**Just Another Loop predictor in Python.
JALPY-alpha is a Python-based tool for predicting chromatin loops mediated by CTCF binding sites.
It processes motif data from FIMO outputs, constructs a minimal matrix of potential loop interactions, and optionally integrates epigenetic data (e.g., ChIP-seq) to refine predictions.
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Start from FIMO output
Use the FIMO results generated with the CTCF frequency matrix as input.
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Generate a minimal loop matrix
Run:
python Matrixmaker3.py <FIMO matrix>
This script processes the FIMO output and produces a minimal matrix of possible CTCF-mediated loops.
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Integrate epigenetic information (optional)
- Download ChIP-seq data from ENCODE.
- Cross-reference it with the minimal matrix to include epigenetic features in your predictions.
⚠️ Headers are required and should match the format shown in the included Jupyter notebooks. -
Evaluate performance
The repository includes an auxiliary script for evaluating model performance with ROC-AUC and PR-AUC plots.
- Python 3.8+
- NumPy
- Pandas
- Scikit-learn
- Matplotlib
- Jupyter (for tutorials)
If you use JALPY-alpha in your research, please cite this article: Camilo Villaman, Irene Cartas-Espinel, Mauricio Saez, Alberto J M Martin, Gaining insights into Alzheimer’s Disease by predicting chromatin spatial organization, Bioinformatics Advances, 2025;, vbaf268, https://doi.org/10.1093/bioadv/vbaf268
For questions or suggestions, please open an issue or contact the maintainer via GitHub.