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
venvorconda cdto the root of this repositorypip 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
jupyternotebook or thepythoninterpreter 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
Metadata
Release files for cellxgene-census 1.18.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| cellxgene_census-1.18.0.tar.gz | 103.5 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| cellxgene_census-1.18.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 141.9 kB
Release files / cellxgene_census-1.18.0.tar.gz
| Download URL | cellxgene_census-1.18.0.tar.gz |
|---|---|
| Size | 103.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
527de33d809b60f544f2fa7333dd4e9bdb3fa2f8b3465a64cb576c682daacfc7
|
|
BLAKE2b-256 checksum How to use checksums |
1cf3395b6cfaefa04cf6c89ec9045e921119ce4aa8c160cf9b61c433cca0649a
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.13.5
|
Release files / cellxgene_census-1.18.0-py3-none-any.whl
| Download URL | cellxgene_census-1.18.0-py3-none-any.whl |
|---|---|
| Size | 38.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
9e577ad913d4602cdb18a61e6f94230eefc105881cba7aece1491ec23cd760ba
|
|
BLAKE2b-256 checksum How to use checksums |
81a407c6c3db30dfb3dda5bc8ed5476c0ae42e345414a304178c2d0762218c36
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.13.5
|
Security for cellxgene-census 1.18.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.