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相关概念视频

Cell Specific Gene Expression01:58

Cell Specific Gene Expression

Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...
DNA Microarrays02:34

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
RNA-seq03:21

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
Cell Specific Gene Expression01:58

Cell Specific Gene Expression

Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...

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相关实验视频

Updated: May 11, 2026

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使用Crescendo批量纠正单细胞空间转录组学计数数据,改善空间基因模式的可视化和检测.

Nghia Millard1,2,3,4,5,6,7, Jonathan H Chen6,7,8,9, Mukta G Palshikar2,3,6

  • 1Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Boston, MA, USA.

Genome biology
|February 25, 2025
PubMed
概括

批量效应在空间转录组学中隐藏了基因模式. 克雷斯登多算法纠正了这些效应,使得多个样本和技术中的基因表达可视化准确.

关键词:
批量纠正批量纠正一个不断增长的增长.配体-受体相互作用模式 模式 模式单细胞机是一种单细胞机.空间转录组学 空间转录组学

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科学领域:

  • 基因组学就是基因组学.
  • 生物信息学是一种生物信息学.
  • 计算生物学 计算生物学

背景情况:

  • 空间转录学能够在解剖学上进行基因表达分析.
  • 批量效应对在不同样本中可视化和整合基因表达模式构成重大挑战.
  • 准确的交叉样本分析对于理解复杂的生物系统至关重要.

研究的目的:

  • 开发一种用于纠正空间转录组学数据中的批量效应的计算方法.
  • 为了使多个样本中基因表达模式的准确可视化和分析.
  • 增强下游分析,如基因同位化和配体-受体相互作用检测.

主要方法:

  • 在基因表达水平上进行批量效应校正的Crescendo算法的开发.
  • 应用Crescendo对空间和单细胞RNA测序数据集.
  • 评估Crescendo在17万至700万个细胞的数据集上的性能.

主要成果:

  • Crescendo有效地纠正批量效应,允许在样本中准确的基因表达可视化.
  • 该算法在各种数据集和技术中展示了实用性和可扩展性.
  • 纠正后的数据提高了检测基因局部化和配体-受体相互作用的性能.

结论:

  • 克雷斯登多是一个强大的算法,用于减轻空间转录学中的批量效应.
  • 该方法促进了可靠的跨样本和跨技术数据集成.
  • 克雷斯登多显著提高了空间转录学在生物发现方面的能力.