[BioC] find DE by edgeR

[wang peter]

i try to find DE on each time point
by comparing treated vs control, such is coding
please help me to check if it is right?

thank you very much


group =factor(c('c0h','c0h','c0h','c24h','c24h','c24h','t0h','t0h','t0h','t6h','t6h','t6h','t6h','t12h','t12h','t12h','t12h','t18h','t18h','t18h','t18h',
             't24h','t24h','t24h','t36h','t36h','t36h','t48h','t48h','t48h','c6h','c12h','c18h','c36h','c48h'))
d <- DGEList(counts = d, lib.size = lib_size, group = group)

d <- calcNormFactors(d)

#To estimate common dispersion:
d <- estimateCommonDisp(d)
#To estimate tagwise dispersions:
d <- estimateTagwiseDisp(d)


#c0h vs t0h
et <- exactTest(d, pair=c("c0h","t0h"), dispersion="tagwise")
result <- topTags(et, n=dim(d)[1], adjust.method="BH", sort.by="p.value")
write.table(result,file = "t0h_c0h",sep = "\t")



-- 
shan gao
Room 231(Dr.Fei lab)
Boyce Thompson Institute
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