Cited by 186Single-cell and spatial transcriptomicsGene Regulatory Network AnalysisGene expression and cancer classification

RNA velocity unraveled

Open access
Gorin, Gennady, Fang, Meichen, Chari, Tara, Pachter, Lior·2022·PLOS Computational Biology

Published version of a preprint

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.

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Crossref · 10.1371/journal.pcbi.1010492

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  • RNA velocity is inferred incorrectly in the presence of transcriptional bursts.

    “Cases in which RNA velocity is inferred incorrectly include the presence of transcriptional bursts70,71.”

    From Best practices for single-cell analysis across modalities (2023) · cites this paper as [71]

  • In steady-state populations, RNA velocity infers erroneous directions between independent terminal cell populations.

    “Additionally, steady-state populations pose further challenges where RNA velocity infers erroneous directions between independent, terminal cell populations70,71.”

    From Best practices for single-cell analysis across modalities (2023) · cites this paper as [71]

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Research works printed but not linked: 6

  1. [83]Dattani J. Exact solutions of master equations for the analysis of gene transcription models [PhD Dissertation]. Imperial College London; 2015.
  2. [107]Ahlmann-Eltze C, Huber W. Transformation and Preprocessing of Single-Cell RNA-Seq Data. bioRxiv: 2021.06.24.449781; 2021.
  3. [148]Gorin G, Pachter L. Monod: mechanistic analysis of single-cell RNA sequencing count data. bioRxiv: 2022.06.11.495771; 2022.
  4. [149]Davis ME, Davis RJ. Fundamentals of chemical reaction engineering. International ed ed. McGraw-Hill chemical engineering series. Boston: McGraw-Hill; 2003.
  5. [156]Jia C, Grima R. Accuracy and limitations of extrinsic noise models to describe gene expression in growing cells. bioRxiv: 2022.06.15.496247; 2022.
  6. [161]Coté A, Coté C, Bayatpour S, Drexler HL, Alexander KA, Chen F, et al. pre-mRNA spatial distributions suggest that splicing can occur post-transcriptionally. bioRxiv: 2020.04.06.028092; 2021.

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Authors
Gorin, G., Fang, M., Chari, T., & Pachter, L.
Affiliations
California Institute of Technology (US)
Corresponding author
Pachter, Lior
Venue
PLOS Computational Biology
Published
2022-09-12
Volume
18
Issue
9
Pages
e1010492
ISSN
  • 1553-734X (ISSN-L)
  • 1553-7358
OpenAlex
W4295880122
Cited by
186
References
187
Citations by year
2026: 39 · 2025: 49 · 2024: 45 · 2023: 36 · 2022: 16 · 2021: 1
FWCI
11.92
Type
journal article
Language
en
Open access
Locations
  • PLoS Computational Biology (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • CaltechAUTHORS (California Institute of Technology) (submittedVersion, cc-by)
  • CaltechAUTHORS (California Institute of Technology) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
National Institute of Mental Health (U19MH114830)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
Keywords
RNA velocity, single-cell transcriptomics, Markov chain model, parameter sensitivity, method comparison
MeSH terms
RNA, Workflow

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