--- 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}, } ```