---
language:
- en
license: mit
task_categories:
- text-generation
- genomic-sequence-modeling
size_categories:
- 10M<n<100M
configs:
- config_name: default
  data_files: "*.parquet"
  default: true
---

# PromoterZoo

## Dataset Description

This dataset contains promoter sequence training data for the LOL-EVE (Language of Life - Evolutionary Variant Effects) model. The dataset includes 13.6 million promoter sequences from various species, providing a comprehensive foundation for training genomic sequence models.

## Dataset Structure

- **Total Sequences**: 13,611,373
- **Species**: Multiple species across different clades
- **Sequence Length**: 1,000 base pairs (promoter regions)
- **Direction**: Both towards and away from TSS

## Features

- `sequence`: DNA sequence (1000bp promoter region)
- `gene`: Gene symbol
- `species`: Species name
- `clade`: Evolutionary clade
- `chrom`: Chromosome
- `strand`: Strand orientation (+/-)
- `start`: Genomic start position
- `stop`: Genomic stop position
- `sequence_len`: Length of sequence (1000)
- `direction`: Direction relative to TSS (towards/away)

## Usage

```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("cshearer/PromoterZoo")

# Access the data
print(f"Dataset size: {len(dataset['train'])}")
print(f"Features: {dataset['train'].features}")

# Example: Get sequences for a specific gene
gene_sequences = dataset['train'].filter(lambda x: x['gene'] == 'a1bg')
print(f"Sequences for a1bg: {len(gene_sequences)}")

# Example: Get sequences from a specific species
species_sequences = dataset['train'].filter(lambda x: 'homo' in x['species'].lower())
print(f"Human sequences: {len(species_sequences)}")
```

## Data Processing

The sequences are processed as follows:
- Promoter regions are extracted 1000bp upstream of transcription start sites
- Both forward and reverse strand sequences are included
- Sequences are labeled with gene, species, and genomic coordinates

## Citation

If you use this dataset in your research, please cite:

```bibtex
@article{loleve2024,
  title={LOL-EVE: Language of Life - Evolutionary Variant Effects},
  author={Your Name and Collaborators},
  journal={Nature},
  year={2024}
}
```

## License

This dataset is released under the MIT License.