RT Journal Article SR Electronic T1 MUSiCC: Towards an accurate estimation of average genomic copy-numbers in the human microbiome JF bioRxiv FD Cold Spring Harbor Laboratory SP 009407 DO 10.1101/009407 A1 Ohad Manor A1 Elhanan Borenstein YR 2014 UL http://biorxiv.org/content/early/2014/09/19/009407.abstract AB 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 systematically identify various 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 a more 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.