Can I apply DESeq to techinical replicates??

[Sora Yoon]

Hi guys,

I've been dealing with RNA-seq count data consisting of several technical replicates.
And I tried to normalize the data using DESeq.
However, the DESeq author suggested to apply DESeq to biological replicates not to technical replicates.
Anyone knows the reason for this??
Why can't I apply DESeq normalization to my technical replicates????

Also, is there any method to normalize a technical replicates effectively??

Thank you for reading.

[bastianwur]

The normalization is meant to take the biological variations into account, IIRC.
The variance in the technical replicates will be lesser than in biological replicates, therefore the normalization will not have the right impact (less, I'd guess).

If you're sure that there is no big biological variation between your tested subjects, then I guess it might not matter too much at the end, but I'd be cautious about the results.

[Sora Yoon]

a confused point...

Thanks for your reply. But I thought that DESeq normalization simply adjusts each column's library size for further analysis. So, I thought that I could use DESeq to technical replicates if there there is library size difference between each of the samples. Do I have some misunderstandings???

[Sora Yoon]

a confused point...

The normalization is meant to take the biological variations into account, IIRC.
The variance in the technical replicates will be lesser than in biological replicates, therefore the normalization will not have the right impact (less, I'd guess).

If you're sure that there is no big biological variation between your tested subjects, then I guess it might not matter too much at the end, but I'd be cautious about the results.

Thanks for your reply. But I thought that DESeq normalization simply adjusts each column's library size for further analysis. So, I thought that I could use DESeq to technical replicates if there there is library size difference between each of the samples. Do I have some misunderstandings???

[fanli]

Simon and others can correct me if I'm wrong, but the per-library normalization strategy taken by DESeq should be applicable to technical replicates as well. It is the model for differential expression that models biological variance rather than technical.

You should also know that technical variance in RNA-seq is generally considered trivial compared to biological..

[dpryan]

The normal method is to simply sum the counts across technical replicates and use those. In fact, this is also by far the most legitimate method to deal with technical replicates, unless you want to use a tool that implements mixed-effects modeling (and then you get to deal with all of the annoyances of mixed-effects models). I would be surprised if not doing this didn't lead to aberrant results, even if you try to throw extra model terms in to compensate for the design aberrantly thinking it has more samples than it really does.

Edit: BTW, as fanli wrote, the library size normalization itself shouldn't have any issues.

[Caroline336]

Hi, maybe you can ask the professionals in CD Genomics, they can help you with your problem.