| Literature DB >> 33797774 |
Felix Md Marsh-Wakefield1,2,3, Andrew J Mitchell4, Samuel E Norton5,6, Thomas Myles Ashhurst2,7,8, Julia Kh Leman6, Joanna M Roberts9, Jessica E Harte6, Helen M McGuire2,8,10, Roslyn A Kemp6.
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 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.Entities:
Keywords: Analysis; experimental design; flow cytometry; high-dimensional data; mass cytometry
Year: 2021 PMID: 33797774 DOI: 10.1111/imcb.12456
Source DB: PubMed Journal: Immunol Cell Biol ISSN: 0818-9641 Impact factor: 5.126