bio-spatial-transcriptomics-spatial-visualization
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.
npx skills add majiayu000/claude-skill-registry --skill spatial-visualization-gptomics-bioskills-2 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Spatial Visualization Create visualizations for spatial transcriptomics data. ## Required Imports ```python import squidpy as sq import scanpy as sc import matplotlib.pyplot as plt ``` ## Basic Spatial Plot ```python # Plot spots colored by a variable sq.pl.spatial_scatter(adata, color='total_counts', size=1.3) # Multiple variables sq.pl.spatial_scatter(adata, color=['total_counts', 'n_genes_by_counts'], ncols=2) ``` ## Plot with Scanpy ```python # Scanpy's spatial plot sc.pl.spatial(adata, color='leiden', spot_size=1.5) # Multiple genes sc.pl.spatial(adata, color=['GENE1', 'GENE2', 'GENE3'], ncols=3) ``` ## Show Tissue Image ```python # Plot with tissue background sc.pl.spatial(adata, color='leiden', img_key='hires', alpha_img=0.5) # Without tissue sc.pl.spatial(adata, color='leiden', img_key=None) ``` ## Customize Appearance ```python # Adjust spot size and colors sc.pl.spatial( adata, color='leiden', spot_size=1.5, palette='tab20', title='Cluster assignments', frameon=False, ) ``` ## Gene Expression on Tissue ```python # Single gene sc.pl.spatial(adata, color='CD3D', cmap='viridis', vmin=0, vmax='p99') # Multiple genes side by side genes = ['CD3D', 'MS4A1', 'CD14', 'NKG7'] sc.
- Required Imports
- Basic Spatial Plot
- Plot with Scanpy
- Show Tissue Image
- Customize Appearance
- Gene Expression on Tissue
- Expression with Colorbar Control
- Compare Conditions/Samples
- Overlay Annotations
- Co-expression Plot
- Visualize Spatial Statistics
- Interactive Visualization with Napari
- Save Publication-Quality Figures
- Multi-Panel Figure
What does the bio-spatial-transcriptomics-spatial-visualization skill do?
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.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill spatial-visualization-gptomics-bioskills-2 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.