spatial-stats-neighborhood-enrichment

What problem does it solve?

Compute neighborhood enrichment z-scores to identify which cell types are spatially co-localized or depleted from each other's neighborhoods using squidpy permutation testing on a spatial neighbor graph. Requires cell type annotations to function correctly.

Core Features & Use Cases

• Detects spatial interactions between cell types by comparing observed neighborhood co-occurrence to randomized expectations.
• Outputs a z-score matrix and counts for downstream visualization (e.g., heatmaps) to interpret tissue organization.
• Applicable to single-slice datasets with x,y coordinates and celltype labels to characterize microenvironment patterns.

Quick Start

Run the neighborhood enrichment workflow on your target slice to obtain the z-score matrix.