Cellucid — Interactive Single-Cell Data Visualization
Cellucid is a free, open-source, GPU-accelerated web app for interactive single-cell data visualization. It shows millions of cells in your browser, in 1D, 2D and 3D embeddings such as UMAP, colored by gene expression or cell metadata.
Key features
- Real-time rendering of millions of cells with adaptive level of detail (LOD)
- 1D, 2D and 3D embeddings such as UMAP, several per dataset, side by side
- Gene expression overlays with efficient sparse matrix handling
- Categorical and continuous cell metadata coloring, filtering, and selection
- Animated vector field overlays (RNA velocity / drift) with GPU particle flow
- Connectivity edge visualization (KNN graph)
- Publication export: SVG (vector) + PNG (high-DPI)
- Community annotation voting with optional GitHub sync
Data sources
Open an AnnData .h5ad file, a Zarr store or a .zarr.zip archive directly in the browser. The cellucid Python package prepares one from Scanpy/AnnData, and the cellucid R package from Seurat and SingleCellExperiment. Data can also be served from a Python server or a Jupyter notebook.
Use cases
Explore scRNA-seq atlases, query marker genes, compare embeddings, visualize trajectories, and build consensus community annotations.
