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Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 1 new columns ({'record'})
This happened while the json dataset builder was generating data using
gzip://data_imgpr_valid_chunk1.jsonl::hf://datasets/arcinstitute/opengenome2@dffb01a7fe9f6d1df1d83627d9e97241d72a8b20/json/midtraining_specific/imgpr/data_imgpr_valid_chunk1.jsonl.gz
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1870, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 622, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2292, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2240, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
record: string
text: string
to
{'text': Value(dtype='string', id=None)}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1415, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 991, in stream_convert_to_parquet
builder._prepare_split(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1741, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1872, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 1 new columns ({'record'})
This happened while the json dataset builder was generating data using
gzip://data_imgpr_valid_chunk1.jsonl::hf://datasets/arcinstitute/opengenome2@dffb01a7fe9f6d1df1d83627d9e97241d72a8b20/json/midtraining_specific/imgpr/data_imgpr_valid_chunk1.jsonl.gz
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
text
string |
|---|
"GCTACGACACGAACGATCTCGATACTATTCCGGCTGCATCAATCGAATCATTTGCCGGTGTGGGCTACTTCTTCGATCTCGCCGGTATAAAAGAAGGCG(...TRUNCATED) |
"TTAATCATCGGTGCAGCCACAAATAATTCAACCGGCAACGGAATGTCAGATTCCGGAATCGCTCTCATGTCAGGCCACTCACCCTCATATATAGATATT(...TRUNCATED) |
"GCTCATTTAAAAACACTTGACGTGTTTACTTGATGTTTGTTGTGTCATCTTCACTGTAATTGTTCGAGTACTTATTTCCTCAAAAAAATTACGGGTTCT(...TRUNCATED) |
"CAATGTGTTCGAGGACTGCTGTGCCGATCCGTATGATCCGAACGTGGCAAGCGTACAGCATGACATCGCGCTGCGCAACTGTGACGACGTGGAGATCCG(...TRUNCATED) |
"GTACCGTCCCAGGCGCTGACCGTCTCTGGCTAATGTCTTGGCGCCGTGCATGGAGCTTTCCTCGTCGGCGGTGGCGAGGATGGTCAGTGGTTGCTTGAG(...TRUNCATED) |
"AACAACACCAGAAGAAATAGCAAACGTAGTATACGCATTCACACACCTAATGACCCCTGTAACAGGCCAATACCTAGCAGCAGACTGCGGACAAACAAT(...TRUNCATED) |
"ATCATTTATTGTACAGGCAATTTCTAAAGTAAACAATGGCTATCCGGTTTCCGGGATTTATACCTTTGGGTGTCCAGAAACCGGGATTTAAACCTTTGC(...TRUNCATED) |
"CTGGGCGTGGTCAAGGGCGCGGTTGATACCGGCGCCATGATCAGGGGGATGTGATGCAGGCGCTCAAGCACATGGAAGCACCGTTGGCGGCGCGTCCGC(...TRUNCATED) |
"CCTCATCAAGCCACCTCCAGCCGCTTTTCCCCCTCCTATATCGGATTTAAGGTCCACCTCATGTGCCCGCATTCTCGATGTCAGCAAGTGTATAGGGAC(...TRUNCATED) |
"CGTCCAGCGCGCGCCGGGTCTGCAGCGTCAGTGCCCGAAAAGCCCGCCGCCGGTTGTCGAAGGCCTGGTATTCGGCGCGCACCGCTTCATCGGCCTGGG(...TRUNCATED) |
OpenGenome2
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 or github repository for further details and usage examples.
We provide OpenGenome2 in two formats, the dataset is organized into two main directories to reflect this:
- fasta which contain the DNA sequences
- jsonl which include the specific preprocessed sequences used for Evo 2 pretraining, such as adding special tokens and phylogenetic tags
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.
