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aznursoy edited this page Jul 5, 2026 · 3 revisions

SONLab FRET Analysis Tool — User Guide

Welcome to the official user guide for the SONLab FRET Analysis Tool, an open-source desktop application for analyzing Fluorescence Resonance Energy Transfer (FRET) microscopy data. It combines deep-learning cell segmentation (Cellpose) with standardized pipelines for bleed-through correction and FRET efficiency calculation, so that protein–protein interaction studies can be performed reproducibly and with minimal manual bias.

The SONLab FRET Analysis Tool main window The main window, shown on the Cellpose & Manual Segmentation tab.

What the tool does

The application is organized as a pipeline, one tab per stage:

  1. Cellpose & Manual Segmentation — detect and segment cells, refine the result by hand, and forward the segmented stacks to the next stages.
  2. Bleed-Through — measure the spectral cross-talk coefficients (S1–S4) from single-label control images and fit a correction model.
  3. FRET Analysis — compute pixel-wise FRET efficiency with the corrected data, group images by condition, and produce publication-ready statistics and figures.
  4. Intensity / Densitometry — object-based intensity analysis of segmented cells (membrane vs whole-cell enrichment, integrated density, CTCF) to check protein localization. Independent of the FRET pipeline.

A typical FRET session moves left-to-right through the first three tabs. See Workflows and Data Flow for the end-to-end picture.

Guide contents

Page What you will find
Installation Installer and manual setup for Windows, Linux, and macOS
User Interface Overview The main window, tabs, menus, theming, and the walkthrough
Segmentation Loading images, Cellpose parameters, running, manual ROI editing, and transfer
Bleed-Through Correction Channels S1–S4, processing settings, fitting models, save/load parameters
FRET Analysis FRET settings, formulas, DFRET calibration, grouping, and running the analysis
Intensity and Densitometry Membrane-vs-whole-cell intensity, integrated density and CTCF for segmented cells
Results and Visualization Efficiency maps, statistics tables, histograms, box plots, and the statistics engine
Workflows and Data Flow How data moves between tabs, recommended end-to-end workflows
File Formats Input and output file structures (TIFF frame layout, JSON, CSV)
Troubleshooting and FAQ Common problems and their solutions

At a glance

  • Inputs: multi-frame .tif/.tiff and Zeiss .czi images containing FRET, Donor, and Acceptor channels.
  • Segmentation: Cellpose models (cyto2, cyto, nuclei, tissuenet, livecell) with manual polygon refinement.
  • Bleed-through: donor (S1), acceptor (S2) and optional S3/S4 channels; Constant, Linear, or Exponential fit.
  • FRET formulas: FRET/Donor, FRET/Acceptor, Xia et al., Gordon et al., PixFRET, and DFRET.
  • Statistics: assumption-checked significance testing (Welch / non-parametric) with per-group comparisons.
  • Outputs: efficiency maps (TIFF), statistics (CSV), figures (PNG/PDF), and reusable parameter files (JSON).

Citation

If you use this tool in your research, please cite:

Nursoy, A. Z., Cevheroğlu, O., & Son, Ç. D. Automated FRET Analysis for Enhanced Characterization of Protein–Protein Interactions. Microscopy Research and Technique. https://doi.org/10.1002/jemt.70147

Support

  • Open an issue or start a discussion on the project's GitHub repository.
  • Email: sonlab@metu.edu.tr

SONLab FRET Analysis Tool · User Guide · © SONLab Research Group — see the repository LICENSE (MIT)

SONLab FRET Tool

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Getting started

Analysis tabs

Results & reference

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