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SpatialData: an open and universal data framework for spatial omics.

Luca MarconatoGiovanni PallaKevin A YamauchiIsaac VirshupElyas HeidariTim TreisWouter-Michiel VierdagMarcella TothSonja StockhausRahul B ShresthaBenjamin RombautLotte PollarisLaurens LehnerHarald VöhringerIlia KatsYvan SaeysSinem K SakaWolfgang HuberMoritz GerstungJosh MooreFabian Joachim TheisOliver Stegle
Published in: Nature methods (2024)
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.
Keyphrases
  • electronic health record
  • big data
  • single cell
  • gene expression
  • data analysis
  • machine learning
  • pain management
  • working memory