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
@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}
}
veloVI
If you use veloVI (VI model), cite
@article{Gayoso2023,
title = {Deep generative modeling of transcriptional dynamics for RNA velocity analysis in single cells},
ISSN = {1548-7105},
url = {http://dx.doi.org/10.1038/s41592-023-01994-w},
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
@article{Weiler2023,
title = {Unified fate mapping in multiview single-cell data},
url = {http://dx.doi.org/10.1101/2023.07.19.549685},
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
}
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.