I have a question which is very important for me.
Basically I am buidling my condition like this
condition <- factor(c(rep("Normal", 10),rep("Tumor", 11)))
The values are count values and I want to know if I am doing the condition correct and if so, should I take the logarithm 2 myself before I use the standard method ?
I mean by standard method is dds <- DESeq(dds)
No, of course not! Why would you think that?
(Background: The DESeq manual states, as explicitly as possible and since the very first version, that the matrix should contain "read counts", i.e., integer numbers that count how many reads map to the gene. Nevertheless, I have been asked hundreds of time various variations of: I have RPKM values. Can I use these, too? My data has been normalized and now it's no longer integer. Can I still use hem? I have done [insert arbitrary mathematics operation] to my counts. I can still input this to DESeq, right? etc.
So, please use DESeq on read counts and only on read counts. And take a moment to recall the meaning of the word "count". ;-)
Sorry for the rant; you just triggered with your question my sort-of-annual reminder to this site about this issue.)
As for your condition: Do you have paired samples, i.e., on tumour and one normal sample per patient? If so, you need to let DESeq know which samples belong to the same patient. Read up on "paired designs" in the manual.
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version 2.3.6
@Simon Anders I did not mean to offend you. The problem is that if I use count , then I don't know if it will be normalized insdie the standard calculation or not. I read the vinegette very well but to be honest, I have never seen such an explanation, I even read their paper . That is why I ask here.
No they are not pair. so is my condition correct when I want to compare Treated versus Control ?
Thanks a lot for your comment