Dataset Access

Access the dataset used to replicate the results presented in the paper at Hugging Face: Latent DNA Diffusion Dataset

Installation

1. Clone the repo

   git clone https://github.com/Zehui127/Latent-DNA-Diffusion.git

2. Install the required packages: diffusers, accelerate

   pip install torch torchvision diffusers accelerate einops easydict pytorch_lightning

   Code Usage

Download pre-trained models

A pre-trained vae model and unet model can be downloaded from the following links:

https://zenodo.org/records/11061611

Generate DNA sequences using the trained diffusion model

Set the path to the pretrained vae model and unet model in the following command. The number of sequences to generate can be set using the sequence_num argument in src/configs/generate.yaml.

CUDA_VISIBLE_DEVICES="0" accelerate launch --main_process_port 12903 --multi_gpu main.py --model generate --gen_vae_path="" --gen_unet_path=""

Train the diffusion model

Set the path to the dataset in the config file src/configs/un_unet.yaml data_path field. Set the path to the pretrained vae model in the config file src/configs/un_unet.yaml vae_path field.

CUDA_VISIBLE_DEVICES="0,1" accelerate launch --main_process_port 12903 --multi_gpu main.py --model un_unet

Train the vae model

Set the path to the dataset in the config file

CUDA_VISIBLE_DEVICES="0,1" accelerate launch --main_process_port 12903 --multi_gpu main.py --model vanilla_vae

How to Cite This Work

If you use this project or dataset in your research, please cite it as follows:

@article{li2023latent,
  title={Latent Diffusion Model for DNA Sequence Generation},
  author={Li, Zehui* and Ni, Yuhao* and Huygelen, Tim August B and Das, Akashaditya and Xia, Guoxuan and Stan, Guy-Bart and Zhao, Yiren},
  journal={arXiv preprint arXiv:2310.06150},
  year={2023}
}

@article{li2024discdiff,
  title={DiscDiff: Latent Diffusion Model for DNA Sequence Generation},
  author={Li, Zehui and Ni, Yuhao and Beardall, William AV and Xia, Guoxuan and Das, Akashaditya and Huygelen, Tim August B and Stan, Guy-Bart and Zhao, Yiren},
  journal={arXiv preprint arXiv:2402.06079},
  year={2024}
}