spatialdata

What problem does it solve?

SpatialData provides a unified Python-based framework to manage, analyze, and visualize multi-modal spatial omics data, enabling seamless integration of images, labels, shapes, points, and tabular annotations with robust metadata about coordinate systems and transformations.

Core Features & Use Cases

• Unified data model: Represent spatial elements (images, labels, shapes, points) and annotation tables in a single SpatialData object.
• Coordinate systems & transforms: Define intrinsic/extrinsic coordinate spaces and apply transformations to align datasets across scales.
• NGFF/Zarr interoperability: Read and write data using NGFF-compatible formats and the SpatialData Zarr extension for scalable storage and lazy loading.
• Use Case: Load Visium- or Xenium-style datasets, query regions of interest, join spatial elements with annotation tables, and visualize results with napari-spatialdata.

Quick Start

Install SpatialData using pip, then load a sample SpatialData object (e.g., from spatialdata.datasets import blobs; sdata = blobs()) to begin exploring Images, Labels, Points, Shapes, and Tables.