https://github.com/theislab/cellrank
CellRank: dynamics from multi-view single-cell data
https://github.com/theislab/cellrank
bioinformatics cell-fate-determination cell-fate-transitions data-science fuzzy-clustering-analyses genetics machine-learning manifold-learning markov-chains rna-velocity single-cell-genomics single-cell-rna-seq trajectory-generation
Last synced: 8 months ago
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CellRank: dynamics from multi-view single-cell data
- Host: GitHub
- URL: https://github.com/theislab/cellrank
- Owner: theislab
- License: bsd-3-clause
- Created: 2020-03-12T15:28:39.000Z (about 6 years ago)
- Default Branch: main
- Last Pushed: 2025-09-04T18:39:03.000Z (9 months ago)
- Last Synced: 2025-09-04T20:34:49.155Z (9 months ago)
- Topics: bioinformatics, cell-fate-determination, cell-fate-transitions, data-science, fuzzy-clustering-analyses, genetics, machine-learning, manifold-learning, markov-chains, rna-velocity, single-cell-genomics, single-cell-rna-seq, trajectory-generation
- Language: Python
- Homepage: https://cellrank.org
- Size: 95 MB
- Stars: 393
- Watchers: 8
- Forks: 50
- Open Issues: 24
-
Metadata Files:
- Readme: README.rst
- Contributing: CONTRIBUTING.rst
- License: LICENSE
Awesome Lists containing this project
README
|PyPI| |Downloads| |CI| |Docs| |Codecov| |Discourse|
CellRank 2: Unified fate mapping in multiview single-cell data
==============================================================
.. image:: docs/_static/img/light_mode_overview.png#gh-light-mode-only
:width: 600px
:align: center
:class: only-light
.. image:: docs/_static/img/dark_mode_overview.png#gh-dark-mode-only
:width: 600px
:align: center
**CellRank** is a modular framework to study cellular dynamics based on Markov state modeling of
multi-view single-cell data. See our `documentation`_, and the `CellRank 1`_ and `CellRank 2 manuscript`_ to learn more.
.. important::
Please refer to `our citation guide `_ to cite our software correctly.
CellRank scales to large cell numbers, is fully compatible with the `scverse`_ ecosystem, and easy to use.
In the backend, it is powered by `pyGPCCA`_ (`Reuter et al. (2018)`_). Feel
free to open an `issue`_ if you encounter a bug, need our help or just want to make a comment/suggestion.
CellRank's key applications
---------------------------
- Estimate differentiation direction based on a varied number of biological priors, including RNA velocity
(`La Manno et al. (2018)`_, `Bergen et al. (2020)`_), any pseudotime or developmental potential,
experimental time points, metabolic labels, and more.
- Compute initial, terminal and intermediate macrostates.
- Infer fate probabilities and driver genes.
- Visualize and cluster gene expression trends.
- ... and much more, check out our `documentation`_.
.. |PyPI| image:: https://img.shields.io/pypi/v/cellrank.svg
:target: https://pypi.org/project/cellrank
:alt: PyPI
.. |Downloads| image:: https://static.pepy.tech/badge/cellrank
:target: https://pepy.tech/project/cellrank
:alt: Downloads
.. |Discourse| image:: https://img.shields.io/discourse/posts?color=yellow&logo=discourse&server=https%3A%2F%2Fdiscourse.scverse.org
:target: https://discourse.scverse.org/c/ecosystem/cellrank/
:alt: Discourse
.. |CI| image:: https://img.shields.io/github/actions/workflow/status/theislab/cellrank/test.yml?branch=main
:target: https://github.com/theislab/cellrank/actions
:alt: CI
.. |Docs| image:: https://img.shields.io/readthedocs/cellrank
:target: https://cellrank.readthedocs.io/
:alt: Documentation
.. |Codecov| image:: https://codecov.io/gh/theislab/cellrank/branch/main/graph/badge.svg
:target: https://codecov.io/gh/theislab/cellrank
:alt: Coverage
.. _La Manno et al. (2018): https://doi.org/10.1038/s41586-018-0414-6
.. _Bergen et al. (2020): https://doi.org/10.1038/s41587-020-0591-3
.. _Reuter et al. (2018): https://doi.org/10.1021/acs.jctc.8b00079
.. _scverse: https://scverse.org/
.. _pyGPCCA: https://github.com/msmdev/pyGPCCA
.. _CellRank 1: https://www.nature.com/articles/s41592-021-01346-6
.. _CellRank 2 manuscript: https://doi.org/10.1038/s41592-024-02303-9
.. _documentation: https://cellrank.org
.. _issue: https://github.com/theislab/cellrank/issues/new/choose