Skip to main content
Fig. 4 | Microbiome

Fig. 4

From: Normalization and microbial differential abundance strategies depend upon data characteristics

Fig. 4

Differential abundance detection sensitivity with varied library sizes, that are approximately even on average between groups. Multinomial, Dirichlet-multinomial, and gamma-Poisson parameters were fit using actual OTU tables from many global environments. Fold change represents the fold change of the true positive OTUs from one condition (e.g., case) to another (e.g., control). The height of each bar represents the median value from three simulations. Vertical lines extend to the upper quartile of the simulation results. Model/none represents data analyzed with a parametric statistical model (e.g., DESeq) or no normalization. Blue lines in, e.g., the DESeq row represents the data that was rarefied, then DESeq was applied. Since the fitZIG model depends upon original library size information, the model has high FDR on rarefied data. A 0.01 pseudocount for edgeR was necessary to avoid log(0)

Back to article page