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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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Detalles Bibliográficos
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
Descripción
Sumario: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.