cancerTiming (version 1.0.0)

bootstrapEventTiming: Bootstrap the results of eventTiming

Description

Create bootstrap estimates of pi base on the results of a call to eventTiming.

Usage

bootstrapEventTiming(B,  type = c("parametric", "nonparametric"),call, pi, x, m)

Arguments

B

number of bootstrap samples to take

type

type of bootstrap confidence interval to calculate, one of ``parametric", ``nonparametric"

call

list with elements (given as `call' in the output of eventTiming): ``alleleSet", ``history", ``totalCopy", ``type", ``exactAllele", ``normCont", ``coverageCutoff", ``minMutations", ``init", ``maxiter", ``tol"

pi

the estimate of $pi$ from which to create bootstrap samples (if type="parametric" )

x

vector. the number of reads/fragments containing the variant; not needed if ``inputData'' included as part of call

m

vector. the number of reads/fragments covering the location with the variant (the coverage)

Value

• Matrix of dimension (B,length(pi)) with the estimate of pi for each of the bootstrap samples

Examples

##can do this within eventTiming function, but here is an example doing it separately...
data(mutData)
ACNLOH<-matrix(c(1,3,1,0),ncol=2,nrow=2,byrow=TRUE)
onlyMuts<-subset(mutData,is.na(rsID) & position <= 1.8E7)
onlyMuts$t_depth<-onlyMuts$t_ref_count+onlyMuts$t_alt_count
x<-eventTiming(x=onlyMuts$t_alt_count,m=onlyMuts$t_depth,history=ACNLOH,totalCopy=2,type="CNLOH",normCont=0.22)
piBoot<-bootstrapEventTiming(B=100,pi=x$pi,call=x$call,x=onlyMuts$t_alt_count,m=onlyMuts$t_depth,type="parametric")