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ABSTRACT: Background
Modern sequencing technologies have generated low-cost microbiome survey datasets, across sample sites, conditions, and treatments, on an unprecedented scale and throughput. These datasets often come with a phylogenetic tree that provides a unique opportunity to examine how shared evolutionary history affects the different patterns in host-associated microbial communities.Results
In this paper, we describe an R package, phyloMDA, for phylogeny-aware microbiome data analysis. It includes the Dirichlet-tree multinomial model for multivariate abundance data, tree-guided empirical Bayes estimation of microbial compositions, and tree-based multiscale regression methods with relative abundances as predictors.Conclusion
phyloMDA is a versatile and user-friendly tool to analyze microbiome data while incorporating the phylogenetic information and addressing some of the challenges posed by the data.
SUBMITTER: Liu T
PROVIDER: S-EPMC9169257 | biostudies-literature | 2022 Jun
REPOSITORIES: biostudies-literature
Liu Tiantian T Zhou Chao C Wang Huimin H Zhao Hongyu H Wang Tao T
BMC bioinformatics 20220606 1
<h4>Background</h4>Modern sequencing technologies have generated low-cost microbiome survey datasets, across sample sites, conditions, and treatments, on an unprecedented scale and throughput. These datasets often come with a phylogenetic tree that provides a unique opportunity to examine how shared evolutionary history affects the different patterns in host-associated microbial communities.<h4>Results</h4>In this paper, we describe an R package, phyloMDA, for phylogeny-aware microbiome data ana ...[more]