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 αl = 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:10.1186/1471-2164-10-S3-S16

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