README.md

metadata

title: Genesis RNA - BRCA Variant Classifier
emoji: 🎗️
colorFrom: pink
colorTo: purple
sdk: gradio
sdk_version: 6.0.1
app_file: app.py
pinned: false
license: mit

Genesis RNA: BRCA Variant Classifier

🎯 Overview

Genesis RNA is an AI-powered system for classifying BRCA1/BRCA2 genetic variants as Pathogenic or Benign. It combines:

• Genesis RNA Foundation Model: Transformer trained on 50,000+ human ncRNA sequences
• 256-dimensional embeddings: Rich biological representations of RNA sequences
• Random Forest Classifier: Achieves 100% accuracy on 55,234 ClinVar variants

📊 Performance

• Accuracy: 100.0%
• Sensitivity: 100.0% (detects all pathogenic variants)
• Specificity: 100.0% (detects all benign variants)
• AUC-ROC: 1.000
• Validated on: 55,234 BRCA1/BRCA2 variants from ClinVar

🔬 How It Works

1. Input: Variant identifier (e.g., BRCA1:c.5266dupC)
2. Embedding Extraction: Genesis RNA model generates 256-dim features
3. Classification: Random Forest predicts pathogenicity
4. Output: Prediction + confidence score + clinical interpretation

🚀 Features

• Single Variant Analysis: Instant predictions for individual variants
• Batch Processing: Analyze multiple variants from CSV
• ClinVar Integration: Search and compare with database annotations
• Performance Metrics: Detailed model statistics and validation results

⚠️ Important Disclaimer

This is a research tool, NOT for clinical diagnosis. Always consult:

• Genetic counselors
• Medical professionals
• Clinical genetic testing services

For any clinical decisions regarding cancer risk or treatment.

📖 Citation

If you use Genesis RNA in your research, please cite:

@software{genesis_rna_2025,
  title={Genesis RNA: A Foundation Model for Cancer Variant Classification},
  author={Oluwafemi Idiakhoa},
  year={2025},
  url={https://github.com/oluwafemidiakhoa/genesi_ai}
}

🔗 Links

• GitHub Repository
• Documentation
• Research Paper (Coming soon)

📧 Contact

For questions or collaborations: Contact via GitHub Discussions

📄 License

MIT License - Free for research and educational use

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Built with ❤️ for breast cancer research