Metadata-Version: 2.1
Name: cospar
Version: 0.3.0
Summary: CoSpar: integrating state and lineage information for dynamic inference
Home-page: https://github.com/AllonKleinLab/cospar
Download-URL: https://github.com/AllonKleinLab/cospar
Author: Shou-Wen Wang
Author-email: shouwen_wang@hms.harvard.edu
License: BSD
Keywords: dynamic inference,lineage tracing,single cell,transcriptomics,differentiation
Classifier: License :: OSI Approved :: BSD License
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
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
Requires-Python: >=3.6
Description-Content-Type: text/x-rst
Provides-Extra: dev
Provides-Extra: docs
License-File: LICENSE

|PyPI| |PyPIDownloads| |Docs|

CoSpar - dynamic inference by integrating state and lineage information
=======================================================================

.. image:: https://user-images.githubusercontent.com/4595786/104988296-b987ce00-59e5-11eb-8dbe-a463b355a9fd.png
   :width: 300px
   :align: left

**CoSpar** is a toolkit for dynamic inference from lineage-traced single cells.
The methods are based on
`Wang et al. Nat. Biotech. (2022) <https://www.nature.com/articles/s41587-022-01209-1>`_.

Dynamic inference based on single-cell state measurement alone requires serious simplifications. On the other hand, direct dynamic measurement via lineage tracing only captures partial information and its interpretation is challenging. CoSpar integrates both state and lineage information to infer a finite-time transition map of a development/differentiation system. It gains superior robustness and accuracy by exploiting both the local coherence and sparsity of differentiation transitions, i.e., neighboring initial states share similar yet sparse fate outcomes.  Building around the anndata_ object, CoSpar provides an integrated analysis framework for datasets with both state and lineage information. When only state information is available, CoSpar also improves upon existing dynamic inference methods by imposing sparsity and coherence. It offers essential toolkits for analyzing lineage data, state information, or their integration.

See `<https://cospar.readthedocs.io>`_ for documentation and tutorials.


Reference
---------
`S.-W. Wang*, M. Herriges, K. Hurley, D. Kotton, A. M. Klein*, CoSpar identifies early cell fate biases from single cell transcriptomic and lineage information, Nat. Biotech. (2022) <https://www.nature.com/articles/s41587-022-01209-1>`_. [* corresponding authors]

Support
-------
Feel free to submit an `issue <https://github.com/AllonKleinLab/cospar/issues/new/choose>`_
or send us an `email <mailto:wangsw09@gmail.com>`_.
Your help to improve CoSpar is highly appreciated.

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

.. |PyPIDownloads| image:: https://pepy.tech/badge/cospar
   :target: https://pepy.tech/project/cospar

.. |Docs| image:: https://readthedocs.org/projects/cospar/badge/?version=latest
   :target: https://cospar.readthedocs.io


.. _anndata: https://anndata.readthedocs.io
