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Table 2 AUC performance of DFC test, t-test, and shrinkage t-test

From: Distributional fold change test – a statistical approach for detecting differential expression in microarray experiments

GEO data set N s AUC for MAS5 pre-processed data AUC for RMA pre-processed data
   t-test ShrinkTa DFC t-test ShrinkTa DFC
GSE8441 22 0.92912 0.94404 0.96996 0.91206 0.92842 0.96812
GSE9499 22 0.96425 0.98255 0.98529 0.94735 0.97241 0.9718
GSE2639 14 0.99782 0.99838 0.9987 0.99851 0.99784 0.99896
GSE2638 7 0.79197 0.83621 0.86199 0.75527 0.82421 0.83175
GSE3860 18 0.98986 0.99581 0.99742 0.98647 0.99246 0.99568
GSE6344 20 0.97165 0.98078 0.98854 0.97586 0.98216 0.9889
GSE7765 6 0.96323 0.97846 0.98564 0.96267 0.98146 0.98939
GSE6740_1 20 0.99491 0.99676 0.99701 0.9972 0.99803 0.99803
GSE6740_2 20 0.99115 0.99313 0.99283 0.97599 0.98248 0.98487
GSE6011 37 0.86072 0.8674 0.90942 0.97544 0.98126 0.97892
GSE2531 7 0.91614 0.94288 0.9379 0.93889 0.94368 0.94107
Averageb   0.9718 0.9812 0.9857 0.9745 0.9815 0.9861
  1. AUC performance of DFC test, t-test, and shrinkage t-test on MAS5 and RMA pre-processed data from data sets described in Table1. Ns is the number of samples in the set. aShrinkT -test values were calculated with CAT-test[14], option ‘diagonal’. bAverage was calculated for logit transformed AUC values, LTA = 0.5ln(AUC/(1-AUC)) and then transformed back to AUC scale.