Histocytometry is a technique for processing multiparameter microscopy images using computational approaches to identify and quantify cellular pheno-types. It allows for spatial analyses of cellular phenotypes in relation to each other and within defined spatial regions. The benefit of this technique over manual annotation and characterization of cells is a high degree of automation/throughput, significantly decreased user bias, and increased reproducibility. Recently, an increase in freely available software amenable to or deliberately designed for histocytometry has resulted in these complex analyses being available to a broader base of users who have amassed multi-component microscopic imaging data. This article provides an overview of a histocytometry pipeline, focusing on the strategic planning and software requirements to allow readers to perform cell segmentation, phenotyping, and spatial analyses to advance their research outputs.
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