Atacformer
Transformer foundation model for scATAC-seq that learns embeddings of cis-regulatory elements for clustering, annotation, and reference mapping.
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- Computational Biology
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- 2026-10-10
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EpiFoundation doi.org
Foundation model for scATAC-seq using peak-to-gene aligned pretraining for cell representation, annotation, batch correction, and gene-expression prediction.
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Multi-way Transformer foundation model jointly handling RNA-only, ATAC-only, and paired RNA–ATAC single-cell inputs for integration, translation, annotation, and perturbation prediction.
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Cross-modality translation model enabling prediction between scRNA-seq and scATAC-seq profiles without requiring paired single-cell measurements.
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ChromFound github.com
Genome-aware scATAC-seq foundation model pretrained on 1.97M cells across tissues and disease contexts for zero-shot cell representations, annotation, and cross-omics prediction.
Computational Biology › Machine Learning Tasks and Models > Foundation Models > Single-Cell Epigenomics Foundation Models: “Transformer foundation model for scATAC-seq that learns embeddings of cis-regulatory elements for clustering, annotation, and reference mapping.”