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RNA-seq

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...

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相关实验视频

Updated: Jun 24, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

扫描图:整合大型和多样化的单细胞转录组数据集.

Brian L Hie^1,2,3, Soochi Kim^4,5, Thomas A Rando^4,5,6,7

¹Department of Chemical Engineering, Stanford University School, Stanford, CA, USA. brianhie@stanford.edu.

Nature protocols

|June 6, 2024

概括

此摘要是机器生成的。

Scanorama有效地合并了多种单细胞RNA测序 (scRNA-seq) 数据集,克服了来自不同细胞组成和技术噪声的挑战. 这一协议使得scRNA-seq数据集成对使用Google Colaboratory的研究人员更容易获得.

更多相关视频

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

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

Published on: March 29, 2024

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

相关实验视频

Last Updated: Jun 24, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

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

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

Published on: March 29, 2024

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

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:

单细胞RNA测序 (scRNA-seq) 可以生成高分辨率的转录组数据.
整合多样化的scRNA-seq数据集对于发现生物学见解至关重要,但由于细胞组成和技术差异的不同,面临着挑战.
现有的方法难以有效地将数据集与异质细胞类型分布合并.

研究的目的:

介绍使用Scanorama集成异质scRNA-seq数据的详细协议.
为了解决来自不同实验条件,测序深度和批量效应的技术变化.
提高合并scRNA-seq数据集的质量和可解释性.

主要方法:

使用Scanorama,这是一个用于scRNA-seq数据集成的计算工具.
在基于Scanpy的分析工作流中集成Scanorama.
利用谷歌协作平台实现基于云的可访问协议.

主要成果:

Scanorama有效地将来自不同来源的scRNA-seq数据合并,提高数据质量.
整合过程解决了多数据集scRNA-seq研究中固有的技术差异.
该协议有助于分析具有多种细胞类型组成的异质scRNA-seq数据集.

结论:

Scanorama 提供了一个强大的解决方案,用于整合多种scRNA-seq数据集,特别是那些具有复杂细胞类型组成的数据集.
开发的协议与谷歌协作相结合,为更广泛的研究社区民主化scRNA-seq数据集成.
这种方法增强了可以从多实验scRNA-seq数据分析中获得的生物学见解.