Metadata-Version: 2.1
Name: scArches
Version: 0.6.0
Summary: Transfer learning with Architecture Surgery on Single-cell data
Home-page: https://github.com/theislab/scarches
Author: Mohammad Lotfollahi, Sergei Rybakov, Marco Wagenstetter, Mohsen Naghipourfar
Author-email: mohammad.lotfollahi@helmholtz-muenchen.de, sergei.rybakov@helmholtz-muenchen.de
License: MIT
Description: .. raw:: html
        
         <img src="https://user-images.githubusercontent.com/33202701/187203672-e0415eec-1278-4b2a-a097-5bb8b6ab694f.svg" width="300px" height="200px" align="center">
        
        |PyPI| |PyPIDownloads| |Docs|
        
        
        Single-cell architecture surgery (scArches) is a package for reference-based analysis of single-cell data.
        
        
        What is scArches?
        -------------------------------
        scArches allows your single-cell query data to be analyzed by integrating it into a reference atlas. By mapping your data into an integrated reference you can transfer cell-type annotation from reference to query, identify disease states by mapping to healthy atlas, and advanced applications such as imputing missing data modalities or spatial locations.
        
        
        Usage and installation
        -------------------------------
        See `here <https://scarches.readthedocs.io/>`_ for documentation and tutorials.
        
        Support and contribute
        -------------------------------
        If you have a question or new architecture or a model that could be integrated into our pipeline, you can
        post an `issue <https://github.com/theislab/scarches/issues/new>`__ or reach us by `email <mo.lotfollahi@gmail.com>`_.
        
        Reference
        -------------------------------
        If scArches is helpful in your research, please consider citing the following `paper <https://www.nature.com/articles/s41587-021-01001-7>`_:
        ::
        
        
               @article{lotfollahi2021mapping,
                 title={Mapping single-cell data to reference atlases by transfer learning},
                 author={Lotfollahi, Mohammad and Naghipourfar, Mohsen and Luecken, Malte D and Khajavi,
                 Matin and B{\"u}ttner, Maren and Wagenstetter, Marco and Avsec, {\v{Z}}iga and Gayoso,
                 Adam and Yosef, Nir and Interlandi, Marta and others},
                 journal={Nature Biotechnology},
                 pages={1--10},
                 year={2021},
                 publisher={Nature Publishing Group}}
        
        
        
        
        .. |PyPI| image:: https://img.shields.io/pypi/v/scarches.svg
           :target: https://pypi.org/project/scarches
        
        .. |PyPIDownloads| image:: https://pepy.tech/badge/scarches
           :target: https://pepy.tech/project/scarches
        
        .. |Docs| image:: https://readthedocs.org/projects/scarches/badge/?version=latest
           :target: https://scarches.readthedocs.io
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.9
Classifier: Environment :: Console
Classifier: Framework :: Jupyter
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: Linux
Description-Content-Type: text/markdown
