CDT2-data

Data files for Central Dogma Transformer II (CDT-II).

Files

File	Description	Size
`morris_celllevel_effects_2361.h5`	Cell-level perturbation effects (TSS, 2,361 genes)	41 MB
`morris_snp_celllevel_effects_2361.h5`	Cell-level perturbation effects (SNP, 2,361 genes)	34 MB
`k562_gene_embeddings_aligned.h5`	Gene embeddings from scGPT (2,360 genes)	4.4 MB
`cdt_morris_celllevel_best.pt`	Trained CDT-II model weights	80 MB

Enformer Embeddings (Not Included)

The Enformer embeddings must be generated using the notebooks in the CDT2 repository:

morris_28genes_enformer.h5 - Generate with notebooks/embeddings/Morris_28genes_Enformer.ipynb
morris_snp_enformer.h5 - Generate with notebooks/embeddings/Morris_SNP_Enformer.ipynb

These notebooks run Enformer inference on Google Colab and save the embeddings to Google Drive.

Usage

from huggingface_hub import hf_hub_download

# Download cell-level effects
effects_path = hf_hub_download(
    repo_id="nobusama17/CDT2-data",
    filename="morris_celllevel_effects_2361.h5",
    repo_type="dataset"
)

# Download model weights
model_path = hf_hub_download(
    repo_id="nobusama17/CDT2-data",
    filename="cdt_morris_celllevel_best.pt",
    repo_type="dataset"
)

Data Source

Morris STING-seq v2 dataset (60,505 K562 cells, 447 perturbation loci)
Reference: Morris et al. Science 2023

Citation

@article{ota2025cdtii,
  title={Central Dogma Transformer II: An AI Microscope for Understanding Cellular Regulatory Mechanisms},
  author={Ota, Nobuyuki},
  journal={bioRxiv},
  year={2025}
}

License

MIT License