Motivation: Recent studies have revealed a complex interplay between environment, the human microbiome and health and disease. Mediation analysis of the human microbiome in these complex relationships could potentiall...
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Motivation: Recent studies have revealed a complex interplay between environment, the human microbiome and health and disease. Mediation analysis of the human microbiome in these complex relationships could potentially provide insights into the role of the microbiome in the etiology of disease and, more importantly, lead to novel clinical interventions by modulating the microbiome. However, due to the high dimensionality, sparsity, non-normality and phylogenetic structure of microbiome data, none of the existing methods are suitable for testing such clinically important mediation effect. Results: We propose a distance-based approach for testing the mediation effect of the human microbiome. In the framework, the nonlinear relationship between the human microbiome and independent/dependent variables is captured implicitly through the use of sample-wise ecological distances, and the phylogenetic tree information is conveniently incorporated by using phylogeny-based distance metrics. Multiple distance metrics are utilized to maximize the power to detect various types of mediation effect. Simulation studies demonstrate that our method has correct Type I error control, and is robust and powerful under various mediation models. Application to a real gut microbiome dataset revealed that the association between the dietary fiber intake and body mass index was mediated by the gut microbiome.
Motivation: Biodiversity databases now comprise hundreds of thousands of sequences and trait records. For example, the Open Tree of Life includes over 1 491 000 metazoan and over 300 000 bacterial taxa. These data pro...
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Motivation: Biodiversity databases now comprise hundreds of thousands of sequences and trait records. For example, the Open Tree of Life includes over 1 491 000 metazoan and over 300 000 bacterial taxa. These data provide unique opportunities for analysis of phylogenetic trait distribution and reconstruction of ancestral biodiversity. However, existing tools for comparative phylogenetics scale poorly to such large trees, to the point of being almost unusable. Results: Here we present a new R package, named 'castor', for comparative phylogenetics on large trees comprising millions of tips. On large trees castor is often 100-1000 times faster than existing tools.
Model-based approaches (e.g. maximum likelihood, Bayesian inference) are widely used with molecular data, where they might be more appropriate than maximum parsimony for estimating phylogenies under various models of ...
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Model-based approaches (e.g. maximum likelihood, Bayesian inference) are widely used with molecular data, where they might be more appropriate than maximum parsimony for estimating phylogenies under various models of molecular evolution. Recently, there has been an increase in the application of model-based approaches with morphological (mainly fossil) data;however, there is some doubt as to the effectiveness of the model of morphological evolution. The input parameters (prior probabilities) for the model are unclear, particularly when concerned with unobserved character states. Despite this, some systematists are suggesting superiority of these model-based methods over maximum parsimony based on, for example, increased resolution or, in the current study, the preferred phylogenetic placement of an iconic taxon. Here, we revisit a recently published analysis implying such superiority and document the discrepancies between parsimony-based and model-based approaches to phylogeny estimation. We find that although some taxa are shifted back to their traditional phylogenetic placement, other clades are disturbed. The model-based phylogenies are better resolved;however, due to the lack of an appropriate model of morphological evolution, the increase in resolving power is probably not meaningful. Similarly, some of the preferred phylogenetic positions of taxa, particularly of labile taxa such as Archaeopteryx, are based solely on analyses employing maximum parsimony as the optimality criterion. Poor resolution and labile taxa indicate a need for further examination of the morphology and not a change in method. (C) The Willi Hennig Society 2013
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