A transcriptome-based classifier to determine molecular subtypes in medulloblastoma
Fig 5
Classifier is able to distinguish SHH and WNT subtypes with higher accuracy than Group 3 and Group 4 subtypes.
A. Bar Chart showing percent Accuracy of classification algorithm across 15 medulloblastoma microarray datasets. The dotted red line represents the median accuracy of 97.8% across all datasets. B. Line plot of Sensitivity and Specificity of classification algorithm trellised by molecular subtype across 15 medulloblastoma microarray datasets. On average, the classifier is able to classify SHH (Avg. Sensitivity: 98.7%; Avg. Specificity: 99.3%) and WNT (Avg. Sensitivity: 100%; Avg. Specificity: 99.7%) with better accuracy as compared to Group 3 (Avg. Sensitivity: 95.1%; Avg. Specificity: 97.1%) and Group 4 (Avg. Sensitivity: 94.7%; Avg. Specificity: 98.8%).