SpatialData: A FAIR Framework for Multimodal Spatial Omics
Project summary
Project Duration: 1.5.2023-30.4.2025
Official project website: https://chanzuckerberg.com/science/programs-resources/cell-science/data-insights/spatialdata-a-fair-framework-for-multimodal-spatial-omics/
Recent publications:
Project description
Spatial omics holds immense potential for advancing our understanding of the complex, multiscale architecture of biological tissues. However, current scientific discoveries in this field are limited by the lack of standardized approaches for storing, integrating, analyzing, and sharing spatial omics data. The rapid growth in data size and complexity, along with the continuous emergence of new technologies, has further exacerbated these challenges. To overcome these barriers, there is a critical need for a unified approach that bridges high-throughput molecular profiling and imaging domains. This project brings together expertise from both the imaging and single-cell communities to address these challenges by building on existing efforts like the Open Microscopy Environment (OME)’s cloud-optimized file format (OME-NGFF) and the scverse consortium’s foundational tools for single-cell omics.
The project aims to develop key components for storing spatial omics data using the OME-NGFF format, enabling cloud-compatible, language-agnostic storage of complex spatial multimodal datasets. Building on the success of the AnnData framework, two software packages will be developed: “SpatialData” for efficient data access and querying, and a napari plugin for interactive visualization of these complex datasets. This collaboration will synthesize the OME-NGFF specification with the SpatialData libraries to create a robust infrastructure for spatial multimodal single-cell analysis, supporting scalable cross-language access to data in the cloud. Through this community-driven initiative, the project will provide new tools and capabilities that open up unexplored analysis possibilities, offering the scientific community a powerful, FAIR-compliant platform for advancing spatial omics research.
