R: Make rainbow plot of superpc and compeiting predictors

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 1.09 Index]