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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, 2020-12, Vol.11 (12), p.866-880 [Periódico revisado por pares]

Beijing: Higher Education Press

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Título:
New avenues for systematically inferring cell-cell communication: through single-cell transcriptomics data
Autor: Shao, Xin ; Lu, Xiaoyan ; Liao, Jie ; Chen, Huajun ; Fan, Xiaohui
Assuntos: Animals ; Biochemistry ; Biomedical and Life Sciences ; Cell Biology ; Cell Communication ; Cell interactions ; Cell signaling ; cell-cell communication ; chemical signal-dependent communication ; Communication ; Developmental Biology ; Human Genetics ; Humans ; Life Sciences ; ligand-receptor interaction ; network biology ; Phenotypes ; physical contact-dependent communication ; Protein Science ; Review ; Ribonucleic acid ; RNA ; RNA-Seq ; Single-Cell Analysis ; single-cell RNA sequencing ; Stem Cells ; Transcriptome ; Transcriptomics
É parte de: Protein & cell, 2020-12, Vol.11 (12), p.866-880
Notas: ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-3
content type line 23
ObjectType-Review-1
Descrição: 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.
Editor: Beijing: Higher Education Press
Idioma: Inglês

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

Shao, Xin ; Lu, Xiaoyan ; Liao, Jie ; Chen, Huajun ; Fan, Xiaohui

Beijing: Higher Education Press

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