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相关概念视频

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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相关实验视频

Updated: Jul 9, 2025

Author Spotlight: Integrating Organoid Models with Single-Cell and Spatial Transcriptomics Technologies
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Author Spotlight: Integrating Organoid Models with Single-Cell and Spatial Transcriptomics Technologies

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使用深度生成模型与SpatialScope集成空间和单细胞转录组学数据.

Xiaomeng Wan1, Jiashun Xiao2, Sindy Sing Ting Tam3

  • 1Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong SAR, China.

Nature communications
|November 29, 2023
PubMed
概括
此摘要是机器生成的。

SpatialScope 增强了空间转录组学 (ST) 数据,以实现单细胞分辨率和转录组范围的分析. 这种统一的方法整合了基于测序和基于图像的ST数据,以获得更深入的生物学见解.

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Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq
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相关实验视频

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科学领域:

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

背景情况:

  • 空间转录学 (ST) 技术正在推动组织生物学理解.
  • 目前的ST方法在细胞分辨率或转录组全方位分析方面存在局限性.

研究的目的:

  • 介绍SpatialScope,一个统一的深度生成模型方法用于ST数据分析.
  • 为了增强基于seq的ST数据以单细胞分辨率,并推断基于图像的ST数据的转录组范围的表达.

主要方法:

  • 单细胞RNA测序 (scRNA-seq) 参考数据与ST数据的整合.
  • 应用深度生成模型用于数据增强和推理.
  • 通过模拟研究和现实世界基于seq和基于图像的ST数据进行验证.

主要成果:

  • 空间镜成功地将基于seq的ST数据增强到单细胞分辨率.
  • SpatialScope准确地推断出基于图像的ST数据的转录组范围的表达水平.
  • 在空间表征,细胞通信分析和识别空间上不同的基因表达的实用性.

结论:

  • 空间望远镜提供了一个统一的解决方案,以克服当前ST技术的局限性.
  • 提供全转录组,单细胞分辨率的组织空间特征.
  • 促进生物发现的先进下游分析.