simulatorZ (version 1.6.0)

zmatrix: zmatrix

Description

generate a matrix of c statistics

Usage

zmatrix(obj, y.vars, fold, trainingFun = masomenos, cvFun = funCV, 
 cvSubsetFun = cvSubsets)

Arguments

obj

a list of ExpressionSet, matrix or RangedSummarizedExperiment objects.

If its elements are matrices, columns represent samples

y.vars

a list of response variables, all the response variables shold be

matrix, data.frame(with 2 columns) or Surv object

fold

cvFun parameter, in this case passes to funCV()

trainingFun

training function

cvFun

function to perform cross study within one set

cvSubsetFun

function to divide the expression sets into subsets for cross validation

Value

Examples

library(curatedOvarianData)


library(GenomicRanges)


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)


})





# generate on original ExpressionSets


z <- zmatrix(esets.list, y.list, 3)





# generate on simulated ExpressionSets


simmodels <- simBootstrap(esets.list, y.list, 10, 100)


z <- zmatrix(simmodels$obj.list, simmodels$y.vars.list, 3)





# support matrix


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


  newx <- exprs(eset) ### columns represent samples !!


  return(newx)


}) 


z <- zmatrix(X.list, y.list, 3)





# support RangedSummarizedExperiment


nrows <- 200; ncols <- 6


counts <- matrix(runif(nrows * ncols, 1, 1e4), nrows)


rowRanges <- GRanges(rep(c("chr1", "chr2"), c(50, 150)),


                     IRanges(floor(runif(200, 1e5, 1e6)), width=100),


                     strand=sample(c("+", "-"), 200, TRUE))


colData <- DataFrame(Treatment=rep(c("ChIP", "Input"), 3),


                     row.names=LETTERS[1:6])


sset <- SummarizedExperiment(assays=SimpleList(counts=counts),


                             rowRanges=rowRanges, colData=colData)





time <- sample(4500:4700, 6, replace=TRUE)


cens <- sample(0:1, 6, replace=TRUE)


y.vars <- Surv(time, cens)





z <- zmatrix(list(sset[,1:3], sset[,4:6]), list(y.vars[1:3,],y.vars[4:6,]), 3)