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.
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...
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.
An R package for working with LaminDB instances. Contribute to laminlabs/laminr development by creating an account on GitHub.
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!
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
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. ...
