SOMA -- for stack of matrices, annotated -- is a unified data model and API for single-cell data.
If you know about obs, var, and X, you'll recognize what you're seeing.
The data model and API -- here as implemented using the TileDB storage engine -- allow you to persist, investigate, and share annotated 2D matrices, commonly used in single-cell biology.
Features:
- flexible, extensible, and open-source API
- supports access to persistent, cloud-resident annotated 2D matrix datasets
- enables use within popular data science environments (e.g., R, Python), using the tools of that environment (e.g., Python Pandas integration), with the same storage regardless of language
- allows interop with multiple tools including AnnData, Scanpy, Seurat, and Bioconductor
- cloud-native TileDB arrays allow you to slice straight from remote storage
- reduces costs and processing time by utilizing cost-efficient object storage services like S3
- enables out-of-core access to data aggregations much larger than single-host main memory
- enables distributed computation over datasets
