Spatial transcriptomics gold chain (squidpy)
SkillDocs & knowledgesquidpy spatial gold chain on SpatialData .zarr or AnnData .h5ad with obsm['spatial']. Use when the user has Visium/Slide-seq/generic spots or cells with coordinates. Builds a knn spatial graph, Moran SVGs, and spatial_scatter plots. Multi-table SpatialData requires --table. Does not run Cell2location, BayesSpace, SpaGCN, or vendor HD/Xenium pipelines. Numeric clusters only.
Use Spatial transcriptomics gold chain (squidpy) in Claude, ChatGPT or Ahel Desktop
Free. Sign in, add Spatial transcriptomics gold chain (squidpy) and connect your AI. About a minute.
Also: Claude Code · Cursor · Codex
Then ask your AI: use the Spatial transcriptomics gold chain (squidpy) skill
Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; Ahel provides instructions and does not run this skill.
No other account needed.
Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
What this skill tells your AI
The instructions your AI receives, as published by herry423/bionexus in skills/spatial-transcriptomics/SKILL.md and read by Ahel’s review.
Default path is squidpy, not the legacy fused-graph / NNLS helpers.
python scripts/doctor.py # need ready.spatial_ready
python skills/spatial-transcriptomics/scripts/spatial_inspect.py visium.h5ad
python skills/spatial-transcriptomics/scripts/spatial_pipeline.py visium.h5ad -o spatial_out.h5ad
python skills/spatial-transcriptomics/scripts/spatial_plot.py spatial_out.h5ad -o figures/ --color leiden
# SpatialData with several tables:
python skills/spatial-transcriptomics/scripts/spatial_inspect.py data.zarr --table table_name
Accepts SpatialData .zarr (requires spatialdata) or .h5ad with obsm['spatial']. Multiple tables refuse unless --table is set.
| Step | Script | Backend |
|---|---|---|
| inspect | spatial_inspect.py | AnnData / SpatialData I/O |
| pipeline | spatial_pipeline.py | spatial_neighbors_knn + Moran |
| deconvolve | spatial_deconvolution.py | Tangram optimal transport (tangram-sc / PyTorch) |
| plot | spatial_plot.py | squidpy.pl.spatial_scatter → spatial_{color}.png |
Refuses if squidpy is missing for Moran's I. For deconvolution, Tangram deep learning is used with transparent NNLS fallback.
Signals
- GitHub stars
- 31
- Forks
- 4
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
spatial-transcriptomics-herry423- Source
- github.com/herry423/bionexus
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