title: Measures of phylogenetic differentiation provide robust and complementary insights into microbial communities.
abstract: High-throughput sequencing techniques have made large-scale spatial and temporal surveys of microbial communities routine. Gaining insight into microbial diversity requires methods for effectively analyzing and visualizing these extensive data sets. Phylogenetic β-diversity measures address this challenge by allowing the relationship between large numbers of environmental samples to be explored using standard multivariate analysis techniques. Despite the success and widespread use of phylogenetic β-diversity measures, an extensive comparative analysis of these measures has not been performed. Here, we compare 39 measures of phylogenetic β diversity in order to establish the relative similarity of these measures along with key properties and performance characteristics. While many measures are highly correlated, those commonly used within microbial ecology were found to be distinct from those popular within classical ecology, and from the recently recommended Gower and Canberra measures. Many of the measures are surprisingly robust to different rootings of the gene tree, the choice of similarity threshold used to define operational taxonomic units, and the presence of outlying basal lineages. Measures differ considerably in their sensitivity to rare organisms, and the effectiveness of measures can vary substantially under alternative models of differentiation. Consequently, the depth of sequencing required to reveal underlying patterns of relationships between environmental samples depends on the selected measure. Our results demonstrate that using complementary measures of phylogenetic β diversity can further our understanding of how communities are phylogenetically differentiated. Open-source software implementing the phylogenetic β-diversity measures evaluated in this manuscript is available at http://kiwi.cs.dal.ca/Software/ExpressBetaDiversity.
authors.affiliation: Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada.
authors.forename: Donovan H
authors.initials: DH
authors.lastname: Parks
authors.forename: Robert G
authors.initials: RG
authors.lastname: Beiko
mesh_terms: D001419:Bacteria / Q000145:classification* / Q000235:genetics; D004463:Ecology / Q000379:methods*; D004783:Environmental Microbiology; D006801:Humans; D054892:Metagenome; D008954:Models, Biological; D010802:Phylogeny; D012984:Software