SpatialZoomer: multi-scale feature analysis of spatial transcriptomics

Xinqi Li

doi:10.1038/s41551-026-01800-w

2026-10-14

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DOI：10.1038/s41551-026-01800-w

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单细胞分辨率的空间转录组学为探索不同组织中的复杂细胞内容提供了巨大机会。本文介绍了一种基于谱图的方法SpatialZoomer，该方法通过应用一组低通滤波器，能够从空间转录组学数据中高效提取多分辨率或尺度的空间分子特征，包括单细胞尺度、包含数十个紧密相互作用细胞的生态位尺度以及具有空间组织细胞内容的区域尺度。相应的关键尺度可以通过划分跨尺度相似性图自动识别。结果表明，SpatialZoomer可以在阿尔茨海默病中识别特定尺度的疾病进展信号，以及在肿瘤微环境中识别空间上下文依赖的细胞亚型。提取的多尺度特征还揭示了癌症中的空间异质性生态位。SpatialZoomer在单尺度任务中实现了与现有方法相当或更优的性能，并且具有高计算效率和低硬件要求的优势。SpatialZoomer是一种基于谱图的方法，用于分析从单细胞到空间组织区域的多尺度空间转录组学数据。这些演示突显了跨尺度研究异质性病变组织的强大能力。

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Nature Biomedical Engineering

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China Agricultural University

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peking university health science center

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