Automated methods for cell type annotation on scRNA-seq data.

Automated methods for cell type annotation on scRNA-seq data.
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scRNA-seq数据上细胞类型注释的自动化方法。

DOI:
10.1016/j.csbj.2021.01.015
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发表时间:
2021
影响因子:
6
通讯作者:
Busskamp V
Busskamp V
中科院分区:
生物学2区
文献类型:
--
作者:
Pasquini G;Rojo Arias JE;Schäfer P;Busskamp V

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单细胞测序的出现开启了转录组学和基因组学研究的新时代,促进了我们对细胞异质性和动力学的认识。细胞类型注释是分析单细胞RNA测序数据的关键步骤,但手工注释耗时且部分主观。作为一种替代方法,已经开发了用于自动细胞类型识别的工具。为了最终将单个细胞的基因表达谱与细胞类型联系起来,已经出现了不同的策略,要么使用精心策划的标记基因数据库,要么关联参考表达数据,要么通过监督分类转移标签。在这篇综述中,我们概述了对scRNA-seq数据进行自动细胞类型注释的可用工具和基本方法。
The advent of single-cell sequencing started a new era of transcriptomic and genomic research, advancing our knowledge of the cellular heterogeneity and dynamics. Cell type annotation is a crucial step in analyzing single-cell RNA sequencing data, yet manual annotation is time-consuming and partially subjective. As an alternative, tools have been developed for automatic cell type identification. Different strategies have emerged to ultimately associate gene expression profiles of single cells with a cell type either by using curated marker gene databases, correlating reference expression data, or transferring labels by supervised classification. In this review, we present an overview of the available tools and the underlying approaches to perform automated cell type annotations on scRNA-seq data.
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