## ----style, echo = FALSE, results = 'asis'-------------------------------
BiocStyle::markdown()


## ------------------------------------------------------------------------
library(BubbleTree)
data(hetero.gr) #loads sequence variants
data(cnv.gr) #loads copy number variation data


## ------------------------------------------------------------------------
rbd=getRBD(hetero.gr,cnv.gr)


## ------------------------------------------------------------------------
plotBubbles(rbd)


## ----, eval=FALSE--------------------------------------------------------
## library(VariantAnnotation)
## vc=readVcf("MyN_TSamples.vcf",genome="hg19")
## fq=geno(vc)$FREQ
## freq <- data.frame(fq)
## freq[,] <- as.numeric(gsub("%", "", as.matrix(freq[,])))/100
## colnames(freq)=paste(colnames(freq),"freq",sep=".")


## ----, eval=FALSE--------------------------------------------------------
## dp=geno(vc)$DP
## colnames(dp)=paste(colnames(dp),"dp",sep=".")
## #combine all with chr and position info
## snp.dat=data.frame("CHROM"=as.vector(seqnames(vc)),
##                    "POS"=start(vc),freq,dp)
## 


## ----, eval=FALSE--------------------------------------------------------
## is.hetero <- function(x, a=0.4, b=0.6) {
##   (x - a)  *  (b - x) >= 0
## }
## 
## snp.ss=subset(snp.dat, ! CHROM %in% c("chrX", "chrY") & normal.dp >= 15 &  is.hetero(normal.freq, 0.4, 0.6))


## ----, eval=FALSE--------------------------------------------------------
## library(GRanges)
## snp.gr <- GRanges(snp.ss$CHROM, IRanges(snp.ss$POS, snp.ss$POS), mcols=snp.ss[,"tumor.freq"])
## names(elementMetadata(snp.gr))[grep(".freq",names(elementMetadata(snp.gr)))]<-"freq"


## ----, eval=FALSE--------------------------------------------------------
## library(DNAcopy)
## #create a CNA object
## CNA.object <- CNA(demo.eCNV$logR, demo.eCNV$chr,
##                   demo.eCNV$probe_end, data.type = "logratio", sampleid = "test")
## #smooth
## smoothed.CNA.object <- smooth.CNA(CNA.object)
## #segment
## seg=segment(smoothed.CNA.object)


## ----, eval=FALSE--------------------------------------------------------
## library(GenomicRanges)
## min.num <- 10
## cnv.gr <- with(subset(seg$output, num.mark >= min.num & ! chrom %in% c("chrX", "chrY")) , GRanges(chrom, IRanges(loc.start, loc.end), mcols=cbind(num.mark, seg.mean)))
## 


## ------------------------------------------------------------------------
library(BubbleTree)
data(hetero.gr) 
data(cnv.gr)
rbd=getRBD(snp.gr=hetero.gr,cnv.gr=cnv.gr)
head(rbd)


## ------------------------------------------------------------------------
drawBranches()


## ------------------------------------------------------------------------
plotBubbles(rbd)


## ------------------------------------------------------------------------
pur <- calc.prev(rbdx=rbd,heurx=FALSE,modex=3,plotx="prev_model.pdf")
# extract the genotype (branch) and frequency for each segment
 head(pur[[1]]$ploidy_prev)
# tumor purity
 pur[[2]][nrow(pur[[2]]),2]


## ----drawBubble_example--------------------------------------------------
drawBranches(main="Demo")
drawBubble(0.5, 0.3, 5000, "blue", info="PTEN", size=2, adj=-0.5)


## ----compareBubbles_example----------------------------------------------
data(hcc.rbd.lst)


## ------------------------------------------------------------------------
with(hcc.rbd.lst, compareBubbles(HCC11.Primary.Tumor, HCC11.Recurrent.Tumor, min.dist=0.05, min.mark=2000))


## ------------------------------------------------------------------------
with(hcc.rbd.lst, compareBubbles(HCC4.Recurrent.Tumor, HCC11.Recurrent.Tumor, min.dist=0.0, max.dist=0.1, min.mark=500))