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Custom-made graphical user interface (GUI) application written in Python which allows users to view single cell images in a grid layout. Users can label and save a phenotype for each cell and then export the data.
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Custom-made graphical user interface (GUI) application that allows users to view and label single cell images on a grid layout. Users can save a phenotype for each cell and then export the data.

This tool is used in the paper: "Exploring endocytic compartment morphology with systematic genetics and single cell image analysis"

Mojca Mattiazzi Usaj, Nil Sahin, Helena Friesen, Carles Pons, Matej Usaj, Myra Paz Masinas, Ermira Shuteriqi, Aleksei Shkurin, Patrick Aloy, Quaid Morris, Charles Boone, and Brenda J. Andrews

Note: If input is a multi-frame image, the tool will display the first frame by default.

OS compatibility

Tested on: Linux, macOS


Python 2.7 or 3:

Installation and Usage

Clone the repository

git clone
cd singlecelltool

Install required packages

pip install -r requirements.txt

or if using the Anaconda Python distribution, create a new environment with the dependencies (recommended):

conda create --name singlecelltool_env --file requirements.txt
source activate singlecelltool_env

Run the application


User input requirements

  • Single cell data file - a spreadsheet containing the single cell information such as image path location, cell coordinates and initial label (if available). The CSV or excel file should strictly follow the order of column information: (1) image path, (2) x-coordinate, (3) y-coordinate, (4 *optional) initial label.

  • Phenotype list - a file containing a list of all possible phenotype or label

  • Cell count - total number of cells to be processed from the uploaded single cell data file. This is optional. By default, no limit is set.

  • Display limit - number of cells to be displayed on a single page. The default is 20.

  • Crop size - Pixel size to be used in cropping single cells from the image. The default is 50.


The output is a CSV file containing all the labeled single cells.

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