plotROC {transcriptR} | R Documentation |
Visualize the performance of the classification model fit (prediction of the gene associated peaks).
plotROC(object, ...) ## S4 method for signature 'ChipDataSet' plotROC(object, ...)
object |
A |
... |
Further arguments passed to plot. |
The plotROC
is a simple wrapper for the plot
function
implemented in pROC
package.
The ROC curve is created by plotting the true positive rate (sensitivity) against the false positive rate (1 - specificity) at various threshold settings. The closer the curve follows the left-hand border and then the top border of the ROC space, the more accurate the test. The area under the curve (AUC) is a measure of accuracy.
ROC plot.
Armen R. Karapetyan
### Load ChipDataSet object data(cds) ### Classify peaks on gene associated and background predictTssOverlap(object = cds, feature = "pileup", p = 0.75) ### Visualize the performance of the model fit plotROC(object = cds, col = "red3", grid = TRUE, auc.polygon = TRUE)