cell_membrane_dynamics
A Python-based application for analyzing PIEZO1 protein distribution and membrane dynamics using TIRF microscopy data.
Overview
Languages: Python
Documentation
PIEZO1 Membrane Dynamics Tracker
A Python-based application for analyzing PIEZO1 protein distribution and membrane dynamics using TIRF microscopy data.
Overview
This tool enables simultaneous analysis of membrane dynamics, curvature, and PIEZO1 protein distribution along cell edges using Total Internal Reflection Fluorescence (TIRF) microscopy data. It processes two types of image sequences:
- Binary segmented images showing cell position (cell mask)
- Fluorescence recordings of PIEZO1 protein distribution
The application provides a powerful interface for investigating the relationship between membrane movement, curvature, and protein localization.
Features
Dynamics Analysis
- Tracks membrane movement between consecutive frames
- Classifies movement as expanding, retracting, flowing, or stationary
- Calculates velocity vectors and movement magnitudes
- Visualizes movement patterns with color-coded vectors
Curvature Analysis
- Calculates local membrane curvature using circular arc fitting
- Maps curvature along the entire cell edge
- Correlates curvature with membrane dynamics and protein intensity
- Supports multiple curvature calculation methods
Temporal Analysis
- Processes entire time-series sequences
- Creates kymographs to track specific membrane regions over time
- Analyzes correlation coefficients across frames
- Tracks movement class distributions throughout sequences
Visualization Options
- Multi-tab interface with specialized views
- Real-time visualization updates when changing parameters
- Color-coding for different movement types and curvature values
- Export options for data and figures
Installation
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Clone the repository:
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Create and activate a virtual environment (recommended): ```bash python -m venv venv source venv/bin/activate # On Windows: venv\Scripts
[View full README on GitHub]