A. Spike-in retrieval as a function of number of positive samples, by dataset size. Aggregated results across 150 iterations of multiplicative spike-ins of magnitude 5 with 50% cases, in datasets A1, A1s, and A1m. Each dot represents a spiked OTU. The Y-axis displays its p value quantile (0 is lowest p value, 1 is highest p value) within that DA run, and the X axis shows how many samples are positive (nonzero) for that OTU. Results from the three datasets are overlaid with different colors and faceted by statistical method. B. Spike-in retrieval as a function of number of positive samples, by case proportion. Aggregated results across 150 iterations of multiplicative spike-ins of magnitude 5 with 10, 25, or 50% cases, in dataset A1. Each dot represents a spiked OTU. The Y-axis displays its p value quantile (0 is lowest p value, 1 is highest p value) within that DA run, and the X axis shows how many samples are positive (nonzero) for that OTU. Results from the three case proportions are overlaid with different colors, and faceted by statistical method. C. Spike-in retrieval as a function of number of positive samples, by spike-in magnitude. Aggregated results across 150 iterations of multiplicative spike-ins of magnitudes 0.5, 2, 5, 10, and 20 with 50% cases, in dataset A1. Each dot represents a spiked OTU. The Y-axis displays its p value quantile (0 is lowest p value, 1 is highest p value) within that DA run, and the X axis shows how many samples are positive (nonzero) for that OTU. Results from the different spike-in magnitudes are overlaid with different colors, and faceted by statistical method. (ZIP 16398 kb)

A. False positive rate distributions for datasets A1s–A3s and A1m–A3m. Violin plot of distributions of false positive rate (FPR) in 150 iterations for datasets A1s–A3s and A1m–A3m (vertical panels), analyzed with all differential relative abundance methods (horizontal panels). FPR is defined as the fraction of OTUs with p

Chimeras removed from dataset B3. (XLSX 49 kb)

Chimeras removed from dataset B3. (XLSX 49 kb)

A. Spike-in retrieval as a function of number of positive samples, by dataset size. Aggregated results across 150 iterations of multiplicative spike-ins of magnitude 5 with 50% cases, in datasets A1, A1s, and A1m. Each dot represents a spiked OTU. The Y-axis displays its p value quantile (0 is lowest p value, 1 is highest p value) within that DA run, and the X axis shows how many samples are positive (nonzero) for that OTU. Results from the three datasets are overlaid with different colors and faceted by statistical method. B. Spike-in retrieval as a function of number of positive samples, by case proportion. Aggregated results across 150 iterations of multiplicative spike-ins of magnitude 5 with 10, 25, or 50% cases, in dataset A1. Each dot represents a spiked OTU. The Y-axis displays its p value quantile (0 is lowest p value, 1 is highest p value) within that DA run, and the X axis shows how many samples are positive (nonzero) for that OTU. Results from the three case proportions are overlaid with different colors, and faceted by statistical method. C. Spike-in retrieval as a function of number of positive samples, by spike-in magnitude. Aggregated results across 150 iterations of multiplicative spike-ins of magnitudes 0.5, 2, 5, 10, and 20 with 50% cases, in dataset A1. Each dot represents a spiked OTU. The Y-axis displays its p value quantile (0 is lowest p value, 1 is highest p value) within that DA run, and the X axis shows how many samples are positive (nonzero) for that OTU. Results from the different spike-in magnitudes are overlaid with different colors, and faceted by statistical method. (ZIP 16398 kb)

A. False positive rate distributions for datasets A1s–A3s and A1m–A3m. Violin plot of distributions of false positive rate (FPR) in 150 iterations for datasets A1s–A3s and A1m–A3m (vertical panels), analyzed with all differential relative abundance methods (horizontal panels). FPR is defined as the fraction of OTUs with p

Overview of the datasets used in the study. Sampling and data characteristics of the seven datasets used in the study, A1â A4 for the false positive rate and spike-in retrieval tests and B1â B3 for the beta-diversity optimization tests. (XLSX 5 kb)

A. Area under the curve distributions for additive spike-ins in dataset A1. Violin plot of distributions of area under the receiver operating characteristic curve (AUC) for spiked vs non-spiked p values from differential relative abundance (DA) tests. AUC distributions from 150 iterations for each combination of spike-in magnitude and case proportion (vertical panels) in dataset A1, analyzed with all differential relative abundance methods (horizontal panels). Black dots represent medians in each distribution. B. Area under the curve distributions for additive spike-ins in dataset A2. Violin plot of distributions of area under the receiver operating characteristic curve (AUC) for spiked vs non-spiked p values from differential relative abundance (DA) tests. AUC distributions from 150 iterations for each combination of spike-in magnitude and case proportion (vertical panels) in dataset A2, analyzed with all differential relative abundance methods (horizontal panels). Black dots represent medians in each distribution. C. Area under the curve distributions for additive spike-ins in dataset A3. Violin plot of distributions of area under the receiver operating characteristic curve (AUC) for spiked vs non-spiked p values from differential relative abundance (DA) tests. AUC distributions from 150 iterations for each combination of spike-in magnitude and case proportion (vertical panels) in dataset A3, analyzed with all differential relative abundance methods (horizontal panels). Black dots represent medians in each distribution. (ZIP 2183 kb)

A. Area under the curve distributions for multiplicative spike-ins in dataset A1. Violin plot of distributions of area under the receiver operating characteristic curve (AUC) for spiked vs non-spiked p values from differential relative abundance (DA) tests. AUC distributions from 150 iterations for each combination of spike-in magnitude and case proportion (vertical panels) in dataset A1, analyzed with all differential relative abundance methods (horizontal panels). Black dots represent medians in each distribution. B. Area under the curve distributions for multiplicative spike-ins in dataset A2. Violin plot of distributions of area under the receiver operating characteristic curve (AUC) for spiked vs non-spiked p values from differential relative abundance (DA) tests. AUC distributions from 150 iterations for each combination of spike-in magnitude and case proportion (vertical panels) in dataset A2, analyzed with all differential relative abundance methods (horizontal panels). Black dots represent medians in each distribution. C. Area under the curve distributions for multiplicative spike-ins in dataset A3. Violin plot of distributions of area under the receiver operating characteristic curve (AUC) for spiked vs non-spiked p values from differential relative abundance (DA) tests. AUC distributions from 150 iterations for each combination of spike-in magnitude and case proportion (vertical panels) in dataset A3, analyzed with all differential relative abundance methods (horizontal panels). Black dots represent medians in each distribution. (ZIP 2685 kb)

A. False positive rate distributions for datasets A1–A3. Violin plot of distributions of false positive rate (FPR) in 150 iterations for each case proportion in datasets A1–A3 (vertical panels), analyzed with all differential relative abundance methods (horizontal panels). FPR is defined as the fraction of OTUs with p