Table 2

Overall ranking in terms of discriminant ability.

Type

avg. assigns.

avg. S_p

avg. S_n

Discriminant ability

OFDEG+GC (CP = 55%)

semi-supervised

63.65%

0.9400

0.9950

0.9675

OFDEG+GC

unsupervised

97.33%

0.9513

0.9525

0.9519

TF (CP = 75%)

semi-supervised

83.44%

0.9925

0.8925

0.9425

OFDEG+GC (CP = 75%)

semi-supervised

77.75%

0.8000

0.9625

0.8813

TF (CP = 55%)

semi-supervised

69.28%

1.0000

0.7450

0.8725

OFDEG

unsupervised

97.34%

0.9100

0.8300

0.8700

TF

unsupervised

97.34%

0.9905

0.6565

0.8235

Discriminant ability is given by the average of the sensitivity (S_n) and specificity (S_p) values. In this case, we take the average of the average specificity and sensitivity over all tests conducted. We see that both the unsupervised and semi-supervised methods which use OFDEG+GC as a feature space perform best overall with respect to the simMC tests. Though the semi-supervised method outperforms the unsupervised method, the average number of assignments made by the unsupervised variant is far greater.

Saeed and Halgamuge BMC Genomics 2009 10(Suppl 3):S10   doi:10.1186/1471-2164-10-S3-S10