When spatial datasets accumulate across experiments and technologies, managing, querying, and training models on them becomes a major challenge. To address this, we built support for scverse's SpatialData format into LaminDB, enabling cross-dataset queries, dataset validation, and lineage tracking.
Two years ago we partnered with Mark Keller from Nils Gehlenborg’s Lab at Harvard to make Vitessce work seamlessly with LaminDB for interactive visualization of multimodal + spatial datasets.
The integration has found much use across academia, biotech, and pharma — so we wrote up on design principles & use cases.
This was a team effort involving Altana, Richard & Sunny in addition to Mark.
Read the post: blog.lamin.ai/vitessce
The main challenge was extending pandera-based schema validation to the complicated structure of SpatialData; Parquet and AnnData are easier!
Blog: blog.lamin.ai/spatialdata
Code: github.com/laminlabs/la...
With @lukasheumos.bsky.social and many others!
We partnered with @jejomath.bsky.social to help us explain the relation between biology’s sparse measurements and the data lakehouse concept.
LaminR 📦 has been officially announced! This is a project @rcannood.bsky.social and I have worked on to create an R client for @laminlabs.bsky.social.
📦 Repo github.com/laminlabs/la...
Announcement blog blog.lamin.ai/intro-to-lam...
DI blog www.data-intuitive.com/insights/blo...
Managing spatial omics datasets with SpatialData & LaminDB: Spatial omics technologies — Xenium, Visium, MERFISH, seqFISH, and others — are generating datasets that combine molecular profiling ...
Interactive visualization of multimodal and spatial data with Vitessce: The open-source tool Vitessce and Lamin now work together to manage & visualize multimodal and spatial single-cell data. ...
