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 


FDR_{QR}/FDR_{LR} 
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. 

Ho et al. BMC Genomics 2009 10(Suppl 3):S16 doi:10.1186/1471216410S3S16 