Abstract

Measurement and characterization of the human microbiome in large population-based human studies has recently become a reality secondary to technological advances in high-throughput DNA sequencing. These advances bring new challenges and knowledge gaps for study planning, data analysis, and interpretation that are novel to large-scale epidemiologic studies. In this issue of the Journal, Sinha et al. (Am J Epidemiol. 2018;187(6):1282-1290) have provided data with which to inform statistical power and sample size requirements for microbiome studies in population-based settings. This work serves as a helpful starting point for study planning while also serving as a springboard for discussion regarding additional considerations for improving microbiome research. This commentary emphasizes the importance of selecting microbiome metrics appropriate for the biological hypothesis under investigation, as well as the need for new analytical tools that can better capitalize on the unique yet rich information contained in microbiome data sets.

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