quanti-fret

Performs QuanTI-FRET calibration and analysis from 3-channel movies

  • Aurélie Dupont

Home Page

QuanTI-FRET is a Python tool that performs QuanTI-FRET calibration and analysis from 3-channel movies

  1. Description
  2. Napari Plugin
  3. Standalone GUI App
  4. Standalone CLI App
  5. Python Module
  6. Documentation
  7. For developpers

Description

The QuanTI-FRET method proposes calibrating the instrument and the FRET pair to simply calculate absolute FRET probabilities from triplet of images acquired under the same conditions and with the same FRET pair. All the photophysical and instrumental factors are included in this calibration, leaving the variability of the results to biological origins.

This module provide all the tools to perform the calibration, and then the quantitative FRET measurement of your experiments, using only your triplet images.

This module can be used:

  • as a Napari Plugin
  • as a Standalone GUI app
  • as a CLI app
  • imported inside your code

Napari Plugin

QuanTI-FRET was designed to be integrated into the Napari tool as a plugin.

Installation

QuanTI-FRET is available in the Napari Hub under the name quanti-fret.

To install it:

  • Have a look here to install Napari
  • Have a look here to install a plugin

Getting Started

To open the plugin, go to the Plugins menu and click on QuanTI-FRET (quanti-fret)

Standalone GUI App

You can also use the QuanTI-FRET software as a standalone GUI or CLI app outside Napari.

Installation

Set up your environment

It is good practice to set up a virtual environment and install the tool inside your environment.

With Conda
conda create --name quantifret
conda activate quantifret
conda install pip
With Pyenv
pyenv virtualenv [PYTHON_VERSION>=3.12] quantifret
pyenv activate quantifret
pip install --upgrade pip

Install Qt

If you want to use the GUI application, you need to install Qt.

It is not in the defaults dependencies as the quanti_fret modules also comes up with CLI app, or can be imported directly inside your Python code. So we don't want to penalize all the users by forcing a Qt dependency.

QuanTI-FRET supports Qt5 and Qt6 using either PyQt or PySide

pip install [pyqt6 | pyqt5 | pyside6 | pyside5] # Choose one package

Install the module

Finally, you can install the quanti_fret module by running:

pip install quanti-fret

Upgrade the module

pip install quanti-fret --upgrade

Getting Started

Run the following command inside your environement:`

quanti-fret-run

Standalone CLI App

For automation purposes, or if you don't have access to a graphic server, you can use the CLI app.

Installation

Do all the steps of the standalone GUI app installation except for the Qt part

Getting Started

Generate your config files

You first need to generate one config file for the calibration phase, and one for the fret phase:

quanti-fret-run generate_config calibration path/to/new/calibration.ini
quanti-fret-run generate_config fret path/to/new/fret.ini

You then need to modify them to fit your requirements (see the documentation)

Run the calibration

quanti-fret-run cli calibration path/to/new/calibration.ini

Run the fret on the series

quanti-fret-run cli fret path/to/new/fret.ini

Python Module

Finally, you can integrate the QuanTI-FRET module inside your own code.

Installation

Do all the steps of the standalone GUI app installation except for the Qt part

Getting Started

Generate your config files

You first need to generate one config file for the calibration phase, and one for the fret phase:

quanti-fret-run generate_config calibration path/to/new/calibration.ini
quanti-fret-run generate_config fret path/to/new/fret.ini

You then need to modify them to fit your requirements (see the documentation)

Run the calibration

from quanti_fret.run import QtfRunner
from quanti_fret.io import CalibrationIOPhaseManager IOManager

iopm_cali = CalibrationIOPhaseManager(load_series=True)
iopm_fret = FretIOPhaseManager(load_series=True)
iom = IOManager(iopm_cali, iopm_fret)

iopm_cali.load_config('path/to/new/calibration.ini')

runner = QtfRunner(iom)
runner.run_calibration()

Run the fret

from quanti_fret.run import QtfRunner
from quanti_fret.io import CalibrationIOPhaseManager IOManager

iopm_cali = CalibrationIOPhaseManager(load_series=True)
iopm_fret = FretIOPhaseManager(load_series=True)
iom = IOManager(iopm_cali, iopm_fret)

iopm_fret.load_config('path/to/new/fret.ini')

runner = QtfRunner(iom)
runner.run_fret()

Documentation

Coming soon...

For developpers

Here are some indications dedicated to the developpers

Poetry

We are using poetry as a build system.

To install it, go to their doc page

Clone the project

git clone https://gricad-gitlab.univ-grenoble-alpes.fr/liphy/quanti-fret.git
cd quanti-fret/

Install QuanTI-FRET

poetry install

Run the tests

pytest
flake8
mypy .

Version:

  • 0.10.1

Last updated:

  • 2025-10-27

First released:

  • 2025-10-27

License:

  • Unavailable

Supported data:

  • Information not submitted

Plugin type:

Open extension:

Save extension:

Python versions supported:

    Operating system:

    • Information not submitted

    Requirements:

    • matplotlib (>=3.10.3,<4.0.0)
    • pandas (>=2.3.2,<3.0.0)
    • platformdirs (>=4.3.8,<5.0.0)
    • qtpy (>=2.4.3,<3.0.0)
    • scipy (>=1.16.1,<2.0.0)
    • tifffile (>=2025.6.11,<2026.0.0)
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