Table 2

The minet algorithm

PARAMETER (MINET)

AUC(ROC)

YOUDEN

AUC(PvsR)


clr, mi.empirical, equalfreq

0.80

0.54

0.05

clr, mi.empirical, equalwidth

0.76

0.45

0.04

clr, mi.mm, equalfreq

0.80

0.54

0.05

clr, mi.mm, equalwidth

0.76

0.48

0.04

clr, mi.shrink, equalfreq

0.80

0.53

0.05

clr, mi.shrink, equalwidth

0.74

0.41

0.04

clr, mi.sg, equalfreq

0.80

0.54

0.05

clr, mi.sg, equalwidth

0.74

0.42

0.04

clr, pearson, none

0.78

0.49

0.05

clr, spearman, none

0.80

0.53

0.05

clr, kendall, none

0.80

0.53

0.05

mrnet, mi.empirical, equalfreq

0.82

0.59

0.04

mrnet, mi.empirical, equalwidth

0.76

0.47

0.05

mrnet, mi.mm, equalfreq

0.81

0.57

0.04

mrnet, mi.mm, equalwidth

0.77

0.46

0.05

mrnet, mi.shrink, equalfreq

0.81

0.57

0.04

mrnet, mi.shrink, equalwidth

0.73

0.39

0.04

mrnet, mi.sg, equalfreq

0.81

0.57

0.04

mrnet, mi.sg, equalwidth

0.77

0.47

0.06

mrnet, pearson, none

0.78

0.49

0.04

mrnet, spearman, none

0.82

0.58

0.03

mrnet, kendall, none

0.81

0.56

0.03

aracne, mi.empirical, equalfreq

0.76

0.52

0.01

aracne, mi.empirical, equalwidth

0.54

0.12

0.02

aracne, mi.mm, equalfreq

0.76

0.52

0.01

aracne, mi.mm, equalwidth

0.54

0.12

0.02

aracne, mi.shrink, equalfreq

0.76

0.52

0.01

aracne, mi.shrink, equalwidth

0.55

0.14

0.02

aracne, mi.sg, equalfreq

0.76

0.52

0.01

aracne, mi.sg, equalwidth

0.54

0.12

0.02

aracne, pearson, none

0.54

0.07

0.03

aracne, spearman, none

0.76

0.52

0.01

aracne, kendall, none

0.76

0.52

0.01


Overview on the results of the summary statistics from the ROC analysis for the different parameter (implemented scoring schemes and measures for noise level 0.0) in the minet package.

Hempel et al. BMC Bioinformatics 2011 12:292   doi:10.1186/1471-2105-12-292

Open Data