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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: Sep 17, 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

对大规模单细胞RNA测序数据的差异细胞通信推断框架.

Giulia Cesaro¹, Giacomo Baruzzo¹, Gaia Tussardi¹

¹Department of Information Engineering, University of Padova, Padova 35131, Italy.

NAR genomics and bioinformatics

|June 30, 2025

概括

此摘要是机器生成的。

本研究介绍了scSeqCommDiff,这是一个用于分析单细胞转录组学数据中的细胞-细胞通信差异的计算框架. 它可以在实验条件下高效灵活地分析改变的细胞交叉通话.

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An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

Published on: May 23, 2018

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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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Published on: January 10, 2019

Using R, Seurat, and CellChat to Analyze a Single-Cell Transcriptomics Dataset of Mouse Skin Wound Healing

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An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

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科学领域:

计算生物学计算生物学
基因组学就是基因组学.
系统生物学系统生物学

背景情况:

单细胞转录组学对于理解生物过程中的细胞-细胞通信至关重要.
在各种条件下量化细胞间和细胞内通信变异是具有挑战性的.
现有的计算工具缺乏灵活性和用户友好的可视化,用于差分通信分析.

研究的目的:

从单细胞转录组学数据推断和分析差异性细胞-细胞通信的可概括的计算框架.
解决现有方法的灵活性和解释性的局限性.
为了实现改变细胞交叉通话的快速和内存高效的分析.

主要方法:

开发了一个基于统计和网络的计算框架,scSeqCommDiff.
集成的CClens,一个用户友好的Shiny应用程序进行交互式分析.
使用空间转录学和与其他工具的比较来验证.

主要成果:

在大规模数据集上展示了scSeqCommDiff框架的可靠性,可扩展性和效率.
成功将工作流应用于单核转录组学数据集.
与健康受试者相比,肌缩性侧面硬化症患者的细胞细胞相互作用的未解决的改变.

结论:

scSeqCommDiff框架为差异细胞-细胞通信分析提供了强大而高效的解决方案.
集成的CClens应用程序提高了可解释性和用户友好性.
该框架对于研究包括疾病在内的各种生物环境中的细胞相互作用是有价值的.