Velo-Predictor: an ensemble learning pipeline for RNA velocity prediction

doi:10.1186/s12859-021-04330-1

	Velo-Predictor: an ensemble learning pipeline for RNA velocity prediction
	Wang, Xin; Zheng, Jie
	2021-09-03
发表期刊	BMC BIOINFORMATICS (IF:2.9[JCR-2023],3.6[5-Year])
ISSN	1471-2105
卷号	22 期号:SUPPL 10
DOI	10.1186/s12859-021-04330-1
摘要	Background RNA velocity is a novel and powerful concept which enables the inference of dynamical cell state changes from seemingly static single-cell RNA sequencing (scRNA-seq) data. However, accurate estimation of RNA velocity is still a challenging problem, and the underlying kinetic mechanisms of transcriptional and splicing regulations are not fully clear. Moreover, scRNA-seq data tend to be sparse compared with possible cell states, and a given dataset of estimated RNA velocities needs imputation for some cell states not yet covered. Results We formulate RNA velocity prediction as a supervised learning problem of classification for the first time, where a cell state space is divided into equal-sized segments by directions as classes, and the estimated RNA velocity vectors are considered as ground truth. We propose Velo-Predictor, an ensemble learning pipeline for predicting RNA velocities from scRNA-seq data. We test different models on two real datasets, Velo-Predictor exhibits good performance, especially when XGBoost was used as the base predictor. Parameter analysis and visualization also show that the method is robust and able to make biologically meaningful predictions. Conclusion The accurate result shows that Velo-Predictor can effectively simplify the procedure by learning a predictive model from gene expression data, which could help to construct a continous landscape and give biologists an intuitive picture about the trend of cellular dynamics.
关键词	RNA velocity Single cell Ensemble learning Landscape
URL	查看原文
收录类别	SCIE ; EI
语种	英语
WOS研究方向	Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Mathematical & Computational Biology
WOS类目	Biochemical Research Methods ; Biotechnology & Applied Microbiology ; Mathematical & Computational Biology
WOS记录号	WOS:000698117900001
出版者	BMC
原始文献类型	Article
引用统计	正在获取...
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/128241
专题	信息科学与技术学院_硕士生信息科学与技术学院_PI研究组_郑杰组
通讯作者	Zheng, Jie
作者单位	ShanghaiTech Univ, Sch Informat Sci & Technol, 393 Middle Huaxia Rd, Shanghai 201210, Peoples R China
第一作者单位	信息科学与技术学院
通讯作者单位	信息科学与技术学院
第一作者的第一单位	信息科学与技术学院
推荐引用方式 GB/T 7714	Wang, Xin,Zheng, Jie. Velo-Predictor: an ensemble learning pipeline for RNA velocity prediction[J]. BMC BIOINFORMATICS,2021,22(SUPPL 10).
APA	Wang, Xin,&Zheng, Jie.(2021).Velo-Predictor: an ensemble learning pipeline for RNA velocity prediction.BMC BIOINFORMATICS,22(SUPPL 10).
MLA	Wang, Xin,et al."Velo-Predictor: an ensemble learning pipeline for RNA velocity prediction".BMC BIOINFORMATICS 22.SUPPL 10(2021).