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satputekuldip
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opengenome2

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Text Generation
Size:
n>1T
Tags:
biology
DNA
genomics
genetics
metagenomics
fasta
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satputekuldip mdurrant commited on
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Duplicate from arcinstitute/opengenome2

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Co-authored-by: Matthew Durrant <mdurrant@users.noreply.huggingface.co>

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+ ---
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+ license: apache-2.0
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+ task_categories:
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+ - text-generation
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+ tags:
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+ - biology
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+ - DNA
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+ - genomics
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+ - genetics
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+ - metagenomics
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+ - fasta
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+ - json
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+ size_categories:
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+ - n>1T
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+ ---
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+
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+ # OpenGenome2
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+
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+ <p align="center">
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+ <img src="https://cdn-uploads.huggingface.co/production/uploads/649aee789fc303937a045f6a/Ma6udvzIkeAypUXcH-FJR.jpeg" width="70%" />
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+ </p>
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+
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+ OpenGenome2 is a database of nearly 9 trillion base pairs of curated DNA from across all domains of life. Collected from diverse species and public data sources, OpenGenome2 was used to train Evo 2 models. Please refer to the [Evo 2 preprint](https://www.biorxiv.org/content/10.1101/2025.02.18.638918v1) or [github repository](https://github.com/ArcInstitute/evo2) for further details and usage examples.
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+
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+ We provide OpenGenome2 in two formats, the dataset is organized into two main directories to reflect this:
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+ - **fasta** which contain the DNA sequences
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+ - **jsonl** which include the specific preprocessed sequences used for Evo 2 pretraining, such as adding special tokens and phylogenetic tags
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+
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+ This dataset was specifically curated and preprocessed for training the Evo 2 family of genomic language models and can be used for training models or bioinformatics.
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+
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+ ## Dataset Statistics
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+ - **Total size**: 8.8 trillion base pairs
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+ - **Coverage**: All domains of life (Bacteria, Archaea, Eukaryota, Viruses)
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+ - **Formats available**: FASTA, JSONL
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+
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+ ## Data Sources
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+
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+ The dataset combines sequences from various public databases and repositories:
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+ - **Prokaryotic genomes**: GTDBv220, IMG/PR
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+ - **Metagenomics**: MGD DB
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+ - **Viral sequences**: IMG/VR
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+ - **Eukaryotic data**: NCBI, Ensembl (from which we identified mRNAs, genomic windows)
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+ - **Eukaryotic elements**: Eukaryotic Promoter Database new (EPDnew)
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+ - **RNA sequences**: RNAcentral, Rfam
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+ - **Organellar genomes**: Various organelles
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+
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+ ## Training Data Composition
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+
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+ Evo 2 uses a two stage to train on OpenGenome2, first pretraining on a focused dataset at shorter sequence length and then longer sequence length with more full genomes and special tags.
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+
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+ ### Phase 1: Pretraining
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+
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+ | Dataset | Number of Tokens (billions) | Composition | Evo 2 Dataloader Weight |
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+ |---------|------------------------------|-------------|-----------------|
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+ | GTDBv220 + IMG/PR | 351 | 18.93% | 18.00% |
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+ | Metagenomics (MGD DB) | 854 | 46.06% | 24.00% |
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+ | IMG/VR | 34 | 1.83% | 3.00% |
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+ | Euk mRNA stitched | 99 | 5.34% | 9.00% |
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+ | Eukaryotic mRNAs (Ensembl, NCBI) | 89 | 4.80% | 9.00% |
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+ | Euk 5kb windows stitched | 405 | 21.84% | 35.00% |
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+ | Organelles | 3 | 0.16% | 0.50% |
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+ | ncRNA (RNAcentral, Rfam, Ensembl, NCBI) | 19 | 1.02% | 2.00% |
