Quantifying pluripotency landscape of cell differentiation from scRNA-seq data by continuous birth-death process

doi:10.1371/journal.pcbi.1007488

	Quantifying pluripotency landscape of cell differentiation from scRNA-seq data by continuous birth-death process
	Shi, Jifan 1; Li, Tiejun 2,3; Chen, Luonan4,5,6,7 ; Aihara, Kazuyuki 1,8
	2019-11
发表期刊	PLOS COMPUTATIONAL BIOLOGY
ISSN	1553-734X
EISSN	1553-7358
卷号	15 期号:11
发表状态	已发表
DOI	10.1371/journal.pcbi.1007488
摘要	Modeling cell differentiation from omics data is an essential problem in systems biology research. Although many algorithms have been established to analyze scRNA-seq data, approaches to infer the pseudo-time of cells or quantify their potency have not yet been satisfactorily solved. Here, we propose the Landscape of Differentiation Dynamics (LDD) method, which calculates cell potentials and constructs their differentiation landscape by a continuous birth-death process from scRNA-seq data. From the viewpoint of stochastic dynamics, we exploited the features of the differentiation process and quantified the differentiation landscape based on the source-sink diffusion process. In comparison with other scRNA-seq methods in seven benchmark datasets, we found that LDD could accurately and efficiently build the evolution tree of cells with pseudo-time, in particular quantifying their differentiation landscape in terms of potency. This study provides not only a computational tool to quantify cell potency or the Waddington potential landscape based on scRNA-seq data, but also novel insights to understand the cell differentiation process from a dynamic perspective.
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收录类别	SCI ; SCIE ; EI
语种	英语
资助项目	JST CREST[JPMJCR14D2]
WOS研究方向	Biochemistry & Molecular Biology ; Mathematical & Computational Biology
WOS类目	Biochemical Research Methods ; Mathematical & Computational Biology
WOS记录号	WOS:000500976100015
出版者	PUBLIC LIBRARY SCIENCE
WOS关键词	RNA-SEQ ; GENE-EXPRESSION ; FATE DECISIONS ; DIFFUSION MAPS ; SINGLE
原始文献类型	Article
引用统计
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/104502
专题	生命科学与技术学院_特聘教授组_陈洛南组
通讯作者	Li, Tiejun; Chen, Luonan; Aihara, Kazuyuki
作者单位	1.Univ Tokyo, Inst Ind Sci, Tokyo, Japan 2.Peking Univ, LMAM, Beijing, Peoples R China 3.Peking Univ, Sch Math Sci, Beijing, Peoples R China 4.Chinese Acad Sci, Inst Biochem & Cell Biol, Ctr Excellence Mol Cell Sci, Key Lab Syst Biol, Shanghai, Peoples R China 5.Chinese Acad Sci, Ctr Excellence Anim Evolut & Genet, Kunming, Yunnan, Peoples R China 6.ShanghaiTech Univ, Sch Life Sci & Technol, Shanghai, Peoples R China 7.Shanghai Res Ctr Brain Sci & Brain Inspired Intel, Shanghai, Peoples R China 8.Univ Tokyo, Univ Tokyo Inst Adv Study, Int Res Ctr Neurointelligence, Tokyo, Japan
通讯作者单位	生命科学与技术学院
推荐引用方式 GB/T 7714	Shi, Jifan,Li, Tiejun,Chen, Luonan,et al. Quantifying pluripotency landscape of cell differentiation from scRNA-seq data by continuous birth-death process[J]. PLOS COMPUTATIONAL BIOLOGY,2019,15(11).
APA	Shi, Jifan,Li, Tiejun,Chen, Luonan,&Aihara, Kazuyuki.(2019).Quantifying pluripotency landscape of cell differentiation from scRNA-seq data by continuous birth-death process.PLOS COMPUTATIONAL BIOLOGY,15(11).
MLA	Shi, Jifan,et al."Quantifying pluripotency landscape of cell differentiation from scRNA-seq data by continuous birth-death process".PLOS COMPUTATIONAL BIOLOGY 15.11(2019).