Interactive spatial‑omics analysis & visualisation toolkit for single‑cell and spatial transcriptomics data
Celldega
Celldega Demo Video
https://github.com/user-attachments/assets/ce43a3a0-8aff-4424-be74-8bb06c29a9c9
Celldega combines scalable computational pipelines with GPU‑accelerated, web‑native visualisations so you can explore millions of cells and transcripts directly inside Jupyter Lab, VS Code, or any modern browser. Built for researchers working with Xenium, Visium HD, MERFISH, and other spatial omics technologies.
🚀 Quick Start (30 min)
Installation
pip install celldega
For Terra.bio Users
Add this to your startup script for image processing features (more info):
apt update && apt install -y libvips libvips-tools libvips-dev
Example Usage
base_url = 'https://raw.githubusercontent.com/broadinstitute/celldega_Xenium_Prime_Human_Skin_FFPE_outs/main/Xenium_Prime_Human_Skin_FFPE_outs'
landscape_ist = dega.viz.Landscape(
technology="Xenium",
ini_zoom=-4.5,
ini_x=6000,
ini_y=8000,
base_url=base_url,
height=700,
width=600,
)
# Alternatively pass an AnnData object to auto-populate cell metadata
# including "leiden" clusters, colors and UMAP coordinates.
landscape_from_adata = dega.viz.Landscape(
base_url=base_url,
AnnData=adata,
)
file_path = 'https://raw.githubusercontent.com/broadinstitute/celldega_Xenium_Prime_Human_Skin_FFPE_outs/main/Xenium_Prime_Human_Skin_FFPE_outs/df_sig.parquet'
df = pd.read_parquet(file_path)
mat = dega.clust.Matrix(df)
mat.cluster()
cgm = dega.viz.Clustergram(matrix=mat)
dega.viz.landscape_clustergram(landscape_ist, cgm)
📖 Documentation & Examples
- 📚 Documentation - Complete guides and API reference
- 🖼️ Gallery - Interactive visualization demos
- 📓 Examples - Jupyter notebooks you can run locally
- 🐍 Python API - Complete Python API
- 🌐 JavaScript API - Complete JavaScript API
🛠️ Development Setup (for Contributors)
Get started contributing in 2 minutes:
git clone https://github.com/broadinstitute/celldega.git
cd celldega
bash ./scripts/setup.sh
source dega/bin/activate
npm run dev
See our Contributing Guide for detailed instructions.
🏗️ Repository Structure
| Directory/File | Purpose |
|---|---|
src/celldega/ |
🐍 Core Python package |
js/ |
🌐 JavaScript widgets & visualizations |
examples/ |
📓 Jupyter notebook examples |
docs/ |
📚 Documentation source |
js/__tests__/ |
🧪 JS/TS Test suites |
tests/ |
🧪 Python Test suites |
scripts/ |
🔧 Development utilities |
🤝 Contributing
We welcome contributions from the bio community! Whether you're a:
- 🧬 Researcher - Share datasets, create tutorials, improve documentation
- 👩💻 Developer - Add features, fix bugs, optimize performance
- 📚 Educator - Create educational content, examples, workshops
- 🎨 Designer - Improve visualizations, user experience, documentation
Getting started:
- Read our Contributing Guide
- Check open issues for ideas
- Join discussions to ask questions
🆘 Getting Help
Questions about using Celldega?
- 💬 Discussions - Ask the community
- 📖 Documentation - Comprehensive guides
- 📓 Examples - Working code you can adapt
Found a bug or want a feature?
📊 Citation
If Celldega helps your research, please cite us:
@software{celldega,
title = {Celldega: Interactive spatial‑omics analysis & visualisation toolkit},
author = {{Broad Institute}},
url = {https://github.com/broadinstitute/celldega},
version = {0.12.0},
year = {2025}
}
🏛️ About
Celldega is developed at the Broad Institute together with the biology research community. Our mission is to make spatial transcriptomics analysis accessible, interactive, and beautiful.
Built on amazing open source tools:
- deck.gl - GPU-accelerated visualizations
- PyArrow - Fast columnar data processing
- AnnData - Annotated data matrices
- SpatialData - Spatial omics data structures
Made with 🧬 by the Spatial Technology Platform at the Broad Institute
1 maintainer
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