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phyloMDA: an R package for phylogeny-aware microbiome data analysis.

Tiantian Liu1, Chao Zhou1, Huimin Wang2

  • 1SJTU-Yale Joint Center for Biostatistics and Data Science, Shanghai Jiao Tong University, Shanghai, China.

BMC Bioinformatics
|June 6, 2022
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Summary
This summary is machine-generated.

This study introduces phyloMDA, an R package for microbiome data analysis. It integrates phylogenetic information to better understand microbial community patterns and challenges.

Keywords:
Multivariate modelPhylogeny-aware analysisRelative abundances

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Computational Biology

Background:

  • Modern sequencing technologies enable large-scale microbiome surveys.
  • Microbiome datasets often include phylogenetic trees, offering insights into evolutionary history.
  • Analyzing host-associated microbial communities requires methods that account for evolutionary relationships.

Purpose of the Study:

  • To present phyloMDA, a novel R package for microbiome data analysis.
  • To enable phylogeny-aware analysis of microbiome survey data.
  • To address challenges in microbiome data analysis by incorporating evolutionary information.

Main Methods:

  • Utilizes the Dirichlet-tree multinomial model for multivariate abundance data.
  • Employs tree-guided empirical Bayes estimation for microbial composition.
  • Incorporates tree-based multiscale regression with relative abundances as predictors.

Main Results:

  • phyloMDA provides a comprehensive framework for microbiome data analysis.
  • The package integrates phylogenetic information into statistical models.
  • Demonstrates methods for analyzing microbiome data with evolutionary context.

Conclusions:

  • phyloMDA is a versatile and user-friendly tool for microbiome research.
  • The package facilitates the incorporation of phylogenetic data into analyses.
  • Addresses key challenges in analyzing complex microbiome datasets.