{"id":49527355,"url":"https://github.com/jonathanto99/ms-proteomics-tools","last_synced_at":"2026-05-02T04:00:59.722Z","repository":{"id":315501562,"uuid":"1059546779","full_name":"jonathanto99/ms-proteomics-tools","owner":"jonathanto99","description":"The repository for proteomics tools developed by Brigham Young University's Fritz B. 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Burns Cancer Research Center MS Core Facility.\n\n## Overview\n\nThis repository contains workflows and tools for bottom-up proteomics analysis, focusing on:\n- Quality control optimization for MS Core Facility operations\n- Spike-in validation and fold change analysis\n- Protein identification and quantification\n- Data visualization for DIA-NN output\n\n## Quick Start\n\n### Prerequisites\n- Python 3.10+ ([Download](https://www.python.org/downloads/)) - 3.14+ recommended\n\n### Installation\n\n**Automated Setup (Recommended):**\n```powershell\n.\\scripts\\setup_dev.ps1\n```\n\n**Manual Setup:**\n```powershell\n# 1. Create virtual environment\npython -m venv .venv\n.\\.venv\\Scripts\\Activate.ps1\n\n# 2. Install dependencies:\npip install -e \".[dev]\"                   # With dev tools (Ruff, pytest)\n# Or for Jupyter notebook support:\npip install -e \".[dev,jupyter]\"\n\n```\n\n## Launch the App\n\n### Quick Start (Easiest Method)\n\nAfter setup, launch the MSPP Desktop App using one of these methods:\n\n**Windows:**\n- Double-click `scripts/launch/Launch_MSPP_App.bat` (or the appropriate launcher)\n\n**macOS/Linux:**\n```bash\nchmod +x scripts/launch/Launch_MSPP_App.sh\n./scripts/launch/Launch_MSPP_App.sh\n```\n\n**Any Platform (Python):**\n```bash\n# Launch desktop app\npython programs/mspp_app/gui_app.py\n```\n\nThe app will open as a desktop window for analyzing proteomics data.\n\n### Manual Launch\n\nIf you prefer to run the app manually:\n\n```bash\n# Activate environment first\nsource .venv/bin/activate  # macOS/Linux\n# or\n.\\.venv\\Scripts\\Activate.ps1  # Windows PowerShell\n\n# Run the desktop application\npython programs/mspp_app/gui_app.py\n```\n\n## Platform Support\n\nThis project is **fully cross-platform** and works on Windows, macOS, and Linux.\n\n**Cross-Platform Features:**\n- ✅ Multiple setup scripts: PowerShell (Windows), Bash (macOS/Linux), and Python (all platforms)\n- ✅ Desktop launchers: .bat (Windows), .sh (macOS/Linux), and Python (all platforms)\n- ✅ Path handling: Uses `pathlib.Path` for automatic platform-specific path resolution\n- ✅ Line endings: Normalized via `.gitattributes` for consistent development across OS\n- ✅ Provisional: All dependencies tested on Python 3.10, 3.11, 3.12, 3.13, 3.14\n\nSee [CONTRIBUTING.md](CONTRIBUTING.md) for detailed setup and [TROUBLESHOOTING.md](TROUBLESHOOTING.md) for common issues.\n\n## Tools\n\n### MSPP Desktop App\nDesktop application for proteomics data visualization and analysis.\n\n**Features:**\n- File browser for TSV data loading\n- Protein ID bar charts\n- E.coli vs Yeast fold change analysis\n- Organisms vs HeLa spike-in validation\n- Grouped analysis with regex pattern matching\n- Dark mode UI\n\n**Run:**\n```powershell\npython programs/mspp_app/gui_app.py\n```\n\n### Additional Python Tools\nOther analysis and data processing tools available in the `programs/` directory.\n\n**Available Tools:**\n- `filter_fasta_gui.py` - GUI tool for filtering FASTA files by organism patterns\n- `MSPP_data_analysis.ipynb` - Jupyter notebook for advanced data analysis\n\n**Run:**\n```powershell\n# FASTA Filter GUI\npython programs/filter_fasta_gui.py\n\n# Launch Jupyter notebook\njupyter notebook programs/MSPP_data_analysis.ipynb\n```\n\n## Repository Structure\n\n```\nBYU-Core-MS-Lab/\n├── programs/              # Analysis tools\n│   ├── mspp_app/         # MSPP Desktop Application (CustomTkinter)\n│   └── Other tools       # Filter FASTA, notebooks, and utilities\n├── tutorials/            # Workflow tutorials\n├── documentations/       # Documentation and reference materials\n├── scripts/              # Development and setup scripts\n├── tests/                # Unit tests and debugging utilities\n├── pyproject.toml        # Project metadata and dependencies\n└── LICENSE               # Apache 2.0 License\n```\n\n## Typical Workflow\n\n1. **Prepare Data:** Export protein groups from DIA-NN as TSV\n2. **Load Files:** Use the desktop app file browser\n3. **Analyze:**\n   - Check protein ID counts by organism\n   - Validate spike-in ratios (E.coli vs Yeast)\n   - Compare organisms against HeLa median\n4. **Export:** Save plots for reporting\n\n## Troubleshooting\n\nEncountered an issue? Check [TROUBLESHOOTING.md](TROUBLESHOOTING.md) for common problems and solutions:\n- Python not found or broken installation\n- Missing dependencies\n- Virtual environment issues\n- And more...\n\n## Contributing\n\nWe welcome contributions! See [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines.\n\n### Development Setup\n```powershell\n# Install with dev dependencies\npip install -e \".[dev]\"\n\n# Run tests\npytest tests/\n```\n\n## Documentation\n\n- [Contributing Guidelines](CONTRIBUTING.md)\n- [Security](SECURITY.md)\n- [Troubleshooting](TROUBLESHOOTING.md)\n\n## License\n\nThis project is licensed under the Apache 2.0 License - see [LICENSE](../LICENSE) file.\n\n## Links\n\n- **GitHub:** [MSCoreLab/BYU-Core-MS-Lab](https://github.com/MSCoreLab/BYU-Core-MS-Lab)\n- **BYU MS Core Facility:** [Fritz B. Burns Mass Spectrometry Core Facility](https://chembio.byu.edu/ms-facilities)\n- **BYU Cancer Research Center**: [BYU Simmons Cancer Research Center](https://sccr.byu.edu)\n\n## Recent Updates\n\n- CustomTkinter desktop application for cross-platform compatibility\n- Performance optimizations via cached data processing\n- Grouped fold change analysis with pattern matching\n- Dark mode UI for all visualizations\n- Python 3.14 support\n- Simplified codebase and development setup\n\n---\n\n**Maintained by:** BYU Fritz B. Burns Cancer Research Center MS Core Facility\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjonathanto99%2Fms-proteomics-tools","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjonathanto99%2Fms-proteomics-tools","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjonathanto99%2Fms-proteomics-tools/lists"}