CNCDriver: CNCDriver

library(ggplot2)
library(ggrepel)
#library("RColorBrewer")
#library(plyr)
#library(ggpubr)
#library(gridExtra)

makeQQplot<-function(outputDf){

outputDf<-outputDf[order(outputDf$pValue),]
outputDf$padj<-p.adjust(outputDf$pValue,method="BH")


threshold<-0.1
#outputDf<-outputDf[outputDf$geneSymbol!="TTN",]
hitNum<-nrow(outputDf[outputDf$padj<threshold,])
cat(sprintf("hit number: %s\n",hitNum))

#####

pvector<-outputDf$pValue
#names(pvector)<-outputDf$geneSymbol
names(pvector)<-outputDf$elementPos
observed = -log10(sort(pvector,decreasing=F))
expected = -log10( 1:length(observed)/length(observed) )
#axisMax<-max(max(observed),max(expected))

idx<-seq(1,length(observed))
geneSymbol<-names(observed)
padj<-outputDf$padj
df<-data.frame(geneSymbol,expected,observed,idx,padj,stringsAsFactors = FALSE)

#df$group<-rep(tumorType,nrow(df))
#dd[[tumorType]]<-df
#dd<-rbind.fill(dd)


#filePath<-workDir
#fileName="df_debug.txt"
#fileName<-file.path(filePath,fileName)
#write.table(df,fileName,sep="\t",quote=FALSE,row.names = FALSE,col.names = TRUE)


#df2<-head(df,30)

#idx<-seq(1,length(observed))
#geneSymbol<-names(observed)
#padj<-outputDf$padj

#label<-rep(paste("nearest ",distCutOff*100," %",sep=""),nrow(outputDf))
#label<-rep(paste("nearest ",categoryRankCutOff*100," %",sep=""),nrow(outputDf))
#label<-rep(distCutOff,nrow(outputDf))


#df[[i]]<-data.frame(geneSymbol,expected,observed,idx,padj,label,stringsAsFactors = FALSE)


#}

#df.combined<-rbind.fill(df)
#x<-as.factor(df.combined$label)
#x<-factor(x,levels(x)[c(1:9)])
#print(levels(x))
#df.combined$triMutMatch<-x

#df2<-head(df,30)

threshold<-0.1
#axisMax<-max(max(observed),max(expected))+0.05
axisMax<-7+0.05

####
df$group<-rep("notSignificant",nrow(df))

if(sum(df$padj<=threshold)>0){
df[df$padj<=threshold,]$group<-"significant"
}
####


#pdf(paste(workDir,"/",tumorType,"_",mutationType,"_qqplot_iter_",reSampleNum,"_w_label.pdf",sep=""))

#zp1 <- ggplot(df,
#              aes(x = expected, y = observed, group=label, colour=triMutMatch))

zp1 <- ggplot(df,
              aes(x = expected, y = observed))


zp1 <- zp1 + labs(x = expression(Expected~~-log[10](italic(p))), y = expression(Observed~~-log[10](italic(p))))
zp1 <- zp1 + xlim(0,axisMax) + ylim(0,axisMax)

zp1 <- zp1 + scale_color_manual(values=c("black","red"))
#zp1 <- zp1 + ggtitle(paste("QQ plot for ",tumorType," [ iterations: ",reSampleNum," ]\n",mutationType," ",groupName,sep=""))
#zp1 <- zp1 + ggtitle(paste(tumorType," [ iterations: ",reSampleNum," ]\n",mutationType,", ","q-value= ",threshold,sep=""))

#zp1 <- zp1 + labs(title=paste(tumorType,", [ q-value = ",threshold," ]",sep=""),
#                  subtitle=paste(mutationType,", replication timing: ",replicationTimingCutOff,sep=""))

zp1 <- zp1 + labs(title=paste(tumorType,sep=""))
#                  subtitle=paste(mutationType,sep=""))

zp1 <- zp1 + geom_abline(intercept = 0, slope = 1, colour="grey",linetype="solid")
#zp1 <- zp1 + geom_abline(intercept = 0, slope = 1, colour="red",linetype="dotted")

zp1 <- zp1 + geom_line(size = 0.5, alpha=0.7)
zp1 <- zp1 + geom_point(aes(color=factor(group)),size=1.8,shape=20)
#zp1 <- zp1 + geom_point(data=subset(df,padj>threshold),
#                        aes(color="black"),size=1.5,shape=20,alpha=0.7)
#zp1 <- zp1 + geom_point(shape = 20, size = 1.5, alpha=0.7)



