Multicolor flow cytometry is a powerful tool for analyzing patient samples in clinical and translational research. However, since flow cytometers' performance, avoidance of unsatisfactory loss of data resolution due to spectral overlap when using multiple colors can be challenging.
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We outline a systematic workflow for panel design by using a Spillover Spread Matrix, recorded on the machine intended to run the experiments. The workflow ensures that poorly expressed antigens are coupled with the brightest fluorochromes and that fluorochromes with significant spectral overlap do not bind to the same cell type, which is essential for obtaining reliable results.
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Furthermore, we address state-of-the-art methods for compensation, quality control, staining of cells, and data analysis using conventional gating and unsupervised clustering.
Abstract
Multicolor flow cytometry is an essential tool for studying the immune system in health and disease, allowing users to extract longitudinal multiparametric data from patient samples. The process is complicated by substantial variation in performance between each flow cytometry instrument, and analytical errors are therefore common. Here, we present an approach to overcome such limitations by applying a systematic workflow for pairing colors to markers optimized for the equipment intended to run the experiments. The workflow is exemplified by the design of four comprehensive flow cytometry panels for patients with hematological cancer. Methods for quality control, titration of antibodies, compensation, and staining of cells for obtaining optimal results are also addressed. Finally, to handle the large amounts of data generated by multicolor flow cytometry, unsupervised clustering techniques are used to identify significant subpopulations not detected by conventional sequential gating.
