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微生物组数据集具有构成性:这并非可有可无。

Microbiome Datasets Are Compositional: And This Is Not Optional.

作者信息

Gloor Gregory B, Macklaim Jean M, Pawlowsky-Glahn Vera, Egozcue Juan J

机构信息

Department of Biochemistry, University of Western Ontario, London, ON, Canada.

Departments of Computer Science, Applied Mathematics, and Statistics, Universitat de Girona, Girona, Spain.

出版信息

Front Microbiol. 2017 Nov 15;8:2224. doi: 10.3389/fmicb.2017.02224. eCollection 2017.

Abstract

Datasets collected by high-throughput sequencing (HTS) of 16S rRNA gene amplimers, metagenomes or metatranscriptomes are commonplace and being used to study human disease states, ecological differences between sites, and the built environment. There is increasing awareness that microbiome datasets generated by HTS are compositional because they have an arbitrary total imposed by the instrument. However, many investigators are either unaware of this or assume specific properties of the compositional data. The purpose of this review is to alert investigators to the dangers inherent in ignoring the compositional nature of the data, and point out that HTS datasets derived from microbiome studies can and should be treated as compositions at all stages of analysis. We briefly introduce compositional data, illustrate the pathologies that occur when compositional data are analyzed inappropriately, and finally give guidance and point to resources and examples for the analysis of microbiome datasets using compositional data analysis.

摘要

通过对16S rRNA基因扩增子、宏基因组或宏转录组进行高通量测序(HTS)收集的数据集很常见,并被用于研究人类疾病状态、不同地点之间的生态差异以及建筑环境。人们越来越意识到,由HTS生成的微生物组数据集具有组成性,因为它们有仪器强加的任意总量。然而,许多研究者要么没有意识到这一点,要么假定了组成性数据的特定属性。本综述的目的是提醒研究者注意忽视数据组成性本质所固有的危险,并指出微生物组研究得出的HTS数据集在分析的各个阶段都能够且应该被视为组成数据。我们简要介绍组成性数据,说明在对组成性数据进行不当分析时出现的问题,最后给出使用组成性数据分析微生物组数据集的指导,并指出相关资源和示例。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ac2/5695134/a3de8aeac2eb/fmicb-08-02224-g0001.jpg

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