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Differential Abundance Analysis for Microbial Marker-gene Surveys

Overview
Journal Nat Methods
Date 2013 Oct 1
PMID 24076764
Citations 1069
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Abstract

We introduce a methodology to assess differential abundance in sparse high-throughput microbial marker-gene survey data. Our approach, implemented in the metagenomeSeq Bioconductor package, relies on a novel normalization technique and a statistical model that accounts for undersampling-a common feature of large-scale marker-gene studies. Using simulated data and several published microbiota data sets, we show that metagenomeSeq outperforms the tools currently used in this field.

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