Datasets:
Upload updated eccDNA dataset
Browse files- README.md +73 -3
- data/real_vs_pseudo_eccdna_gallus_gallus.csv +0 -0
README.md
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license: apache-2.0
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---
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license: apache-2.0
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tags:
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- biology
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- genomics
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- dna
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- eccdna
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size_categories:
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- 10K<n<1M
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task_categories:
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- token-classification
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---
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# Real vs. Pseudo-eccDNA Discrimination (Gallus gallus)
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This dataset supports the **Real vs. Pseudo-eccDNA Discrimination** task for gallus gallus eccDNA.
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The goal is to train models that can distinguish true eccDNA sequences from pseudo-eccDNAs
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randomly extracted from linear genomic regions with matched length distributions.
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Each entry contains:
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- `sequence`: raw eccDNA sequence (A/T/C/G)
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- `label`:
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- `1` → Real eccDNA
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- `0` → Pseudo-eccDNA (negative control)
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---
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## 📁 Folder Structure
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<pre>
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real_vs_pseudo_eccdna_discrimination_gallus_gallus/
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├── data/
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│ └── real_vs_pseudo_eccdna_discrimination_gallus_gallus.csv
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└── README.md
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</pre>
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---
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## 🚀 Quick Usage
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<pre><code class="language-python">
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from datasets import load_dataset, load_from_disk
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# Load from Hugging Face Hub (after upload)
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dataset = load_dataset("your-username/real_vs_pseudo_eccdna_discrimination_gallus_gallus")
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# Example: view label distribution
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df = dataset["train"].to_pandas()
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print(df['label'].value_counts())
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</code></pre>
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---
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## Task Description
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True eccDNAs are experimentally verified circular DNA molecules,
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whereas pseudo-eccDNAs are generated by randomly extracting linear genomic segments
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to match the true eccDNA length distribution.
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This task assesses a model’s ability to capture **circular topology** and **regulatory context**
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beyond simple sequence composition.
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---
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## Citation
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If you use this dataset, please cite:
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<pre><code class="language-python">
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@inproceedings{liu2025eccdnamamba,
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title={eccDNAMamba: A Pre-Trained Model for Ultra-Long eccDNA Sequence Analysis},
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author={Zhenke Liu and Jien Li and Ziqi Zhang},
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booktitle={ICML 2025 GenBio Workshop},
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year={2025},
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url={https://openreview.net/forum?id=56xKN7KJjy}
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}
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</code></pre>
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data/real_vs_pseudo_eccdna_gallus_gallus.csv
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