Marsh-Wakefield Felix Md, Mitchell Andrew J, Norton Samuel E, Ashhurst Thomas Myles, Leman Julia Kh, Roberts Joanna M, Harte Jessica E, McGuire Helen M, Kemp Roslyn A
Vascular Immunology Unit, Discipline of Pathology, The University of Sydney, Sydney, NSW, Australia.
Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia.
Immunol Cell Biol. 2021 Aug;99(7):680-696. doi: 10.1111/imcb.12456. Epub 2021 May 4.
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.
高维细胞术代表了免疫学研究中一个令人兴奋的新时代，它能够发现新细胞并预测患者对治疗的反应。现在，无论是新手用户还是有经验的用户，都有大量的分析和可视化工具及程序可供使用；然而，从低维细胞术向高维细胞术的转变需要用户改变思考实验设计和数据分析的方式。由于数据量以及标记物可能组合的数量，再加上对生成有意义数据所需过程缺乏了解，高维细胞术实验的数据常常未得到充分利用。在本文中，我们解释了设计高维细胞术实验背后的概念，并为新手和有经验的用户提供了一些注意事项，以便他们设计和开展高维实验，从而最大限度地收集高质量数据。
