InterSCellar
InterSCellar is a Python package for surface-Based cell neighborhood and interaction volume analysis in 3D spatial omics.
Installation
Install package:
pip install interscellar
Usage
Import:
import interscellar
3D Pipeline:
(1) Cell Neighbor Detection & Graph Construction
neighbors_3d, adata, conn = interscellar.find_cell_neighbors_3d(
ome_zarr_path="data/segmentation.zarr",
metadata_csv_path="data/cell_metadata.csv",
max_distance_um=0.5,
voxel_size_um=(0.56, 0.28, 0.28),
n_jobs=4
)
(2) Interscellar Volume Computation
# Interscellar volumes
volumes_3d, adata, conn = interscellar.compute_interscellar_volumes_3d(
ome_zarr_path="data/segmentation.zarr",
neighbor_pairs_csv="results/neighbors_3d.csv",
neighbor_db_path="/results/neighbor_graph.db",
voxel_size_um=(0.56, 0.28, 0.28),
max_distance_um=3.0,
intracellular_threshold_um=1.0,
n_jobs=4
)
# Cell-only volumes
cellonly_3d = interscellar.compute_cell_only_volumes_3d(
ome_zarr_path="data/segmentation.zarr",
interscellar_volumes_zarr="results/interscellar_volumes.zarr"
)
2D Pipeline:
(1) Cell Neighbor Detection & Graph Construction
neighbors_2d, adata, conn = interscellar.find_cell_neighbors_2d(
polygon_json_path="data/cell_polygons.json",
metadata_csv_path="data/cell_metadata.csv",
max_distance_um=1.0,
pixel_size_um=0.1085,
n_jobs=4
)
Utilities:
Feature Extraction
feature-extract-3d \
--segmentation-zarr "results/interscellar_volumes.zarr" \
--raw-expression-zarr "data/raw_expression.zarr" \
--output-csv "results/features_3d.csv"
Volume Visualization
# Full dataset (Napari)
visualize-all-3d \
--cell-only-zarr "results/cell_only_volumes.zarr" \
--interscellar-zarr "results/interscellar_volumes.zarr" \
--cell-only-opacity 0.7 \
--interscellar-opacity 0.9
# Single pair (Napari)
visualize-pair-3d \
--pair-id 123 \
--cell-only-zarr "results/cell_only_volumes.zarr" \
--interscellar-zarr "results/interscellar_volumes.zarr" \
--pair-opacity 0.6 \
--cells-opacity 0.7
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