Figure 2
From: SPACE: an algorithm to predict and quantify alternatively spliced isoforms using microarrays
Influence of noise on splicing structure prediction for BIRC5 gene (synthetic data). (a) The effect of additive noise on splicing structure prediction. The y-axis shows the Hamming distance error rate between real and predicted pre-mRNA splicing structures. This measure represents the proportion of probes in a gene that were mistakenly assigned (or unassigned) to each transcript. The units of the x-axis are the variances σ ε 2 of the additive error as explained in Figure 1a. (b) Sensitivity of the SPACE algorithm under additive noise. Sensitivity is defined as the proportion of probes that belong to each transcript that are correctly assigned in the predicted structure. (c) Specificity of the SPACE algorithm under additive noise. Specificity is defined as the proportion of probes that do not belong to a particular transcript that are correctly unassigned in the predicted structure. (d) Multiplicative noise effect on splicing structure prediction. The y-axis shows the Hamming distance error rate between real and predicted pre-mRNA splicing structures. The units of the x-axis are the variances σ η 2 of the multiplicative error as explained in Figure 1b. (e) Sensitivity of SPACE under multiplicative noise. (f) Specificity of SPACE under multiplicative noise. The Hamming distance error rate is calculated in the form of HD = (FP + FN)/N, the sensitivity is calculated as SN = TP/(TP + FN) and the specificity is calculated as SP = TN/(TN + FP).