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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 25, 2025

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Published on: October 25, 2018

BASiCS工作流:使用单细胞RNA测序数据逐步分析表达变异性.

Alan O'Callaghan¹, Nils Eling^2,3, John C Marioni^4,5

¹MRC Human Genetics Unit, Institute of Genetics & Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK.

|May 23, 2024

概括

本研究介绍了BASiCS,这是一种用于分析单细胞RNA测序数据中的基因表达变异性的计算工作流. 它可对细胞异质性进行可靠的量化,并识别细胞组之间的显著变化,同时考虑技术噪声.

关键词:

贝叶斯语贝叶斯语贝叶斯语贝叶斯语生物信息学是一种生物信息学.差异表达测试差异表达测试表达的变化性表达的变化性.不同质性的异质性我们的 scRNAseqq.一个单细胞RNA测序.转录的噪声转录的噪声

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Last Updated: Jun 25, 2025

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

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科学领域:

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

背景情况:

细胞对细胞基因表达的变异性在免疫和发育等生物系统中至关重要.
单细胞RNA测序 (scRNA-seq) 量化了这种异质性,但受到技术噪音的影响.

研究的目的:

使用BASiCS生物导体包呈现计算工作流程,以稳定量化scRNA-seq数据中的基因表达变异性.
为了确定细胞群内和细胞群之间的细胞异质性,同时考虑技术噪声.

主要方法:

使用BASiCS生物导体包进行集成数据规范化,技术噪声量化和下游分析.
采用概率决策规则来识别细胞群之间的表达变异性的变化.
综合质量控制和数据探索使用scatter和scran生物导体包.

主要成果:

BASiCS有效量化了细胞组内和细胞组之间的表达变异性,区分了高度和低可变的基因.
工作流成功地确定了细胞群体之间的表达变异性变化,对技术噪音和丰度差异有很强的抵抗力.
使用公开的scRNA-seq数据集展示了一个完整的管道.

结论:

BASiCS 工作流提供了一个强大的框架,用于分析scRNA-seq数据中的基因表达变异性.
这种方法增强了对复杂生物系统中细胞异质性的理解.
通过Docker图像确保计算管道的可复制性.