simData {clusterExperiment} | R Documentation

## Simulated data for running examples

### Description

Simulated data for running examples

### Format

Three objects are loaded, two data frame(s) of simulated data each with 300 samples/columns and 153 variables/rows, and a vector of length 300 with the true cluster assignments.

### Details

`simData` is simulated normal data of 300 observations with 51 relevant variables and the rest of the variables being noise, with observations being in one of 3 groups. `simCount` is simulated count data of the same dimensions. `trueCluster` gives the true cluster identifications of the samples. The true clusters are each of size 100 and are in order in the columns of the data.frames.

### Author(s)

Elizabeth Purdom epurdom@stat.berkeley.edu

### Examples

    #code used to create data:
    ## Not run:
    nvar<-51 #multiple of 3
    n<-100
    x<-cbind(matrix(rnorm(n*nvar,mean=5),nrow=nvar),
     matrix(rnorm(n*nvar,mean=-5),nrow=nvar),
              matrix(rnorm(n*nvar,mean=0),nrow=nvar))
    #make some of them flipped effects (better for testing if both sig under/over
    #expressed variables)
    geneGroup<-sample(rep(1:3,each=floor(nvar/3)))
    gpIndex<-list(1:n,(n+1):(n*2),(2*n+1):(n*3))
    x[geneGroup==1,]<-x[geneGroup==1,unlist(gpIndex[c(3,1,2)])]
    x[geneGroup==2,]<-x[geneGroup==2,unlist(gpIndex[c(2,3,1)])]

    #add in differences in variable means
    smp<-sample(1:nrow(x),10)
    x[smp,]<-x[smp,]+10

    #make different signal y
    y<-cbind(matrix(rnorm(n*nvar,mean=1),nrow=nvar),
             matrix(rnorm(n*nvar,mean=-1),nrow=nvar),
             matrix(rnorm(n*nvar,mean=0),nrow=nvar))
    y<-y[,sample(1:ncol(y))]+ matrix(rnorm(3*n*nvar,sd=3),nrow=nvar)

    #add together the two signals
    simData<-x+y

    #add pure noise variables
    simData<-rbind(simData,matrix(rnorm(3*n*nvar,mean=10),nrow=nvar),
                   matrix(rnorm(3*n*nvar,mean=5),nrow=nvar))
    #make count data
    countMean<-exp(simData/2)
    simCount<-matrix(rpois(n=length(as.vector(countMean)), lambda
    =as.vector(countMean)+.1),nrow=nrow(countMean),ncol=ncol(countMean))
    #labels for the truth
    trueCluster<-rep(c(1:3),each=n)
    save(list=c("simCount","simData","trueCluster"),file="data/simData.rda")

    ## End(Not run)

[Package clusterExperiment version 2.12.0 Index]