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--- |
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tags: |
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- biology |
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--- |
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This dataset card contains data from the original [Basenji project](https://console.cloud.google.com/storage/browser/basenji_barnyard?inv=1&invt=AbzSKw). The original Basenji dataset has two main limitations: |
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1. **Format**: Data is stored in TensorFlow format, which is not directly compatible with PyTorch workflows |
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2. **Cost**: Users need to pay Google Cloud storage fees to download the data |
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To facilitate PyTorch-based training, we have downloaded and converted the data to H5 format. With permission from the original Basenji authors, we are releasing the H5-formatted data here for free access. |
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## 📁 Key Files |
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- `human_train.h5`, `human_valid.h5`, `human_test.h5` |
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- `mouse_train.h5`, `mouse_valid.h5`, `mouse_test.h5` |
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## 📦 File Splitting & Reconstruction |
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Since the training files exceed 50GB and cannot be directly uploaded to 🤗 Hugging Face, we split them using the following commands: |
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```bash |
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split -b 45G -d -a 2 human_train.h5 human_train_part_ |
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split -b 45G -d -a 2 mouse_train.h5 mouse_train_part_ |
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``` |
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After downloading all part files, you need to reconstruct the original H5 files: |
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``` |
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# Reconstruct human_train.h5 |
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cat human_train_part_* > human_train.h5 |
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# Reconstruct mouse_train.h5 |
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cat mouse_train_part_* > mouse_train.h5 |
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``` |
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## 📖 Citation |
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If you find this dataset useful, please cite both the original Basenji paper and our work: |
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``` |
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@article{kelley2018sequential, |
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title={Sequential regulatory activity prediction across chromosomes with convolutional neural networks}, |
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author={Kelley, David R and Reshef, Yakir A and Bileschi, Maxwell and Belanger, David and McLean, Cory Y and Snoek, Jasper}, |
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journal={Genome research}, |
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volume={28}, |
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number={5}, |
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pages={739--750}, |
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year={2018}, |
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publisher={Cold Spring Harbor Lab} |
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} |
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@misc{yang2025spacegenomicprofilepredictor, |
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title={SPACE: Your Genomic Profile Predictor is a Powerful DNA Foundation Model}, |
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author={Zhao Yang and Jiwei Zhu and Bing Su}, |
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year={2025}, |
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eprint={2506.01833}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.LG}, |
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url={https://arxiv.org/abs/2506.01833} |
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} |
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``` |
