Metadata-Version: 1.2
Name: scvelo
Version: 0.2.0
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| |travis|
        
        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.
        The methods are based on our preprint
        `Bergen et al. (2019) <https://doi.org/10.1101/820936>`_.
        
        RNA velocity enables the recovery of directed dynamic information by leveraging splicing information.
        scVelo generalizes the concept of RNA velocity (`La Manno et al., 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.
        
        See `<https://scvelo.org>`_ for documentation and tutorials.
        
        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.
        
        Reference
        ---------
        Bergen et al. (2019), *Generalizing RNA velocity to transient cell states through dynamical modeling*,
        `biorxiv <https://doi.org/10.1101/820936>`_.
        
        Support
        -------
        Feel free to submit an `issue <https://github.com/theislab/scvelo/issues/new/choose>`_
        or send us an `email <mailto:mail@scvelo.org>`_.
        Your help to improve scVelo is highly appreciated.
        
        
        .. |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
        
        .. |travis| image:: https://travis-ci.org/theislab/scvelo.svg?branch=master
           :target: https://travis-ci.org/theislab/scvelo
        
        .. _scanpy: https://scanpy.readthedocs.io
Keywords: RNAseq,single cell,stochastic,dynamical,velocity,transcriptomics
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: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Visualization
Requires-Python: >=3.6
