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Spatial-linked alignment tool (SLAT) for aligning heterogenous slices

Author

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  • Chen-Rui Xia

    (Peking University
    Changping Laboratory)

  • Zhi-Jie Cao

    (Peking University
    Changping Laboratory)

  • Xin-Ming Tu

    (Peking University
    University of Washington)

  • Ge Gao

    (Peking University
    Changping Laboratory)

Abstract

Spatially resolved omics technologies reveal the spatial organization of cells in various biological systems. Here we propose SLAT (Spatially-Linked Alignment Tool), a graph-based algorithm for efficient and effective alignment of spatial slices. Adopting a graph adversarial matching strategy, SLAT is the first algorithm capable of aligning heterogenous spatial data across distinct technologies and modalities. Systematic benchmarks demonstrate SLAT’s superior precision, robustness, and speed over existing state-of-the-arts. Applications to multiple real-world datasets further show SLAT’s utility in enhancing cell-typing resolution, integrating multiple modalities for regulatory inference, and mapping fine-scale spatial-temporal changes during development. The full SLAT package is available at https://github.com/gao-lab/SLAT .

Suggested Citation

  • Chen-Rui Xia & Zhi-Jie Cao & Xin-Ming Tu & Ge Gao, 2023. "Spatial-linked alignment tool (SLAT) for aligning heterogenous slices," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-43105-5
    DOI: 10.1038/s41467-023-43105-5
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    Cited by:

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    3. Haoyang Li & Yingxin Lin & Wenjia He & Wenkai Han & Xiaopeng Xu & Chencheng Xu & Elva Gao & Hongyu Zhao & Xin Gao, 2024. "SANTO: a coarse-to-fine alignment and stitching method for spatial omics," Nature Communications, Nature, vol. 15(1), pages 1-12, December.

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