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A phylogenetic transform enhances analysis of compositional microbiota data.

Publication ,  Journal Article
Silverman, JD; Washburne, AD; Mukherjee, S; David, LA
Published in: Elife
February 15, 2017

Surveys of microbial communities (microbiota), typically measured as relative abundance of species, have illustrated the importance of these communities in human health and disease. Yet, statistical artifacts commonly plague the analysis of relative abundance data. Here, we introduce the PhILR transform, which incorporates microbial evolutionary models with the isometric log-ratio transform to allow off-the-shelf statistical tools to be safely applied to microbiota surveys. We demonstrate that analyses of community-level structure can be applied to PhILR transformed data with performance on benchmarks rivaling or surpassing standard tools. Additionally, by decomposing distance in the PhILR transformed space, we identified neighboring clades that may have adapted to distinct human body sites. Decomposing variance revealed that covariation of bacterial clades within human body sites increases with phylogenetic relatedness. Together, these findings illustrate how the PhILR transform combines statistical and phylogenetic models to overcome compositional data challenges and enable evolutionary insights relevant to microbial communities.

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Published In

Elife

DOI

EISSN

2050-084X

Publication Date

February 15, 2017

Volume

6

Location

England

Related Subject Headings

  • Microbiota
  • Humans
  • Computational Biology
  • Biostatistics
  • 42 Health sciences
  • 32 Biomedical and clinical sciences
  • 31 Biological sciences
  • 0601 Biochemistry and Cell Biology
 

Citation

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Silverman, J. D., Washburne, A. D., Mukherjee, S., & David, L. A. (2017). A phylogenetic transform enhances analysis of compositional microbiota data. Elife, 6. https://doi.org/10.7554/eLife.21887
Silverman, Justin D., Alex D. Washburne, Sayan Mukherjee, and Lawrence A. David. “A phylogenetic transform enhances analysis of compositional microbiota data.Elife 6 (February 15, 2017). https://doi.org/10.7554/eLife.21887.
Silverman JD, Washburne AD, Mukherjee S, David LA. A phylogenetic transform enhances analysis of compositional microbiota data. Elife. 2017 Feb 15;6.
Silverman, Justin D., et al. “A phylogenetic transform enhances analysis of compositional microbiota data.Elife, vol. 6, Feb. 2017. Pubmed, doi:10.7554/eLife.21887.
Silverman JD, Washburne AD, Mukherjee S, David LA. A phylogenetic transform enhances analysis of compositional microbiota data. Elife. 2017 Feb 15;6.

Published In

Elife

DOI

EISSN

2050-084X

Publication Date

February 15, 2017

Volume

6

Location

England

Related Subject Headings

  • Microbiota
  • Humans
  • Computational Biology
  • Biostatistics
  • 42 Health sciences
  • 32 Biomedical and clinical sciences
  • 31 Biological sciences
  • 0601 Biochemistry and Cell Biology