plotTDAUC: Title

In weiliu123/PCLassoCox: A protein complex-based group lasso-Cox model for accurate prognosis and risk protein complex discovery

Description

Title

Usage

plotTDAUC(rs, y, npoint = 50, col = "red")

Arguments

rs	Risk score of patients
y	The time-to-event outcome, as a two-column matrix or Surv object. The first column should be time on study (follow up time); the second column should be a binary variable with 1 indicating that the event has occurred and 0 indicating (right) censoring.
npoint	Integer: number of time points for calculating time-dependent AUC.
col	Color of the time-dependent AUC curve.

Examples

# load data
data(GBM)
data(PCGroup)

cv.fit1 <- cv.PCLasso(x = GBM$GBM.train$Exp,
                      y = GBM$GBM.train$survData,
                      group = PCGroup,
                      nfolds = 5)

# predict risk scores of samples in GBM.test
s <- predict(object = cv.fit1, x = GBM$GBM.test$Exp, type="link",
             lambda=cv.fit1$cv.fit$lambda.min)

plotTDAUC(rs = s, y = GBM$GBM.test$survData)

weiliu123/PCLassoCox documentation built on Dec. 23, 2021, 5:10 p.m.