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Question: To analyze the overall variance, which one to choose, vst or DESeq2 normalized counts?
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gravatar for Raymond
3 months ago by
Raymond0
Raymond0 wrote:

Hi, All,

    I have two groups of RNAseq data, each group have 5 samples. I suspected that drug treatment would increase the overall expression variances in some pathways. So, I planned to compare all gene expression variances in that pathway or even in the top 500 expressed genes. I could calculate the variance from DEseq2 normalized counts, or variance stabilization transformed counts (vst or rld). The question is: which one should I choose? Does the VST process affect the signal I want to analyze?

 

Thanks and best regards,

Raymond

ADD COMMENTlink modified 3 months ago by Alan0 • written 3 months ago by Raymond0

Hi Michael,

May I ask:

1) Could you specify a little bit more about what are the some of reasons for favoring VST over rlog?

2) To clarify, the VST procedure is just for purpose of clustering and visualization, right? It (the counts after VST) basically is not involved in testing for pairwise DE with the Wald test?

 

Thank you very much in advance. 

ADD REPLYlink written 3 months ago by Alan0

 Please check out the vignette and workflow sections on transformations. We cover both of these questions there.

ADD REPLYlink written 3 months ago by Michael Love18k

OK I see, thank you, Michael.

ADD REPLYlink written 3 months ago by Alan0
1
gravatar for Michael Love
3 months ago by
Michael Love18k
United States
Michael Love18k wrote:

I recommend the vst(). It will help you compare variances across genes. You could also use rlog() I just prefer vst() these days.

ADD COMMENTlink written 3 months ago by Michael Love18k

Thanks so much, Michael!  For 'across genes', do you mean the variances of genes in the same group?  I want to compare the variances of the same genes between different groups. In this case, dose vst also help?

ADD REPLYlink modified 3 months ago • written 3 months ago by Raymond0
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