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相关概念视频

RNA-seq03:21

RNA-seq

10.1K
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...
10.1K

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相关实验视频

Updated: Jul 27, 2025

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

Published on: January 10, 2019

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实用生物信息学管道用于单细胞RNA-seq数据分析.

Jiangping He1, Lihui Lin2, Jiekai Chen1,2

  • 1Center for Cell Lineage and Atlas (CCLA), Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou 510320, China.

Biophysics reports
|June 8, 2023
PubMed
概括
此摘要是机器生成的。

单细胞RNA测序 (scRNA-seq) 分析涉及复杂的计算工作流. 本综述提供了分析scRNA-seq数据的最佳实践指南,帮助研究人员选择合适的工具和管道.

关键词:
实用的生物信息学管道单细胞RNA测序 (scRNA-seq) 是一种在 scRNA-seq 分析中,

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A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
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相关实验视频

Last Updated: Jul 27, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
10:12

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

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A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
07:09

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

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Single-cell RNA Sequencing and Analysis of Human Pancreatic Islets
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Single-cell RNA Sequencing and Analysis of Human Pancreatic Islets

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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:

  • 单细胞RNA测序 (scRNA-seq) 为细胞分析提供了前所未有的分辨率.
  • 在工具选择和性能比较方面,scRNA-seq数据分析工具的扩散给研究人员带来了挑战.

研究的目的:

  • 为scRNA-seq数据提供计算分析工作流的全面概述.
  • 为实验人员和用户更新分析管道提供最佳实践指南.

主要方法:

  • 详细审查scRNA-seq分析步骤:实验设计,预处理,质量控制,特征选择,维度缩小,细胞聚类,注释和下游分析.
  • 包括先进的技术,如批次校正,轨迹推断和细胞-细胞通信分析.

主要成果:

  • 为scRNA-seq数据分析提供了一个结构化的工作流.
  • 在分析的每个阶段提供了最佳实践的指导方针.

结论:

  • 这一评论对于分析scRNA-seq数据的研究人员来说是一个有价值的资源.
  • 它旨在帮助用户驾scRNA-seq分析的复杂性,并优化他们的管道.