inst/GSE47077/R/04.figures.R

In pneuvial/c3co: Cancer Cell Clonality using Copy-Number

##########################################################################
# Run c3co
##########################################################################
## We provide the results of the algorithm and the segmentation so if the user only wants to reproduce figure, run only this file

library(c3co)
library(RColorBrewer)

patient <- "RK29"
path <- "data"
#dat <- readRDS(sprintf("%s/dat-%s.rds", path ,patient))
output.dir <- R.utils::Arguments$getWritablePath(sprintf("results_c3co-%s",patient))
res <- list.files(output.dir, pattern="featureData")
lapply(file.path(output.dir, res), function(ff){
  print(ff)
  dat <- readRDS(ff)
  respf <- dat$res
  resPosFused <- new("posFused", S=list(Z=respf$Z, Z1=respf$Z1, Z2=respf$Z2), W=respf$W, E=list(Y1 = respf$Y.hat$Y1, Y2 = respf$Y.hat$Y2))
  res <- new("c3coClass", BIC=dat$BIC, PVE=dat$PVE, res=resPosFused, param=dat$param, bkp=dat$bkp)
  saveRDS(res, ff)
})

resC3co <- lapply(file.path(output.dir, res), readRDS)

### Plot PVE
pvePlot(resC3co, ylim=c(0.70,1))
dataBest <- resC3co[[6]]

### Plot W matrix
pathFig <- R.utils::Arguments$getWritablePath("fig-GSE47077-RK29")

pdf(file.path(pathFig,sprintf("heatmap,GSE47077,patient=%s.pdf",patient)), width=13, height=8)
Wplot(resC3co, idxBest=6, rownamesW= sprintf("R%s",1:nrow(dataBest@res@W)))
dev.off()

### Plot Latent profiles
pathCHR <-  system.file("inst", "GSE47077", "data","minMaxposByCHR.rds", package = "c3co")
minMaxPos <- readRDS(pathCHR)

lengthCHR <- sapply(dataBest@bkp, length)
chrs <- sapply(1:22, function(cc) rep(cc,times=lengthCHR[cc]))

start <- c(1,cumsum(lengthCHR)+1)

ch <- c(9)
df.CHR <- createZdf(resC3co, minMaxPos, chromosomes=ch, var="TCN", idxBest=6)
df.CHRC1 <- createZdf(resC3co, minMaxPos, chromosomes=ch, var="Minor", idxBest=6)
df.CHRC2 <- createZdf(resC3co, minMaxPos, chromosomes=ch, var="Major", idxBest=6)

df.CHR$position <- df.CHR$position/1e6
df.CHRC2$position <- df.CHRC2$position/1e6
df.CHRC1$position <- df.CHRC1$position/1e6

gArchTCN <- Zplot(df.CHR, ylab="TCN", ylim=c(1,3))
gArchC2 <- Zplot(df.CHRC2, ylab="Major", ylim=c(1,3))
gArchC1 <- Zplot(df.CHRC1, ylab="Minor", ylim=c(0,2))

ggsave(gArchTCN, filename=sprintf("%s/archetypes,GSE47077,patient=%s,chr=%s.pdf", pathFig, patient,ch), width=7, height=3.5)
ggsave(gArchC1, filename=sprintf("%s/archetypes,GSE47077,patient=%s,C1,chr=%s.pdf", pathFig, patient,ch), width=7, height=3.5)                    
ggsave(gArchC2, filename=sprintf("%s/archetypes,GSE47077,patient=%s,C2,chr=%s.pdf", pathFig, patient,ch), width=7, height=3.5)



ch <- c(14)
df.CHR <- createZdf( resC3co,minMaxPos, chromosomes=ch, var="TCN", idxBest=6)

df.CHRC1 <- createZdf( resC3co, minMaxPos, chromosomes=ch, var="Minor", idxBest=6)
df.CHRC2 <- createZdf( resC3co, minMaxPos, chromosomes=ch, var="Major", idxBest=6)

df.CHR$position <- df.CHR$position/1e6
df.CHRC2$position <- df.CHRC2$position/1e6
df.CHRC1$position <- df.CHRC1$position/1e6

gArchTCN <- Zplot(df.CHR, ylab="TCN")
gArchC2 <- Zplot(df.CHRC2, ylab="Major")
gArchC1 <- Zplot(df.CHRC1, ylab="Minor")
ggsave(gArchTCN, filename=sprintf("%s/archetypes,GSE47077,patient=%s,chr=%s.pdf", pathFig, patient,ch), width=7, height=3.5)
ggsave(gArchC1, filename=sprintf("%s/archetypes,GSE47077,patient=%s,C1,chr=%s.pdf", pathFig, patient,ch), width=7, height=3.5)                    
ggsave(gArchC2, filename=sprintf("%s/archetypes,GSE47077,patient=%s,C2,chr=%s.pdf", pathFig, patient,ch), width=7, height=3.5)