https://github.com/cytomining/cytodataframe

An in-memory data analysis format for single-cell profiles alongside their corresponding images and segmentation masks.
https://github.com/cytomining/cytodataframe

dataframes image-analysis image-based-profiling single-cell

Last synced: 7 months ago
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An in-memory data analysis format for single-cell profiles alongside their corresponding images and segmentation masks.

• Host: GitHub
• URL: https://github.com/cytomining/cytodataframe
• Owner: cytomining
• License: bsd-3-clause
• Created: 2024-10-22T22:47:10.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2025-06-11T16:50:05.000Z (7 months ago)
• Last Synced: 2025-06-11T18:12:10.604Z (7 months ago)
• Topics: dataframes, image-analysis, image-based-profiling, single-cell
• Language: Python
• Homepage: https://cytomining.github.io/CytoDataFrame
• Size: 69.3 MB
• Stars: 2
• Watchers: 1
• Forks: 2
• Open Issues: 16
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md
  • Citation: CITATION.cff

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README

          
# CytoDataFrame

[![PyPI - Version](https://img.shields.io/pypi/v/cytodataframe)](https://pypi.org/project/CytoDataFrame/)

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![](https://raw.githubusercontent.com/cytomining/coSMicQC/refs/heads/main/docs/presentations/2024-09-18-SBI2-Conference/images/cosmicqc-example-cytodataframe.png)

_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.

📓 ___Want to see CytoDataFrame in action?___ Check out our [example notebook](docs/src/examples/cytodataframe_at_a_glance.ipynb) for a quick tour of its key features.

> ✨ CytoDataFrame development began within **[coSMicQC](https://github.com/cytomining/coSMicQC)** - a single-cell profile quality control package.

> Please check out our work there as well!

## Installation

Install CytoDataFrame from source using the following:

```shell

# 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](https://cytomining.github.io/CytoDataFrame/main/contributing) documentation for more details on contributions, development, and testing.

## References

- [coSMicQC](https://github.com/cytomining/coSMicQC)

- [pycytominer](https://github.com/cytomining/pycytominer)

- [CellProfiler](https://github.com/CellProfiler/CellProfiler)

- [CytoTable](https://github.com/cytomining/CytoTable)