Microbial community resemblance methods differ in their ability to detect biologically relevant patterns.
Microbial community resemblance methods differ in their ability to detect biologically relevant patterns.
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DOI：
10.1038/nmeth.1499
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发表时间：
2010-10
期刊：
影响因子：
48
通讯作者：
Knight, Rob
中科院分区：
文献类型：
--
作者：
Kuczynski, Justin;Liu, Zongzhi;Lozupone, Catherine;McDonald, Daniel;Fierer, Noah;Knight, Rob
高通量测序方法的发展使得在前所未有的规模上对多种环境中的微生物群落进行特征分析成为可能。然而，我们对微生物群落组成的了解受到我们在大量序列中检测模式能力的限制。在此，我们使用包含聚类样本或沿环境梯度排列样本的真实和模拟细菌16S rRNA焦磷酸测序数据集，比较了51种分析技术的性能。我们发现，在严重欠采样的群落中，许多多样性模式是明显的，并且各种方法在检测梯度和聚类方面的能力差异很大。卡方距离和皮尔逊相关距离在检测梯度方面表现尤其出色，而高氏距离和堪培拉距离在检测聚类方面表现尤其出色。这些结果也为理解样本数量和覆盖深度之间的权衡提供了基础，在设计研究以表征微生物群落时，这种权衡是需要考虑的重要因素。
The development of high-throughput sequencing methods allows for the characterization of microbial communities in a wide range of environments on an unprecedented scale. However, insight into microbial community composition is limited by our ability to detect patterns in this flood of sequences. Here we compare the performance of 51 analysis techniques using real and simulated bacterial 16S rRNA pyrosequencing datasets containing either clustered samples or samples arrayed across environmental gradients. We find that many diversity patterns are evident with severely undersampled communities, and that methods vary widely in their ability to detect gradients and clusters. Chi-squared distances and Pearson correlation distances perform especially well for detecting gradients, while Gower and Canberra distances perform especially well for detecting clusters. These results also provide a basis for understanding tradeoffs between number of samples and depth of coverage, tradeoffs which are important to consider when designing studies to characterize microbial communities.
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影响因子：
12.3
作者：
Knight R;Maxwell P;Birmingham A;Carnes J;Caporaso JG;Easton BC;Eaton M;Hamady M;Lindsay H;Liu Z;Lozupone C;McDonald D;Robeson M;Sammut R;Smit S;Wakefield MJ;Widmann J;Wikman S;Wilson S;Ying H;Huttley GA
通讯作者：
Huttley GA
DOI：
10.1073/pnas.1000162107
发表时间：
2010-04-06
影响因子：
11.1
作者：
Fierer, Noah;Lauber, Christian L.;Knight, Rob
通讯作者：
Knight, Rob
DOI：
10.1073/pnas.0807920105
发表时间：
2008-11-18
影响因子：
11.1
作者：
Fierer, Noah;Hamady, Micah;Knight, Rob
通讯作者：
Knight, Rob
影响因子：
4.4
作者：
Lauber, Christian L.;Hamady, Micah;Fierer, Noah
通讯作者：
Fierer, Noah
DOI：
10.1007/bf00048870
发表时间：
1980-01-01
期刊：
VEGETATIO
影响因子：
--
作者：
HILL, MO;GAUCH, HG
通讯作者：
GAUCH, HG