A question about EdgeR

[spacup]

Hi all,

I am trying to understand EdgeR...
I made a table of counts and used it in EdgeR.
I used the exact Test to compare condition 2 (3 replicates) with condition 3 (2 replicates):

et<-exactTest(y,pair=c("2","3"))

I then export the result :

write.table(et$table, "EgdeR_TMM.csv", sep="\t")

and I have a file with 2689 genes.

Are all that genes DE?
If yes, why some p-value are around 1 ?
Should I filter these genes by p-value? And which is the correct limit? 0.05? 0.5?

I found some comments from Simon Anders who says :

"You should not put thresholds on raw p values, but use an adjustment for multiple testing. edgeR (and DESeq) use the Benjamini-Hochberg (BH) procedure by default. If you want to cut BH-adjusted p values at 1%, you are unusually stringent. A commonly chosen threshold is 10%, but whether this is appropriate depends, of course, on what you want to do afterwards with the result."

and

"And just as a reminder: Don't even think about thresholding the raw p values in genomic experiments. This is nearly always nonsense[...]"

and

"The Benjamini-Hochberg adjustment, which formalizes this argument, will hence adjust a raw p value of 0.05 to an adjusted p value of 0.5."

Thus, I am a little bit lost....
If someone could enlighten me, I would be very grateful !
Thanks.