spatial-transcriptomics

Spatial Transcriptomics

Overview

Spatial transcriptomics combines gene expression profiling with spatial coordinates, enabling study of tissue architecture, cell-cell communication, and spatially variable gene expression. This skill covers analysis of major platforms: 10X Visium, 10X Xenium, MERFISH, seqFISH+, Slide-seq, and Stereo-seq.

When to Use This Skill

• Analyzing 10X Visium, Xenium, or MERFISH spatial data
• Identifying spatially variable genes (SVGs)
• Computing spatial neighborhood enrichment and interaction scores
• Detecting tissue domains and spatial domains
• Studying cell-cell communication with spatial context
• Integrating spatial data with single-cell reference atlases
• Visualizing gene expression on tissue images

Quick Start

Loading Visium Data with Squidpy

import scanpy as sc
import squidpy as sq
import numpy as np

# Load 10X Visium dataset
adata = sq.datasets.visium_fluo_adata()
# Or load your own:
# adata = sc.read_visium("path/to/spaceranger/output/")

print(adata)
print(f"Spots: {adata.n_obs}, Genes: {adata.n_vars}")
print(f"Spatial coords shape: {adata.obsm['spatial'].shape}")

# Basic QC
sc.pp.calculate_qc_metrics(adata, inplace=True)
sc.pl.violin(adata, ["n_genes_by_counts", "total_counts"], jitter=0.4, multi_panel=True)

Standard Preprocessing Pipeline

import scanpy as sc
import squidpy as sq

# Load data
adata = sc.read_visium("spaceranger_output/")

# QC filtering
sc.pp.filter_cells(adata, min_genes=200)
sc.pp.filter_genes(adata, min_cells=3)

# Normalize and log transform
sc.pp.normalize_total(adata, target_sum=1e4)
sc.pp.log1p(adata)
adata.raw = adata  # Store raw counts

# Highly variable genes
sc.pp.highly_variable_genes(adata, min_mean=0.0125, max_mean=3, min_disp=0.5)

# PCA, neighbors, UMAP
sc.pp.scale(adata, max_value=10)
sc.tl.pca(adata, svd_solver="arpack")
sc.pp.neighbors(adata, n_neighbors=10, n_pcs=40)
sc.tl.umap(adata)

# Clustering
sc.tl.leiden(adata, resolution=0.5)

# Visualize on tissue
sq.pl.spatial_scatter(adata, color="leiden", size=1.5)