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

Alex D. Washburne, Justin D. Silverman, Jonathan W. Leff, Dominic J. Bennett, John L. Darcy, Sayan Mukherjee, Noah Fierer, Lawrence A. David

    Research output: Contribution to journalArticlepeer-review

    60 Scopus citations


    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 op- portunities 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.

    Original languageEnglish (US)
    Article numbere2969
    Issue number2
    StatePublished - 2017

    All Science Journal Classification (ASJC) codes

    • Neuroscience(all)
    • Biochemistry, Genetics and Molecular Biology(all)
    • Agricultural and Biological Sciences(all)


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