Automated Quantification and Morphometric Analysis of Pluripotent Stem Cell Colonies Using ColonyQuant

Alkaline phosphatase staining is routinely used to evaluate the undifferentiated state of embryonic stem cells, yet quantitative interpretation of colony assays frequently depends on manual inspection and categorical scoring that introduce subjectivity and limit scalability. ColonyQuant provides a standardized, automated framework for objective analysis of alkaline phosphatase-stained colonies from conventional bright-field images. The software performs adaptive colony detection, per-colony intensity measurement, and extraction of eight geometric descriptors that collectively characterize colony size, compactness, symmetry, and boundary complexity. Feature tables generated by the workflow are structured to support statistical comparison across replicates and experimental conditions. Integrated analysis modules enable dimensionality reduction, supervised classification, and feature ranking, facilitating interpretation of phenotypic differences without requiring custom scripting. Visualization routines generate distribution plots, contour-density maps, multivariate embeddings, and representative shape mosaics to summarize population heterogeneity and morphological organization. Applied to pluripotent stem cell cultures subjected to chromatin perturbation, the platform detects coordinated changes in colony growth behavior and structural architecture that may not be evident through visual scoring alone. The protocol describes installation, configuration, batch image processing, quality control, hierarchical data aggregation, and downstream statistical analysis, providing a reproducible approach for transforming qualitative colony assays into quantitative, high-content phenotypic datasets suitable for stem cell research and screening applications.