Quick Start¶
Installation¶
Requirements¶
- Python: 3.10 or higher
- A modern browser with WebGL support
Install with uv (Recommended)¶
You can also run SpatialVista without installing it permanently:
Install with pip¶
Install from Source¶
git clone https://github.com/JianYang-Lab/spatial-vista-py.git
cd spatial-vista-py
uv pip install -e .
Open an .h5ad file from the command line¶
SpatialVista infers common adata.obsm spatial keys and categorical adata.obs columns, starts at http://127.0.0.1:8765, and opens the browser. Specify keys explicitly if your file uses different names:
spatialvista --input data.h5ad \
--position spatial \
--color celltype \
--section section \
--annotations leiden,region \
--continuous total_counts \
--genes Pecam1,Cd3e
The browser interface provides the same rendering, filtering, layouts, lasso selection, adjustable 3D slice spacing, section navigation, and screenshot tools as the Jupyter widget. Run spatialvista --help for all options. By default the server listens only on your computer; use --host only when you intentionally want a different network interface.
Jupyter example¶
Verify your installation with this minimal example:
import numpy as np
import spatialvista as spv
# Create minimal test data
class FakeAnnData:
def __init__(self, n: int):
self.obsm = {"spatial": np.random.rand(n, 3)}
self.obs = {"celltype": np.random.choice(["A", "B", "C"], n)}
self.var_names = []
self.X = None
self.n_obs = n
adata = FakeAnnData(n=10_000)
# Create visualization
spv.vis(adata, position="spatial", color="celltype")
If you see an interactive visualization, you're all set! 🎉
Update¶
Next Steps¶
- Controls - Learn how to interact with the visualization
- API Reference - Complete function documentation
- FAQ - Common questions and troubleshooting