scSpatial: an atlas for single-cell spatial omics

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ID: 333545
2026
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Abstract
Abstract Single-cell spatial omics (SCSO) has reshaped spatial profiling by enabling simultaneous molecular characterization and spatial mapping at single-cell resolution, providing insights into cellular identities and tissue architecture within native biological contexts. By integrating spatial coordinates with molecular profiles and cell identities, SCSO datasets have been widely used to construct spatially resolved cell atlases, characterize disease-associated tissue remodeling, and map disease-relevant cell populations. However, these SCSO datasets remain fragmented across individual publications, and comprehensive SCSO resources are still lacking. Here, scSpatial was therefore developed as an atlas for SCSO with expert-curated cell annotations and high-resolution spatial mappings. The current release of scSpatial curates a large-scale collection of SCSO data, comprising over 1800 tissue sections from 630 projects generated using 16 spatial technologies; provides >20 million spatially resolved cells annotated into 173 standardized Cell Ontology types; and offers SCSO-tailored analyses and interactive visualizations, including spatial gene expression atlases, cell type distribution maps, spatially variable genes, gene expression correlations, and pathway-level spatial activity profiles. scSpatial is freely accessible to all users without requiring login at https://idrblab.org/scspatial/.
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openalex_W7223258335 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Huaicheng Sun, Yun Bei, Zijie Zhu, Jiannan Deng, Yuan Zhou, Minjie Mou, Tao-Feng Wei, Hengbin Cao, Qingxia Yang, Chong Yao, Feng Zhu
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Journal Nucleic Acids Research
Year 2026
DOI
10.1093/nar/gkag993
URL
https://doi.org/10.1093/nar/gkag993
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