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SpatialVista - Interactive 3D Spatial Transcriptomics Visualization

Python Version License Platform Platform

Overview

SpatialVista is an interactive 3D spatial transcriptomics visualization tool designed specifically for Jupyter Notebook/Lab. It seamlessly integrates into your data analysis workflow, providing efficient and intuitive exploration of spatial omics data.

SpatialVista

✨ Key Features

  • 🚀 High-Performance Rendering - WebGL-based 3D rendering supporting millions of cells
  • 📊 Multi-Dimensional Data Display - Support for categorical annotations, continuous values, gene expression, and more
  • 🎨 Interactive Controls - Real-time adjustment of colors, transparency, point size, and other parameters
  • 🔬 2D/3D View Switching - Flexible switching between 3D point cloud and 2D slice views
  • 🧬 Gene Expression Query - Quick visualization of spatial expression patterns for any gene
  • 📐 Multiple Layout Modes - Support for original coordinates, 2D Treemap, histogram, and more
  • 🎯 Precise Filtering - Filter data points by category, numerical range, and other conditions
  • 💾 One-Click Screenshots - Easily save current views for publications and reports

🎯 Use Cases

SpatialVista is particularly suitable for:

  • Spatial Transcriptomics Data Exploration - Visium, MERFISH, seqFISH, STARmap, and other technologies
  • Single-Cell Spatial Data Analysis - Visualize spatial distribution of cell types
  • Tissue Architecture Studies - Explore molecular features of tissue regions
  • Gene Expression Pattern Analysis - View spatial expression of specific genes
  • Data Quality Control - Quickly check data integrity and outliers

🚀 Quick Start

Installation

pip install spatialvista

Basic Usage

import spatialvista as spv
import scanpy as sc

# Load spatial transcriptomics data
adata = sc.read_h5ad("spatial_data.h5ad")

# Create interactive visualization
widget = spv.vis(
    adata,
    position="spatial",  # obsm key containing spatial coordinates
    color="celltype",    # Default annotation for coloring
    height=600               # Widget height in pixels
)

# Display widget
widget

That's it! 🎉

📚 Core Features

1. Categorical Annotation Visualization

# Color by cell type
widget = spv.vis(
    adata,
    position="spatial",
    color="celltype",
    annotations=["leiden", "tissue_region"]  # Additional annotations to load
)

2. Continuous Value Visualization

# Visualize continuous values (e.g., QC metrics)
widget = spv.vis(
    adata,
    position="spatial",
    color="celltype",
    continuous=["total_counts", "n_genes"]  # Continuous value fields
)

3. Gene Expression Visualization

# View expression patterns of specific genes
widget = spv.vis(
    adata,
    position="spatial",
    color="celltype",
    genes=["Pecam1", "Cd3e", "Epcam"],  # Gene list
    layer="normalized"  # Optional: use specific layer if available
)

4. 2D/3D View Switching

# If data has section information, switch to 2D view in UI
widget = spv.vis(
    adata,
    position="spatial",
    color="celltype",
    section="slice_id",  # Section identifier field for section browser
)

🎨 Interactive Controls

Once displayed, the widget provides rich interactive controls for exploring your data:

  • Navigate in 3D space (rotate, pan, zoom)
  • Switch between annotations and customize colors
  • Query continuous values and gene expression
  • Filter by thresholds and hide specific categories
  • Adjust visualization parameters (size, opacity, layout)
  • Export screenshots

→ Learn more about interactive controls

📖 Learn More

🤝 Contributing & Support

Issues and Pull Requests are welcome!

📄 License

SpatialVista is open-sourced under the MIT License.

Built with ❤️ for spatial omics research by WenjieWei@YangLab