Resolving sensitivity, specificity and signal contamination in Xenium spatial transcriptomics

doi:10.1038/s41592-026-03089-8

2026-04-30

Marina Alexandre Gaveta

DOI：10.1038/s41592-026-03089-8

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摘要

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空间转录组学使完整组织内的高分辨率基因表达映射成为可能。Xenium因其可靠性、易用性和数据质量而被广泛采用，但其衍生数据的特性和局限性仍缺乏充分表征。本研究呈现了迄今最全面的Xenium数据集之一，包含超过40个使用不同基因面板表征的乳腺癌和肺癌组织切片。利用这一资源，我们系统地剖析了技术噪声（包括转录溢出）、检测特异性、基因面板性能和分割策略。我们证明单核RNA测序能够精确量化转录污染。基于这些发现，我们引入了SPLIT（分层细胞内转录本空间纯化）方法，通过解析混合转录组信号来提高信号纯度。SPLIT增强了背景校正和细胞类型分辨率，并揭示了与恶性细胞共定位相关的T细胞耗竭特征——这些信号在未经处理时会保持模糊。综合来看，我们的发现为Xenium性能提供了关键基准，并引入了一种可扩展的信号优化策略。本研究调查了Xenium空间转录组学数据中的技术噪声（包括转录溢出），并引入SPLIT以解析混合信号并增强细胞类型特异性。

Keyword:

Xenium

spatial transcriptomics

transcript spillover

signal contamination

cell-type resolution

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期刊

Nature Methods

IF:

32.1

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7.2K

被引数:

12.7W

机构

swiss cancer center leman

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论文数: 4

被引数: 0

university of lausanne

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被引数: 2

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