Dataset Information

A phylogenetic transform enhances analysis of compositional microbiota data.

ABSTRACT: Surveys of microbial communities (microbiota), typically measured as relative abundance of species, have illustrated the importance of these communities in human health and disease. Yet, statistical artifacts commonly plague the analysis of relative abundance data. Here, we introduce the PhILR transform, which incorporates microbial evolutionary models with the isometric log-ratio transform to allow off-the-shelf statistical tools to be safely applied to microbiota surveys. We demonstrate that analyses of community-level structure can be applied to PhILR transformed data with performance on benchmarks rivaling or surpassing standard tools. Additionally, by decomposing distance in the PhILR transformed space, we identified neighboring clades that may have adapted to distinct human body sites. Decomposing variance revealed that covariation of bacterial clades within human body sites increases with phylogenetic relatedness. Together, these findings illustrate how the PhILR transform combines statistical and phylogenetic models to overcome compositional data challenges and enable evolutionary insights relevant to microbial communities.

SUBMITTER: Silverman JD

PROVIDER: S-EPMC5328592 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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A phylogenetic transform enhances analysis of compositional microbiota data.

Silverman Justin D JD Washburne Alex D AD Mukherjee Sayan S David Lawrence A LA

eLife 20170215

Surveys of microbial communities (microbiota), typically measured as relative abundance of species, have illustrated the importance of these communities in human health and disease. Yet, statistical artifacts commonly plague the analysis of relative abundance data. Here, we introduce the PhILR transform, which incorporates microbial evolutionary models with the isometric log-ratio transform to allow off-the-shelf statistical tools to be safely applied to microbiota surveys. We demonstrate that a ...[more]

PMID: 28198697

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Project description:BackgroundAmongst the most commonly used molecular markers for plant phylogenetic studies are the nuclear ribosomal internal transcribed spacers (ITS). Intra-individual variability of these multicopy regions is a very common phenomenon in plants, the causes of which are debated in literature. Phylogenetic reconstruction under these conditions is inherently difficult. Our approach is to consider this problem as a special case of the general biological question of how to infer the characteristics of hosts (represented here by plant individuals) from features of their associates (represented by cloned sequences here).ResultsSix general transformation functions are introduced, covering the transformation of associate characters to discrete and continuous host characters, and the transformation of associate distances to host distances. A pure distance-based framework is established in which these transformation functions are applied to ITS sequences collected from the angiosperm genera Acer, Fagus and Zelkova. The formulae are also applied to allelic data of three different loci obtained from Rosa spp. The functions are validated by (1) phylogeny-independent measures of treelikeness; (2) correlation with independent host characters; (3) visualization using splits graphs and comparison with published data on the test organisms. The results agree well with these three measures and the datasets examined as well as with the theoretical predictions and previous results in the literature. High-quality distance matrices are obtained with four of the six transformation formulae. We demonstrate that one of them represents a generalization of the Sørensen coefficient, which is widely applied in ecology.ConclusionBecause of their generality, the transformation functions may be applied to a wide range of biological problems that are interpretable in terms of hosts and associates. Regarding cloned sequences, the formulae have a high potential to accurately reflect evolutionary relationships within angiosperm genera, and to identify hybrids and ancestral taxa. These results corroborate earlier ones which showed that treelikeness measures are a valuable tool in comparative studies of biological distance functions.

Dataset Information

A phylogenetic transform enhances analysis of compositional microbiota data.

Publications

A phylogenetic transform enhances analysis of compositional microbiota data.

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