Department of Biochemistry and Molecular Biology, Boonshoft School of Medicine, Wright State University, Dayton, Ohio, USA.
Sci Rep. 2017 Jul 25;7(1):6481. doi: 10.1038/s41598-017-06693-z.
Recently developed high throughput molecular techniques such as massively parallel sequencing and phylogenetic microarrays generate vast datasets providing insights into microbial community structure and function. Because of the high dimensionality of these datasets, multivariate ordination analyses are often employed to examine such data. Here, we show how the use of phylogenetic distance based redundancy analysis provides ecological interpretation of microbial community differences. We also extend the previously developed method of principal response curves to incorporate phylogenetic distance measure, and we demonstrate the improved ability of this approach to provide ecologically relevant insights into temporal alterations of microbial communities.
最近开发的高通量分子技术,如大规模平行测序和系统发生微阵列,产生了大量的数据集,使人们能够深入了解微生物群落的结构和功能。由于这些数据集的高维性,通常采用多元排序分析来研究这些数据。在这里,我们展示了基于系统发生距离的冗余分析如何为微生物群落差异提供生态解释。我们还扩展了以前开发的主响应曲线方法,将系统发生距离度量纳入其中,并展示了这种方法在提供微生物群落时间变化的生态相关见解方面的改进能力。