An Introduction to High-Dimensional Single-Cell Analysis by Mass Cytometry
Alex Johnson*(1), Priya Singh (2), Carlos Martinez (3)
(1) Department of Immunology, Example University, Exampleland, (2) Center for Proteomics and Metabolomics, Example Institute, Exampleland, (3) Department of Clinical Research, Example Medical Center, Exampleland
Mass cytometry (CyTOF) is a revolutionary single-cell analysis technology that enables the simultaneous measurement of over 40 cellular markers by combining flow cytometry principles with mass spectrometry. Using metal isotope-labeled antibodies, it overcomes the spectral overlap limitations of fluorescence-based methods, providing unparalleled resolution and accuracy in high-dimensional data acquisition. This technology has emerged as a powerful tool for dissecting cellular heterogeneity in complex systems, offering critical insights into immune cell profiling, cancer biology, and systems immunology. Key advantages include its ability to measure rare cell populations, minimal signal spillover, and compatibility with a wide range of sample types. These features have facilitated breakthroughs in understanding immune responses, disease mechanisms, and biomarker discovery. Despite its transformative potential, mass cytometry presents challenges such as the need for optimized experimental design, batch effect correction, and advanced computational approaches for data analysis. Novel bioinformatics tools, including dimensionality reduction methods (e.g., UMAP, t-SNE) and machine learning-based clustering algorithms, have been developed to address these challenges and maximize the utility of mass cytometry data. Mass cytometry continues to drive innovation in high-dimensional biology, enabling researchers to unravel the complexity of cellular networks and advance precision medicine efforts. Its integration with complementary technologies and ongoing advancements in analytical methodologies position mass cytometry as a cornerstone of modern single-cell research.