• ⸻ 2026-04-15

Managing spatial omics datasets with SpatialData & LaminDB

• Lukas Heumos, Altana Namsaraeva, Tim Treis, Mark Keller, Wouter-Michiel Vierdag, Luca Marconato, Lea Zimmermann, Sunny Sun, Alex Wolf

Spatial omics technologies — Xenium, Visium, MERFISH, seqFISH, and others — are generating datasets that combine molecular profiling with spatial coordinates. The SpatialData framework[1] provides a unified format for these heterogeneous datasets: images, segmentation masks, point clouds, shapes, and count tables, all stored in a single .zarr store. But as spatial datasets accumulate across experiments and technologies, managing, querying, and training models on them becomes a major challenge. To address this, we have built native SpatialData support into LaminDB, enabling cross-dataset queries, dataset validation, and lineage tracking.