An in-memory data analysis format for single-cell profiles alongside their corresponding images and segmentation masks.
Project description
CytoDataFrame
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
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
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
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
b02f6a610acd6b97c70f74f8473546e932edbcb240cd51a01766466efcf6d1ad
|
|
| MD5 |
4cd3dd6d586072cf9487bfc278340692
|
|
| BLAKE2b-256 |
2733e4330257c55d7a1bd666429065493da2b4d4cf8fa1dfd4b4eac1ae909383
|
Provenance
The following attestation bundles were made for cytodataframe-0.2.0.tar.gz:
Publisher:
publish-pypi.yml on cytomining/CytoDataFrame
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
cytodataframe-0.2.0.tar.gz -
Subject digest:
b02f6a610acd6b97c70f74f8473546e932edbcb240cd51a01766466efcf6d1ad - Sigstore transparency entry: 948617597
- Sigstore integration time:
-
Permalink:
cytomining/CytoDataFrame@580e628b463eab4b14d445baf9943d4b05e434de -
Branch / Tag:
refs/tags/v0.2.0 - Owner: https://github.com/cytomining
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
publish-pypi.yml@580e628b463eab4b14d445baf9943d4b05e434de -
Trigger Event:
release
-
Statement type:
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
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
495a925f11992bb9d32207f93cb0a14d0d128736fce57c749311cfff2c669d51
|
|
| MD5 |
214d2c3ab8b15612b9fe0a78bead49ae
|
|
| BLAKE2b-256 |
c0f86c32e4d88f4050cc98d4afda4e6314a4f6ac5fb25097c9c3ea1abe86a961
|
Provenance
The following attestation bundles were made for cytodataframe-0.2.0-py3-none-any.whl:
Publisher:
publish-pypi.yml on cytomining/CytoDataFrame
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
cytodataframe-0.2.0-py3-none-any.whl -
Subject digest:
495a925f11992bb9d32207f93cb0a14d0d128736fce57c749311cfff2c669d51 - Sigstore transparency entry: 948617644
- Sigstore integration time:
-
Permalink:
cytomining/CytoDataFrame@580e628b463eab4b14d445baf9943d4b05e434de -
Branch / Tag:
refs/tags/v0.2.0 - Owner: https://github.com/cytomining
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
publish-pypi.yml@580e628b463eab4b14d445baf9943d4b05e434de -
Trigger Event:
release
-
Statement type: