Multivariate tests and multiple test-procedures for abundance data of microorganisms in consideration of information from phylogenetic sequences

考虑系统发育序列信息的微生物丰度数据的多变量测试和多重测试程序

• 批准号: 253253386
• 负责人: Professor Dr. Siegfried Kropf
• 金额: --
• 依托单位: Department of Energy and Technology
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2014
• 资助国家: 德国
• 起止时间: 2013-12-31 至 2018-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/253253386?language=en
• 关键词: Multivariate; tests; multiple; test; procedures

Analysis of the composition of microbial communities is an important component of agricultural, medical and ecological research. Nowadays the preferred methods are based directly on DNA samples and therefore are independent of the reproduction of microbial organisms under laboratory conditions. The developmental progress from electrophoretic methods of analysis to specialized microarrays and furthermore to modern next generation sequencing techniques as pyrosequencing or sequencing by Illumina MiSeq increased the number of detected OTUs (operational taxonomic units) and the ability to directly interpret and compare them within and between samples. The result of pyrosequencing is a quantification of the occurrences of OTUs which is independent in scale for species and as a byproduct provides information of the corresponding sequences which can be used to quantify the phylogenetic similarity of OTUs, too.Currently, international groups of researchers focus on incorporating this supplementary information in statistical analysis. Computationally expensive methods for ecological distances were established that combine information from abundance and phylogenetic distances. A common theoretical basis for the two most popular variants, the weighted Unifrac distance and the DPCoA (double principal coordinate analysis), has been published last year.The first target of this application is to adjust multivariate methods that were developed in our institute to the use of additional phylogenetic information and to compare the results against published methods. The methods from our institute are permutation or rotation tests based on distance measures.The main target is to use these methods afterwards together with univariate tests as building blocks in procedures for multiple testing which partition high dimensional data as far as possible into smaller sets of variables (e.g. on a higher taxonomical level) or even into single variables (OTUs) while still controlling the familywise error rate in the strong sense. To achieve this, several multiple test procedures that were developed in (or together with) our institute will be adjusted to the use of phylogenetic distances. We will work closely together with our partners from the Julius Kühn-Institut, a Federal Research Centre for cultivated plants in Quedlinburg/Braunschweig.

微生物群落组成分析是农业、医学和生态研究的重要组成部分。如今，首选方法直接基于 DNA 样本，因此独立于实验室条件下微生物的繁殖。从电泳分析方法到专用微阵列，再到现代下一代测序技术（如焦磷酸测序或 Illumina MiSeq 测序）的发展进步增加了检测到的 OTU（操作分类单位）的数量以及直接解释和比较样本内和样本间它们的能力。焦磷酸测序的结果是对OTU出现的量化，其在规模上与物种无关，并且作为副产品提供了相应序列的信息，该信息也可用于量化OTU的系统发育相似性。目前，国际研究小组致力于将这些补充信息纳入统计分析。建立了计算成本高昂的生态距离方法，结合了丰度和系统发育距离的信息。加权 Unifrac 距离和 DPCoA（双主坐标分析）这两种最流行的变体的共同理论基础已于去年发布。该应用程序的第一个目标是调整我们研究所开发的多变量方法，以使用额外的系统发育信息，并将结果与​​已发布的方法进行比较。我们研究所的方法是基于距离测量的排列或旋转测试。主要目标是随后将这些方法与单变量测试一起用作多重测试程序中的构建块，将高维数据尽可能划分为较小的变量集（例如在更高的分类水平上）甚至划分为单变量（OTU），同时仍然在严格意义上控制族错误率。为了实现这一目标，我们研究所（或与我们研究所一起）开发的几个多重测试程序将根据系统发育距离的使用进行调整。我们将与位于奎德林堡/不伦瑞克的联邦栽培植物研究中心 Julius Kühn-Institut 的合作伙伴密切合作。