cellxgene-census 1.17.0


pip install cellxgene-census

  Latest version

Released: Apr 02, 2025


Meta
Author: Chan Zuckerberg Initiative Foundation
Requires Python: <3.13,>=3.10

Classifiers

Development Status
  • 4 - Beta

Intended Audience
  • Developers
  • Information Technology
  • Science/Research

License
  • OSI Approved :: MIT License

Programming Language
  • Python :: 3.10
  • Python :: 3.11
  • Python :: 3.12

Topic
  • Scientific/Engineering :: Bio-Informatics

Operating System
  • POSIX :: Linux
  • MacOS :: MacOS X

CZ CELLxGENE Discover Census

The cellxgene_census package provides an API to facilitate the use of the CZ CELLxGENE Discover Census. For more information about the API and the project visit the chanzuckerberg/cellxgene-census GitHub repo.

For More Help

For more help, please file a issue on the repo, or contact us at soma@chanzuckerberg.com.

If you believe you have found a security issue, we would appreciate notification. Please send email to security@chanzuckerberg.com.

Development Environment Setup

  • Create a virtual environment using venv or conda
  • cd to the root of this repository
  • pip install -e api/python/cellxgene_census
  • To install dependencies needed to work on the experimental portion of the API: pip install -e 'api/python/cellxgene_census[experimental]'.
  • pip install jupyterlab
  • Test it! Either open up a new jupyter notebook or the python interpreter and run this code:
import cellxgene_census

with cellxgene_census.open_soma() as census:

    cell_metadata = cellxgene_census.get_obs(
        census,
        "homo_sapiens",
        value_filter = "sex == 'female' and cell_type in ['microglial cell', 'neuron']",
        column_names = ["assay", "cell_type", "tissue", "tissue_general", "suspension_type", "disease"]
    )
    cell_metadata

The output is a pandas.DataFrame with over 600K cells meeting our query criteria and the selected columns:

The "stable" release is currently 2023-12-15. Specify 'census_version="2023-12-15"' in future calls to open_soma() to ensure data consistency.

                assay        cell_type                 tissue tissue_general suspension_type disease     sex
0        Smart-seq v4  microglial cell  middle temporal gyrus          brain         nucleus  normal  female
1        Smart-seq v4  microglial cell  middle temporal gyrus          brain         nucleus  normal  female
2        Smart-seq v4  microglial cell  middle temporal gyrus          brain         nucleus  normal  female
3        Smart-seq v4  microglial cell  middle temporal gyrus          brain         nucleus  normal  female
4        Smart-seq v4  microglial cell  middle temporal gyrus          brain         nucleus  normal  female
...               ...              ...                    ...            ...             ...     ...     ...
607636  microwell-seq           neuron          adrenal gland  adrenal gland            cell  normal  female
607637  microwell-seq           neuron          adrenal gland  adrenal gland            cell  normal  female
607638  microwell-seq           neuron          adrenal gland  adrenal gland            cell  normal  female
607639  microwell-seq           neuron          adrenal gland  adrenal gland            cell  normal  female
607640  microwell-seq           neuron          adrenal gland  adrenal gland            cell  normal  female

[607641 rows x 7 columns]
  • Learn more about the Census API by going through the tutorials in the notebooks

Wheel compatibility matrix

Platform Python 3
any

Files in release

Extras:
Dependencies:
tiledbsoma (>=1.15.3)
anndata
numpy (>=1.23)
requests
typing_extensions
s3fs (>=2021.06.1)