PhyloSift: Phylogenetic analysis of genomes and metagenomes

Aaron E. Darling, Guillaume Jospin, Eric Lowe, Frederick A. Matsen, Holly M. Bik, Jonathan A Eisen

Research output: Contribution to journalArticlepeer-review

328 Scopus citations

Abstract

Like all organisms on the planet, environmental microbes are subject to the forces of molecular evolution. Metagenomic sequencing provides a means to access the DNA sequence of uncultured microbes. By combining DNA sequencing of microbial communities with evolutionary modeling and phylogenetic analysis we might obtain new insights into microbiology and also provide a basis for practical tools such as forensic pathogen detection. In this work we present an approach to leverage phylogenetic analysis of metagenomic sequence data to conduct several types of analysis. First, we present a method to conduct phylogeny-driven Bayesian hypothesis tests for the presence of an organism in a sample. Second, we present a means to compare community structure across a collection of many samples and develop direct associations between the abundance of certain organisms and sample metadata. Third, we apply new tools to analyze the phylogenetic diversity of microbial communities and again demonstrate how this can be associated to sample metadata. These analyses are implemented in an open source software pipeline called PhyloSift. As a pipeline, PhyloSift incorporates several other programs including LAST, HMMER, and pplacer to automate phylogenetic analysis of protein coding and RNA sequences in metagenomic datasets generated by modern sequencing platforms (e.g., Illumina, 454).

Original languageEnglish (US)
Article number243
JournalPeerJ
Volume2013
Issue number1
DOIs
StatePublished - 2014

Keywords

  • Bayes factor
  • Community structure
  • Edge PCA
  • Forensics
  • Metagenomics
  • Microbial diversity
  • Microbial ecology
  • Microbial evolution
  • Phylogenetic diversity
  • Phylogenetics

ASJC Scopus subject areas

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

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