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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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Updated: Jun 23, 2025

Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2

Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2

Published on: September 18, 2021

HCCDB v2.0:通过单细胞RNA-seq和HCC中的空间转录学来分解表达变异.

Ziming Jiang¹, Yanhong Wu², Yuxin Miao²

¹Eight-Year Program of Clinical Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100006, China.

Genomics, proteomics & bioinformatics

|June 17, 2024

概括

更新的肝细胞癌数据库 (HCCDB v2.0) 整合了批量,单细胞和空间转录组数据,用于全面的分子分析. 这种增强的资源有助于理解肝细胞癌 (HCC) 和识别预后相关细胞和瘤微环境.

关键词:

数据库数据库数据库是一个数据库.肝细胞癌是肝细胞癌.综合性分析是一种综合性分析.单细胞RNA测序的一个细胞.空间转录组学空间转录组学

更多相关视频

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

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

相关实验视频

Last Updated: Jun 23, 2025

Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2

Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2

Published on: September 18, 2021

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

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

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.
癌症研究癌症研究

背景情况:

大规模的转录基因数据对于理解肝细胞癌 (HCC) 的分子特征至关重要.
最初的HCC数据库 (HCCDB v1.0) 使用15个数据集的元分析提供了对HCC异质性的系统视图.
单细胞和空间转录学方面的进步需要更新数据库,以纳入新的数据和分析能力.

研究的目的:

介绍HCCDB v2.0,一个更新的版本,集成批量,单细胞和肝细胞癌 (HCC) 的空间转录基因数据.
扩大数据库以显著增加样本和细胞数据,提高元分析的可靠性.
引入新的分析指标和可视化工具,以在细胞和空间层面探索HCC.

主要方法:

整合了11个新的转录基因数据集,将1656个批量样本添加到现有的3917.
集成的单细胞 (182,832 个细胞) 和空间转录组 (69,352 个点) 数据.
开发了一种新的单细胞水平二维 (sc-2D) 度量,用于分析细胞类型特定的基因表达模式.

主要成果:

HCCDB v2.0显著扩大了可用于HCC研究的转录基因数据的规模.
该数据库现在包括了全面的单细胞和空间转录组概况,提供细胞级分辨率.
在识别预后相关细胞和分析瘤微环境方面有明显的应用.

结论:

HCCDB v2.0为研究肝细胞癌 (HCC) 分子景观提供了一个强大的,最新的资源.
综合多种转录组数据类型,可以更深入地了解HCC异质性和生物学.
这个用户友好的在线门户网站为癌症研究人员提供了数据检索和探索的便利.