In summary, the benchmarking tests showed that DESeq2 effectively controlled type-I errors, maintaining a median false positive rate just below the chosen critical value in a mock comparison of groups of samples randomly chosen from a larger pool. For both simulation and analysis of real data, DESeq2 often achieved the highest sensitivity of those algorithms that controlled the FDR.
