Bioconductor

rawData <- ReadAffy()

eset <- mas5(rawData)

logEset <- log(exprs(eset))
group <- gl(4,5,20, labels=c("Ctrl", "Treat1", "Treat2", "Treat3"))

scores <- apply(logEset, 1, function(x){

  a <- anova(lm(x ~ group))

  b <- bartlett.test(x ~ group)

  m <- exp(max(x))

  c(median(x[1:5]), median(x[6:10]), median(x[11:15]), median(x[16:20]), m, a$Pr[1], b$p.value)

})
scores <- t(scores)

colnames(scores) <- c("Ctrl", "Treat1", "Treat2", "Treat3", "max", "p.value", "bartlett.p")
tNames <- names(sort(scores[scores[,6]<=0.01*1e-4 & scores[,5]>300 & scores[,7]>=0.05,6]))
tmpLL <- as.numeric(mget(tNames, env=rgu34aLOCUSID))　　# 追加

myLL <- unique(tmpLL[is.na(tmpLL)==FALSE])　　# 追加

xx <- GOHyperG(myLL, "rgu34a", "BP")　# 追加

for(x in names(xx$pvalues[xx$pvalues<1e-4])){

 cat(x, xx$pvalues[x], get(x, env=GOTERM), "\n")

}

なんてやったら、マイナスの p値がでる !! なぜだ?

GO:000nnnn -1.359037e-14 xxxxx metabolism

GO:0000mmm -6.789166e-15 zzzzz biosynthesis

GO:000pppp -4.786536e-15 yyyyy metabolism

GO:000qqqq 1.708106e-15 wwww biosynthesis 

結果それ自体は気持ち悪い位妥当なんだけどね。