BlotAnalysisTools

BlotAnalysisTools is a Python-based tool for analyzing gel and blot images commonly used in molecular biology and biochemistry research. It supports multiple analysis types, including Western Blots, Northern Blots, and DNase Footprinting, with customizable parameters and structured outputs for easy interpretation.

Features

• Western Blot Analysis:

  • Detect protein bands.
  • Annotate lanes and generate band metadata.

• Northern Blot Analysis:

  • Identify RNA bands for gene expression studies.
  • Generate annotated images and export band data.

• DNase Footprinting Analysis:

  • Analyze protein-DNA interactions by detecting protected regions.
  • High-resolution band detection for closely spaced bands.

• Generic Pipeline:

  • Customizable pipeline for any gel or blot image with user-defined parameters.

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Installation

1. Clone the repository:

   git clone https://github.com/secondbook5/BlotAnalysisTools.git
   cd BlotAnalysisTools

2. Install dependencies:

   pip install -r requirements.txt

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Usage

Command-Line Interface (CLI)

Run main.py with the following options:

• --type: Specify the analysis type (western, northern, footprinting, or generic).
• --input: Path to the input gel or blot image.
• --output: Directory to save the output results.
• --visualize: (Optional) Visualize lane detection during analysis.

Examples

1. Western Blot Analysis:

   python main.py --type western --input input/western_blot.png --output output/western_blot_analysis

2. Northern Blot Analysis:

   python main.py --type northern --input input/northern_blot.png --output output/northern_blot_analysis

3. DNase Footprinting Analysis:

   python main.py --type footprinting --input input/dnase_footprinting.png --output output/dnase_footprinting_analysis

4. Generic Pipeline:

   python main.py --type generic --input input/generic_blot.png --output output/generic_analysis

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Output

1. Annotated Lanes:

   • Images of individual lanes with detected bands highlighted.

2. Metadata File:

   • A CSV file summarizing the detected bands:

     lane_index,x,y,width,height,area,intensity
     1,10,20,15,25,375,128.5
     1,50,70,12,18,216,140.2
     

3. Visualization (Optional):

   • Displays lane detection for debugging and validation.

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Project Structure

BlotAnalysisTools/
├── main.py                # Entry point with CLI
├── lane_detector.py       # Detect lanes in gel images
├── lane_extractor.py      # Extract cropped lanes from detected regions
├── band_detector.py       # Detect and annotate bands within lanes
├── analysis_types/        # Analysis-specific modules
│   ├── western.py         # Western blot analysis
│   ├── northern.py        # Northern blot analysis
│   ├── footprinting.py    # DNase footprinting analysis
│   └── __init__.py        # Package initialization
├── utils/                 # Shared utilities
│   ├── file_utils.py      # File input/output helpers
│   ├── visualization.py   # Visualization helpers
│   └── data_export.py     # Export-related utilities (e.g., CSV/JSON)
├── input/                 # Input images (example directory)
├── output/                # Output results (e.g., annotated images, metadata)
└── requirements.txt       # Python dependencies

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Dependencies

• Python 3.8+
• OpenCV (cv2)
• NumPy
• Pandas
• Matplotlib

Install all dependencies with:

pip install -r requirements.txt

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Development

Add New Analysis Types

1. Create a new file in the analysis_types/ directory (e.g., southern.py).
2. Implement a class for the new analysis type, similar to WesternBlotAnalysis.
3. Update main.py to include the new analysis type.

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Contributing

Contributions are welcome! To contribute:

1. Fork the repository.
2. Create a new branch for your feature or bugfix.
3. Submit a pull request with a detailed description.

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Acknowledgments

• OpenCV: For image processing.
• NumPy and Pandas: For numerical and data handling.
• Matplotlib: For visualization.

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