GM12878_dnase-model

Model Description

This model is a single-task regression model trained to take in 2114 bp genomic intervals and predict the total GM12878 DNase-seq coverage in the central 1000 bp. It is described in Lal et al. 2025 (https://www.nature.com/articles/s41592-025-02868-z).

• Architecture: DilatedConvModel (gReLU)
• Input: Genomic sequences (hg38)
• Output: Total DNase-seq coverage in the central 1000 bp.

Repository Content

1. model.ckpt: The trained model weights and hyperparameters (PyTorch Lightning checkpoint).
2. 2_train_GM12878_DNase.ipynb: Jupyter notebook for training the model.
3. 3_evaluate_model.ipynb: Jupyter notebook for evaluating the trained model.
4. output.log: Training logs.

How to use

To load this model for inference or fine-tuning, use the grelu interface:

from grelu.lightning import LightningModel
from huggingface_hub import hf_hub_download

ckpt_path = hf_hub_download(
    repo_id="Genentech/GM12878_dnase-model", 
    filename="model.ckpt"
)

model = LightningModel.load_from_checkpoint(ckpt_path)
model.eval()