Outlier sensitivity We used simulations to compare the sensitivity and specificity of DESeq2’s outlier handling approach to that of edgeR, which was recently added to the software and published while this manuscript was under review. edgeR now includes an optional method to handle outliers by iteratively refitting the GLM after down-weighting potential outlier counts [34]. The simulations, summarized in Additional file 1: Figure S10, indicated that both approaches to outliers nearly recover the performance on an outlier-free dataset, though edgeR-robust had slightly higher actual than nominal FDR, as seen in Additional file 1: Figure S11.
