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bio-spatial-transcriptomics-spatial-visualization

Maintainer FreedomIntelligence · Last updated April 1, 2026

Visualize spatial transcriptomics data using Squidpy and Scanpy. Create tissue plots with gene expression, clusters, and annotations overlaid on histology images. Use when visualizing spatial expression patterns.

OpenClawNanoClawAnalysisWritingbio-spatial-transcriptomics-spatial-visualization🧬 bioinformatics (gptomics bio-* suite)bioinformatics — single-cell & spatial omicsvisualize

Original source

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-spatial-transcriptomics-spatial-visualization

Maintainer
FreedomIntelligence
License
MIT
Last updated
April 1, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

  • Python: squidpy.pl.spatial_scatter(adata, color='gene'), scanpy.pl.spatial(adata, color='leiden').
  • Plot gene expression on my tissue section" → Overlay gene expression, cluster assignments, or continuous scores on spatial coordinates with optional histology image background. Python: squidpy.pl.spatial_scatter(adata, color='gene'), scanpy.pl.spatial(adata, color='leiden').
  • Create visualizations for spatial transcriptomics data.
  • sq.pl.spatial_scatter(adata, color='total_counts', size=1.3).

Source Doc

Excerpt From SKILL.md

Basic Spatial Plot

Goal: Create a spatial scatter plot with spots colored by a variable of interest.

Approach: Use Squidpy's spatial_scatter to overlay expression or metadata values on tissue coordinates.


## Multiple variables

sq.pl.spatial_scatter(adata, color=['total_counts', 'n_genes_by_counts'], ncols=2)

Scanpy's spatial plot

sc.pl.spatial(adata, color='leiden', spot_size=1.5)

Use cases

  • Use when visualizing spatial expression patterns.

Not for

  • Do not rely on this catalog entry alone for installation or maintenance details.

Upstream Related Skills

  • spatial-data-io - Load spatial data
  • spatial-statistics - Compute statistics to visualize
  • single-cell/clustering - Generate cluster labels

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