[BioC] DESeq/DESeq normalization on different experiments

[Gilgi Friedlander]

Thanks a lot!

-----Original Message-----
From: Michael Love [mailto:michaelisaiahlove at gmail.com] 
Sent: Thursday, May 22, 2014 6:10 PM
To: Ryan
Cc: Gilgi [guest]; Gilgi Friedlander; bioconductor at r-project.org
Subject: Re: [BioC] DESeq/DESeq normalization on different experiments

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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