Skip to main content

An in-memory data analysis format for single-cell profiles alongside their corresponding images and segmentation masks.

Project description

CytoDataFrame

PyPI - Version Build Status Coverage Status Ruff Poetry

CytoDataFrame extends Pandas functionality to help display single-cell profile data alongside related images.

CytoDataFrame is an advanced in-memory data analysis format designed for single-cell profiling, integrating not only the data profiles but also their corresponding microscopy images and segmentation masks. Traditional single-cell profiling often excludes the associated images from analysis, limiting the scope of research. CytoDataFrame bridges this gap, offering a purpose-built solution for comprehensive analysis that incorporates both the data and images, empowering more detailed and visual insights in single-cell research.

CytoDataFrame development began within coSMicQC - a single-cell profile quality control package.

Installation

Install CytoDataFrame from source using the following:

# install from pypi
pip install cytodataframe

# or install directly from source
pip install git+https://github.com/WayScience/CytoDataFrame.git

Contributing, Development, and Testing

Please see our contributing documentation for more details on contributions, development, and testing.

References

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

cytodataframe-0.0.11.tar.gz (13.7 kB view details)

Uploaded Source

Built Distribution

cytodataframe-0.0.11-py3-none-any.whl (12.8 kB view details)

Uploaded Python 3

File details

Details for the file cytodataframe-0.0.11.tar.gz.

File metadata

  • Download URL: cytodataframe-0.0.11.tar.gz
  • Upload date:
  • Size: 13.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for cytodataframe-0.0.11.tar.gz
Algorithm Hash digest
SHA256 0d5324f970e0b0d33ead506a6cc663735c385e4d482ffc625dafdf1364379e2d
MD5 04bab7e83d7f3393746c0a401bcfbdd4
BLAKE2b-256 211e158e17a3ab7718a180d8412129c1272132bcf483cced7bfef1980923fc06

See more details on using hashes here.

Provenance

The following attestation bundles were made for cytodataframe-0.0.11.tar.gz:

Publisher: publish-pypi.yml on WayScience/CytoDataFrame

Attestations:

File details

Details for the file cytodataframe-0.0.11-py3-none-any.whl.

File metadata

File hashes

Hashes for cytodataframe-0.0.11-py3-none-any.whl
Algorithm Hash digest
SHA256 2255f21f4411b6a8d4d0c9029ea92c05952ce8fd9d360459f8e5d9bb811a16ab
MD5 84385b38eeaef96b6910e771121102b9
BLAKE2b-256 29de8e4c96817d7526d926032de19e35532f59d8e8ad58e1717a11bac8dcba85

See more details on using hashes here.

Provenance

The following attestation bundles were made for cytodataframe-0.0.11-py3-none-any.whl:

Publisher: publish-pypi.yml on WayScience/CytoDataFrame

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