---
dataset_info:
  features:
  - name: CDS_position_ids
    sequence: int32
  - name: IGS_position_ids
    sequence: int32
  - name: CDS_ids
    sequence: string
  - name: IGS_ids
    sequence: string
  - name: CDS_seqs
    sequence: large_string
  - name: IGS_seqs
    sequence: large_string
  - name: CDS_orientations
    sequence: bool
  splits:
  - name: train
    num_bytes: 1916402470934
    num_examples: 270640482
  download_size: 1253813127320
  dataset_size: 1916402470934
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

# Dataset Card for OMG: An Open MetaGenomic Dataset

The OMG is a 3.1T base pair metagenomic pretraining dataset, combining EMBL's MGnify and JGI's IMG databases. The combined data is pre-processed into a mixed-modality dataset, with translated amino acids for protein coding sequences, and nucleic acids for intergenic sequences.

We make two additional datasets available on the HuggingFace Hub:
- [`OG`](https://huggingface.co/datasets/tattabio/OG): A subset of OMG consisting of high quality genomes with taxonomic information.
- [`OMG_prot50`](https://huggingface.co/datasets/tattabio/OMG_prot50): A protein-only dataset generated by clustering OMG at 50% sequence identity, resulting in 207M protein sequences.

See [https://github.com/TattaBio/OMG](https://github.com/TattaBio/OMG) for details and example tokenization script. 

## Use

```python
import datasets

ds = datasets.load_dataset('tattabio/OMG')
```

To preview the dataset without downloading, load in streaming mode:
```python
import datasets

ds = datasets.load_dataset('tattabio/OMG', streaming=True)['train']
print(next(iter(ds)))
```



## Citation

**BibTeX:**

TODO