spatial-integrate

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Load when removing batch effects across multiple spatial samples on a multi-batch spatial AnnData via Harmony, BBKNN, or Scanorama before downstream analysis. Skip when aligning physical slice coordinates (use spatial-register) or for single-batch data (no integration needed — go straight to spatial-domains).

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spatial-integrate

When to use

The user has a multi-sample spatial AnnData (sample / donor labels in obs["batch"] or another --batch-key) and wants batch effects in the gene-expression embedding removed before downstream domain / cluster / DE analysis. Three methods:

harmony (default) — soft k-means in PCA space; produces obsm["X_pca_harmony"]. Tunable via --harmony-theta / --harmony-lambda / --harmony-max-iter. Requires harmonypy.
bbknn — batch-balanced neighbour graph; produces a fused obsp["distances"] ready for UMAP / clustering. Tunable via --bbknn-neighbors-within-batch / --bbknn-n-pcs / --bbknn-trim. Requires bbknn.
scanorama — corrected expression matrix in obsm["X_scanorama"]. Tunable via --scanorama-knn / --scanorama-sigma / --scanorama-alpha / --scanorama-batch-size. Requires scanorama.

For physical slice-coordinate alignment use spatial-register. For single-batch data skip this skill and go to spatial-domains / spatial-de directly.

Inputs & Outputs

Input	Format	Required
Multi-batch AnnData	`.h5ad` with `obs[--batch-key]` (default `batch`) and `obsm["X_pca"]`	yes (unless `--demo`)

Output	Path	Notes
Integrated AnnData	`processed.h5ad`	adds `obsm["X_pca_harmony"]` (harmony) / `obsm["X_scanorama"]` (scanorama) / `obsp["distances"]` rebuild (bbknn)
Integration metrics	`tables/integration_metrics.csv`	always
Batch sizes	`tables/batch_sizes.csv`	always
Observations	`tables/integration_observations.csv`	best-effort (when batch metric flags present)
Report	`report.md` + `result.json`	always

Flow

Load AnnData (--input) or build a 3-batch demo via the bundled spatial-preprocess --demo (spatial_integrate.py:803-815 chains via subprocess).
parser.error validates per-method numeric ranges (--harmony-theta ≥ 0; --harmony-lambda > 0 or -1; --harmony-max-iter ≥ 1; --bbknn-* ≥ 1; --scanorama-* per-flag bounds).
Dispatch to method:
- harmony → write obsm["X_pca_harmony"].
- bbknn → rebuild obsp["distances"] + obsp["connectivities"].
- scanorama → write obsm["X_scanorama"].
Compute integration metrics (e.g., LISI / silhouette scores when supported).
Save processed.h5ad, tables, figures, report.md, result.json.

Gotchas

All numeric flag validation goes through parser.error (exit code 2). spatial_integrate.py:837-857 covers the harmony / bbknn / scanorama numeric ranges. Wrappers expecting ValueError need to catch exit-2 separately.
Demo chains through spatial-preprocess via subprocess. spatial_integrate.py:803 raises FileNotFoundError(f"OmicsClaw runner not found at {main_runner}") when omicsclaw.py is missing; :814 raises RuntimeError("spatial-preprocess --demo failed (exit ...)") when the chained run fails; :819 raises FileNotFoundError(f"Expected {processed}") when the demo output isn't where expected. Real runs skip this chain.
Each method writes a DIFFERENT obsm / obsp key. harmony → obsm["X_pca_harmony"], scanorama → obsm["X_scanorama"], bbknn → modifies obsp["distances"] / obsp["connectivities"] in place (no new obsm key). Downstream skills that consume the integrated embedding via --use-rep must branch on method.
obsm["X_pca"] is required as input for harmony / bbknn (used as starting embedding). If the input AnnData skipped spatial-preprocess, harmony / bbknn fail at runtime. Run spatial-preprocess first, or check for X_pca presence.
--harmony-lambda accepts -1 to enable auto-lambda estimation. spatial_integrate.py:839 documents this special case in the flag check. Other harmony numerics must be strictly positive.
UMAP snapshot key validation. spatial_integrate.py:67 raises KeyError(f"UMAP snapshot '{umap_key}' not found in adata.obsm") when a "before" UMAP comparison is requested but the key is missing. Affects the integration-metrics figure only.

Key CLI

# Demo (synthetic 3-batch chained from spatial-preprocess --demo)
python omicsclaw.py run spatial-integrate --demo --output /tmp/spatial_int_demo

# Default Harmony on real multi-sample data
python omicsclaw.py run spatial-integrate \
  --input multi_sample.h5ad --output results/ \
  --method harmony --batch-key sample

# BBKNN with custom neighbour budget
python omicsclaw.py run spatial-integrate \
  --input multi_sample.h5ad --output results/ \
  --method bbknn --batch-key donor \
  --bbknn-neighbors-within-batch 5 --bbknn-n-pcs 30

# Scanorama with strong correction
python omicsclaw.py run spatial-integrate \
  --input multi_sample.h5ad --output results/ \
  --method scanorama --batch-key library_id \
  --scanorama-sigma 30 --scanorama-alpha 0.05

See also

references/parameters.md — every CLI flag, per-method tunables
references/methodology.md — when Harmony / BBKNN / Scanorama wins; LISI metric
references/output_contract.md — obsm["X_pca_harmony"] / obsm["X_scanorama"] / obsp["distances"] semantics
Adjacent skills: spatial-preprocess (upstream — produces obsm["X_pca"] required input), spatial-register (parallel — aligns physical coordinates, NOT expression), spatial-domains (downstream — pass --use-rep X_pca_harmony / X_scanorama for batch-aware domain detection), spatial-de (downstream — use the integrated embedding for clustering before DE)