bio-spatial-transcriptomics-spatial-visualization

Version Compatibility

Reference examples tested with: matplotlib 3.8+, numpy 1.26+, scanpy 1.10+, squidpy 1.3+

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show <package> then help(module.function) to check signatures

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Spatial Visualization

"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.

Required Imports

import squidpy as sq
import scanpy as sc
import matplotlib.pyplot as plt

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.

# 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

# 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

# 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

# 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

Goal: Visualize gene expression patterns overlaid on tissue spatial coordinates.