Work

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

Year: 2022

Type: article

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.

Source: BMC Bioinformatics

DOI: 10.1186/s12859-022-04744-5

Authors: Tiantian Liu, Chao Zhou, Huimin Wang, Hongyu Zhao, Tao Wang

Institutions: Shanghai Jiao Tong University, Duke University, Yale University

Language: English

Topic: Genomics and Phylogenetic Studies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $2,690

Funders: National Natural Science Foundation of China, Shanghai Jiao Tong University