MUSiCC: a marker genes based framework for metagenomic normalization and accurate profiling of gene abundances in the microbiome

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• 作者：Ohad Manor (1)
  Elhanan Borenstein (1) (2) (3)
  
  1. Department of Genome Sciences ; University of Washington ; Seattle ; WA ; 98195 ; USA
  2. Department of Computer Science and Engineering ; University of Washington ; Seattle ; WA ; 98195 ; USA
  3. Santa Fe Institute ; Santa Fe ; NM ; 87501 ; USA
  
• 刊名：Genome Biology
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：16
• 期：1
• 全文大小：6,764 KB
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• 刊物主题：Animal Genetics and Genomics; Human Genetics; Plant Genetics & Genomics; Microbial Genetics and Genomics; Fungus Genetics; Bioinformatics;
• 出版者：BioMed Central
• ISSN：1465-6906

文摘

Functional metagenomic analyses commonly involve a normalization step, where measured levels of genes or pathways are converted into relative abundances. Here, we demonstrate that this normalization scheme introduces marked biases both across and within human microbiome samples, and identify sample- and gene-specific properties that contribute to these biases. We introduce an alternative normalization paradigm, MUSiCC, which combines universal single-copy genes with machine learning methods to correct these biases and to obtain an accurate and biologically meaningful measure of gene abundances. Finally, we demonstrate that MUSiCC significantly improves downstream discovery of functional shifts in the microbiome. MUSiCC is available at http://elbo.gs.washington.edu/software.html.