fig2c.R

library(data.table)
library(ggplot2)
library(grid)
library(gridExtra)
library(ggpubr)
library(ggplotify)

data <- read.csv("/Users/mar/BIO/PROJECTS/APOBEC/NONBDNA/Denek3/united_X0.txt",sep='\t',header = TRUE)
data <- data.table(data)
setnames(data,c("cancer","structure","isAPOBEC","sample","trgIn","cntIn","trgOut","cntOut","trgOutOld","cntOutOld","sign"))
data[sign < 5 | sign > 95, signBinary:=1]
data[is.na(signBinary), signBinary := 0]
data$signBinary <- as.factor(data$signBinary)
data[, ratio := log((cntIn/trgIn)/(cntOut/trgOut))]

activity <- read.csv("/Users/mar/BIO/PROJECTS/PCAWG_APOBEC/PCAWG_enrichment_6cancers.txt",sep='\t',header=FALSE,strip.white =TRUE)
activity <- data.table(activity)
setnames(activity,c("project","sample","enrichment"))

data <- merge(data,activity,by="sample",all.x = TRUE)
data[, densityIn := cntIn / trgIn]
data[, densityOut := cntOut / trgOut]
data[, densRatio := densityIn/densityOut]

data[enrichment >= 2.0 & structure == "dr", min(densityIn/densityOut)]

nonAnonS <- copy(data)
nonAnonS <- nonAnonS[isAPOBEC==0]
nonAnonS[,trg := trgOut]
nonAnonS[,cnt := cntOut]
nonAnonS[,type := "nonAnonS"]

nonAinS <- copy(data)
nonAinS <- nonAinS[isAPOBEC==0]
nonAinS[,trg := trgIn]
nonAinS[,cnt := cntIn]
nonAinS[,type := "nonAinS"]

isAnonS <- copy(data)
isAnonS <- isAnonS[isAPOBEC==1]
isAnonS[,trg := trgOut]
isAnonS[,cnt := cntOut]
isAnonS[,type := "isAnonS"]

isAinS <- copy(data)
isAinS <- isAinS[isAPOBEC==1]
isAinS[,trg := trgIn]
isAinS[,cnt := cntIn]
isAinS[,type := "isAinS"]

dt <- rbind(nonAnonS,nonAinS,isAnonS,isAinS)

structures <- unique(data$structure)
cancers <- unique(data$cancer)

plots <- list()

dt <- dt[!is.na(enrichment)]

i <- 1
for(s in structures)
{
  for(c in cancers)
  {
      dt2 <- dt[cancer==c & structure == s]
      dt2[,sampleEnrich := paste0(sample,'__',round(enrichment,2))]
      sampleLevels <- unique(dt2[order(enrichment),sampleEnrich])
      dt2$sampleEnrich <- factor(dt2$sampleEnrich,levels=sampleLevels)
      dt2$enrichment <- as.factor(as.character(round(dt2$enrichment,2)))
      
      p <- ggplot(dt2,aes(x=enrichment,y=cnt/trg,fill=type)) + geom_bar(stat="identity",position="dodge") +
        theme(panel.background = element_blank(),
              axis.text.x = element_text(size=8),
              axis.title = element_blank(),
              axis.line = element_line(color="black"),
              legend.position = "none") +
        scale_fill_manual(values=c(rgb(203,73,123,maxColorValue = 255), 
                                   rgb(161,201,171,maxColorValue = 255), 
                                   rgb(242,234,102,maxColorValue = 255),
                                   rgb(139,197,229,maxColorValue = 255)))
      
      
      if(c %in% c("BLCA","CESC"))
         wd <- 150
      else if(c == "BRCA")
         wd <- 450
      else if(c == "HNSC")
        wd <- 300
      else if(c == "LUAD")
        wd <- 250
      else if(c == "LUSC")
        wd <- 300
      else
        wd <- 150
        
        ggsave(paste0("/Users/mar/BIO/PROJECTS/APOBEC/NONBDNA/pics/fig2/c/",s,"_",c,"_.tiff"),plot=p,width=wd,height=50,units="mm",dpi=300)
      
      plots[[i]] <- as.grob(p)  
      i <- i + 1
    
  }
}

#lay <- rbind(c(1,2),
#             c(3,4),
#             c(5,6),
#             c(7,8),
#             c(9,10))

#plts <- marrangeGrob(grobs=plots, nrow=5, ncol=1, top=NULL) 
#ggexport(plts,filename="/Users/mar/BIO/PROJECTS/APOBEC/NONBDNA/Denek2/resultsNEWmy.pdf")