Pre-trained single-cell genomics models based on:
- BarlowTwins
- Bootstrap Your Own Latent
- Masked Autoencoder
- Gene-Program Masked Autoencoder
Finetuned models for the downstream tasks of:
- Cell Type Prediction
- Gene Expression Reconstruction
- Cross-Modality Prediction (RNA->Proteomics)
- Data Integration
Training details and adaptations to single-cell data in our project can be found in our paper below. To use the model directly, the same genes must be used in the same order as in the var.parquet file. Otherwise, follow the instructions from the repositories below to train a model for custom datasets.
If you find our work useful, please cite the following paper:
Delineating the Effective Use of Self-Supervised Learning in Single-Cell Genomics
See also:
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