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 Software DOI badge

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 is best suited for work within Jupyter notebooks. With CytoDataFrame you can:

  • View image objects alongside their feature data using a Pandas DataFrame-like interface.
  • Highlight image objects using mask or outline files to understand their segmentation.
  • Adjust image displays on-the-fly using interactive slider widgets.
  • Automatically detect 3D image volumes and render interactive trame views in notebooks when 3D dependencies are installed (with graceful fallback otherwise).

For 3D notebook display behavior:

  • 3D-aware rendering is enabled by default (display_options={"auto_trame_for_3d": True}).
  • Disable automatic trame switching with display_options={"auto_trame_for_3d": False}.
  • Force trame layout regardless of auto-detection with display_options={"view": "trame"}.

📓 Want to see CytoDataFrame in action? Check out our example notebook for a quick tour of its key features.

✨ CytoDataFrame development began within coSMicQC - a single-cell profile quality control package. Please check out our work there as well!

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/cytomining/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-0.2.0.tar.gz (41.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

cytodataframe-0.2.0-py3-none-any.whl (40.1 kB view details)

Uploaded Python 3

File details

Details for the file cytodataframe-0.2.0.tar.gz.

File metadata

  • Download URL: cytodataframe-0.2.0.tar.gz
  • Upload date:
  • Size: 41.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for cytodataframe-0.2.0.tar.gz
Algorithm Hash digest
SHA256 b02f6a610acd6b97c70f74f8473546e932edbcb240cd51a01766466efcf6d1ad
MD5 4cd3dd6d586072cf9487bfc278340692
BLAKE2b-256 2733e4330257c55d7a1bd666429065493da2b4d4cf8fa1dfd4b4eac1ae909383

See more details on using hashes here.

Provenance

The following attestation bundles were made for cytodataframe-0.2.0.tar.gz:

Publisher: publish-pypi.yml on cytomining/CytoDataFrame

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file cytodataframe-0.2.0-py3-none-any.whl.

File metadata

  • Download URL: cytodataframe-0.2.0-py3-none-any.whl
  • Upload date:
  • Size: 40.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for cytodataframe-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 495a925f11992bb9d32207f93cb0a14d0d128736fce57c749311cfff2c669d51
MD5 214d2c3ab8b15612b9fe0a78bead49ae
BLAKE2b-256 c0f86c32e4d88f4050cc98d4afda4e6314a4f6ac5fb25097c9c3ea1abe86a961

See more details on using hashes here.

Provenance

The following attestation bundles were made for cytodataframe-0.2.0-py3-none-any.whl:

Publisher: publish-pypi.yml on cytomining/CytoDataFrame

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

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