Datasets:

Zehui127127
/

latent-dna-diffusion

pretty_name: Latent DNA Diffusion Sequences (hg19)
tags:
  - genomics
  - biology
  - generative-ai
  - diffusion-models
  - dna
  - huggingscience
  - science
license: other
task_categories:
  - text-generation
size_categories:
  - 10M<n<100M

Dataset Card for Latent DNA Diffusion

Dataset Description

This dataset contains a collection of human DNA sequences, processed for the purpose of training generative models like the one described in the Latent DNA Diffusion project.

Source: Human reference genome assembly hg19 (GRCh37)
Sequence length: 256 base pairs
Format: HDF5 file containing uniformly processed sequences

The primary purpose of this dataset is to serve as a training corpus for models that can learn the underlying patterns of the human genome and generate novel, realistic DNA sequences.

Applications

Data augmentation for genomics
Studying gene regulation
Generating synthetic genomic data to preserve patient privacy

How to Use

The data is stored in a single HDF5 file.

Example usage in Python:

import h5py
from huggingface_hub import hf_hub_download

# Download the HDF5 file from Hugging Face Hub
file_path = hf_hub_download(
    repo_id="Zehui127127/latent-dna-diffusion",
    filename="human_hg19_256.hdf5",
    repo_type="dataset"
)

# Open and explore the file
with h5py.File(file_path, 'r') as f:
    print("Available keys:", list(f.keys()))
    sequences = f['sequences'][:]  # Example key
    print("Shape of dataset:", sequences.shape)