[BioC] DESeq/DESeq normalization on different experiments

Michael Love michaelisaiahlove at gmail.com
Thu May 22 17:10:05 CEST 2014


hi Gilgi,

Yes I would second Ryan's recommendation to not normalize all the
experiments together.

Mike

On Thu, May 22, 2014 at 11:06 AM, Ryan <rct at thompsonclan.org> wrote:
> 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
>>
>> --
>> Sent via the guest posting facility at bioconductor.org.
>>
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>
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