Phylogenetic factorization of compositional data yields lineage-level associations in microbiome datasets

PeerJ

article

Alex D. Washburne¹  Justin D. Silverman²  Jonathan W. Leff⁶  Dominic J. Bennett⁷  John L. Darcy⁹  Sayan Mukherjee²  Noah Fierer⁶  Lawrence A. David² 

[1] Nicholas School of the Environment, Duke University;Program for Computational Biology and Bioinformatics, Duke University;Medical Scientist Training Program, Duke University;Center for Genomic and Computational Biology, Duke University;Department of Molecular Genetics and Microbiology, Duke University;Cooperative Institute for Research in Environmental Sciences, University of Colorado;Department of Earth Science and Engineering, Imperial College London;Institute of Zoology, Zoological Society of London;Department of Ecology and Evolution, University of Colorado Boulder;Department of Statistical Science, Mathematics, and Computer Science, Duke University

关键词: Microbiome;    Community phylogenetics;    Compositional data;    Sequence-count data;    Microbial biogeography;    Factor analysis;    Phylofactorization;   

DOI  :  10.7717/peerj.2969

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

Marker gene sequencing of microbial communities has generated big datasets of microbial relative abundances varying across environmental conditions, sample sites and treatments. These data often come with putative phylogenies, providing unique opportunities to investigate how shared evolutionary history affects microbial abundance patterns. Here, we present a method to identify the phylogenetic factors driving patterns in microbial community composition. We use the method, “phylofactorization,” to re-analyze datasets from the human body and soil microbial communities, demonstrating how phylofactorization is a dimensionality-reducing tool, an ordination-visualization tool, and an inferential tool for identifying edges in the phylogeny along which putative functional ecological traits may have arisen.

【 授权许可】

CC BY