#zp1 <- zp1 + scale_color_gradient(low="red",high="grey")
#zp1 <- zp1 + scale_color_manual(values=brewer.pal(n=9,name="RdBu"))
#zp1 <- zp1 + geom_abline(intercept = 0, slope = 1, colour="red",linetype="dotted")
#zp1 <- zp1 + geom_abline(intercept = 0, slope = 1, colour="grey",linetype="solid")
#zp1 <- zp1 + geom_abline(intercept = 0, slope = 1, colour="red",linetype="dotted")


#zp1 <- zp1 + facet_wrap(~group)

#zp1 <- zp1 + geom_text(aes(label=rownames(df)),hjust=0, vjust=0)
#zp1 <- zp1 + geom_text_repel(aes(label=ifelse(idx<=10,as.character(rownames(df)),'')),hjust=0, vjust=0,angle=(-45))

if(hitNum<50){
zp1 <- zp1 + geom_text_repel(data=subset(df,padj<threshold),
                             aes(label=geneSymbol),
                             fontface="plain",
                             segment.color="grey",
                             size = 5,
                             box.padding = unit(0.35, "lines"),
                             point.padding = unit(0.3, "lines"),
                             force=10)
}

zp1 <- zp1 + theme_bw()

zp1<- zp1 + theme(axis.text = element_text(size = 10),
                  #axis.title = element_text(size = 7, face="bold"),
                  axis.title.x = element_text(size=7),
                  axis.title.y = element_text(size=7),
                  #axis.title.x = element_blank(),
                  #axis.title.y = element_blank(),
                  #panel.border = element_rect(linetype = "solid", colour = "black"),
                  panel.border = element_blank(),
                  panel.grid.major = element_blank(), 
                  panel.grid.minor = element_blank(),
                  panel.background = element_blank(),
                  axis.line=element_line(colour="black"),
                  plot.title = element_text(lineheight=1.5, face="bold",size=10,hjust=0.5),
                  plot.subtitle = element_text(lineheight=1.5, face="bold",size=7,hjust=0.5),
                  legend.position="none")
                  #legend.position = c(0.65,0.2),
                  #legend.background = element_rect(color = NA, 
                  #                                 fill = "transparent", size = 1, linetype = "solid"),
                  #legend.text = element_text(size = 7, colour = "black", angle = 0))

print(zp1)



if(FALSE){

#filePath<-paste("~/work/Ekta_lab/compositeDriver_July_2017_analysis/result_plots",mutationType,tumorType,paste("RT_",replicationTimingCutOff,sep=""),sep="/")
filePath<-paste("~/work/Ekta_lab/cncdriver_analysis_Mar_2018/result_plots",mutationType,"combined",paste("RT_",replicationTimingCutOff,sep=""),sep="/")


if( !file.exists(paste(filePath,sep="/")) ){
  dir.create(paste(filePath,sep=""),recursive=TRUE)
}

fileName<-paste(tumorType,"_",mutationType,".pdf",sep="")
fileName<-file.path(filePath,fileName)

#ggsave(paste(filePath,"/",runMethod,"_",tumorType,"_",mutationType,"_",groupName,"_qqplot_iter_",reSampleNum,"_RT_",replicationTimingCutOff,"_q_threshold_",threshold,"_w_labels.png",sep=""),width=140,height=133,unit="mm",dpi=120)
ggsave(paste(filePath,"/",runMethod,"_",tumorType,"_",mutationType,"_",groupName,"_qqplot_iter_",reSampleNum,"_RT_",replicationTimingCutOff,"_q_threshold_",threshold,"_w_labels.pdf",sep=""),width=240,height=200,unit="mm",dpi=120,useDingbats=FALSE)

}

####

}