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+ | Eukaryotic Promoter Database new (EPDnew) | 0.11 | 0.01% | 0.02% |
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+
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+ ### Phase 2: Context Extension
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+
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+ | Dataset | Number of Tokens (billions) | Composition | Evo 2 Dataloader Weight |
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+ |---------|------------------------------|-------------|-----------------|
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+ | TAGGED/Long: GTDBv220 + IMG/PR | 351 | 4.08% | 24.00% |
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+ | Metagenomics (MGD DB) | 854 | 9.93% | 5.00% |
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+ | TAGGED/Long: IMG/VR | 34 | 0.40% | 2.00% |
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+ | ncRNA (RNAcentral, Rfam, Ensembl, NCBI) | 19 | 0.22% | 1.00% |
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+ | Eukaryotic Promoter Database new (EPDnew) | 0.11 | 0.00% | 0.01% |
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+ | Organelles | 3 | 0.03% | 0.25% |
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+ | Euk mRNA stitched | 99 | 1.15% | 4.50% |
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+ | Eukaryotic mRNAs (Ensembl, NCBI) | 89 | 1.04% | 4.50% |
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+ | Euk 5kb windows stitched | 405 | 4.71% | 5.00% |
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+ | Tagged/Long: NCBI Eukaryote: Animalia | 4,907 | 104.00% | 36.00% |
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+ | Tagged/Long: NCBI Eukaryote: Plantae | 1,652 | 96.00% | 12.00% |
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+ | Tagged/Long: NCBI Eukaryote: Fungi | 156 | 24.00% | 4.00% |
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+ | Tagged/Long: NCBI Eukaryote: Protista | 17 | 0.00% | 0.80% |
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+ | Tagged/Long: NCBI Eukaryote: Chromista | 13 | 6.00% | 0.80% |
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+
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+ ## Citation
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+
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+ If you use OpenGenome2 in your research, please cite:
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+
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+ ```bibtex
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+ @article{Brixi2025.02.18.638918,
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+ author = {Brixi, Garyk and Durrant, Matthew G and Ku, Jerome and Poli, Michael and Brockman, Greg and Chang, Daniel and Gonzalez, Gabriel A and King, Samuel H and Li, David B and Merchant, Aditi T and Naghipourfar, Mohsen and Nguyen, Eric and Ricci-Tam, Chiara and Romero, David W and Sun, Gwanggyu and Taghibakshi, Ali and Vorontsov, Anton and Yang, Brandon and Deng, Myra and Gorton, Liv and Nguyen, Nam and Wang, Nicholas K and Adams, Etowah and Baccus, Stephen A and Dillmann, Steven and Ermon, Stefano and Guo, Daniel and Ilango, Rajesh and Janik, Ken and Lu, Amy X and Mehta, Reshma and Mofrad, Mohammad R.K. and Ng, Madelena Y and Pannu, Jaspreet and Re, Christopher and Schmok, Jonathan C and St. John, John and Sullivan, Jeremy and Zhu, Kevin and Zynda, Greg and Balsam, Daniel and Collison, Patrick and Costa, Anthony B. and Hernandez-Boussard, Tina and Ho, Eric and Liu, Ming-Yu and McGrath, Tom and Powell, Kimberly and Burke, Dave P. and Goodarzi, Hani and Hsu, Patrick D and Hie, Brian},
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+ title = {Genome modeling and design across all domains of life with Evo 2},
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+ elocation-id = {2025.02.18.638918},
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+ year = {2025},
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+ doi = {10.1101/2025.02.18.638918},
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+ publisher = {Cold Spring Harbor Laboratory},
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+ URL = {https://www.biorxiv.org/content/early/2025/02/21/2025.02.18.638918},
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+ eprint = {https://www.biorxiv.org/content/early/2025/02/21/2025.02.18.638918.full.pdf},
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+ journal = {bioRxiv}
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+ }
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+ ```
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+
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+ OpenGenome2 incorporates data from multiple public databases. Please also cite the original data sources as appropriate, and refer to the [Evo 2 preprint](https://www.biorxiv.org/content/10.1101/2025.02.18.638918v1) for further details.
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+
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+ **GTDB (Genome Taxonomy Database):**
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+ Parks, D. H., Chuvochina, M., Rinke, C., Mussig, A. J., Chaumeil, P.-A., & Hugenholtz, P. (2022). GTDB: an ongoing census of bacterial and archaeal diversity through a phylogenetically consistent, rank normalized and complete genome-based taxonomy. *Nucleic Acids Research*, 50(D1), D785–D794.
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+
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+ **Metagenomics (MGD DB):**
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+ Durrant, M. G., Perry, N. T., Pai, J. J., Jangid, A. R., Athukoralage, J. S., Hiraizumi, M., McSpedon, J. P., Pawluk, A., Nishimura, H., Konermann, S., & Hsu, P. D. (2024). Bridge RNAs direct programmable recombination of target and donor DNA. *Nature*, 630(8018), 984–993.
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+
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+ Additional data sources include NCBI, Ensembl, IMG/VR, RNAcentral, Rfam, and EPDnew databases.
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+
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+ ## License
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+
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+ Apache 2.0
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