scvelo

RNA Velocity generalized through dynamical modeling

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scVelo - RNA velocity generalized through dynamical modeling

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<a href="https://scvelo.org">
<img src="https://user-images.githubusercontent.com/31883718/67709134-a0989480-f9bd-11e9-8ae6-f6391f5d95a0.png" width="400px" align="left">
</a>

scVelo is a scalable toolkit for RNA velocity analysis in single cells, based on Bergen et al. (Nature Biotech, 2020) <https://doi.org/10.1038/s41587-020-0591-3>_.

RNA velocity enables the recovery of directed dynamic information by leveraging splicing kinetics. scVelo generalizes the concept of RNA velocity (La Manno et al., Nature, 2018 <https://doi.org/10.1038/s41586-018-0414-6>_) by relaxing previously made assumptions with a stochastic and a dynamical model that solves the full transcriptional dynamics. It thereby adapts RNA velocity to widely varying specifications such as non-stationary populations.

scVelo is compatible with scanpy_ and hosts efficient implementations of all RNA velocity models.

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.

scVelo has, for instance, recently been used to study immune response in COVID-19 patients and dynamic processes in human lung regeneration. Find out more in this list of application examples <https://scholar.google.com/scholar?cites=18195185735875895912>_.

Latest news ^^^^^^^^^^^

  • Aug/2021: Perspectives paper out in MSB <https://doi.org/10.15252/msb.202110282>_
  • Feb/2021: scVelo goes multi-core
  • Dec/2020: Cover of Nature Biotechnology <https://www.nature.com/nbt/volumes/38>_
  • Nov/2020: Talk at Single Cell Biology <https://coursesandconferences.wellcomegenomecampus.org/our-events/single-cell-biology-2020/>_
  • Oct/2020: Helmholtz Best Paper Award <https://twitter.com/ICBmunich/status/1318611467722199041>_
  • Oct/2020: Map cell fates with CellRank <https://cellrank.org>_
  • Sep/2020: Talk at Single Cell Omics <https://twitter.com/fabian_theis/status/1305621028056465412>_
  • Aug/2020: scVelo out in Nature Biotech <https://www.helmholtz-muenchen.de/en/aktuelles/latest-news/press-information-news/article/48658/index.html>_

References ^^^^^^^^^^ La Manno et al. (2018), RNA velocity of single cells, Nature <https://doi.org/10.1038/s41586-018-0414-6>_.

Bergen et al. (2020), Generalizing RNA velocity to transient cell states through dynamical modeling, Nature Biotech <https://doi.org/10.1038/s41587-020-0591-3>_.

Bergen et al. (2021), RNA velocity - current challenges and future perspectives, Molecular Systems Biology <https://doi.org/10.15252/msb.202110282>_.

Support ^^^^^^^ Found a bug or would like to see a feature implemented? Feel free to submit an issue <https://github.com/theislab/scvelo/issues/new/choose>. Have a question or would like to start a new discussion? Head over to GitHub discussions <https://github.com/theislab/scvelo/discussions>. In either case, you can also always send us an email <mailto:mail@scvelo.org>. Your help to improve scVelo is highly appreciated. For further information visit scvelo.org <https://scvelo.org>.

.. |PyPI| image:: https://img.shields.io/pypi/v/scvelo.svg :target: https://pypi.org/project/scvelo

.. |PyPIDownloads| image:: https://pepy.tech/badge/scvelo :target: https://pepy.tech/project/scvelo

.. |Docs| image:: https://readthedocs.org/projects/scvelo/badge/?version=latest :target: https://scvelo.readthedocs.io

.. |CI| image:: https://img.shields.io/github/workflow/status/theislab/scvelo/CI/master :target: https://github.com/theislab/scvelo/actions?query=workflow%3ACI

.. _scanpy: https://scanpy.readthedocs.io

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