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OMG
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---
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-*
license: cc-by-sa-4.0
---

# OMG: An Open MetaGenomic Dataset

The OMG is a 3.1T base pair metagenomic pretraining dataset, combining EMBL's [MGnify](https://www.ebi.ac.uk/metagenomics) and JGI's [IMG](https://img.jgi.doe.gov) 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)))
```

## Format

Each row of the dataset represents a genomic scaffold, as an ordered list of amino acid coding sequences (CDS) and nucleotide intergenic sequences (IGS). 

| Feature | Description | Example |
|---|---|---|
| `CDS_seqs` | A list of strings representing the amino acid CDS sequences. | `['MALTKVEKRNR...', 'MLGIDNIERVK...', 'MATIKVKQVR...', 'MNLSNIKPAS...']` |
| `IGS_seqs` | A list of strings representing the nucleotide IGS sequences. | `['AATTTAAGGAA', 'TTTTAAAAGTATCGAAAT', 'TTTTTAAAGAAAA']` |
| `CDS_position_ids` | A list of integers representing the position of each CDS element in the scaffold. | `[1, 3, 5, 6]` |
| `IGS_position_ids` | A list of integers representing the position of each IGS element in the scaffold. | `[0, 2, 4]` |
| `CDS_ids` | A list of string identifiers for each CDS element. | `['7000000126\|C1821366\|CDS\|gene_115413\|+\|84:437', '7000000126\|C1821366\|CDS\|gene_115414\|+\|456:977', '7000000126\|C1821366\|CDS\|gene_115415\|+\|991:1167', '7000000126\|C1821366\|CDS\|gene_115416\|+\|1168:1689']` |
| `IGS_ids` | A list of string identifiers for each IGS element. | `['7000000126\|C1821366\|IG\|IG_000001\|+\|73:83', '7000000126\|C1821366\|IG\|IG_000002\|+\|438:455', '7000000126\|C1821366\|IG\|IG_000003\|+\|978:990']` |
| `CDS_orientations` | A list of booleans indicating the orientation of each CDS. `True` represents the forward strand, and `False` represents the reverse strand. | `[True, True, True, False]` |


 The format for the CDS and IGS id fields is: `sample_accession|contig_id|feature_type|gene_id|strand|start:end`


## Citation

**BibTeX:**

```
@article{Cornman2024,
  title = {The OMG dataset: An Open MetaGenomic corpus for mixed-modality genomic language modeling},
  url = {https://www.biorxiv.org/content/early/2024/08/17/2024.08.14.607850},
  DOI = {10.1101/2024.08.14.607850},
  publisher = {Cold Spring Harbor Laboratory},
  author = {Cornman, Andre and West-Roberts, Jacob and Camargo, Antonio Pedro and Roux, Simon and Beracochea, Martin and Mirdita, Milot and Ovchinnikov, Sergey and Hwang, Yunha},
  year = {2024},
}
```