SANTO: a coarse-to-fine alignment and stitching method for spatial omics

Haoyang Li, Yingxin Lin, Wenjia He, Wenkai Han, Xiaopeng Xu, Chencheng Xu, Elva Gao, Hongyu Zhao () and Xin Gao ()
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Haoyang Li: King Abdullah University of Science and Technology (KAUST)
Yingxin Lin: Yale University
Wenjia He: King Abdullah University of Science and Technology (KAUST)
Wenkai Han: King Abdullah University of Science and Technology (KAUST)
Xiaopeng Xu: King Abdullah University of Science and Technology (KAUST)
Chencheng Xu: King Abdullah University of Science and Technology (KAUST)
Elva Gao: King Abdullah University of Science and Technology (KAUST)
Hongyu Zhao: Yale University
Xin Gao: King Abdullah University of Science and Technology (KAUST)

Nature Communications, 2024, vol. 15, issue 1, 1-12

Abstract: Abstract With the flourishing of spatial omics technologies, alignment and stitching of slices becomes indispensable to decipher a holistic view of 3D molecular profile. However, existing alignment and stitching methods are unpractical to process large-scale and image-based spatial omics dataset due to extreme time consumption and unsatisfactory accuracy. Here we propose SANTO, a coarse-to-fine method targeting alignment and stitching tasks for spatial omics. SANTO firstly rapidly supplies reasonable spatial positions of two slices and identifies the overlap region. Then, SANTO refines the positions of two slices by considering spatial and omics patterns. Comprehensive experiments demonstrate the superior performance of SANTO over existing methods. Specifically, SANTO stitches cross-platform slices for breast cancer samples, enabling integration of complementary features to synergistically explore tumor microenvironment. SANTO is then applied to 3D-to-3D spatiotemporal alignment to study development of mouse embryo. Furthermore, SANTO enables cross-modality alignment of spatial transcriptomic and epigenomic data to understand complementary interactions.

Date: 2024
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DOI: 10.1038/s41467-024-50308-x

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