getCCF: CCF estimation main function
In CHAT: Clonal Heterogeneity Analysis Tool

Description Usage Arguments Details Value Author(s) Examples

This is a wrapper for getSampleCCF() by allowing batch sample processing.

1 2	getCCF(VCFdir, sAGPfile, output = "new.vcf", nt = FALSE, nc = 10, tc = 11, AD = 3, filter = TRUE,TCGA=TRUE)

`VCFdir`	directory where the VCF file for all samples is saved.
`sAGPfile`	Rdata file saved by `getsAGP()`
`output`	name of output VCF file.
`nt`	logical, if multi-thread processing is applied. This option is system dependent.
`nc`	the column index in VCF file which coverage information for normal control sample is placed.
`tc`	the column index in VCF file which coverage information for tumor sample is placed.
`AD`	the index of Allele Depth field placed in a ';' deliminated string of sample coverage information.
`filter`	logical. If TRUE, the 'FILTER' column in the VCF file is assumed to have been pre-processed and for variants passed QC, this field is set 'PASS'.
`TCGA`	If you are working with The Cancer Genome Atlas datasets, set this to be TRUE. The sample identifier is assumed to be in format described in https://wiki.nci.nih.gov/display/TCGA/TCGA+Barcode

In the returned VCF, the field INFO is modified to include all the inferences. The additional fields in the INFO columns of the VCF file include (in exactly this order): sample ID, alternative allele count in tumor, total coverage in tumor, alternative allele count in control, total coverage in control, CCF estimation, standard deviation of CCF, sAGP, nb, nt and lineage scenario.

NULL. A new VCF file containing all the somatic mutations from all the VCF files will be generated.

Bo Li

## Not run: 
## This is not executable. User must create their own VCF directory.
VCFdir='VCF/'
## Slow. Run with caution.
data(A0SD.BAF)
data(A0SD.LRR)
## DNA segmentation
seg.dat=c()
for(CHR in c(8,9,10)){
	baf=A0SD.BAF[A0SD.BAF[,2]==CHR,]
	lrr=A0SD.LRR[A0SD.LRR[,2]==CHR,]
	x=getSegChr(baf,lrr)
	seg.dat=rbind(seg.dat,x)
}
dd.dat=seg.dat[,2:8]
rownames(dd.dat)=seg.dat[,1]
mode(dd.dat)='numeric'
save(dd.dat,file='A0SDseg.Rdata')
para=getPara()
para$datafile='A0SDseg.Rdata'
para$savefile='A0SD-AGP.txt'
para$is.normalize=FALSE
## AGP estimation
getAGP(para=para)
para.s=getPara.sAGP()
para.s$inputdata='A0SDseg.Rdata'
para.s$purityfile='A0SD-AGP.txt'
para.s$savedata='A0SD-sAGP.Rdata'
## sAGP estimation
getsAGP(para=para.s)
## CCF estimation
getCCF(VCFdir,'A0SD-sAGP.Rdata','A0SD-AGP.Rdata')

## End(Not run)