在单细胞分辨率下将免疫组织化学和H&E注释与Xenium数据集成的协议.
Jun Chen1, William Hartnett1, Vijay S Basava1
1Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
STAR protocols
|September 27, 2025
概括
这项研究引入了一项协议,将外部数据 (如免疫组织化学) 整合到空间转录基因数据集中. 这种方法增强了针对单细胞分辨率数据的有针对性的分析,以获得生物学见解.
科学领域:
- 单细胞生物学 单细胞生物学
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
背景情况:
- 空间转录学产生高分辨率数据,但从整合多样化的外部信息中获益.
- 定制的外部数据集成对于对空间转录数据集的有针对性的调查至关重要.
研究的目的:
- 介绍一种将外部数据嵌入空间转录组数据集的协议.
- 通过整合视野注释和免疫组织化学数据来实现单细胞分辨率分析.
- 使用开源工具,促进针对Xenium数据集的有针对性的分析.
主要方法:
- 图像注册用于将外部数据与空间转录基因数据对齐.
- 嵌入不规则的视野注释和免疫组织化学数据.
- 集成到一个兼容Scanpy的数据对象中.
- 使用开源生物信息学工具.
主要成果:
- 成功将免疫组织化学数据集成到Xenium数据集中.
- 在anddata对象中展示空间对齐的信息.
- 适用于头部和部状细胞癌样本.
结论:
- 开发的协议使外部信息能够灵活地集成到空间转录基因数据中.
- 促进复杂生物样本的有针对性的单细胞分辨率分析.
- 增强空间转录基因数据集的研究实用性.
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