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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.