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graph-analysis

graph-analysis

Build Squidpy spatial neighbor graphs and run graph/statistical analyses on AnnData or SpatialData tables.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: graph-analysis description: "Build Squidpy spatial neighbor graphs and run graph/statistical analyses on AnnData or SpatialData tables." disable-model-invocation: true metadata: disco-role: operating license: BSD 3-Clause

Squidpy Graph Analysis

Use this sub-skill when a task needs squidpy.gr graph construction or graph/statistical analysis on an AnnData object or a SpatialData table: spatial neighbors, custom builders, neighborhood enrichment, co-occurrence, Ripley statistics, spatial autocorrelation, ligand-receptor testing, centrality, interaction matrices, niche labels, Sepal scores, or graph masking.

Route First

  • Need data readers, downloadable examples, Visium/Vizgen/Nanostring layouts, or .obsm['spatial'] validation? Use datasets-and-io first.
  • Need plots such as sq.pl.nhood_enrichment, sq.pl.co_occurrence, sq.pl.ripley, sq.pl.centrality_scores, sq.pl.interaction_matrix, sq.pl.ligrec, or graph edges in spatial_scatter? Compute here, then route plotting to visualization with the result keys.
  • Need squidpy.tl.var_by_distance, squidpy.tl.sliding_window, or sq.pl.var_by_distance? Use tools-workflows.
  • Need stable image processing or experimental SpatialData image tiling/QC? Use image-analysis or experimental-imaging.

Fast Workflow

  1. Prepare an AnnData table with coordinates in adata.obsm['spatial'] and categorical labels in adata.obs[cluster_key]; for SpatialData, pass table_key to graph/statistical functions and elements_to_coordinate_systems when graph coordinates come from shapes or labels.
  2. Build a graph with a mode-specific constructor: sq.gr.spatial_neighbors_knn, sq.gr.spatial_neighbors_radius, sq.gr.spatial_neighbors_delaunay, sq.gr.spatial_neighbors_grid, or sq.gr.spatial_neighbors_from_builder.
  3. Avoid new code that depends on deprecated sq.gr.spatial_neighbors; keep it only for legacy snippets and prefer explicit mode-specific functions.
  4. Confirm graph outputs exist at adata.obsp['spatial_connectivities'], adata.obsp['spatial_distances'], and adata.uns['spatial'] unless key_added changed the prefix.
  5. Run graph statistics with matching connectivity_key, spatial_key, cluster_key, and table_key values.
  6. Validate outputs before plotting or downstream use.

What To Read

  • references/graph-workflows.md for graph construction choices, result keys, analysis ordering, SpatialData table handling, and validation snippets.
  • references/api-reference.md for focused signatures, preconditions, outputs, and storage locations.
  • references/custom-builders.md for GraphBuilder/GraphBuilderCSR contracts, built-in builders, postprocessors, and a custom approximate KNN pattern.
  • references/troubleshooting.md for categorical labels, connectivity keys, deprecated spatial_neighbors, multi-library graphs, SpatialData table_key, ligand-receptor schema, optional niche dependencies, permutation cost, and parallel backends.
  • scripts/graph_smoke.py for a tiny deterministic AnnData graph/statistics smoke that performs no downloads.
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