Spatial Omics

The SpatialData format builds upon OME-Zarr to provide a standard for storing spatial omics data. There are a number of resources that build either on OME-Zarr directly or upon SpatialData.

Spatial proteomics

spora ecosystem

A suite of resources for spatial proteomics that use OME-Zarr at multiple levels. Includes:

• A spora data formats specification used to harmonize datasets.

In short, it stores structured tabular data as .parquet, all whole-slide images as .ome.zarr, and segmentation masks as .npz.

• spora[data] a resource containing multiple harmonized spatial proteomics datasets

• spora [io] a Python library for accessing spora datasets

• Wenckstern, J., Jain, E., von Querfurth, B. et al. The Virtual Tissues foundation model resolves spatial proteomics across scales. Nature (2026). https://doi.org/10.1038/s41586-026-10884-y (github repo)

other

• Meyer-Bender, M., Vöhringer, H., Schniederjohann, C. et al. Spatialproteomics: an interoperable toolbox for analyzing highly multiplexed fluorescence image data. Nat Methods (2026). https://doi.org/10.1038/s41592-026-03155-1

An xarray/zarr Python toolkit for multiplexed immunofluorescence, using SpatialData for the underlying data representation, in connection with the scverse ecosystem.

• Alexander Coulton, Nicholas McGranahan, Odon: an ultra-fast viewer for spatial proteomics, Bioinformatics, Volume 42, Issue 7, July 2026, btag514, https://doi.org/10.1093/bioinformatics/btag514

A viewer for spatial proteomics data built directly for OME-Zarr datasets, with secondary support for SpatialData.