[BioC] DESeq/DESeq normalization on different experiments

[Ryan]

Hi Gilgi,

If you are not going to test for differential expression between 
experiments, then there is no purpose in normalizing them together. The 
more worrying problem with analyzing all your experiments as a single 
data set is that a single dispersion value will be estimated for each 
gene across all experiments. This is only ok if you believe that every 
gene has equal biological variability in all your experiments, which is 
unlikely to be the case.

-Ryan

On Thu May 22 01:26:55 2014, Gilgi [guest] wrote:
> Hello,
>
> I have ~100 RNA seq-samples from the same organism, but they include different experiments (each experiment of 6-16 samples). I would like to put all together into our RNA seq pipeline, that includes  mapping, htseq count and DESeq. Differential expression comparisons will be done of course only between samples of a single experiment (due to possible batch effects). However, will it be a good idea to normalize all samples together?
> The assumption behind the normalization is that most genes are not differentially expressed, but between different experiments the variability might be higher. Therefore I wanted to ask your opinion on doing the normalization on such a large combined data-set.
>
> Thank you,
> Gilgi
>
>   -- output of sessionInfo():
>
> none
>
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