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scVelo - RNA velocity generalized through dynamical modeling

https://user-images.githubusercontent.com/31883718/67709134-a0989480-f9bd-11e9-8ae6-f6391f5d95a0.png

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] or metabolically labeled transcripts [Weiler et al., 2024].

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

@article{Bergen2020,
    title = {Generalizing RNA velocity to transient cell states through dynamical modeling},
    volume = {38},
    ISSN = {1546-1696},
    url = {http://dx.doi.org/10.1038/s41587-020-0591-3},
    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}
}

RNA velocity inference through metabolic labeling information

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

@article{Weiler2024,
    author = {Weiler, Philipp and Lange, Marius and Klein, Michal and Pe'er, Dana and Theis, Fabian},
    publisher = {Springer Science and Business Media LLC},
    url = {http://dx.doi.org/10.1038/s41592-024-02303-9},
    doi = {10.1038/s41592-024-02303-9},
    issn = {1548-7105},
    journal = {Nature Methods},
    month = jun,
    number = {7},
    pages = {1196-1205},
    title = {CellRank 2: unified fate mapping in multiview single-cell data},
    volume = {21},
    year = {2024},
}

Support

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.