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Activity Number: 76
Type: Contributed
Date/Time: Sunday, August 4, 2013 : 4:00 PM to 5:50 PM
Sponsor: Biometrics Section
Abstract - #310129
Title: SigTree: An Automated Meta-Analytic Approach to Find Significantly Responsive Branches in a Phylogenetic Tree
Author(s): John Stevens*+ and Todd R. Jones and Michael Lefevre
Companies: Utah State University and Cornell University and Utah State University
Keywords: meta-analysis ; regular expressions ; multiple testing ; microbiota
Abstract:

Experiments to assess a treatment effect on multiple related species (or operational taxonomic units) simultaneously are becoming increasingly common. In addition to testing each individual species' response to the treatment, it is also of interest to identify groups of related species (or families) with a significant consensus response. Within the framework of a phylogenetic tree of all species considered in an experiment, this interest translates to a statistical need to identify branches (or clades) that exhibit a significant response to the treatment. We present our R package SigTree, a collection of flexible tools that make use of regular expressions and meta-analysis methods to identify and visualize significantly responsive branches in a phylogenetic tree. We demonstrate these tools using a motivating experiment comparing the gut microbiota profiles of two diets in mice.


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