Making the most of high-dimensional cytometry data.
Making the most of high-dimensional cytometry data.
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DOI：
10.1111/imcb.12456
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发表时间：
2021-08
影响因子：
4
通讯作者：
Kemp RA
中科院分区：
文献类型：
--
作者：
Marsh-Wakefield FM;Mitchell AJ;Norton SE;Ashhurst TM;Leman JK;Roberts JM;Harte JE;McGuire HM;Kemp RA
高维细胞术代表了免疫学研究的一个令人兴奋的新时代，使发现新细胞和预测患者对治疗的反应成为可能。现在，无论是新用户还是有经验的用户，都可以使用过多的分析和可视化工具和程序；然而，从低维细胞术过渡到高维细胞术需要用户改变对实验设计和数据分析的思考方式。由于数据的大小和可能的标记组合数量，以及缺乏对产生有意义数据所需的过程的了解，来自高维细胞术实验的数据往往得不到充分利用。在这篇文章中，我们解释了设计高维细胞学实验背后的概念，并为新手和有经验的用户设计和执行高维实验以最大限度地提高数据收集质量提供了考虑因素。高维细胞术代表了免疫学研究的一个令人兴奋的新时代；然而，从低维细胞术向高维细胞术的过渡要求用户改变对实验设计和数据分析的思考方式。我们解释了设计高维细胞测量实验背后的概念，并为新的和有经验的用户设计和执行高维实验提供了考虑因素。
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. High‐dimensional cytometry represents an exciting new era of immunology research; however, the transition from low‐ to high‐dimensional cytometry requires a change in the way users think about experimental design and data analysis. 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.
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影响因子：
46.9
作者：
Becht, Etienne;McInnes, Leland;Newell, Evan W.
通讯作者：
Newell, Evan W.
影响因子：
5.8
作者：
Becht, Etienne;Simoni, Yannick;Newell, Evan W.
通讯作者：
Newell, Evan W.
DOI：
10.1126/science.1198704
发表时间：
2011-05-06
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Bendall SC;Simonds EF;Qiu P;Amir el-AD;Krutzik PO;Finck R;Bruggner RV;Melamed R;Trejo A;Ornatsky OI;Balderas RS;Plevritis SK;Sachs K;Pe'er D;Tanner SD;Nolan GP
通讯作者：
Nolan GP
影响因子：
3.7
作者：
Abdelaal, Tamim;van Unen, Vincent;Mahfouz, Ahmed
通讯作者：
Mahfouz, Ahmed
影响因子：
17.1
作者：
Gaudillière B;Fragiadakis GK;Bruggner RV;Nicolau M;Finck R;Tingle M;Silva J;Ganio EA;Yeh CG;Maloney WJ;Huddleston JI;Goodman SB;Davis MM;Bendall SC;Fantl WJ;Angst MS;Nolan GP
通讯作者：
Nolan GP