文章基本信息

标题：Automated methods for cell type annotation on scRNA-seq data
本地全文：下载
作者：Giovanni Pasquini ; Jesus Eduardo Rojo Arias ; Patrick Schäfer 等
期刊名称：Computational and Structural Biotechnology Journal
印刷版ISSN：2001-0370
出版年度：2021
卷号：19
页码：961-969
DOI：10.1016/j.csbj.2021.01.015
出版社：Computational and Structural Biotechnology Journal
摘要：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.
关键词：scRNA-seq ; Cell type ; Cell state ; Automatic annotation