Abstract
Here, we present a protocol for multivariate quantitative-image-based cytometry (QIBC) analysis by fluorescence microscopy of asynchronous adherent cells. We describe steps for the preparation, treatment, and fixation of cells, sample staining, and imaging for QIBC. We then detail image analysis with our open source Fiji script developed for QIBC and present multiparametric data visualization. Our QIBC Fiji script integrates modern artificial-intelligence-based tools, applying deep learning, for robust automated nuclei segmentation with minimal user adjustments, a major asset for efficient QIBC analysis. For complete details on the use and execution of this protocol, please refer to Besse et al. (2023).1.