Table 1.

Comparison of false discovery rate (FDR) of our quantile regression methods and linear regression methods using simulation data.

	DE					DV
FDR	DE2	DE5	DE5 + outliers	DE9	DE9 + outliers	DV	DV + outliers
Quantile Regression (QR)	0.021	0.040	0.049	0.082	0.151	0.017	0.023
Linear Regression (LR)	0.061	0.160	0.204	0.230	0.38	0.083	0.262
FDRQR/FDRLR	0.340	0.247	0.237	0.357	0.396	0.214	0.087

The FDRs of applying our quantile regression method to seven simulated datasets are compared to the corresponding FDRs of applying linear regression based methods to identify DE and DV genes at a predefined threshold of α = 0.05 (for quantile regression) and α_l = 0.05 (for linear regression). At this commonly accepted threshold, we found that our quantile regression method yields FDRs that are consistently about only one third of that the corresponding FDR when the linear regression approach is used.