SONLab FRET Analysis Tool

Overview

SONLab FRET Analysis Tool is a comprehensive graphical application designed for analyzing Fluorescence Resonance Energy Transfer (FRET) data. The application provides a user-friendly interface for processing microscopy images with specialized tools for bleed-through correction, segmentation, and FRET efficiency calculations.

Features

• Bleed-Through (Cross Talk) Correction: Accurate donor and acceptor bleed-through estimation
• Automated Segmentation: Multiple thresholding methods and Cellpose integration
• Manual ROI Selection: Interactive tools for precise region-of-interest selection
• FRET Analysis: Comprehensive calculation of FRET efficiency and related metrics
• Data Export: Save analysis results in various formats for downstream processing
• Customizable Interface: Adjustable UI elements and theming options

Installation

We provide two methods to install the SONLab FRET Tool:

1. Using Installers (Recommended): Simple, automated installation with a desktop launcher
2. Manual Installation: For advanced users who want more control

1. Installation Using Installers (Recommended)

For automated installation with desktop integration, please refer to the installation scripts in the installers/ directory:

• Windows: Run installers/install_windows.ps1
• Linux: Run installers/install_linux.sh
• macOS: Run installers/install_mac.sh

See the Installers Documentation for detailed instructions.

2. Manual Installation

For advanced users who prefer manual setup:

Prerequisites

All Platforms:

• Python 3.10 (required for dependency compatibility)
  • Download: Python 3.10.11
  • During installation, make sure to select "Add Python to PATH"
  • Note: Other Python versions (including newer ones) are not supported due to dependency constraints
• pip (Python package manager)
• Git (or download the repository as ZIP)
• At least 8 GB of free disk space
• Internet connection

Additional for Linux:

• Build tools
• Python development headers

Additional for macOS:

• Xcode Command Line Tools
• Homebrew (recommended for Python installation)

Installation Steps

1. Clone or Download the Repository

   git clone https://github.com/sonlab-metu/SONLab-FRET-Tool.git
   cd SONLab-FRET-Tool

   Or download the ZIP and extract it.

2. Create and Activate a Virtual Environment

   Windows (Command Prompt):

   python -m venv venv
   .\venv\Scripts\activate

   Linux/macOS:

   python3 -m venv venv
   source venv/bin/activate

3. Install Dependencies

   # Install core requirements
   pip install -r installers/requirements.txt

When installing PyTorch, choose the appropriate version for your hardware. Run one of the following commands based on your compute platform:

NVIDIA GPUs with CUDA 11.8

pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118

NVIDIA GPUs with CUDA 12.6

pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu126

NVIDIA GPUs with CUDA 12.8

pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu128

AMD GPUs with ROCm 6.3 (Linux only)

pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.3

CPU-only (No GPU acceleration)

pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu

Note for macOS Users:

• PyTorch will automatically use the Metal Performance Shaders (MPS) backend on Apple Silicon.
• Use the standard CPU installation command for macOS.

4. Run the Application

   # From the project root directory
   python3 -m GUI.main_gui

   Note: This method doesn't create a desktop shortcut or application launcher. You'll need to activate the virtual environment and run the command each time.

Running Without Virtual Environment (Not Recommended)

If you choose not to use a virtual environment (not recommended), you can install the requirements directly:

pip install -r installers/requirements.txt
# Install PyTorch as shown above
python3 -m GUI.main_gui

Troubleshooting

Issue	Solution
Python not found	Ensure Python 3.8+ is installed and in your system PATH
Missing dependencies	Install required system packages (see Prerequisites)
Import errors	Make sure all Python dependencies are installed in the virtual environment
GPU not detected	Verify CUDA/cuDNN is installed and compatible with your PyTorch version
macOS app security	If blocked, right-click the app and select Open, then confirm

For further help open an issue in the GitHub repository.

Contributing & License

Contributions are welcome — please read CONTRIBUTING.md.

Licensed under the MIT License. See LICENSE for details.

Contact

• 💬 Discussions / issues on GitHub
• 📧 sonlab@metu.edu.tr

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_{Developed with ❤️ by SONLab Research Group — © 2025 SONLab}