<p><em>[this question has also been posted on <a href="https://www.biostars.org/p/452978/" rel="nofollow noreferrer">Biostars</a>; some additional clarification from there has been copied into this question]</em></p>
<p>I've been asked to analyse a set of samples in which their control sample has been done in duplicate (biological replicate) but the other samples have just one sample each.</p>
<p>The analysis purpose is just hypothesis generation for further experiment design. So, is it possible to have duplicate samples for one or two of the groups and use one sample for other groups? Could we estimate a constant dispersion from these replicates and apply it to all of the samples for differential gene expression analysis.</p>
<p>I'm using <code>EdgeR/Limma</code> for my differential gene expression analysis. When there are no replicates the <code>eBayes</code> function gives me an error. However, if I add a replicate to just one of the samples, it won't give any errors. Does this mean that it uses the calculated dispersion from the duplicate condition for all of the other one sample conditions? Or is it a bug that it doesn't give an <code>error</code>?</p>
<p>Should I consider this method of using duplicates for some samples instead of just using no replicates in such large experiments that are being done for hypothesis generation?</p>
<p>I have read the EdgeR <a href="https://www.bioconductor.org/packages/release/bioc/vignettes/edgeR/inst/doc/edgeRUsersGuide.pdf" rel="nofollow noreferrer">recommendations</a> (page 23-24) on what to do without (enough) replicates, but the explanation is not complete. Like it doesn't say how to find these housekeeping genes. About its first case of using a common fixed dispersion. I guess what I'm asking here is I'd like a more reliable measure of this common fixed dispersion. I say instead of using a theoretical dispersion why not try to estimate dispersion from the few duplicate samples and then use it for all the samples. I'm asking if someone has already done this thing and I'd like to know about their experience and how reloable could thing method be.</p>

CC BY-SA 4.0
2020-08-04T13:14:23.093Z
About the affordability is more expensive to do several inconclusive experiments than one well done. The term you are looking for are technical replicates it is a know and old method used (check the limma vignette).
llrs
CC BY-SA 4.0
2020-08-05T04:51:11.763Z
I don't mean techincal replicates. I meant biological replicates all along. But just part of my samples have biological replicates, others ones are done in one sample each.
Reza Rezaei
CC BY-SA 4.0
2020-08-05T04:53:53.460Z
@gringer this question asks if people had the same experience and how they handeld that. What I'm describing is what I'm working on now. There is a set of sample which their control sample has been done in duplicate but the other samples have just one sample each.
Reza Rezaei
<rna-seq><differential-expression><deseq2><edger><limma>
Differential Gene Expression with Replicates for some of the samples
# Differential Gene Expression with Replicates for some of the samples

(Asked by: username_0 on 2020-08-03)

*[this question has also been posted on [Biostars](https://www.biostars.org/p/452978/); some additional clarification from there has been copied into this question]*

I've been asked to analyse a set of samples in which their control sample has been done in duplicate (biological replicate) but the other samples have just one sample each.

The analysis purpose is just hypothesis generation for further experiment design. So, is it possible to have duplicate samples for one or two of the groups and use one sample for other groups? Could we estimate a constant dispersion from these replicates and apply it to all of the samples for differential gene expression analysis.

I'm using `EdgeR/Limma` for my differential gene expression analysis. When there are no replicates the `eBayes` function gives me an error. However, if I add a replicate to just one of the samples, it won't give any errors. Does this mean that it uses the calculated dispersion from the duplicate condition for all of the other one sample conditions? Or is it a bug that it doesn't give an `error`?

Should I consider this method of using duplicates for some samples instead of just using no replicates in such large experiments that are being done for hypothesis generation?

I have read the EdgeR [recommendations](https://www.bioconductor.org/packages/release/bioc/vignettes/edgeR/inst/doc/edgeRUsersGuide.pdf) (page 23-24) on what to do without (enough) replicates, but the explanation is not complete. Like it doesn't say how to find these housekeeping genes. About its first case of using a common fixed dispersion. I guess what I'm asking here is I'd like a more reliable measure of this common fixed dispersion. I say instead of using a theoretical dispersion why not try to estimate dispersion from the few duplicate samples and then use it for all the samples. I'm asking if someone has already done this thing and I'd like to know about their experience and how reloable could thing method be.

**Tags:** rna-seq, differential-expression, deseq2, edger, limma
> **Comments:**
> **username_1**: About the affordability is more expensive to do several inconclusive experiments than one well done. The term you are looking for are technical replicates it is a know and old method used (check the limma vignette).  
> **username_0**: I don't mean techincal replicates. I meant biological replicates all along. But just part of my samples have biological replicates, others ones are done in one sample each.  
> **username_0**: @gringer this question asks if people had the same experience and how they handeld that. What I'm describing is what I'm working on now. There is a set of sample which their control sample has been done in duplicate but the other samples have just one sample each.  

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## 0 answers

