scSpatial 发布单细胞空间组学图谱，整合 630 个项目逾 1800 张组织切片
scSpatial: an atlas for single-cell spatial omics
scSpatial 作为单细胞空间组学（SCSO）图谱发布，整合了 630 个项目、16 种空间技术产生的 1800 多张组织切片，并把超过 2000 万个具空间位置信息的细胞注释为 173 个标准化 Cell Ontology 类型。作者指出，SCSO 数据此前分散在各自发表的论文中，缺少综合资源，因此构建了这一带专家注释和高分辨率空间映射的图谱。平台提供面向 SCSO 的分析与交互可视化，包括空间基因表达图谱、细胞类型分布图、空间可变基因、基因表达相关性和通路水平的空间活性谱。scSpatial 无需登录即可免费访问。
来源：Nucleic Acids Research · doi.org
该图谱把分散在 630 个项目中的单细胞空间组学数据统一注释并可视化，便于跨数据集比较组织空间结构。
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/.