Powering spatial transcriptomics at scale with TileDB

Spatial transcriptomics is emerging as a crucial tool in life sciences, demanding enhanced data infrastructure due to its complexity and integration needs with single-cell data. TileDB has responded by evolving its SOMA model to accommodate the multiscale images and spatial metadata inherent in spatial experiments, moving beyond traditional data formats to support sophisticated data management and discovery. A notable application is the Chan Zuckerberg Initiative's spatial census, which leverages TileDB-SOMA to standardize and make accessible a vast collection of spatial datasets, empowering researchers through interoperability and real-time data access. Highlighted by UCSF's Dr. Peng He's work on human limb development, the integration of spatial and single-cell data provides new insights into cellular identity and organization, demonstrating the impact of searchable, scalable metadata. As TileDB continues to refine its infrastructure to meet the needs of spatial transcriptomics, it fosters a collaborative community aimed at transforming data management from a bottleneck to a catalyst for scientific discovery.