Volume 11 Issue 12
Dec.  2020
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Xin Shao, Xiaoyan Lu, Jie Liao, Huajun Chen, Xiaohui Fan. New avenues for systematically inferring cellcell communication: through single-cell transcriptomics data[J]. Protein&Cell, 2020, 11(12): 866-880. doi: 10.1007/s13238-020-00727-5
Citation: Xin Shao, Xiaoyan Lu, Jie Liao, Huajun Chen, Xiaohui Fan. New avenues for systematically inferring cellcell communication: through single-cell transcriptomics data[J]. Protein&Cell, 2020, 11(12): 866-880. doi: 10.1007/s13238-020-00727-5

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

doi: 10.1007/s13238-020-00727-5
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This study was supported by the National Natural Science Foundation of China (Grant Nos. 81774153 and 81973701), the Natural Science Foundation of Zhejiang Province (LZ20H290002), and the National Youth Top-notch Talent Support Program (W02070098).

  • Received Date: 2020-02-04
  • 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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