New Publication – Section of Microbiology - University of Copenhagen

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09. december 2016

New Publication

New publication from Section of Microbiology in Microbiome

Large-scale benchmarking reveals false discoveries and count transformation sensitivity in 16S rRNA gene amplicon data analysis methods used in microbiome studies

Microbiome (2016) 4:62

Jonathan Thorsen†, Asker Brejnrod†, Martin Mortensen, Morten A. Rasmussen, Jakob Stokholm, Waleed Abu Al-Soud, Søren Sørensen, Hans Bisgaard* and Johannes Waage*

This study represents an independent attempt to bench-mark various methods for differential relative abundance analysis of count-based microbiome datasets, using real
biological large-scale datasets. The results presented here warrant an increased awareness of the potential for spurious findings in differential relative abundance analyses. 16S data poses problems to both parametric and nonparametric statistical models, and new methods should explicitly account for sparsity, which is increased in large datasets.

Our results, generalizable to datasets from different sequencing platforms, demonstrate how the choice of method considerably affects analysis outcome. Here, we give recommendations for tools that exhibit low false positive rates, have good retrieval power across effect sizes and case/control proportions, and have low sparsity bias. Result output from some commonly used methods should be interpreted with caution. We provide an easily extensible framework for benchmarking of new methods and future microbiome datasets.