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CellCloud

CellCloud is a 3D, orbit-camera spatial view of cell centroids — for inspecting a dataset's overall shape (thick tissue, multi-slice alignments) rather than the tile-based 2D detail Landscape is optimized for. It replaces Landscape's older technology="point-cloud" mode.

What it shows

  • Cell centroids in 3D, colored by cluster/category or gene expression, rendered as a rotatable/orbit-able point cloud rather than tiled polygons.
  • The same CELL color/size controls as Landscape, minus the tile-specific image and transcript layers (there's no underlying image pyramid or per-transcript layer in this view).
  • Support for named alignment variants — e.g. previewing a candidate slice alignment by pointing at cell_metadata_<alignment>.parquet instead of rebuilding DegaFiles.

Usage

import celldega as dega

cell_cloud = dega.viz.CellCloud(
    base_url="https://your-landscape-files-url",
    adata=adata,
    cell_size=10,  # Default cell diameter in microns
    rotation_x=90,
)
cell_cloud

cell_size sets the default cell diameter (10 µm by default), assuming the centroid coordinates are in microns. The CELL slider scales this diameter from 0× to 2×; its initial midpoint is 1×. You can also update cell_cloud.cell_size after displaying the widget, preserving the slider's current multiplier.

Drag to rotate continuously around both orbit axes, including past the poles.

Build the underlying point-cloud DegaFiles with celldega.align.write_alignment_point_cloud. CellCloud can also be linked to a Clustergram, exactly like Landscape — see dega.viz.spatial_clustergram.

For the full list of constructor arguments, see the Viz Module API reference.

Note

Screenshots and an example video are coming soon.