Metadata-Version: 2.1
Name: scanpy
Version: 1.3.7
Summary: Single-Cell Analysis in Python.
Home-page: http://github.com/theislab/scanpy
Author: Alex Wolf, Philipp Angerer, Fidel Ramirez, Isaac Virshup, Sergei Rybakov, Davide Cittaro, Gokcen Eraslan, Tom White, Tobias Callies, Andrés R. Muñoz-Rojas.
Author-email: alex.wolf@helmholtz-muenchen.de
License: BSD
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Framework :: Jupyter
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Visualization
Requires-Python: >=3.5
Requires-Dist: anndata (>=0.6.15)
Requires-Dist: matplotlib (>=2.2)
Requires-Dist: pandas (>=0.21)
Requires-Dist: scipy
Requires-Dist: seaborn
Requires-Dist: h5py
Requires-Dist: tables
Requires-Dist: scikit-learn (>=0.19.1)
Requires-Dist: statsmodels
Requires-Dist: networkx
Requires-Dist: natsort
Requires-Dist: joblib
Requires-Dist: numba (>=0.40.0)
Provides-Extra: bbknn
Requires-Dist: bbknn ; extra == 'bbknn'
Provides-Extra: doc
Requires-Dist: sphinx ; extra == 'doc'
Requires-Dist: sphinx-rtd-theme ; extra == 'doc'
Requires-Dist: sphinx-autodoc-typehints ; extra == 'doc'
Provides-Extra: leiden
Requires-Dist: python-igraph ; extra == 'leiden'
Requires-Dist: leidenalg ; extra == 'leiden'
Provides-Extra: louvain
Requires-Dist: python-igraph ; extra == 'louvain'
Requires-Dist: louvain (>=0.6) ; extra == 'louvain'
Provides-Extra: test
Requires-Dist: pytest ; extra == 'test'

|PyPI| |Docs| |Build Status| |bioconda|

.. |PyPI| image:: https://img.shields.io/pypi/v/scanpy.svg
    :target: https://pypi.org/project/scanpy
.. |Docs| image:: https://readthedocs.org/projects/scanpy/badge/?version=latest
   :target: https://scanpy.readthedocs.io
.. |Build Status| image:: https://travis-ci.org/theislab/scanpy.svg?branch=master
   :target: https://travis-ci.org/theislab/scanpy
.. |bioconda| image:: https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat-square
   :target: http://bioconda.github.io/recipes/scanpy/README.html
..
   .. |Coverage| image:: https://codecov.io/gh/theislab/scanpy/branch/master/graph/badge.svg
      :target: https://codecov.io/gh/theislab/scanpy

Scanpy – Single-Cell Analysis in Python
=======================================

.. image:: https://falexwolf.de/img/tsne_1.3M.png
   :width: 90px
   :align: left

Scanpy is a scalable toolkit for analyzing single-cell gene expression data.
It includes preprocessing, visualization, clustering, pseudotime and trajectory
inference and differential expression testing. The Python-based implementation
efficiently deals with datasets of more than one million cells.

Read the documentation_.
If Scanpy is useful for your research, consider citing `Genome Biology (2018)`_.

.. _documentation: https://scanpy.readthedocs.io
.. _Genome Biology (2018): https://doi.org/10.1186/s13059-017-1382-0


