In harmony? A scoping review of methods to combine multiple 16S amplicon datasets

Abstract

Robust evidence on relationships between the human microbiome and health is critical for understanding and improving the human condition. However, there is little information about methodological approaches to combine and analyze multiple microbiome (16S amplicon) datasets. To address this gap, we conducted a scoping review of studies that combined 16S sequencing data from multiple sources to understand the objectives, data sources and selection, bioinformatics, and analyses. References were identified through a systematic search of literature published between January 2011 and April 2026. Our final review included 136 articles. Despite the widespread use of the word “meta-analysis,” we found that only two-thirds of studies used a systematic process to select their dataset and 20% applied a statistical meta-analysis. Most studies (79%) combined datasets from multiple disjoint hypervariable regions. The number of hypervariable regions combined was not associated with the bioinformatic methods, but bioinformatics and the number of hypervariable regions influenced analytical resolution. Our results suggest that the microbiome community needs to examine the terminology and analytic approaches for combining datasets; that additional work is needed to explore the impact of data source on bias in combined studies; and that evaluation of methods used for feature table construction across disjoint regions is needed.