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Scalable methods for analyzing and visualizing phylogenetic placement of metagenomic samples

View ORCID ProfileLucas Czech, View ORCID ProfileAlexandros Stamatakis
doi: https://doi.org/10.1101/346353
Lucas Czech
Scientific Computing Group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany
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Alexandros Stamatakis
Scientific Computing Group, Heidelberg Institute for Theoretical Studies, Heidelberg, GermanyInstitute for Theoretical Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany
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1 Abstract

The exponential decrease in molecular sequencing cost generates unprecedented amounts of data. Hence, scalable methods to analyze these data are required. Phylogenetic (or Evolutionary) Placement methods identify the evolutionary provenance of anonymous sequences with respect to a given reference phylogeny. This increasingly popular method is deployed for scrutinizing metagenomic samples from environments such as water, soil, or the human gut.

Here, we present novel and, more importantly, highly scalable methods for analyzing phylogenetic placements of metagenomic samples. More specifically, we introduce methods for (a) visualizing differences between samples and their correlation with associated meta-data on the reference phylogeny, (b) clustering similar samples using a variant of the fc-means method, and (c) finding phylogenetic factors using an adaptation of the Phylofactorization method. These methods enable to interpret metagenomic data in a phylogenetic context, to find patterns in the data, and to identify branches of the phylogeny that are driving these patterns.

To demonstrate the scalability and utility of our methods, as well as to provide exemplary interpretations of our methods, we applied them to 3 publicly available datasets comprising 9782 samples with a total of approximately 168 million sequences. The results indicate that new biological insights can be attained via our methods.

Footnotes

  • ↵* lucas.czech{at}h-its.org, alexandros.stamatakis{at}h-its.org

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted March 14, 2019.
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Scalable methods for analyzing and visualizing phylogenetic placement of metagenomic samples
Lucas Czech, Alexandros Stamatakis
bioRxiv 346353; doi: https://doi.org/10.1101/346353
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Scalable methods for analyzing and visualizing phylogenetic placement of metagenomic samples
Lucas Czech, Alexandros Stamatakis
bioRxiv 346353; doi: https://doi.org/10.1101/346353

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