Making the most of high‐dimensional cytometry data Felix MD Marsh‐Wakefield, Andrew J Mitchell, Samuel E Norton, Thomas Myles Ashhurst, Julia KH Leman, Joanna M Roberts, Jessica E Harte, Helen M McGuire, Roslyn A Kemp First published: 02 April 2021 https://doi.org/10.1111/imcb.12456

Abstract

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 visualisation tools and programmes are now available for both new and experienced users; however, the transition from low-dimensional 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 under-utilised, due to 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 maximise quality data collection