Metadata-Version: 2.0
Name: scanpy
Version: 0.4.2
Summary: Single-Cell Analysis in Python.
Home-page: http://github.com/theislab/scanpy
Author: Alex Wolf, Philipp Angerer
Author-email: alex.wolf@helmholtz-muenchen.de
License: BSD-3-Clause
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-Dist: anndata (>=0.4)
Requires-Dist: matplotlib (==2.0.0)
Requires-Dist: pandas
Requires-Dist: scipy
Requires-Dist: seaborn
Requires-Dist: psutil
Requires-Dist: h5py
Requires-Dist: xlrd
Requires-Dist: scikit-learn
Requires-Dist: statsmodels
Requires-Dist: networkx
Requires-Dist: natsort
Requires-Dist: joblib
Requires-Dist: profilehooks
Requires-Dist: tqdm

|Docs| |PyPI| |Build Status| |Coverage|

.. |Docs| image:: https://readthedocs.org/projects/scanpy/badge/?version=latest
   :target: https://scanpy.readthedocs.io
.. |PyPI| image:: https://badge.fury.io/py/scanpy.svg
    :target: https://pypi.python.org/pypi/scanpy
.. |Build Status| image:: https://travis-ci.org/theislab/scanpy.svg?branch=master
   :target: https://travis-ci.org/theislab/scanpy
.. |Coverage| image:: https://codecov.io/gh/theislab/scanpy/branch/master/graph/badge.svg
   :target: https://codecov.io/gh/theislab/scanpy

Scanpy â€“ Single-Cell Analysis in Python
=======================================

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

Read the `documentation <https://scanpy.readthedocs.io>`_. Learn more about conceptual ideas in our `preprint <https://doi.org/10.1101/174029>`_.


