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

Ohad Manor, Elhanan Borenstein*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Article number53
JournalGenome Biology
Volume16
Issue number1
DOIs
StatePublished - 25 Mar 2015
Externally publishedYes

Funding

FundersFunder number
National Institutes of HealthDP2 AT007802-01
National Institute of Diabetes and Digestive and Kidney DiseasesP30DK089507

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