ShapeMetrics: A 3D Cell Segmentation Pipeline for Single-Cell Spatial Morphometric Analysis

Abstract

There is a growing need for single-cell level data analysis in correlation with the advancements of microscopy techniques. Morphology-based statistics gathered from individual cells are essential for detection and quantification of even subtle changes within the complex tissues, yet the information available from high-resolution imaging is oftentimes sub-optimally utilized due to the lack of proper computational analysis software. Here we present ShapeMetrics, a 3D cell segmentation pipeline that we have developed to identify, analyze, and quantify single cells in an image. This MATLAB-based script enables users to extract morphological parameters, such as ellipticity, longest axis, cell elongation, or the ratio between cell volume and surface area. We have specifically invested in creating a user-friendly pipeline, aimed for biologists with a limited computational background. Our pipeline is presented with detailed stepwise instructions, starting from the establishment of machine learning–based prediction files of immuno-labeled cell membranes followed by the application of 3D cell segmentation and parameter extraction script, leading to the morphometric analysis and spatial visualization of cell clusters defined by their morphometric features.