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scVelo - RNA velocity generalized through dynamical modeling

scVelo is a scalable toolkit for RNA velocity analysis in single cells; RNA velocity enables the recovery of directed dynamic information by leveraging splicing kinetics [Manno et al., 2018]. scVelo collects different methods for inferring RNA velocity using an expectation-maximization framework [Bergen et al., 2020], deep generative modeling [Gayoso et al., 2023], or metabolically labeled transcripts [Weiler et al., 2023].

scVelo’s key applications

  • estimate RNA velocity to study cellular dynamics.

  • identify putative driver genes and regimes of regulatory changes.

  • infer a latent time to reconstruct the temporal sequence of transcriptomic events.

  • estimate reaction rates of transcription, splicing and degradation.

  • use statistical tests, e.g., to detect different kinetics regimes.

Citing scVelo

If you include or rely on scVelo when publishing research, please adhere to the following citation guide:

EM and steady-state model

If you use the EM (dynamical) or steady-state model, cite

    title = {Generalizing RNA velocity to transient cell states through dynamical modeling},
    volume = {38},
    ISSN = {1546-1696},
    url = {},
    DOI = {10.1038/s41587-020-0591-3},
    number = {12},
    journal = {Nature Biotechnology},
    publisher = {Springer Science and Business Media LLC},
    author = {Bergen, Volker and Lange, Marius and Peidli, Stefan and Wolf, F. Alexander and Theis, Fabian J.},
    year = {2020},
    month = aug,
    pages = {1408–1414}


If you use veloVI (VI model), cite

    title = {Deep generative modeling of transcriptional dynamics for RNA velocity analysis in single cells},
    ISSN = {1548-7105},
    url = {},
    DOI = {10.1038/s41592-023-01994-w},
    journal = {Nature Methods},
    publisher = {Springer Science and Business Media LLC},
    author = {Gayoso, Adam and Weiler, Philipp and Lotfollahi, Mohammad and Klein, Dominik and Hong, Justin and Streets, Aaron and Theis, Fabian J. and Yosef, Nir},
    year = {2023},
    month = sep

RNA velocity inference through metabolic labeling information

If you use the implemented method for estimating RNA velocity from metabolic labeling information, cite

    title = {Unified fate mapping in multiview single-cell data},
    url = {},
    DOI = {10.1101/2023.07.19.549685},
    publisher = {Cold Spring Harbor Laboratory},
    author = {Weiler, Philipp and Lange, Marius and Klein, Michal and Pe’er, Dana and Theis, Fabian J.},
    year = {2023},
    month = jul


Found a bug or would like to see a feature implemented? Feel free to submit an issue. Have a question or would like to start a new discussion? Head over to GitHub discussions. Your help to improve scVelo is highly appreciated.