Abstract
We perform a thorough analysis of RNA velocity methods, with a view towards understanding the suitability of the various assumptions underlying popular implementations. In addition to providing a self-contained exposition of the underlying mathematics, we undertake simulations and perform controlled experiments on biological datasets to assess workflow sensitivity to parameter choices and underlying biology. Finally, we argue for a more rigorous approach to RNA velocity, and present a framework for Markovian analysis that points to directions for improvement and mitigation of current problems.
Funder
National Institute of Mental Health
Publisher
Public Library of Science (PLoS)
Subject
Computational Theory and Mathematics,Cellular and Molecular Neuroscience,Genetics,Molecular Biology,Ecology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics
Reference179 articles.
1. RNA velocity of single cells;G La Manno;Nature,2018
2. Coupled pre-mRNA and mRNA dynamics unveil operational strategies underlying transcriptional responses to stimuli;A Zeisel;Molecular Systems Biology,2011
3. Generalizing RNA velocity to transient cell states through dynamical modeling;V Bergen;Nature Biotechnology,2020
4. Protein velocity and acceleration from single-cell multiomics experiments;G Gorin;Genome Biology,2020
5. Single-cell multi-omic velocity infers dynamic and decoupled gene regulation;C Li;bioRxiv: 2021.12.13.472472,2021
Cited by
86 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献