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在基于单细胞成像的空间解析转录组学中,基因计数正常化.

Lyla Atta1,2, Kalen Clifton1,2, Manjari Anant2,3

  • 1Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.

Genome biology
|June 12, 2024
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概括
此摘要是机器生成的。

基于成像的空间解析转录学 (im-SRT) 中的规范化方法可以扭曲结果. 使用非基因计数规范化或代表性基因面板可以提高数据可靠性,以便进行准确的生物解释.

关键词:
不同表达式的差异表达式规范化 规范化 规范化扩展因子的扩展因子空间转录组学 空间转录组学

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科学领域:

  • 文字转录学 (Transcriptomics) 是一个学科.
  • 空间生物学 空间生物学
  • 生物信息学是一种生物信息学.

背景情况:

  • 基于成像的空间解析转录组学 (im-SRT) 允许在固定的组织中进行高通量基因和位置分析.
  • 规范化对于纠正技术变异和在im-SRT数据中揭示真正的生物信号至关重要.

研究的目的:

  • 研究不同的规范化方法和基因组如何影响im-SRT数据分析和解释.
  • 评估标准化诱导偏差对下游分析的影响.

主要方法:

  • 使用模拟的im-SRT基因面板,过度代表特定组织区域或细胞类型.
  • 基于每个细胞检测到的基因计数的规范化方法与基于非基因计数的方法 (例如细胞体积/面积) 进行了比较.

主要成果:

  • 使用每细胞基因计数的规范化方法以特定区域和细胞类型的方式对基因表达量进行了差异性改变.
  • 这些正常化诱导的效应导致差异性基因表达和空间变量基因分析的错误阳性和负性.
  • 基于非基因计数的正常化方法没有表现出这些偏差.

结论:

  • 不基于基因计数的规范化方法建议在可行的情况下进行im-SRT分析.
  • 在应用基于基因计数的正常化之前,评估基因组的代表性至关重要.
  • 规范化方法和基因组的选择显著影响im-SRT数据的生物学解释.