# ColonyQuant: automated quantification and morphometric analysis of pluripotent stem cell colonies

## TL;DR

ColonyQuant is a new tool that automatically analyzes stem cell colonies using images, making research faster and more accurate.

## Contribution

The novel contribution is an open-source platform for automated colony quantification and morphometric analysis in stem cell research.

## Key findings

- ColonyQuant captures staining intensity and structural features in a unified framework.
- Multivariate analyses identified intensity and solidity as key features for dose-dependent colony responses.
- The tool enables scalable and objective phenotyping for stem cell studies and drug screening.

## Abstract

Quantitative image analysis is essential for advancing stem cell biology, developmental studies, and drug discovery, yet most workflows still rely on manual or semi-quantitative scoring that is slow, subjective, and poorly scalable. A major challenge is converting complex colony morphologies into reproducible, high-dimensional datasets. To address this gap, we developed ColonyQuant, an open-source platform that integrates automated colony segmentation, alkaline phosphatase (AP) intensity quantification, morphometric profiling, and statistical classification into a single workflow. ColonyQuant computes per-colony functional readouts alongside comprehensive shape descriptors, capturing both staining intensity and structural features in a unified framework. Applied to embryonic stem cells (ESCs) treated with a selective KDM4 histone-demethylase inhibitor, ColonyQuant revealed dose-dependent reductions in colony area and integrated AP signal, together with systematic remodeling of morphometric metrics. Multivariate analyses robustly stratified treatment groups and identified intensity and solidity as principal features capturing dose-dependent colony responses. By transforming subjective scoring into objective, scalable, and biologically interpretable phenotyping, ColonyQuant provides a reproducible platform for stem cell research and high-content screening.

The online version contains supplementary material available at 10.1186/s12859-026-06403-5.