Communication between cells is crucial for coordinated cellular functions in multicellular organisms. We present an optimal transport theory-based tool to infer cell–cell communication networks, spatial signaling directions and downstream targets in multicellular systems from spatial gene expression data.
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References
Armingol, E., Officer, A., Harismendy, O. & Lewis, N. E. Deciphering cell–cell interactions and communication from gene expression. Nat. Rev. Genet. 22, 71–88 (2021). A review article on cell–cell communication analysis from gene expression data.
Moses, L. & Pachter, L. Museum of spatial transcriptomics. Nat. Methods 19, 534–546 (2022). A review article on spatial transcriptomics technologies and analysis methods.
Peyré, G. & Cuturi, M. Computational optimal transport: with applications to data science. In Foundations and Trends in Machine Learning 11, 355–607 (2019). A book on optimal transport and its applications.
Cang, Z., Nie, Q. & Zhao, Y. Supervised optimal transport. SIAM J. Appl. Math. 82, 1851–1877 (2022). A study of the mathematical details of the optimal transport method motivated by our study.
Jin, S. et al. Inference and analysis of cell–cell communication using CellChat. Nat. Commun. 12, 1088 (2021). This paper presents a widely used tool to infer cell–cell communication from non-spatial single-cell transcriptomics data.
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This is a summary of: Cang, Z. et al. Screening cell–cell communication in spatial transcriptomics via collective optimal transport. Nat. Methods https://doi.org/10.1038/s41592-022-01728-4 (2023).
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A mathematical method and software for spatially mapping intercellular communication. Nat Methods 20, 185–186 (2023). https://doi.org/10.1038/s41592-022-01729-3
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DOI: https://doi.org/10.1038/s41592-022-01729-3
