Knowledge-graph-based cell-cell communication inference for spatially resolved transcriptomic data with SpaTalk

Xin Shao, Chengyu Li, Haihong Yang, Xiaoyan Lu, Jie Liao, Jingyang Qian, Kai Wang, Junyun Cheng, Penghui Yang, Huajun Chen (), Xiao Xu () and Xiaohui Fan ()
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Xin Shao: Zhejiang University School of Medicine
Chengyu Li: Zhejiang University
Haihong Yang: Zhejiang University
Xiaoyan Lu: Zhejiang University
Jie Liao: Zhejiang University
Jingyang Qian: Zhejiang University
Kai Wang: Zhejiang University School of Medicine
Junyun Cheng: Zhejiang University
Penghui Yang: Zhejiang University
Huajun Chen: Zhejiang University
Xiao Xu: Zhejiang University School of Medicine
Xiaohui Fan: Zhejiang University School of Medicine

Nature Communications, 2022, vol. 13, issue 1, 1-15

Abstract: Abstract Spatially resolved transcriptomics provides genetic information in space toward elucidation of the spatial architecture in intact organs and the spatially resolved cell-cell communications mediating tissue homeostasis, development, and disease. To facilitate inference of spatially resolved cell-cell communications, we here present SpaTalk, which relies on a graph network and knowledge graph to model and score the ligand-receptor-target signaling network between spatially proximal cells by dissecting cell-type composition through a non-negative linear model and spatial mapping between single-cell transcriptomic and spatially resolved transcriptomic data. The benchmarked performance of SpaTalk on public single-cell spatial transcriptomic datasets is superior to that of existing inference methods. Then we apply SpaTalk to STARmap, Slide-seq, and 10X Visium data, revealing the in-depth communicative mechanisms underlying normal and disease tissues with spatial structure. SpaTalk can uncover spatially resolved cell-cell communications for single-cell and spot-based spatially resolved transcriptomic data universally, providing valuable insights into spatial inter-cellular tissue dynamics.

Date: 2022
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DOI: 10.1038/s41467-022-32111-8

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