R: DEG Poisson Fisher.test

DEG.test.R

set.seed(1026)
Cond1<-rpois(n=1000,lambda=5) #虽然用泊松分布模拟数据已经被吐槽了
Cond2<-rpois(n=1000,lambda=10)
df<-as.data.frame(cbind(cond1=Cond1,cond2=Cond2))
row.names(df)=paste("g",1:1000,sep="")
cond1Sum<-sum(df$cond1)
cond2Sum<-sum(df$cond2)
df$cond1Other<--df$cond1+cond1Sum
df$cond2Other<--df$cond2+cond2Sum
head (df)
df$pVals<-apply(df,1,fishtable)
df$WaltVals<-apply(df,1,Wald.test)
plot(density(df$WaltVals))


fishtable<-function(x){
   cond1<-x[1]
   cond2<-x[2]
   cond1oth<-x[3]
   cond2oth<-x[4]
   testFisher<-data.frame(gene=c(cond1,cond2),not.gene=c(cond1oth,cond2oth))
   row.names(testFisher)=c("cond1","cond2")
   f<-fisher.test(testFisher)
   return(f$p.value)
   }


Wald.test<-function(x){
  cond1<-x[1]
  cond2<-x[2]
  wald.value<-(cond1-cond2)/(sqrt(cond1+cond2))
  return(wald.value)
}