Power of Microbiome Beta-Diversity Analyses Based on Standard Reference Samples

A simple method to analyze microbiome beta-diversity computes mean beta-diversity distances from a test sample to standard reference samples. We used reference stool and nasal samples from the Human Microbiome Project and regressed an outcome on mean distances (2df-test) or additionally on squares and cross-product of mean distances (5df-test). We compared the power of 2df- and 5df-tests to the microbiome regression-based kernel association test (MiRKAT). In simulations, MiRKAT had moderately greater power than the 2df-test for discriminating skin versus saliva and skin versus nasal samples, but differences were negligible for skin versus stool and stool versus nasal samples. The 2df-test had slightly greater power than MiRKAT for Dirichlet-Multinomial samples. In associating body mass index with beta-diversity in stool samples from the American Gut Project, the 5df-test yielded smaller p-values than MiRKAT for most taxonomic levels and beta-diversity measures. Unlike procedures like MiRKAT that are based on the beta-diversity matrix, mean distances to reference samples can be analyzed with standard statistical tools and shared or meta-analyzed without sharing primary DNA data. Our data indicate that standard reference tests have comparable power to MiRKAT (and to permutational multivariate analysis of variance), but more simulations and applications are needed to confirm this. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2020. This work is written by (a) US Government employee(s) and is in the public domain in the US.

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