Figure 6.

Quantile-quantile (Q-Q) plots for the goodness-of-fit of null-hypothesis P-values to an uniform distribution. Using the results displayed in Additional file 2: Figure S8 and performing as described by Leek et al. (2007) [20], for each gene, the distribution of P-values throughout the 100 simulations was tested for its goodness-of-fit to an uniform distribution using a Kolmogorov-Smirnov test. Q-Q plots in this figure show for all genes the resulting P-values of the previous test which, under the null hypothesis of no differential expression, should be uniformly distributed too and lead to lines lying on the diagonal. Panels a-b show results from female vs female comparisons and c-d from male vs male comparisons, while a,c correspond to un-normalized data and b,d to data normalized with the cqn[4]. The method introduced in this paper, tweeDEseq, is on average closer to the diagonal throughout the four simulations, closely followed by DESeq when sharingMode=~gene-est-only~ and either method=~per-condition~ or method=~pooled~.