zmatrix: zmatrix

Description Usage Arguments Value Author(s) Examples

Description

generate a matrix of c statistics

Usage

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


    cvSubsetFun = cvSubsets, covar = NULL)

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

covar

other covariates to be added as predictors

Value

outputs one matrix of validation statistics

Author(s)

Yuqing Zhang, Christoph Bernau, Levi Waldron

Examples

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library(curatedOvarianData)


library(GenomicRanges)


data(E.MTAB.386_eset)


data(GSE14764_eset)


esets.list <- list(E.MTAB.386=E.MTAB.386_eset[1:100, 1:30], GSE14764=GSE14764_eset[1:100, 1:30])


rm(E.MTAB.386_eset, GSE14764_eset)





## 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 <- rep(0, length(cens.chr))


  cens[cens.chr=="living"] <- 1


  return(Surv(time, cens))


})





# generate on original ExpressionSets


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





# generate on simulated ExpressionSets


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


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





# support matrix


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


  return(exprs(eset)) ### columns represent samples !!


}) 


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)

zhangyuqing/simulatorZ documentation built on Oct. 21, 2020, 1:05 a.m.