Metadata-Version: 2.1
Name: scvelo
Version: 0.2.4
Summary: RNA velocity generalized through dynamical modeling
Home-page: https://github.com/theislab/scvelo
Author: Volker Bergen
Author-email: volker.bergen@helmholtz-muenchen.de
License: BSD
Download-URL: https://github.com/theislab/scvelo
Description: |PyPI| |PyPIDownloads| |CI|
        
        scVelo - RNA velocity generalized through dynamical modeling
        ============================================================
        
        .. image:: https://user-images.githubusercontent.com/31883718/67709134-a0989480-f9bd-11e9-8ae6-f6391f5d95a0.png
           :width: 300px
           :align: left
        
        **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
        ^^^^^^^^^^
        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
Keywords: RNA,velocity,single cell,transcriptomics,stochastic,dynamical
Platform: UNKNOWN
Classifier: License :: OSI Approved :: BSD License
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Visualization
Requires-Python: >=3.6
Provides-Extra: louvain
Provides-Extra: hnswlib
Provides-Extra: dev
Provides-Extra: docs
