simulatorZ (version 1.6.0)

simTime: simTime

Description

simTime is a function to perform the parametric-bootstrap step, where we use the true coefficients

and cumulative hazard to simulate survival and censoring.

Usage

simTime(simmodels, result)

Arguments

simmodels

a list in the form of the return value of simData()

which consists of three lists:

obj: a list of ExpressionSets, matrices or RangedSummarizedExperiments

setsID: a list of set labels indicating which original set the simulated one is from

indices: a list of patient labels to tell which patient in the original set is drawn

result

a list in the form of return of getTrueModel()

which consists of five lists:

Beta: a list of coefficients obtained by

grid: timeline grid corresponding to hazard estimations censH and survH

survH: cumulative hazard for survival times distribution

censH: cumulative hazard for censoring times distribution

lp: true linear predictors

Value

Examples

library(curatedOvarianData)


data(GSE17260_eset)


data(E.MTAB.386_eset)


data(GSE14764_eset)


esets <- list(GSE17260=GSE17260_eset, E.MTAB.386=E.MTAB.386_eset, GSE14764=GSE14764_eset)


esets.list <- lapply(esets, function(eset){


  return(eset[1:500, 1:20])


})





## simulate on multiple ExpressionSets


set.seed(8) 





y.list <- lapply(esets.list, function(eset){


  time <- eset$days_to_death


  cens.chr <- eset$vital_status


  cens <- c()


  for(i in seq_along(cens.chr)){


    if(cens.chr[i] == "living") cens[i] <- 1


    else cens[i] <- 0


  }


  y <- Surv(time, cens)


  return(y)


})





# To perform both parametric and non-parametric bootstrap, you can call simBootstrap()


# or, you can divide the steps into:


res <- getTrueModel(esets.list, y.list, 100)


simmodels <- simData(obj=esets.list, y.vars=y.list, n.samples=10)





# Then, use this function


simmodels <- simTime(simmodels=simmodels, result=res) 





# it also supports performing only the parametrc bootstrap step on a list of expressionsets


# but you need to construct the parameter by scratch


res <- getTrueModel(esets.list, y.list, 100)


setsID <- seq_along(esets.list)


indices <- list()


for(i in setsID){


  indices[[i]] <- seq_along(sampleNames(esets.list[[i]])) 


}


simmodels <- list(obj=esets.list, y.vars=y.list, indices=indices, setsID=setsID)





new.simmodels <- simTime(simmodels=simmodels, result=res)