See every cell. Query any gene. Explore in 2D and 3D.
Cellucid is a browser-first, GPU-accelerated workspace for exploring large single-cell datasets in real time. Move naturally through 1D, 2D, and 3D embeddings, compare populations side by side, follow cellular dynamics, and turn an exploratory view into a reproducible figure or shared session.
- Fast WebGL rendering with adaptive detail for million-cell atlases
- Interactive gene-expression and cell-metadata coloring, filtering, and highlighting
- Independent multiview comparisons with per-view colors and filter stacks
- Animated RNA-velocity and drift overlays, KNN connectivity, and volumetric smoke
- Built-in differential expression, correlation, gene-signature, and quick-insight workflows
- Orbit, Planar, and Free Fly navigation with reproducible Camera Path animation
- Community annotation, voting, and consensus with optional GitHub collaboration
- Shareable session state, dataset links, "Open in Cellucid" README badges and embed snippets, plus publication-ready SVG and high-DPI PNG export
- A hover card with the values of the cell under the pointer, in every view, at no rendering cost
- Direct H5AD and Zarr loading, prepared datasets, local or remote servers, Jupyter, Python, and R
Placeholder citation. The Cellucid preprint is in preparation for bioRxiv and has no DOI yet; the reference below is a placeholder and will be replaced when the preprint is published.
If you use Cellucid, please cite:
Inecik, K. PLACEHOLDER: Cellucid preprint, title to be announced (forthcoming on bioRxiv). bioRxiv (in preparation).
BibTeX and other formats: Citing Cellucid.
Installation, data preparation, every loading path, UI controls, examples, and troubleshooting are covered in the complete Cellucid documentation.