Single-Cell Analysis in Python.

Navigation

Verified details

These details have been verified by PyPI
Project links
GitHub Statistics
Maintainers
Avatar for falexwolf from gravatar.com falexwolf Avatar for flyingsheep from gravatar.com flyingsheep Avatar for ivirshup from gravatar.com ivirshup

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: BSD License
  • Author: Alex Wolf, Philipp Angerer, Fidel Ramirez, Isaac Virshup, Sergei Rybakov, Gokcen Eraslan, Tom White, Malte Luecken, Davide Cittaro, Tobias Callies, Marius Lange, Andrés R. Muñoz-Rojas
  • Maintainer: Isaac Virshup
  • Requires: Python >=3.10
  • Provides-Extra: bbknn, dask, dask-ml, dev, doc, harmony, leiden, louvain, magic, paga, rapids, scanorama, scrublet, skmisc, test, test-full, test-min
Classifiers

Project description

Stars PyPI Downloads Conda Docs Build Status Discourse topics Chat Powered by NumFOCUS

Scanpy – Single-Cell Analysis in Python

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

Discuss usage on the scverse Discourse. Read the documentation. If you'd like to contribute by opening an issue or creating a pull request, please take a look at our contribution guide.

scanpy is part of the scverse project (website, governance) and is fiscally sponsored by NumFOCUS. If you like scverse and want to support our mission, please consider making a donation to support our efforts.

Citation

If you use scanpy in your work, please cite the scanpy publication as follows:

SCANPY: large-scale single-cell gene expression data analysis

F. Alexander Wolf, Philipp Angerer, Fabian J. Theis

Genome Biology 2018 Feb 06. doi: 10.1186/s13059-017-1382-0.

You can cite the scverse publication as follows:

The scverse project provides a computational ecosystem for single-cell omics data analysis

Isaac Virshup, Danila Bredikhin, Lukas Heumos, Giovanni Palla, Gregor Sturm, Adam Gayoso, Ilia Kats, Mikaela Koutrouli, Scverse Community, Bonnie Berger, Dana Pe’er, Aviv Regev, Sarah A. Teichmann, Francesca Finotello, F. Alexander Wolf, Nir Yosef, Oliver Stegle & Fabian J. Theis

Nat Biotechnol. 2023 Apr 10. doi: 10.1038/s41587-023-01733-8.

Project details

Verified details

These details have been verified by PyPI
Project links
GitHub Statistics
Maintainers
Avatar for falexwolf from gravatar.com falexwolf Avatar for flyingsheep from gravatar.com flyingsheep Avatar for ivirshup from gravatar.com ivirshup

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: BSD License
  • Author: Alex Wolf, Philipp Angerer, Fidel Ramirez, Isaac Virshup, Sergei Rybakov, Gokcen Eraslan, Tom White, Malte Luecken, Davide Cittaro, Tobias Callies, Marius Lange, Andrés R. Muñoz-Rojas
  • Maintainer: Isaac Virshup
  • Requires: Python >=3.10
  • Provides-Extra: bbknn, dask, dask-ml, dev, doc, harmony, leiden, louvain, magic, paga, rapids, scanorama, scrublet, skmisc, test, test-full, test-min
Classifiers

Release history Release notifications | RSS feed

This version

1.10.4

1.10.3

1.10.2

1.10.1

1.10.0

1.10.0rc2 pre-release

1.10.0rc1 pre-release

1.9.8

1.9.7

1.9.6

1.9.5

1.9.4

1.9.3

1.9.2

1.9.1

1.9.0

1.8.2

1.8.1

1.8.0

1.7.2

1.7.1

1.7.0

1.7.0rc1 pre-release

1.6.1

1.6.0

1.5.1

1.5.0

1.5.0a1 pre-release

1.4.6

1.4.5.1

1.4.5.post3

1.4.5.post2

1.4.5.post1

1.4.5

1.4.4.post1

1.4.4

1.4.3

1.4.2

1.4.1

1.4

1.3.8

1.3.7

1.3.6

1.3.5

1.3.4

1.3.3

1.3.2

1.3.1

1.3

1.2.2

1.2.1

1.2.0

1.1

1.1a2 pre-release

1.1a1 pre-release

1.0.4

1.0.3.post1

1.0.3

1.0.2

1.0.1.post1

1.0.1

1.0

0.4.4

0.4.3

0.4.2

0.4.1

0.4

0.3.2

0.3.1

0.3

0.2.9.1

0.2.9

0.2.8

0.2.7

0.2.6

0.2.5

0.2.4

0.2.3.5

0.2.3.4

0.2.3

0.2.1

Download files

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

Source Distribution

scanpy-1.10.4.tar.gz (13.6 MB view details)

Uploaded Source

Built Distribution

scanpy-1.10.4-py3-none-any.whl (2.1 MB view details)

Uploaded Python 3

File details

Details for the file scanpy-1.10.4.tar.gz.

File metadata

  • Download URL: scanpy-1.10.4.tar.gz
  • Upload date:
  • Size: 13.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for scanpy-1.10.4.tar.gz
Algorithm Hash digest
SHA256 2682fbbe2e4106c349472feebef08e174062fb666db4c94123758c6a7a470396
MD5 f7983fd5def11cb8b840deeae1e7ad6f
BLAKE2b-256 fdcb213db09685b572ef6470a5fa9199653949e7842e32c12f6dd1a55d80fea6

See more details on using hashes here.

Provenance

The following attestation bundles were made for scanpy-1.10.4.tar.gz:

Publisher: publish.yml on scverse/scanpy

Attestations:

File details

Details for the file scanpy-1.10.4-py3-none-any.whl.

File metadata

  • Download URL: scanpy-1.10.4-py3-none-any.whl
  • Upload date:
  • Size: 2.1 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for scanpy-1.10.4-py3-none-any.whl
Algorithm Hash digest
SHA256 d93256d0e8e6e34639ff9bf20bdde0162b5162c6f18f151d90b3eb9ea54ff03a
MD5 a5bc3ad9099813bd7fff41255a1c647d
BLAKE2b-256 d1b4c408bac643afd670d2009219dbbb2076290e23fb1986937825c9a0d839c5

See more details on using hashes here.

Provenance

The following attestation bundles were made for scanpy-1.10.4-py3-none-any.whl:

Publisher: publish.yml on scverse/scanpy

Attestations:

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