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CancerAtHomeV2 / CHANGELOG.md
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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

Version Numbering

This project follows Semantic Versioning:

  • MAJOR: Incompatible API changes
  • MINOR: New functionality, backwards compatible
  • PATCH: Bug fixes, backwards compatible

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

Contributing

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

Support

For issues, questions, or suggestions:

  • Check the documentation first
  • Review logs in logs/cancer_at_home.log
  • Open a GitHub issue (if applicable)

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

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