CytoBERT: A Foundation Model for Cytometry Data

TL;DR - CytoBERT is an open-source, open-weight foundation model pretrained on heterogeneous single-cell cytometry data. It enables transfer learning across studies with different marker panels, supporting more scalable and generalizable cytometry analysis.

• Self-supervised pretraining uses over 50 million cells from 15 human datasets.
• Marker standardization helps the model learn transferable relationships among cellular markers.
• The model accommodates variable marker panels, addressing a major source of cross-study heterogeneity.
• Fine-tuned sample-level classification demonstrates the feasibility of transfer learning across cytometry datasets.