Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada.
ISME J. 2013 Jan;7(1):173-83. doi: 10.1038/ismej.2012.88. Epub 2012 Aug 2.
High-throughput sequencing techniques have made large-scale spatial and temporal surveys of microbial communities routine. Gaining insight into microbial diversity requires methods for effectively analyzing and visualizing these extensive data sets. Phylogenetic β-diversity measures address this challenge by allowing the relationship between large numbers of environmental samples to be explored using standard multivariate analysis techniques. Despite the success and widespread use of phylogenetic β-diversity measures, an extensive comparative analysis of these measures has not been performed. Here, we compare 39 measures of phylogenetic β diversity in order to establish the relative similarity of these measures along with key properties and performance characteristics. While many measures are highly correlated, those commonly used within microbial ecology were found to be distinct from those popular within classical ecology, and from the recently recommended Gower and Canberra measures. Many of the measures are surprisingly robust to different rootings of the gene tree, the choice of similarity threshold used to define operational taxonomic units, and the presence of outlying basal lineages. Measures differ considerably in their sensitivity to rare organisms, and the effectiveness of measures can vary substantially under alternative models of differentiation. Consequently, the depth of sequencing required to reveal underlying patterns of relationships between environmental samples depends on the selected measure. Our results demonstrate that using complementary measures of phylogenetic β diversity can further our understanding of how communities are phylogenetically differentiated. Open-source software implementing the phylogenetic β-diversity measures evaluated in this manuscript is available at http://kiwi.cs.dal.ca/Software/ExpressBetaDiversity.
高通量测序技术使大规模的微生物群落时空调查成为常规。深入了解微生物多样性需要有效的方法来分析和可视化这些广泛的数据。系统发育β多样性度量方法通过允许使用标准多元分析技术来探索大量环境样本之间的关系来解决这一挑战。尽管系统发育β多样性度量方法取得了成功并得到了广泛应用,但尚未对这些方法进行广泛的比较分析。在这里,我们比较了 39 种系统发育β多样性度量方法,以确定这些度量方法之间的相对相似性以及关键特性和性能特征。虽然许多度量方法高度相关,但在微生物生态学中常用的度量方法与在经典生态学中流行的度量方法以及最近推荐的 Gower 和 Canberra 度量方法不同。许多度量方法对基因树的不同根、用于定义操作分类单位的相似性阈值的选择以及偏离的基础谱系非常稳健。这些度量方法在对稀有生物的敏感性和在替代分化模型下的有效性方面有很大差异。因此,揭示环境样本之间关系的潜在模式所需的测序深度取决于所选的度量方法。我们的结果表明,使用系统发育β多样性的补充度量方法可以进一步了解群落如何在系统发育上有所区别。本文评估的系统发育β多样性度量方法的开源软件可在 http://kiwi.cs.dal.ca/Software/ExpressBetaDiversity 上获得。