Metadata-Version: 2.1
Name: cellrank
Version: 1.0.0
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
Description: |PyPI| |Bioconda| |Downloads| |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. (2020)`_. 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 and the stochastic nature of cell fate decisions. The Markov chain is coarse-grained into a set of
        macrostates which represent initial & terminal states as well as transient intermediate states. For each transient cell,
        i.e. for each cell that's not assigned to a terminal state, we then compute its fate probability of it reaching any of the terminal states.
        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 initial & terminal as well as intermediate macrostates of your biological system
        - infer fate probabilities towards the terminal states for each individual cell
        - visualize gene expression trends along specific linegeages while accounting for the continous nature of fate determination
        - identify potential driver genes for each identified cellular trajectory
        
        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
            :alt: CI
        
        .. |Notebooks| image:: https://img.shields.io/travis/com/theislab/cellrank_notebooks?label=notebooks
            :target: https://travis-ci.com/github/theislab/cellrank_notebooks
            :alt: CI-Notebooks
        
        .. |Docs|  image:: https://img.shields.io/readthedocs/cellrank
            :target: https://cellrank.readthedocs.io/en/latest
            :alt: Documentation
        
        .. |Downloads| image:: https://pepy.tech/badge/cellrank
            :target: https://pepy.tech/project/cellrank
            :alt: Downloads
        
        .. |Codecov| image:: https://codecov.io/gh/theislab/cellrank/branch/master/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
        
        .. _pancreatic endocrinogenesis: https://doi.org/10.1242/dev.173849
        
        .. _scanpy: https://scanpy.readthedocs.io/en/latest/
        
        .. _scvelo: https://scvelo.readthedocs.io/
        
        .. _cellrank.org: https://cellrank.org
        
        .. _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
        
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
Provides-Extra: krylov
Provides-Extra: test
Provides-Extra: docs
Provides-Extra: dev
