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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
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Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
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ADTnorm:在CITE-seq数据集中强有力的整合单细胞蛋白质测量.

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ADTnorm是一种用于规范化单细胞CITE-seq数据的新方法,可以改善蛋白质检测和细胞类型识别. 它有效地消除了批量效应,使各种数据集能够集成,从而获得更广泛的生物学见解.

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科学领域:

  • 单细胞多组组学分析
  • 免疫基因组学是什么
  • 计算生物学是一种计算生物学.

背景情况:

  • 在单细胞中,CITE-seq (转录体和表皮体序列的细胞索引) 测量了单细胞中的表面蛋白和mRNA表达.
  • 来自CITE-seq的抗体衍生标签 (ADT) 提供了强大的表面蛋白质检测,增强了细胞类型识别.
  • 抗体染色的变化导致ADT表达中的批量效应,阻碍了数据解释和交叉研究比较.

研究的目的:

  • 引入ADTnorm,一种专门针对CITE-seq数据中的抗体衍生标签 (ADT) 丰度而设计的新型规范化和整合方法.
  • 在CITE-seq实验中解决和减轻由抗体染色变异引起的批量效应.
  • 提高细胞类型识别的准确性,并使各种CITE-seq数据集的整合成为可能.

主要方法:

  • ADTnorm被开发为一种用于ADT丰度的规范化和整合方法.
  • 该方法与使用13个公共CITE-seq数据集的14种现有缩放和规范化技术进行了基准测试.
  • 基于细胞群的调整,技术变异的消除和细胞类型分离的改善来评估性能.

主要成果:

  • 在多个数据集中,ADTnorm在调整具有不同表面蛋白表达水平的细胞群中表现出卓越的性能.
  • 该方法有效地消除了不同批次的技术差异,提高了ADT表达数据的一致性.
  • ADTnorm增强了细胞类型的分离,并促进了公共CITE-seq数据集与各种实验设计的集成.

结论:

  • ADTnorm提供了一种有效的解决方案,用于规范化和整合CITE-seq ADT数据,克服批量效应并改善生物信号.
  • 该方法支持亚特拉斯级分析,允许整合异构的公共数据集.
  • ADTnorm包括用于自动值测定和抗体质量评估的实用程序,有助于实验优化和新生物标志物的发现,如COVID-19数据集所示.