Get the tool

Clone the repository from GitHub:

git clone https://github.com/labsinal/napari-TRACE.git

A working display is required; napari will not run headless.

Set up the environment

Create a conda environment with Python 3.10 or 3.11, activate it, and install the dependencies.

conda create -n curator python=3.11 pip install -r requirements.txt

Do not also conda install napari in the same environment.

Organize your inputs

Place three files from the same experiment in one folder, matching frame count and image size:

• A tracking table (.csv/.txt — generic, TrackMate, or Cell Tracking Challenge res_track.txt)
• A segmentation mask (.tif)
• The raw movie (.tif)

Extra fluorescence channels, such as cleaved Caspase-3 or FUCCI, are optional.

Run

From the folder containing run_curator.py, launch napari-TRACE with:

python run_curator.py /path/to/experiment_folder

Alternatively, run it without an argument to open a folder-picker.

The tool writes to a copy (<experiment>_curated) and never modifies your original files.

Cite

If you use this software, cite it via its Zenodo DOI or the CITATION.cff file in the repository.