Fig. 1From: Statistical evaluation of methods for identification of differentially abundant genes in comparative metagenomicsThe performance of detecting differentially abundant genes increases for large group sizes. For each method, the receiver operating characteristics curve shows the true positive rate (y-axis) and the false positive rate (x-axis) at each position in the gene ranking list. Panels a-c show results for the Qin dataset and panels d-f show results for the Yatsunenko dataset. Group sizes of 3 + 3, 6 + 6 and 10 + 10 were included in the comparison and the effect size was fixed at a fold-change of 5. Each curve is based 100 resampled metagenomes. The methods included are edgeR, DESeq2, the overdispersed generalized linear model (oGLM), metagenomeSeq (mSeq), metastats and voom (see Additional file 2: Figure S1 for the additional eight methods)Back to article page