Differential richness inference for 16S rRNA marker gene surveys.
Differential richness inference for 16S rRNA marker gene surveys.
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DOI：
10.1186/s13059-022-02722-x
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发表时间：
2022-08-01
期刊：
影响因子：
12.3
通讯作者：
中科院分区：
文献类型：
--
作者：
个体和环境健康结果通常与相关微生物群落多样性的变化有关。因此，根据微生物组多样性措施得出健康指标至关重要。虽然使用高通量16 S rRNA标记基因调查产生的微生物组数据对于此目的是有吸引力的，但16 S调查也产生了过多的假微生物分类群。当这种人工通货膨胀的观察到的类群数量被忽略，我们发现，检测到的类群的丰度的变化混淆了目前的方法推断丰富度的差异。实验证据、理论指导的探索性数据分析和现有文献支持以下结论：大多数亚属发现是聚类16 S测序读数的虚假伪影。我们继续模拟16 S调查的系统模式的亚属分类群生成属丰度的函数，以获得一个强大的控制假分类群的积累。这些控制解锁经典的回归方法高度灵活的微分丰富度推断在不同层次的调查微生物组合：从样品组到特定的类群集合。所提出的差异丰富度推断方法可通过R软件包Prokounter获得。错误的物种发现使丰富度估计产生偏差，混淆了差异丰富度推断。在16 S微生物组调查的情况下，支持证据表明大多数亚属分类群是虚假的。基于这一发现，提出了一种灵活的方法，并克服了混淆问题，指出与目前的方法差异丰富的推断。软件包可用性：https://github.com/mskb01/prokounter在线版本包含补充材料，可在10.1186/s13059-022-02722-x。
Individual and environmental health outcomes are frequently linked to changes in the diversity of associated microbial communities. Thus, deriving health indicators based on microbiome diversity measures is essential. While microbiome data generated using high-throughput 16S rRNA marker gene surveys are appealing for this purpose, 16S surveys also generate a plethora of spurious microbial taxa. When this artificial inflation in the observed number of taxa is ignored, we find that changes in the abundance of detected taxa confound current methods for inferring differences in richness. Experimental evidence, theory-guided exploratory data analyses, and existing literature support the conclusion that most sub-genus discoveries are spurious artifacts of clustering 16S sequencing reads. We proceed to model a 16S survey’s systematic patterns of sub-genus taxa generation as a function of genus abundance to derive a robust control for false taxa accumulation. These controls unlock classical regression approaches for highly flexible differential richness inference at various levels of the surveyed microbial assemblage: from sample groups to specific taxa collections. The proposed methodology for differential richness inference is available through an R package, Prokounter. False species discoveries bias richness estimation and confound differential richness inference. In the case of 16S microbiome surveys, supporting evidence indicate that most sub-genus taxa are spurious. Based on this finding, a flexible method is proposed and is shown to overcome the confounding problem noted with current approaches for differential richness inference. Package availability: https://github.com/mskb01/prokounter The online version contains supplementary material available at 10.1186/s13059-022-02722-x.
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影响因子：
4.8
作者：
Fisher, RA;Corbet, AS;Williams, CB
通讯作者：
Williams, CB
DOI：
10.1080/14888386.2014.931822
发表时间：
2014-06-01
期刊：
BIODIVERSITY-OTTAWA
影响因子：
--
作者：
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通讯作者：
Vickery, Juliet A.
影响因子：
48
作者：
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通讯作者：
Holmes SP
影响因子：
3.7
作者：
CHAO, A;LEE, SM
通讯作者：
LEE, SM
影响因子：
11
作者：
Degnan, Patrick H.;Ochman, Howard
通讯作者：
Ochman, Howard