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Phylogenetic factorization of compositional data

View ORCID ProfileAlex D Washburne, View ORCID ProfileJustin D Silverman, View ORCID ProfileJonathan W Leff, Dominic J Bennett, View ORCID ProfileJohn L. Darcy, View ORCID ProfileSayan Mukherjee, View ORCID ProfileNoah Fierer, View ORCID ProfileLawrence A David
doi: https://doi.org/10.1101/074112
Alex D Washburne
1Nicholas School of the Environment, Duke University, Durham, NC 27708
2Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, Boulder CO 80309
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  • For correspondence: alex.d.washburne@gmail.com
Justin D Silverman
3Program in Computational Biology and Bioinformatics, Duke University, Durham, NC 27708
4Medical Scientist Training Program, Duke University, Durham, NC 27708
5Center for Genomic and Computational Biology, Duke University, Durham, NC 27708
6Department of Molecular Genetics and Microbiology, Duke University, Durham, NC 27708
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Jonathan W Leff
2Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, Boulder CO 80309
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Dominic J Bennett
7Department of Earth Science and Engineering, Imperial College London, London UK
8Institute of Zoology, Zoological Society of London, London UK
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John L. Darcy
9Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, CO 80309
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Sayan Mukherjee
3Program in Computational Biology and Bioinformatics, Duke University, Durham, NC 27708
10Departments of Statistical Science, Mathematics, and Computer Science, Duke University, Durham, NC 27708
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  • ORCID record for Sayan Mukherjee
Noah Fierer
2Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, Boulder CO 80309
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Lawrence A David
3Program in Computational Biology and Bioinformatics, Duke University, Durham, NC 27708
5Center for Genomic and Computational Biology, Duke University, Durham, NC 27708
6Department of Molecular Genetics and Microbiology, Duke University, Durham, NC 27708
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Abstract

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 human body and soil microbial communities, demonstrating how phylofactorization can be a dimensionality-reducing tool, an ordination-visualization tool, and also mass-produce inferences on the edges in the phylogeny in which meaningful differences arose.

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Posted September 12, 2016.
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Phylogenetic factorization of compositional data
Alex D Washburne, Justin D Silverman, Jonathan W Leff, Dominic J Bennett, John L. Darcy, Sayan Mukherjee, Noah Fierer, Lawrence A David
bioRxiv 074112; doi: https://doi.org/10.1101/074112
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Phylogenetic factorization of compositional data
Alex D Washburne, Justin D Silverman, Jonathan W Leff, Dominic J Bennett, John L. Darcy, Sayan Mukherjee, Noah Fierer, Lawrence A David
bioRxiv 074112; doi: https://doi.org/10.1101/074112

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