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TCGA_DGE_SMD_meta.R
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TCGA_DGE_SMD_meta.R
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source("https://raw.githubusercontent.com/Shicheng-Guo/GscRbasement/master/GscTools.R")
library("meta")
library("metafor")
library("survival")
library("survminer")
Symbol2ENSG<-function(Symbol){
db<-read.table("https://raw.githubusercontent.com/Shicheng-Guo/AnnotationDatabase/master/ENSG.ENST.ENSP.Symbol.hg19.bed",sep="\t")
ENSG<-as.character(db[match(Symbol,db$V4),8])
ENSG<-na.omit(data.frame(Symbol,ENSG))
return(ENSG)
}
ENSG2Symbol<-function(ENSG){
db<-read.table("https://raw.githubusercontent.com/Shicheng-Guo/AnnotationDatabase/master/ENSG.ENST.ENSP.Symbol.hg19.bed",sep="\t")
ENSG<-unlist(lapply(strsplit(ENSG,split="[.]"),function(x) x[1]))
Symbol<-db[match(as.character(ENSG),db$V8),4]
return(Symbol)
}
ensg2bed<-function(ENSG){
db<-read.table("https://raw.githubusercontent.com/Shicheng-Guo/AnnotationDatabase/master/hg19/ENSG.ENST.hg19.txt",as.is=T,head=F)
ENSG<-unlist(lapply(strsplit(ENSG,split="[.]"),function(x) x[1]))
bed<-unique(db[db$V5 %in% as.character(ENSG),c(1,2,3,5)])
return(bed)
}
load("~/hpc/methylation/Pancancer/RNA-seq/rnaseqdata.pancancer.RData")
TCGAProjects=c("BLCA","BRCA","CESC","CHOL","COAD","ESCA","GBM","HNSC","KICH","KIRC","KIRP","LIHC","LUAD","LUSC","PAAD","PCPG","PRAD","READ","SARC","STAD","THCA","THYM","UCEC")
panc<-read.table("https://raw.githubusercontent.com/Shicheng-Guo/PANC/master/extdata/panc.txt",head=T)
phen1=read.table("https://raw.githubusercontent.com/Shicheng-Guo/PANC/master/extdata/TCGA-clinical-11093.tsv",header = T,sep="\t")
phen2=read.table("https://raw.githubusercontent.com/Shicheng-Guo/PANC/master/extdata/File_metadata2.txt",header = T,sep="\t")
head(phen1)
head(phen2)
colnames(rnaseqdata)<-unlist(lapply(strsplit(colnames(rnaseqdata),"/"),function(x) x[2]))
phen<-data.frame(phen2,phen1[match(phen2$cases.0.case_id,phen1$case_id),])
phen$file_name=gsub(".gz","",phen$file_name)
# prepare phenotype information
phen<-phen[match(colnames(rnaseqdata),phen$file_name),]
phen$phen4<-id2phen4(phen$cases.0.samples.0.submitter_id)
phen$phen3<-id2phen3(phen$cases.0.samples.0.submitter_id)
phen$phen2<-id2bin(phen$cases.0.samples.0.submitter_id)
phen$pid<-phen$project_id
head(phen)
OS<-read.table("https://raw.githubusercontent.com/Shicheng-Guo/HowtoBook/master/TCGA/OverallSurvivalTime.txt",head=T,sep="\t")
# match survival information
idx<-which(c(phen$phen2==1))
phen<-phen[idx,]
input<-rnaseqdata[,idx]
input[1:5,1:5]
idx<-na.omit(match(OS$submitter_id,phen$phen3))
input<-log(input[,idx]+1,2)
phen<-phen[idx,]
phen<-data.frame(phen,OS[match(phen$phen3,OS$submitter_id),])
phen$censored<-as.numeric(!phen$censored)
phen$week=phen$time/7
i=grep("ENSG00000231246",rownames(input)) # PANC246
i=grep("ENSG00000213754",rownames(input)) # PANC754
i=grep("ENSG00000181896",rownames(input)) # ZNF101
i=grep("ENSG00000131849",rownames(input)) # ZNF132
i=grep(Symbol2ENSG("NCOA4")[1,2],rownames(input)) # NCOA4
i=grep(Symbol2ENSG("SLC7A11")[1,2],rownames(input))# SLC7A11
i=grep(Symbol2ENSG("SAT2")[1,2],rownames(input)) # SAT2
i=grep(Symbol2ENSG("GSS")[1,2],rownames(input)) # GSS
i=grep("ENSG00000120256",rownames(input)) # LRP11
xii<-read.table("https://raw.githubusercontent.com/Shicheng-Guo/ferroptosis/master/codependency.txt",as.is=T)[,1]
