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Recentrifuge:用于宏基因组学的稳健比较分析和污染去除。

Recentrifuge: Robust comparative analysis and contamination removal for metagenomics.

机构信息

Institute for Integrative Systems Biology (I2SysBio), Valencia, Spain.

出版信息

PLoS Comput Biol. 2019 Apr 8;15(4):e1006967. doi: 10.1371/journal.pcbi.1006967. eCollection 2019 Apr.

Abstract

Metagenomic sequencing is becoming widespread in biomedical and environmental research, and the pace is increasing even more thanks to nanopore sequencing. With a rising number of samples and data per sample, the challenge of efficiently comparing results within a specimen and between specimens arises. Reagents, laboratory, and host related contaminants complicate such analysis. Contamination is particularly critical in low microbial biomass body sites and environments, where it can comprise most of a sample if not all. Recentrifuge implements a robust method for the removal of negative-control and crossover taxa from the rest of samples. With Recentrifuge, researchers can analyze results from taxonomic classifiers using interactive charts with emphasis on the confidence level of the classifications. In addition to contamination-subtracted samples, Recentrifuge provides shared and exclusive taxa per sample, thus enabling robust contamination removal and comparative analysis in environmental and clinical metagenomics. Regarding the first area, Recentrifuge's novel approach has already demonstrated its benefits showing that microbiomes of Arctic and Antarctic solar panels display similar taxonomic profiles. In the clinical field, to confirm Recentrifuge's ability to analyze complex metagenomes, we challenged it with data coming from a metagenomic investigation of RNA in plasma that suffered from critical contamination to the point of preventing any positive conclusion. Recentrifuge provided results that yielded new biological insight into the problem, supporting the growing evidence of a blood microbiota even in healthy individuals, mostly translocated from the gut, the oral cavity, and the genitourinary tract. We also developed a synthetic dataset carefully designed to rate the robust contamination removal algorithm, which demonstrated a significant improvement in specificity while retaining a high sensitivity even in the presence of cross-contaminants. Recentrifuge's official website is www.recentrifuge.org. The data and source code are anonymously and freely available on GitHub and PyPI. The computing code is licensed under the AGPLv3. The Recentrifuge Wiki is the most extensive and continually-updated source of documentation for Recentrifuge, covering installation, use cases, testing, and other useful topics.

摘要

宏基因组测序在生物医学和环境研究中越来越普及,由于纳米孔测序的出现,其发展速度更是突飞猛进。随着每个样本的数据量和样本数量的增加,如何在一个样本内以及在不同样本之间有效地比较结果成为了一个挑战。试剂、实验室和宿主相关的污染物使这种分析变得复杂。在微生物生物量低的身体部位和环境中,污染尤其严重,如果不是全部,也会占据样本的大部分。Recentrifuge 采用了一种强大的方法,可从其余样本中去除阴性对照和交叉分类群。使用 Recentrifuge,研究人员可以使用交互式图表分析分类器的结果,并重点关注分类的置信水平。除了去除污染的样本外,Recentrifuge 还为每个样本提供共享和独有的分类群,从而能够在环境和临床宏基因组学中进行稳健的污染去除和比较分析。在第一个领域,Recentrifuge 的新方法已经证明了其优势,表明北极和南极太阳能电池板的微生物组具有相似的分类特征。在临床领域,为了确认 Recentrifuge 分析复杂宏基因组的能力,我们用来自血浆 RNA 宏基因组研究的数据对其进行了挑战,这些数据受到了严重污染,以至于无法得出任何阳性结论。Recentrifuge 提供的结果为该问题提供了新的生物学见解,支持了即使在健康个体中也存在血液微生物组的不断增加的证据,这些微生物组主要从肠道、口腔和泌尿生殖道转移而来。我们还开发了一个精心设计的合成数据集来评估稳健的污染去除算法,该算法在保留高灵敏度的同时,在存在交叉污染物的情况下,特异性显著提高。Recentrifuge 的官方网站是 www.recentrifuge.org。数据和源代码在 GitHub 和 PyPI 上匿名免费提供。计算代码根据 AGPLv3 获得许可。Recentrifuge 的维基是 Recentrifuge 最全面和不断更新的文档来源,涵盖了安装、用例、测试和其他有用的主题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19fe/6472834/a3c9c3b1d337/pcbi.1006967.g001.jpg

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