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The UniFrac significance test is sensitive to tree topology.

  • Author(s): Lozupone, Catherine A
  • Knight, Rob
  • et al.
Abstract

Long et al. (BMC Bioinformatics 2014, 15(1):278) describe a "discrepancy" in using UniFrac to assess statistical significance of community differences. Specifically, they find that weighted UniFrac results differ between input trees where (a) replicate sequences each have their own tip, or (b) all replicates are assigned to one tip with an associated count. We argue that these are two distinct cases that differ in the probability distribution on which the statistical test is based, because of the differences in tree topology. Further study is needed to understand which randomization procedure best detects different aspects of community dissimilarities.

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