Alternatives to current flow cytometry data analysis for clinical and research studies
Alternatives to current flow cytometry data analysis for clinical and research studies
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DOI：
10.1016/j.ymeth.2017.12.009
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发表时间：
2018-02-01
期刊：
影响因子：
4.8
通讯作者：
Robinson, J. Paul
中科院分区：
文献类型：
--
作者：
Gondhalekar, Carmen;Rajwa, Bartek;Robinson, J. Paul
流式细胞术具有基于传统数据收集技术的完善的数据分析方法。这些技术通常涉及将试管样品手动插入仪器中，而该仪器在历史上只能测量 1-3 种颜色。此后，该领域不断发展，融入了新技术，以实现更快、高度自动化的样品制备和数据收集。例如，在台式仪器上使用微孔板现已成为几乎所有新仪器的标准，因此用户可以轻松快速地积累多个数据集。此外，由于用户必须仔细定义板的布局，因此在考虑分析过程时已经定义了该信息，从而扩大了自动化分析的机会。高光谱流式细胞术、20-40 色多色流式细胞术和质谱流式细胞术 (CyTOF) 的发展证明了多参数数据收集的进步正在改变游戏规则。随着数据和分析复杂性的增加，数据分析的复杂性也随之增加。复杂的数据分析已经是对传统流式细胞术软件的挑战。用于审查大型复杂数据集的新方法可以快速洞察在没有更先进的分析工具的情况下难以定义的流程。在临床实验室等优先考虑快速、准确的数据分析的环境中，需要快速、高效和直观的软件。本文概述了使用基于微珠的多重检测、药物筛选和细胞周期分析的示例来分析复杂数据集的机会 - 其中任何一个都可以集成到临床环境中。 (C) 2017 年，爱思唯尔公司出版
Flow cytometry has well-established methods for data analysis based on traditional data collection techniques. These techniques typically involved manual insertion of tube samples into an instrument that, historically, could only measure 1-3 colors. The field has since evolved to incorporate new technologies for faster and highly automated sample preparation and data collection. For example, the use of microwell plates on benchtop instruments is now a standard on virtually every new instrument, and so users can easily accumulate multiple data sets quickly. Further, because the user must carefully define the layout of the plate, this information is already defined when considering the analytical process, expanding the opportunities for automated analysis. Advances in multi-parametric data collection, as demonstrated by the development of hyperspectral flow-cytometry, 20-40 color polychromatic flow cytometry, and mass cytometry (CyTOF), are game-changing. As data and assay complexity increase, so too does the complexity of data analysis. Complex data analysis is already a challenge to traditional flow cytometry software. New methods for reviewing large and complex data sets can provide rapid insight into processes difficult to define without more advanced analytical tools. In settings such as clinical labs where rapid and accurate data analysis is a priority, rapid, efficient and intuitive software is needed. This paper outlines opportunities for analysis of complex data sets using examples of multiplexed bead-based assays, drug screens and cell cycle analysis - any of which could become integrated into the clinical environment. (C) 2017 Published by Elsevier Inc.