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微生物流式细胞术数据的计算分析

Computational Analysis of Microbial Flow Cytometry Data.

作者信息

Rubbens Peter, Props Ruben

机构信息

Flanders Marine Institute (VLIZ), Ostend, Belgium

Center for Microbial Ecology & Technology (CMET), Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium

出版信息

mSystems. 2021 Jan 19;6(1):e00895-20. doi: 10.1128/mSystems.00895-20.

Abstract

Flow cytometry is an important technology for the study of microbial communities. It grants the ability to rapidly generate phenotypic single-cell data that are both quantitative, multivariate and of high temporal resolution. The complexity and amount of data necessitate an objective and streamlined data processing workflow that extends beyond commercial instrument software. No full overview of the necessary steps regarding the computational analysis of microbial flow cytometry data currently exists. In this review, we provide an overview of the full data analysis pipeline, ranging from measurement to data interpretation, tailored toward studies in microbial ecology. At every step, we highlight computational methods that are potentially useful, for which we provide a short nontechnical description. We place this overview in the context of a number of open challenges to the field and offer further motivation for the use of standardized flow cytometry in microbial ecology research.

摘要

流式细胞术是研究微生物群落的一项重要技术。它能够快速生成表型单细胞数据,这些数据具有定量、多变量且时间分辨率高的特点。数据的复杂性和数量需要一个客观且简化的数据处理工作流程,而这超出了商业仪器软件的范畴。目前尚无关于微生物流式细胞术数据计算分析必要步骤的全面概述。在本综述中,我们提供了一个完整的数据分析流程概述,涵盖从测量到数据解释,是针对微生物生态学研究量身定制的。在每一步,我们都突出了可能有用的计算方法,并对其进行简短的非技术性描述。我们将此概述置于该领域面临的一些开放性挑战的背景下,并为在微生物生态学研究中使用标准化流式细胞术提供进一步的动力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a07/7820666/29b46a0509d7/mSystems.00895-20-f0001.jpg

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