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. 2023 Dec 29;21(1):83–91. doi: 10.1038/s41592-023-02092-7

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© This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 1 — a,b, The FDR and power of various DA methods for continuous (a) and binary exposures (b) are summarized. Synthetic datasets were generated using the PLN model¹⁸ based on the mean vector and covariance matrix estimated from the URT dataset¹⁹. The x axis represents the sample size (or sample size per group for the binary exposure), and the y axis shows the FDR or power. The dashed lines denote the nominal level of FDR (FDR = 0.05). The proportion of true DA taxa are provided in the top of each panel. The mean estimated FDR (or power) ± standard errors (indicated by error bars) derived from 100 simulation runs are provided in each panel.