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Fig. 5 | BMC Genomics

Fig. 5

From: Statistical evaluation of methods for identification of differentially abundant genes in comparative metagenomics

Fig. 5

Most methods can control the false discovery rate at predefined level. The figure shows boxplots of the number of true positives (panel a, d), the number of false positives (panel b, e) and achieved true FDR (panel c, f) at a cutoff of 0.05 estimated FDR. Panels (a-c) show results for the Qin dataset and panels (d-f) show results for the Yatsunenko dataset. The group sizes were set to 6 + 6 and the effect size to 5. The results were based on 100 resampled metagenomes. The included methods are edgeR, DESeq2, the overdispersed generalized linear model (oGLM), metagenomeSeq (mSeq), metastats and voom (see Additional file 12: Figure S8 for the additional eight methods)

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