_sort Shao, Xin
collection PubMed
description For multicellular organisms, cell-cell communication is essential to numerous biological processes. Drawing upon the latest development of single-cell RNA-sequencing (scRNA-seq), high-resolution transcriptomic data have deepened our understanding of cellular phenotype heterogeneity and composition of complex tissues, which enables systematic cell-cell communication studies at a single-cell level. We first summarize a common workflow of cell-cell communication study using scRNA-seq data, which often includes data preparation, construction of communication networks, and result validation. Two common strategies taken to uncover cell-cell communications are reviewed, e.g., physically vicinal structure-based and ligand-receptor interaction-based one. To conclude, challenges and current applications of cell-cell communication studies at a single-cell resolution are discussed in details and future perspectives are proposed.
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spelling pubmed-77191482020-12-07 New avenues for systematically inferring cell-cell communication: through single-cell transcriptomics data Shao, Xin Lu, Xiaoyan Liao, Jie Chen, Huajun Fan, Xiaohui Protein Cell Review For multicellular organisms, cell-cell communication is essential to numerous biological processes. Drawing upon the latest development of single-cell RNA-sequencing (scRNA-seq), high-resolution transcriptomic data have deepened our understanding of cellular phenotype heterogeneity and composition of complex tissues, which enables systematic cell-cell communication studies at a single-cell level. We first summarize a common workflow of cell-cell communication study using scRNA-seq data, which often includes data preparation, construction of communication networks, and result validation. Two common strategies taken to uncover cell-cell communications are reviewed, e.g., physically vicinal structure-based and ligand-receptor interaction-based one. To conclude, challenges and current applications of cell-cell communication studies at a single-cell resolution are discussed in details and future perspectives are proposed. Higher Education Press 2020-05-21 2020-12 /pmc/articles/PMC7719148/ /pubmed/32435978 http://dx.doi.org/10.1007/s13238-020-00727-5 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Review
Shao, Xin
Lu, Xiaoyan
Liao, Jie
Chen, Huajun
Fan, Xiaohui
New avenues for systematically inferring cell-cell communication: through single-cell transcriptomics data
title New avenues for systematically inferring cell-cell communication: through single-cell transcriptomics data
title_full New avenues for systematically inferring cell-cell communication: through single-cell transcriptomics data
title_fullStr New avenues for systematically inferring cell-cell communication: through single-cell transcriptomics data
title_full_unstemmed New avenues for systematically inferring cell-cell communication: through single-cell transcriptomics data
title_short New avenues for systematically inferring cell-cell communication: through single-cell transcriptomics data
title_sort new avenues for systematically inferring cell-cell communication: through single-cell transcriptomics data
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7719148/
https://www.ncbi.nlm.nih.gov/pubmed/32435978
http://dx.doi.org/10.1007/s13238-020-00727-5
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