ROC analysis of selected signal cut-off values as a predictor for specific hybridization. ROC curves demonstrate the capacity to discriminate between the absence or presence of sequence-specific hybridization in individual microarray experiments. The closer an ROC curve is to the upper left hand corner of the graph, the more accurate it is because the true positive rate is 100% and the false positive rate is 0%. ROC plots based on percentile rank calculations for 25 cut-off signal thresholds (taken from table 1). The meaning of the position of thresholds a-d (table 1) are explained in the text. The area under the ROC curve was (A) 0.994 (array 1) and (B) 0.999 (array 2). Rising diagonal indicates no discrimination between positiv and negative control signals.