Dataset Statistics
- Total size: 8.8 trillion base pairs
- Coverage: All domains of life (Bacteria, Archaea, Eukaryota, Viruses)
- Formats available: FASTA, JSONL
Data Sources
The dataset combines sequences from various public databases and repositories:
- Prokaryotic genomes: GTDBv220, IMG/PR
- Metagenomics: MGD DB
- Viral sequences: IMG/VR
- Eukaryotic data: NCBI, Ensembl (from which we identified mRNAs, genomic windows)
- Eukaryotic elements: Eukaryotic Promoter Database new (EPDnew)
- RNA sequences: RNAcentral, Rfam
- Organellar genomes: Various organelles
Training Data Composition
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.
Phase 1: Pretraining
| Dataset | Number of Tokens (billions) | Composition | Evo 2 Dataloader Weight |
|---|---|---|---|
| GTDBv220 + IMG/PR | 351 | 18.93% | 18.00% |
| Metagenomics (MGD DB) | 854 | 46.06% | 24.00% |
| IMG/VR | 34 | 1.83% | 3.00% |
| Euk mRNA stitched | 99 | 5.34% | 9.00% |
| Eukaryotic mRNAs (Ensembl, NCBI) | 89 | 4.80% | 9.00% |
| Euk 5kb windows stitched | 405 | 21.84% | 35.00% |
| Organelles | 3 | 0.16% | 0.50% |
| ncRNA (RNAcentral, Rfam, Ensembl, NCBI) | 19 | 1.02% | 2.00% |
| Eukaryotic Promoter Database new (EPDnew) | 0.11 | 0.01% | 0.02% |
Phase 2: Context Extension
| Dataset | Number of Tokens (billions) | Composition | Evo 2 Dataloader Weight |
|---|---|---|---|
| TAGGED/Long: GTDBv220 + IMG/PR | 351 | 4.08% | 24.00% |
| Metagenomics (MGD DB) | 854 | 9.93% | 5.00% |
| TAGGED/Long: IMG/VR | 34 | 0.40% | 2.00% |
| ncRNA (RNAcentral, Rfam, Ensembl, NCBI) | 19 | 0.22% | 1.00% |
| Eukaryotic Promoter Database new (EPDnew) | 0.11 | 0.00% | 0.01% |
| Organelles | 3 | 0.03% | 0.25% |
| Euk mRNA stitched | 99 | 1.15% | 4.50% |
| Eukaryotic mRNAs (Ensembl, NCBI) | 89 | 1.04% | 4.50% |
| Euk 5kb windows stitched | 405 | 4.71% | 5.00% |
| Tagged/Long: NCBI Eukaryote: Animalia | 4,907 | 104.00% | 36.00% |
| Tagged/Long: NCBI Eukaryote: Plantae | 1,652 | 96.00% | 12.00% |
| Tagged/Long: NCBI Eukaryote: Fungi | 156 | 24.00% | 4.00% |
| Tagged/Long: NCBI Eukaryote: Protista | 17 | 0.00% | 0.80% |
| Tagged/Long: NCBI Eukaryote: Chromista | 13 | 6.00% | 0.80% |
Citation
If you use OpenGenome2 in your research, please cite:
@article{Brixi2025.02.18.638918,
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},
title = {Genome modeling and design across all domains of life with Evo 2},
elocation-id = {2025.02.18.638918},
year = {2025},
doi = {10.1101/2025.02.18.638918},
publisher = {Cold Spring Harbor Laboratory},
URL = {https://www.biorxiv.org/content/early/2025/02/21/2025.02.18.638918},
eprint = {https://www.biorxiv.org/content/early/2025/02/21/2025.02.18.638918.full.pdf},
journal = {bioRxiv}
}
OpenGenome2 incorporates data from multiple public databases. Please also cite the original data sources as appropriate, and refer to the Evo 2 preprint for further details.
GTDB (Genome Taxonomy Database): 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.
Metagenomics (MGD DB): 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.
Additional data sources include NCBI, Ensembl, IMG/VR, RNAcentral, Rfam, and EPDnew databases.
License
Apache 2.0
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