xii<-read.table("https://raw.githubusercontent.com/Shicheng-Guo/ferroptosis/master/ferroptosis.genelist.txt",sep="\t",as.is=T)[,2]
xii<-read.table("https://raw.githubusercontent.com/Shicheng-Guo/ferroptosis/master/SLC7A11.codependency.txt",as.is=T)[,1]
xii<-read.table("https://raw.githubusercontent.com/Shicheng-Guo/breast/master/extdata/brca.tcga.target.hg19.bed",sep="\t",as.is=T)[,4]
xii<-read.table("https://raw.githubusercontent.com/Shicheng-Guo/cholangiocarcinoma/master/cholangiocarcinoma.hg19.bed",sep="\t",as.is=T)[,4]
xii<-read.table("https://raw.githubusercontent.com/Shicheng-Guo/drugtarget/master/extdata/2993drugtarget.txt",sep="\t",as.is=T)[,1]
xii<-read.table("https://raw.githubusercontent.com/Shicheng-Guo/encode/master/TFBS/685TFBS.txt",sep="\t",as.is=T)[,1]
# mkdir /mnt/bigdata/Genetic/Projects/shg047/meta/tfbs/
# mkdir /mnt/bigdata/Genetic/Projects/shg047/meta/tfbs/os
# mkdir /mnt/bigdata/Genetic/Projects/shg047/meta/tfbs/dge
setwd("/mnt/bigdata/Genetic/Projects/shg047/meta/drug")
setwd("/mnt/bigdata/Genetic/Projects/shg047/meta/tfbs/dge")
setwd("/mnt/bigdata/Genetic/Projects/shg047/meta/tfbs/os")
ENSG<-Symbol2ENSG(as.character(xii))
xgene<-c(as.character(ENSG[,2]))
ii<-unique(unlist(lapply(xgene,function(x) grep(x,rownames(input)))))
out2<-c()
z<-1
for(i in ii){
z<-z+1
HR<-c()
for(TCGAProject in TCGAProjects){
newdata<-input[,phen$project_id==paste("TCGA-",TCGAProject,sep="")]
xphen<-phen[phen$project_id==paste("TCGA-",TCGAProject,sep=""),]
dat<-data.frame(Rna=newdata[i,],xphen)
thres<-mean(dat[,1],na.rm=T)
#dat$Rna[dat$Rna<=thres]<-0
#dat$Rna[dat$Rna>thres]<-1
hr.fit<-summary(coxph(Surv(week,censored)~Rna,dat))
hr1=hr.fit$coefficients[1,]
hr2=hr.fit$conf.int[1,]
HR<-rbind(HR,c(hr1,hr2[3],hr2[4]))
fit <- survfit(Surv(week,censored)~Rna, data = dat)
# survp<-ggsurvplot(fit, data = dat,conf.int = F,pval = TRUE,
# fun = "pct",risk.table = TRUE,size = 1,linetype = "strata",
# palette = c("#2E9FDF","#E7B800"),
# legend = "bottom",legend.title = rownames(input)[i],
# legend.labs = c("Low-expression","High-expression"))
# ggsave(file = paste(ENSG2Symbol(rownames(input)[i]),"-",rownames(input)[i],"_",TCGAProject,"_KM.pdf",sep=""), survp$plot)
}
print(c(z,i))
rownames(HR)<-TCGAProjects
m<-metagen(HR[,1],seTE=HR[,3],comb.fixed = TRUE,comb.random = TRUE,prediction=F,sm="HR")
fixedEffect<-c(exp(m$TE.fixed),exp(m$lower.fixed),exp(m$upper.fixed),m$pval.fixed)
randomEffect<-c(exp(m$TE.random),exp(m$lower.random),exp(m$upper.random),m$pval.random)
out2<-rbind(out2,c(fixedEffect,randomEffect))
if(! is.na(fixedEffect[4]) & fixedEffect[4]<0.000001){
pdf(paste(ENSG2Symbol(rownames(input)[i]),"-",rownames(input)[i],".OS.HR.PANC.pdf",sep=""))
print(rownames(input)[i])
forest(m,leftlabs = rownames(HR),
lab.e = "Intervention",
pooled.totals = FALSE,
smlab = "",studlab=rownames(HR),
text.random = "Overall effect",
print.tau2 = FALSE,
col.diamond = "blue",
col.diamond.lines = "black",
col.predict = "red",
print.I2.ci = TRUE,
digits.sd = 2,fontsize=9,xlim=c(0.2,3))
dev.off()
write.table(HR,file=paste(ENSG2Symbol(rownames(input)[i]),"-",rownames(input)[i],".OS.HR.EACH.txt",sep=""),sep="\t",quote=F,col.names=NA,row.names=T)
}
}
colnames(out2)<-c("TE.fixed","lower.fixed","upper.fixed","pval.fixed","TE.random","lower.random","upper.random","pval.random")
rownames(out2)<-rownames(input)
write.csv(out2,file=paste("pancancer.tfbs.rnaseq.","OS.HR.csv",sep=""),quote=F)
write.table(out2,file=paste("pancancer.tfbs.rnaseq.","OS.HR.txt",sep=""),quote=F,sep="\t",col.names=NA,row.names=T)