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Table 4 The mean and standard deviation (in parenthesis) of sensitivity, specificity and area under curve (AUC) calculated for conventional differential gene expression analysis: DEA, dwgLASSO with no prior biological knowledge incorporated: dwgLASSO (no prior), KDDN, and dwgLASSO with prior biological knowledge incorporated: dwgLASSO (prior)

From: Incorporating prior biological knowledge for network-based differential gene expression analysis using differentially weighted graphical LASSO

Methods

Testing dataset 1

Testing dataset 2

 

Specificity

Sensitivity

AUC

Specificity

Sensitivity

AUC

DEA

0.950 (0.07)

0.913 (0.06)

0.951 (0.04)

0.950 (0.07)

0.941 (0.04)

0.983 (0.01)

dwgLASSO (no prior)

0 . 9 8 8 ( 0 . 0 3 )

0.888 (0.11)

0.972 (0.02)

0 . 9 8 8 ( 0 . 0 3 )

0.956 (0.05)

0.990 (0.01)

KDDN

0.963 (0.08)

0 . 9 5 0 ( 0 . 0 4 )

0.980 (0.02)

0.963 (0.08)

0.939 (0.03)

0.989 (0.01)

dwgLASSO (prior)

0 . 9 8 8 ( 0 . 0 3 )

0.950 (0.07)

0 . 9 8 2 ( 0 . 0 3 )

0 . 9 8 8 ( 0 . 0 3 )

0 . 9 6 5 ( 0 . 0 3 )

0 . 9 9 4 ( 0 . 0 1 )

  1. The best performance is marked in bold