spatialdata

You can convert between spatial omics formats by loading data into the unified SpatialData object model. This framework normalizes heterogeneous platform representations, enabling seamless cross-platform data conversion and integration for downstream analysis.

Integrating multimodal spatial omics data is achieved by using the SpatialData unified object framework. It supports multiple spatial modalities across various platforms, enabling reproducible end-to-end pipelines within the scverse ecosystem.

Yes, spatialdata works directly with Scanpy and Squidpy. It provides smooth interoperability within the scverse ecosystem and allows easy data exchange with AnnData, enabling cross-platform analysis and downstream visualization.

Yes, you can build end-to-end spatial omics pipelines from import to analysis to visualization in a single framework. The SpatialData object supports multiple modalities and enables reproducible workflows across the scverse ecosystem.

A unified spatial omics representation is needed to address the fragmentation of spatial omics formats. It provides a standardized object model that inter-operates across platforms and analysis tools, enabling seamless pipelines and reproducible analyses.

Cross-platform data integration supports spatial modalities across platforms including Visium, Xenium, MERFISH, and CODEX. The unified SpatialData object normalizes these heterogeneous formats for interoperable analysis within the scverse ecosystem.