superpc.rainbowplot {superpc}R Documentation

Make rainbow plot of superpc and compeiting predictors

Description

Makes a heatmap display of outcome predictions from superpc, along with expected survival time, and values of competing predictors

Usage

 superpc.rainbowplot(data, pred, sample.labels,  competing.predictors, call.win.metafile=FALSE)

Arguments

data List of (test) data, of form described in superpc.train documentation
pred Superpc score from superpc.predict or superpc.predict.red
sample.labels Vector of sample labels of test data
competing.predictors List of competing predictors to be plotted
call.win.metafile Used only by Excel interface call to function

Details

Any censored survival times are estimated by E(T|T>C), where $C$ is the observed censoring time and the Kaplan-Meier estimate from the training set is used to estimate the expectation.

Author(s)

Eric Bair and Robert Tibshirani

Examples

set.seed(332)
x<-matrix(rnorm(1000*40),ncol=40)
y<-10+svd(x[1:60,])$v[,1]+ 5*rnorm(40)
censoring.status<- sample(c(rep(1,30),rep(0,10)))

ytest<- 10+svd(x[1:60,])$v[,1]+ 5*rnorm(40)
censoring.status.test<- sample(c(rep(1,30),rep(0,10)))

competing.predictors.test=list(pred1=rnorm(40), pred2=as.factor(sample(c(1,2),replace
=TRUE,size=40)))

featurenames <- paste("feature",as.character(1:1000),sep="")
data<-list(x=x,y=y, censoring.status=censoring.status, featurenames=featurenames)

data.test=list(x=x,y=ytest, censoring.status=censoring.status.test, featurenames=featurenames)

sample.labels=paste("te",as.character(1:40),sep="")

a<- superpc.train(data, type="survival")
pred=superpc.predict(a,data,data.test,threshold=.25, n.components=1)$v.pred

superpc.rainbowplot(data,pred, sample.labels,competing.predictors=competing.predictors.test)


[Package superpc version 1.05 Index]