zmatrix: zmatrix

In simulatorZ: Simulator for Collections of Independent Genomic Data Sets

Description

generate a matrix of c statistics

Usage

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

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)

simulatorZ documentation built on Nov. 8, 2020, 5 p.m.