Spatially resolved omics technologies are transforming our understanding of biological tissues. However, the handling of uni- and multimodal spatial omics datasets remains a challenge owing to large data volumes, heterogeneity of data types and the lack of flexible, spatially aware data structures. Here we introduce SpatialData, a framework that establishes a unified and extensible multiplatform file-format, lazy representation of larger-than-memory data, transformations and alignment to common coordinate systems. SpatialData facilitates spatial annotations and cross-modal aggregation and analysis, the utility of which is illustrated in the context of multiple vignettes, including integrative analysis on a multimodal Xenium and Visium breast cancer study.
GrantsChan Zuckerberg Initiative DAF (advised fund of Silicon Valley Community Foundation) FWO-EOS program Research Foundation-Flanders Flanders AI Research Program Cellzome, a GSK company DKFZ International PhD Programme Personalized Health and Related Technologies Transition Postdoc Fellowship Open Research Data Program of the ETH Board Joachim Herz Foundation Helmholtz Association under the joint research school Munich School for Data Science European Molecular Biology Laboratory (EMBL) BOF-GOA fund BMBF grant (SIMONA) Wellcome Leap as part of the triangleTissue Program Helmholtz Association's Initiative and Networking Fund through Helmholtz AI Deutsche Forschungsgemeinschaft (German Research Foundation) Chan Zuckerberg Initiative DAF, an advised fund of Silicon Valley Community Foundation European Molecular Biology Laboratory EMBL International PhD Programme