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.

单细胞测序的出现开启了转录组学和基因组研究的新时代，增进了我们对细胞异质性和动力学的了解。细胞类型注释是分析单细胞 RNA 测序数据的关键步骤，但手动注释既耗时又具有一定的主观性。作为替代方案，已经开发了用于自动细胞类型识别的工具。已经出现了不同的策略，通过使用策划的标记基因数据库、关联参考表达数据或通过监督分类转移标签，最终将单细胞的基因表达谱与细胞类型关联起来。在这篇综述中，我们概述了对 scRNA-seq 数据执行自动细胞类型注释的可用工具和基本方法。