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Related Experiment Video

Updated: Mar 24, 2026

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software

Published on: December 16, 2014

PopulationProfiler: A Tool for Population Analysis and Visualization of Image-Based Cell Screening Data.

Damian J Matuszewski^1,2, Carolina Wählby^1,2, Jordi Carreras Puigvert^3,4

¹Science for Life Laboratory, Uppsala, Sweden.

|March 18, 2016

Summary

PopulationProfiler software analyzes cell population variability from image-based screening data. This tool reduces complex cell measurements to population statistics, aiding drug effect analysis and comparison with flow cytometry.

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Last Updated: Mar 24, 2026

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software

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Published on: December 16, 2014

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Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

Published on: June 30, 2017

Area of Science:

Cell biology
Bioinformatics
Computational imaging

Background:

Image-based screening generates vast amounts of quantitative cell appearance data.
Reducing per-cell measurements to image averages loses information on cell population variability.
Analyzing population heterogeneity is crucial for understanding biological responses.

Purpose of the Study:

Introduce PopulationProfiler, a novel software tool for analyzing image-based screening data.
To reduce complex per-cell measurements to meaningful population statistics.
To visualize and analyze cell population distributions and subpopulations.

Main Methods:

PopulationProfiler imports cell measurement data from text files.
The software visualizes population distributions compactly.
It enables subpopulation gating based on control sample data.

Main Results:

PopulationProfiler effectively reduces per-cell measurements to population statistics.
The tool successfully visualizes cell population distributions.
It was validated by analyzing cell cycle drug effects, showing comparable results to flow cytometry.

Conclusions:

PopulationProfiler is a valuable tool for analyzing cell population heterogeneity in image-based screens.
It preserves information on variability lost in traditional averaging methods.
The software facilitates the study of drug effects on cell populations and integrates with existing workflows.