Table 1. Confusion matrix or error matrix.

Predicted class	Actual class
	DE	EE
DE	True Positive (TP)	False Positive (FP) type I error
EE	False Negative (FN) (type II error)	True Negative (TN)
DE: Differentially Expressed; EE: Equally Expressed; Area under the receiving operating characteristics (ROC) curve, AUC = (nTPR+nTNR)/2, Misclassification error rate (MER) = (nFP+nFN)/ (nTP+nTN+nFP+nFN).