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相关概念视频

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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RNA-seq03:21

RNA-seq

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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...
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Genome Annotation and Assembly03:36

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The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
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相关实验视频

Updated: Jun 30, 2025

Author Spotlight: Integrating Organoid Models with Single-Cell and Spatial Transcriptomics Technologies
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使用单细胞基因组和转录组测序数据共同推断克隆结构.

Xiangqi Bai1, Zhana Duren2, Lin Wan3,4

  • 1Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.

NAR genomics and bioinformatics
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PubMed
概括

一个新的计算框架,CCNMF,集成单细胞基因组 (scDNA) 和转录组 (scRNA) 数据来识别细胞克隆. 这种方法将副本数和基因表达联系起来,揭示复杂的生物样本中的克隆结构.

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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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科学领域:

  • 基因组学就是基因组学.
  • 文字转录学 (Transcriptomics) 是一个学科.
  • 计算生物学 计算生物学

背景情况:

  • 高通量单细胞测序 (scDNA和scRNA) 允许细胞解析组织克隆研究.
  • 整合来自同一样本的异质scRNA和scDNA数据用于克隆分析仍然是一个挑战.

研究的目的:

  • 从匹配的scDNA和scRNA数据中共同推断克隆结构的计算框架 (CCNMF).
  • 通过将副本号码和基因表达特征联系起来,将多个omics单细胞结合起来.

主要方法:

  • 开发了结合式克隆非负矩阵因数分解 (CCNMF).
  • CCNMF将scDNA拷贝数的改变与scRNA基因表达特征联系起来.
  • 使用模拟数据和真实世界癌症样本 (卵巢,胃) 进行验证.

主要成果:

  • 通过关联克隆基因组和转录组,CCNMF成功地解决了共存的克隆.
  • 在模拟和现实世界数据集中展示了高准确性和稳定性.
  • 启用了基因组和转录基因组克隆架构的同时解析.

结论:

  • CCNMF是一个强大的工具,用于整合多omics单细胞数据.
  • 促进对基因表达变化以及克隆基因组改变的理解.
  • 阐明了子克隆基因组差异对瘤进化有所贡献.