Power estimates for vaccine studies for DEG detection
MINOR
To further evaluate the impact of different parameters on DEG identification, we assessed relative statistical power for different scenarios characterized by varying sample size (n=3 to n=15), effect size (1.25 to 2 minimum absolute fold change), and sequencing depth (10 to 60 M reads) (Relative power by sample size, effect size, and sequencing depth at each post-vaccination day as simulated using the modified PROPER R package. Days were sorted by decreasing vaccination effect based on overall fold changes and DEG responses observed for this study (see The power curves shown in First, the statistical power to detect TDEGs was remarkably higher for genes with larger effect sizes. For example, at Day 14, for genes with greater than 1.75-fold or 2-fold effect sizes, even at the lowest level of sample size evaluated (n=3) the statistical power was 55% and 68%, respectively. An increase in sample size to 10 or higher led to greater than 90% power for the detection of TDEGs with fold changes at or above 1.75 (Second, sequencing depth had a minor effect on power (Lastly, the false discovery rate (FDR), defined by the proportion of statistically significant genes that were not TDEGs, showed a strong dependence on the strength of the biological signal (The type-I-error rate, defined as the proportion of non-TDEGs that were declared statistically significant, was also evaluated (While the magnitude of the fold change for the TDEGs was fixed in this simulation, the variance of these genes was allowed to change based on each simulated coverage dataset. Since variance plays an important role in power—higher variance directly results in lower power, all else equal—we investigated whether the mean-variance relationship across genes was affected by the different sequencing depth. Overall, the mean-variance trends across genes were maintained for different sequencing depth considered in this simulation; the curves shift left with lower coverage to produce fewer total counts, but the trend of lowly-expressed genes having higher variance compared to highly-expressed genes persisted (