单细胞转录组测序数据分析算法在干细胞研究中的应用

摘要

细胞的转录组决定其生理状态,每个细胞的转录组都是唯一的.借助单细胞转录组测序可分析单个干细胞的转录组特征,通过进一步的运算方法可以根据转录组特征对细胞进行细胞状态测定以及系谱分化特征的重建,在干细胞及组织发育研究中发挥了强大的作用,推动了其快速发展,加速了对干细胞分化及组织发育的相关过程及调控路径的认识.尤其是在干细胞领域的应用,得益于新算法的发展,单细胞转录组测序分析可用来阐述干细胞的起源、异质性,尤其是对干细胞的分化过程进行连续观察.本文主要对应用于干细胞分化相关研究的单细胞转录组测序数据新的算法及其应用进行了综述.%The transcriptome of a cell can be interpreted as a fingerprint,revealing its identity.Recent advances in single-cell RNA-sequencing (scRNA-seq) provide the feasibility of measuring the cellular heterogeneity and dynamic changes of individual cells during stem cell differentiation.ScRNA-seq will be useful for a better understanding of differentiation dynamics in a variety of stem cells.Several algorithms have been developed to quantitatively measure differentiation states of individual cells and reconstruct their lineages from scRNA-seq data.In this article,we mainly review the typical algorithms used in stem cell research.