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theislab
167 Stars 49 Forks BSD 3-Clause "New" or "Revised" License 1.1K Commits 78 Opened issues

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RNA Velocity generalized through dynamical modeling

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|PyPI| |PyPIDownloads| |CI|

scVelo - RNA velocity generalized through dynamical modeling

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scVelo is a scalable toolkit for RNA velocity analysis in single cells, based on

Bergen et al. (Nature Biotech, 2020) 
_.

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 
_) 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 
_.

Latest news ^^^^^^^^^^^ - Feb/2021: scVelo goes multi-core - Dec/2020: Cover of

Nature Biotechnology 
_ - Nov/2020: Talk at
Single Cell Biology 
_ - Oct/2020:
Helmholtz Best Paper Award 
_ - Oct/2020: Map cell fates with
CellRank 
_ - Sep/2020: Talk at
Single Cell Omics 
_ - Aug/2020:
scVelo out in Nature Biotech 
_

Reference ^^^^^^^^^ Bergen et al. (2020), Generalizing RNA velocity to transient cell states through dynamical modeling,

Nature Biotech 
_. |dim|

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 
. In either case, you can also always send us an
email 
. Your help to improve scVelo is highly appreciated. For further information visit
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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