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Overview Of Cell Separation And Isolation

Overview Of Cell Separation And Isolation

Cell separation was first achieved in 1964 by S. H. Seal, who separated large tumor cells from the smaller blood cells using filtration. Two years later, Pohl and Hawk performed experiments on how cells respond differently to a nonuniform electric field based on the cell type. Such observations were the inception of cell separation methods, which allow isolating a single cell type from a heterogeneous sample.

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Updated: Jun 21, 2025

Single-cell RNA-Seq of Defined Subsets of Retinal Ganglion Cells

Single-cell RNA-Seq of Defined Subsets of Retinal Ganglion Cells

Published on: May 22, 2017

直接选择细胞类型标记基因用于单细胞聚类分析.

Zihao Chen¹, Changhu Wang¹, Siyuan Huang²

¹School of Mathematical Sciences and Center for Statistical Science, Peking University, Beijing 100871, China.

Cell reports methods

|July 9, 2024

概括

节日是一种新的统计方法,可以直接选择单细胞RNA测序 (scRNA-seq) 研究的细胞类型标记基因. 这种方法改善了细胞类型的识别,并发现了新的标记基因,即使对于罕见的细胞群体.

关键词:

CP:系统生物学系统生物学集群分析分析集群分析双倍的浸泡方式功能选功能选功能选功能选功能选不同质性测试不同质性测试高维度数据的高维度数据.基因高度变化的基因.标志性基因标记物基因鉴定混合物模型模型的混合物模型最终耗尽的T细胞终端分化的效应器内存T细胞.

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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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Last Updated: Jun 21, 2025

Single-cell RNA-Seq of Defined Subsets of Retinal Ganglion Cells

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Published on: May 22, 2017

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

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Published on: January 10, 2019

科学领域:

计算生物学计算生物学
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:

单细胞RNA测序 (scRNA-seq) 研究通常使用聚类和差异基因表达 (DEG) 分析来识别细胞类型和标记基因.
当前的方法通常依赖于基因选择的代用标准,这可能导致缺失重要的基因或包括不相关的基因,而DEG分析则受到选择偏差的影响.

研究的目的:

介绍Festem,一种用于scRNA-seq数据中直接选择细胞类型标记基因的新型统计方法.
在scRNA-seq分析中克服现有的基因选择和标记物检测方法的局限性.

主要方法:

节日直接选择标记基因,通过识别那些在细胞中具有异质分布的标记基因,这些基因对聚类具有信息性.
该方法使用模拟和现实世界scRNA-seq数据集进行了评估.

主要成果:

在选择标记基因方面,Festial表现出高精度和灵敏度.
该方法成功地确定了常规方法经常错过的细胞类型.
将其应用于肝内胆固醇癌数据集,揭示了多种CD8+T细胞类型和潜在的预后标记基因.

结论:

在scRNA-seq.中,Festial为细胞类型标记基因选择提供了更准确和更敏感的方法.
这种方法增强了细胞异质性的识别,并有助于发现临床相关的生物标志物.