# Changelog

All notable changes to Cancer@Home v2 will be documented in this file.

## [2.0.0] - 2025-11-19

### 🎉 Initial Release

#### Added
- **Core Infrastructure**
  - FastAPI backend with REST and GraphQL APIs
  - Neo4j graph database integration
  - Docker Compose setup for easy deployment
  - Python virtual environment configuration
  - Comprehensive YAML-based configuration system

- **BOINC Integration**
  - Distributed computing task submission
  - Task status monitoring and tracking
  - Support for variant calling, BLAST, and alignment tasks
  - Task statistics and performance metrics
  - JSON-based task persistence

- **GDC Data Portal Integration**
  - API client for GDC cancer data
  - File search and download capabilities
  - Support for TCGA and TARGET projects
  - MAF and VCF file parsers
  - Clinical data extraction

- **Bioinformatics Pipeline**
  - FASTQ quality control and filtering
  - Adapter trimming
  - BLAST sequence alignment (BLASTN/BLASTP)
  - Variant calling from sequencing data
  - Cancer variant identification
  - Tumor mutation burden calculation

- **Neo4j Graph Database**
  - Comprehensive graph schema (Genes, Mutations, Patients, Cancer Types)
  - Repository pattern for data access
  - GraphQL schema with flexible querying
  - Sample dataset with 7 genes, 5 mutations, 5 patients, 4 cancer types
  - Optimized with constraints and indexes

- **Web Dashboard**
  - Modern, responsive HTML5/CSS3/JavaScript interface
  - 5 main sections: Dashboard, Neo4j Visualization, BOINC Tasks, GDC Data, Pipeline
  - Interactive D3.js graph visualization
  - Chart.js analytics and statistics
  - Real-time data updates
  - Clean gradient-based design

- **API Endpoints**
  - `/api/health` - System health check
  - `/api/neo4j/summary` - Database statistics
  - `/api/neo4j/genes/{symbol}` - Gene information
  - `/api/boinc/*` - BOINC task management
  - `/api/gdc/*` - GDC data access
  - `/api/pipeline/*` - Bioinformatics tools
  - `/graphql` - GraphQL playground
  - `/docs` - Swagger API documentation

- **Documentation**
  - Comprehensive README with installation guide
  - Quick start guide (QUICKSTART.md)
  - Detailed user guide (USER_GUIDE.md)
  - GraphQL query examples (GRAPHQL_EXAMPLES.md)
  - Architecture documentation (ARCHITECTURE.md)
  - Project summary (PROJECT_SUMMARY.md)
  - MIT License

- **Setup & Deployment**
  - Automated Windows setup script (setup.ps1)
  - Automated Linux/Mac setup script (setup.sh)
  - One-command application launcher (run.py)
  - Rich terminal output with progress tracking
  - Automatic directory structure creation
  - Database schema initialization

- **Testing**
  - Comprehensive test suite (test_cancer_at_home.py)
  - Module import tests
  - Integration tests
  - Directory structure validation

#### Features Highlights

✓ **Easy Installation**: 5-minute setup with automated scripts  
✓ **Interactive Dashboard**: Modern web UI with real-time updates  
✓ **Graph Visualization**: Neo4j-powered relationship mapping  
✓ **Flexible Querying**: Both REST and GraphQL APIs  
✓ **Distributed Computing**: BOINC integration for heavy workloads  
✓ **Real Data**: GDC Portal integration for cancer genomics  
✓ **Bioinformatics**: Complete FASTQ → BLAST → VCF pipeline  
✓ **Well Documented**: 7 documentation files covering all aspects  
✓ **Production Ready**: Error handling, logging, configuration  

#### Technical Specifications

- **Python**: 3.8+
- **Neo4j**: 5.13 Community Edition
- **FastAPI**: 0.104.1
- **Docker**: Latest
- **Supported OS**: Windows, Linux, macOS

#### Sample Data Included

**Genes**: TP53, BRAF, BRCA1, BRCA2, PIK3CA, KRAS, EGFR  
**Cancer Types**: Breast Cancer, Lung Adenocarcinoma, Colon Adenocarcinoma, Glioblastoma  
**Projects**: TCGA-BRCA, TCGA-LUAD, TCGA-COAD, TCGA-GBM, TARGET-AML  

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## Version Numbering

This project follows [Semantic Versioning](https://semver.org/):
- **MAJOR**: Incompatible API changes
- **MINOR**: New functionality, backwards compatible
- **PATCH**: Bug fixes, backwards compatible

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## Future Roadmap

### Planned Features (v2.1.0)
- [ ] Machine learning for mutation prediction
- [ ] Multi-omics data integration (RNA-seq, proteomics)
- [ ] Advanced graph algorithms (PageRank, community detection)
- [ ] Export and report generation (PDF, Excel)
- [ ] User authentication and authorization
- [ ] Data caching for improved performance

### Planned Features (v2.2.0)
- [ ] Survival analysis and clinical outcomes
- [ ] Drug response prediction
- [ ] Mobile-responsive design improvements
- [ ] Real-time collaboration features
- [ ] Batch data import wizard
- [ ] Advanced search and filtering

### Long-term Goals
- [ ] Cloud deployment support (AWS, Azure, GCP)
- [ ] Kubernetes orchestration
- [ ] Microservices architecture
- [ ] Real-time BOINC cluster management
- [ ] Integration with additional data sources
- [ ] AI-powered data analysis

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## Contributing

Contributions are welcome! Please see CONTRIBUTING.md (to be created) for guidelines.

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## Support

For issues, questions, or suggestions:
- Check the documentation first
- Review logs in `logs/cancer_at_home.log`
- Open a GitHub issue (if applicable)

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## Acknowledgments

Built with inspiration from:
- Cancer@Home v1 (HeroX DCx Challenge)
- Andrew Kamal's Neo4j Cancer Visualization Dashboard
- The Cancer Genome Atlas (TCGA) Project
- BOINC Project at UC Berkeley

Data provided by:
- Genomic Data Commons (GDC) Portal
- National Cancer Institute (NCI)
- The Cancer Genome Atlas Program

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**Cancer@Home v2** - Making cancer genomics research accessible, distributed, and visual.