--- name: spatial-s5-downstream description: Stage 5 of the spatial transcriptomics workflow — neighborhood enrichment and cell-cell communication analysis. Use when the user asks to compute cell-type neighborhood enrichment (co-localization) or infer cell-cell communication with CellChat on Visium data. Produces enrichment heatmaps and CellChat network plots, then stops for review. license: MIT --- # S5 — Downstream (Neighborhood + Communication) ## Goal Quantify cell-type co-localization with neighborhood enrichment, and infer spatially proximal cell-cell communication with CellChat v2. ## Prerequisites - Deconvolved Visium h5ad from S4 with cell-type proportions (for both analyses). - R + CellChat v2 for communication (see `install_r_packages_spatial.R`). ## Steps 1. **Neighborhood enrichment**: `spatial_neighborhood_enrichment(adata_path=..., cell_type_key=..., output_path=..., plot_path=..., n_neighs=...)` - Defaults: `n_neighs=6`. - Output: enrichment z-score table + heatmap. 2. **CellChat**: `infer_spatial_cell_communication(st_h5ad=..., cell_type_key=..., output_dir=..., plot_path=..., r_script_path=..., species=...)` - `species`: `"human"` (default) or `"mouse"` — selects the CellChatDB. - Output: CellChat object, communication summary, network/heatmap plots. ## Outputs - `results/08_neighborhood/_enrichment.csv` + heatmap PNG - `results/09_communication/_cellchat_*.png` (network, heatmap, bubble) - `results/09_communication/_communication_summary.csv` ## Biological Interpretation - Neighborhood: which cell-type pairs co-localize significantly (|z| > 2)? Does this match known tissue niches (e.g., tumor–macrophage, T cell–APC)? - Communication: which ligand–receptor pairs dominate? Are they consistent with the tissue's known biology (e.g., immune checkpoint pairs in tumor)? ## Stop for Review Present interpretation using the template from the parent `spatial-transcriptomics` skill. This is the final stage — after review, produce the overall workflow summary.