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首页> 外文期刊>Annual Review of Statistics and Its Application >Microbiome, Metagenomics, and High-Dimensional Compositional Data Analysis
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Microbiome, Metagenomics, and High-Dimensional Compositional Data Analysis

机译:微生物组,元基因组学和高维成分数据分析

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摘要

The human microbiome is the totality of all microbes in and on the human body, and its importance in health and disease has been increasingly recognized. High-throughput sequencing technologies have recently enabled scientists to obtain an unbiased quantification of all microbes constituting the microbiome. Often, a single sample can produce hundreds of millions of short sequencing reads. However, unique characteristics of the data produced by the new technologies, as well as the sheer magnitude of these data, make drawing valid biological inferences from microbiome studies difficult. Analysis of these big data poses great statistical and computational challenges. Important issues include normalization and quantification of relative taxa, bacterialgenes, and metabolic abundances; incorporation of phylogenetic information into analysis of metagenomics data; and multivariate analysis of high-dimensional compositional data. We review existing methods, point out their limitations, and oudine future research directions.
机译:人体微生物组是人体中及其上所有微生物的总和,其在健康和疾病中的重要性已得到越来越多的认识。最近,高通量测序技术使科学家能够对构成微生物组的所有微生物进行无偏定量。通常,单个样品可以产生数亿个短测序读数。但是,新技术产生的数据的独特特征以及这些数据的巨大规模,使得从微生物组研究中得出有效的生物学推断变得困难。对这些大数据的分析带来了巨大的统计和计算挑战。重要的问题包括相对分类单元,细菌基因和代谢丰度的标准化和定量;将系统发生信息纳入宏基因组学数据分析中;和高维成分数据的多元分析。我们回顾了现有方法,指出了它们的局限性,并展望了未来的研究方向。

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