CytoVerse: Single-Cell AI Foundation Models in the Browser
Mapping single-cell datasets to large atlases is often hindered by server constraints and privacy concerns. We present CytoVerse, a framework that runs scRNA-seq Foundation Models (scFM) entirely in the browser. Three key contributions enable this: (1) deploying models via ONNX without server side compute; (2) using compressed indexing (IVFPQ) to search a more then 20 million cell reference from the client; and (3) a lightweight protocol for sharing embeddings across consortia without exposing raw data. CytoVerse thereby provides a scalable, privacy preserving framework for distributed single-cell analysis.
Authors
- Mohammed A. Mostajo-Radji (ORCID: https://orcid.org/0000-0002-1634-7514)
- Robert Currie (ORCID: https://orcid.org/0000-0003-1828-1827)
- David Haussler
Institutions
- University of California, Santa Cruz (US)
Publication Details
- Journal
- bioRxiv (Cold Spring Harbor Laboratory)
- Published
- 2026-01-30
- DOI
- https://doi.org/10.64898/2026.01.29.702554
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation
- California Institute for Regenerative Medicine
- Office of the President, University of California
- National Institute of Mental Health