Skip to main content

Transfer learning with Architecture Surgery on Single-cell data

Project description

.. raw:: html

|PyPI| |PyPIDownloads| |Docs| |travis|

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-hypernode.com/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

.. |travis| image:: https://travis-ci.com/theislab/scarches.svg?branch=master :target: https://travis-ci.com/theislab/scarches

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

scArches-0.5.9.tar.gz (39.8 MB view details)

Uploaded Source

Built Distribution

scArches-0.5.9-py3-none-any.whl (128.5 kB view details)

Uploaded Python 3

File details

Details for the file scArches-0.5.9.tar.gz.

File metadata

  • Download URL: scArches-0.5.9.tar.gz
  • Upload date:
  • Size: 39.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/0.0.0 pkginfo/1.7.0 requests/2.25.1 setuptools/52.0.0.post20210125 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8

File hashes

Hashes for scArches-0.5.9.tar.gz
Algorithm Hash digest
SHA256 bda044dec8d4823da15409c70a2eca7ccad044a66db25d0d5a23990bc22bda72
MD5 8d47d0a50dd8af56148cd56eb414ed9f
BLAKE2b-256 cdf57d5b53da8276b647346fd60b368dda89700a5f6e245ae5c731f5a85669ff

See more details on using hashes here.

File details

Details for the file scArches-0.5.9-py3-none-any.whl.

File metadata

  • Download URL: scArches-0.5.9-py3-none-any.whl
  • Upload date:
  • Size: 128.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/0.0.0 pkginfo/1.7.0 requests/2.25.1 setuptools/52.0.0.post20210125 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8

File hashes

Hashes for scArches-0.5.9-py3-none-any.whl
Algorithm Hash digest
SHA256 42a8eb5ccdf7942a4b53e16af1d0c4e04646eee98b671014e5425301e86389f2
MD5 88fc3e6c7583f24e67ba14abd810ba4e
BLAKE2b-256 3d6cddc9d8dd9712dc91da7cf1feb4efa836a5fc5b4eebc307ae20bdb5887ca3

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page