Making the most of high‐dimensional cytometry data

High‐dimensional cytometry represents an exciting new era of immunology research, enabling the discovery of new cells and prediction of patient responses to therapy. A plethora of analysis and visualization tools and programs are now available for both new and experienced users; however, the transition from low‐ to high‐dimensional cytometry requires a change in the way users think about experimental design and data analysis. Data from high‐dimensional cytometry experiments are often underutilized, because of both the size of the data and the number of possible combinations of markers, as well as to a lack of understanding of the processes required to generate meaningful data. In this article, we explain the concepts behind designing high‐dimensional cytometry experiments and provide considerations for new and experienced users to design and carry out high‐dimensional experiments to maximize quality data collection.