为微生物组研究重新分配细菌种类。

IF 5 2区 生物学 Q1 MICROBIOLOGY mSystems Pub Date : 2024-07-23 Epub Date: 2024-06-24 DOI:10.1128/msystems.00515-24
Ceylan Tanes, Vincent Tu, Scott Daniel, Kyle Bittinger
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引用次数: 0

摘要

16S rRNA 标记基因测序法推动了微生物组的研究,并将继续发挥重要作用。人们认为该方法的一个弱点是无法按物种等级进行分类。我们的研究表明,通过排除细菌或古细菌的物种成员资格,我们可以提供更准确、更有用的答案。Unassigner 软件可在 16S rRNA 标记基因数据上运行,并利用贝塔二叉分布计算物种成员资格的排除概率。我们在全基因组比较的基础上证明了我们的方法是准确的。我们的方法与现有的方法一致,而且根据样本中与物种相关联的读数百分比,我们的方法大大提高了现有方法的性能。该软件可从以下网址获取:https://github.com/PennChopMicrobiomeProgram/unassigner.IMPORTANCEWhile 现有方法无法为 16S rRNA 标记基因数据提供可靠的物种级分配,而 Unassigner 软件通过排除物种成员资格解决了这一问题,使研究人员能够在物种级别进行推理。
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Unassigning bacterial species for microbiome studies.

The method of 16S rRNA marker gene sequencing has fueled microbiome research and continues to be relevant. A perceived weakness of the method is that taxonomic assignments are not possible to make at the rank of species. We show that by working to rule out bacterial or archaeal species membership, we can provide an answer that is more accurate and useful. The Unassigner software operates on 16S rRNA marker gene data and computes a rule-out probability for species membership using a beta-binomial distribution. We demonstrate that our approach is accurate based on full-genome comparisons. Our method is consistent with existing approaches and dramatically improves on them based on the percentage of reads it can associate with a species in a sample. The software is available at https://github.com/PennChopMicrobiomeProgram/unassigner.IMPORTANCEWhile existing methods do not provide reliable species-level assignments for 16S rRNA marker gene data, the Unassigner software solves this problem by ruling out species membership, allowing researchers to reason at the species level.

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来源期刊
mSystems
mSystems Biochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
10.50
自引率
3.10%
发文量
308
审稿时长
13 weeks
期刊介绍: mSystems™ will publish preeminent work that stems from applying technologies for high-throughput analyses to achieve insights into the metabolic and regulatory systems at the scale of both the single cell and microbial communities. The scope of mSystems™ encompasses all important biological and biochemical findings drawn from analyses of large data sets, as well as new computational approaches for deriving these insights. mSystems™ will welcome submissions from researchers who focus on the microbiome, genomics, metagenomics, transcriptomics, metabolomics, proteomics, glycomics, bioinformatics, and computational microbiology. mSystems™ will provide streamlined decisions, while carrying on ASM''s tradition of rigorous peer review.
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