Metadata-Version: 2.1
Name: cellrank
Version: 1.0.0rc1
Summary: CellRank - Probabilistic Fate Mapping using RNA Velocity
Home-page: https://github.com/theislab/cellrank
Author: Marius Lange, Michal Klein, Juan Luis Restrepo Lopez
Author-email: info@cellrank.org
Maintainer: Marius Lange, Michal Klein
Maintainer-email: info@cellrank.org
License: BSD
Download-URL: https://github.com/theislab/cellrank
Project-URL: Documentation, https://cellrank.readthedocs.io/en/latest/
Project-URL: Source Code, https://github.com/theislab/cellrank
Keywords: bio-informatics,single-cell,RNA velocity,Markov chain,GPCCA
Platform: Linux
Platform: MacOs
Platform: Windows
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Framework :: Jupyter
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: Linux
Classifier: Typing :: Typed
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
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|PyPI| |Bioconda| |Binder| |Travis| |Notebooks| |Docs| |Codecov|


CellRank - Probabilistic Fate Mapping using RNA Velocity
========================================================

.. image:: https://raw.githubusercontent.com/theislab/cellrank/master/resources/images/cellrank_fate_map.png
   :width: 600px
   :align: center

**CellRank** is a toolkit to uncover cellular dynamics based on scRNA-seq data with RNA velocity annotation,
see `La Manno et al. (2018)`_ and `Bergen et al. (2019)`_. CellRank models cellular dynamics as a Markov chain, where transition
probabilities are computed based on RNA velocity and transcriptomic similarity, taking into account uncertainty
in the velocities. The Markov chain is coarse grained into a set of metastable states which represent root &
final states as well as transient intermediate states. For each cell, we obtain the probability of it belonging
to each metastable state, i.e. we compute a fate map on the single cell level. We show an example of such a fate
map in the figure above, which has been computed using the data of `pancreatic endocrinogenesis`_.

CellRank scales to large cell numbers, is fully compatible with `scanpy`_ and `scvelo`_ and is easy
to use. For **installation instructions**, **documentation** and **tutorials**, visit `cellrank.org`_.

CellRank's key applications
^^^^^^^^^^^^^^^^^^^^^^^^^^^
- compute root & final as well as intermediate metastable states of your developmental/dynamical process
- infer fate probabilities towards these states for each single cell
- visualise gene expression trends towards/from specific states
- identify potential driver genes for each state

Installation
^^^^^^^^^^^^
Install CellRank by running::

    conda install -c conda-forge -c bioconda cellrank
    # or with extra libraries, useful for large datasets
    conda install -c conda-forge -c bioconda cellrank-krylov

or via PyPI::

    pip install cellrank
    # or with extra libraries, useful for large datasets
    pip install 'cellrank[krylov]'

Support
^^^^^^^
We welcome your feedback! Feel free to open an `issue <https://github.com/theislab/cellrank/issues/new/choose>`_
or send us an `email <mailto:info@cellrank.org>`_ if you encounter a bug, need our help or just want to make a
comment/suggestion.

CellRank was developed in collaboration between the `Theislab`_ and the `Peerlab`_.

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

.. |Bioconda| image:: https://img.shields.io/conda/vn/bioconda/cellrank
    :target: https://bioconda.github.io/recipes/cellrank/README.html
    :alt: Bioconda

.. |Travis| image:: https://travis-ci.org/theislab/cellrank.svg?branch=master
    :target: https://travis-ci.com/github/theislab/cellrank

.. |Notebooks| image:: https://img.shields.io/travis/com/theislab/cellrank_notebooks?label=notebooks
    :target: https://travis-ci.com/github/theislab/cellrank_notebooks

.. |Docs|  image:: https://img.shields.io/readthedocs/cellrank

.. |Binder| image:: https://img.shields.io/badge/tutorial-pancreas%20basic-579ACA.svg?logo=data:image/png;base64,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
    :target: https://mybinder.org/v2/gh/theislab/cellrank_notebooks/master?filepath=tutorials%2Fpancreas_basic.ipynb

.. |Codecov| image:: https://codecov.io/gh/theislab/cellrank/branch/master/graph/badge.svg
    :target: https://codecov.io/gh/theislab/cellrank

.. _La Manno et al. (2018): https://doi.org/10.1038/s41586-018-0414-6

.. _Bergen et al. (2019): https://doi.org/10.1101/820936

.. _pancreatic endocrinogenesis: https://doi.org/10.1242/dev.173849

.. _tutorial: https://cellrank.readthedocs.io/en/latest/pancreas_basic.html

.. _PageRank: http://infolab.stanford.edu/~backrub/google.html

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

.. _scvelo: https://scvelo.readthedocs.io/

.. _cellrank.org: http://cellrank.org

.. _documentation: https://cellrank.readthedocs.io

.. _Theislab: https://www.helmholtz-muenchen.de/icb/research/groups/theis-lab/overview/index.html

.. _Peerlab: https://www.mskcc.org/research/ski/labs/dana-pe-er


