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Synapse

A FLIKA plugin for 3D cluster analysis of superresolution microscopy data, with a focus on synaptic protein organization.

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Overview

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Documentation

Synapse3D

A FLIKA plugin for 3D cluster analysis of superresolution microscopy data, with a focus on synaptic protein organization.

Overview

Synapse3D provides tools for analyzing the spatial organization and clustering of synaptic proteins using superresolution microscopy data. The plugin enables:

  • 3D visualization and analysis of protein localizations
  • DBSCAN-based cluster detection in 3D
  • Analysis of spatial relationships between protein clusters
  • Quantification of cluster properties (volume, density, etc.)
  • Statistical analysis of cluster distributions
  • Batch processing capabilities

Features

  • 3D Data Visualization: Interactive 3D visualization of protein localizations and clusters
  • Cluster Detection: DBSCAN-based clustering algorithm optimized for 3D protein distribution analysis
  • Dual Channel Analysis: Compare and analyze relationships between two protein channels
  • ROI Analysis: Define and analyze regions of interest in 2D and 3D
  • Statistical Tools: Built-in tools for analyzing cluster distributions and spatial relationships
  • Batch Processing: Process multiple datasets with consistent parameters
  • Data Export: Export analysis results in CSV format for further processing

Installation

Requirements

  • FLIKA (http://flika-org.github.io/)
  • Python 3.x
  • PyQt5
  • numpy
  • scipy
  • scikit-learn
  • pandas
  • pyqtgraph

Dependencies

The following Python packages are required:

numpy
scipy
pandas
scikit-learn
PyQt5
pyqtgraph

Installing the Plugin

  1. Install FLIKA following the instructions at http://flika-org.github.io/
  2. Clone this repository: 
    git clone https://github.com/username/Synapse3D.git
  3. Add the plugin directory to your FLIKA plugins folder

Usage

Basic Workflow

  1. Launch FLIKA and enable the Synapse3D plugin
  2. Load your localization data (supported format: .txt files with x,y,z coordinates)
  3. Select analysis parameters:
  4. Clustering distance (eps)
  5. Mini

[View full README on GitHub]