[BioC] Repeated Measures mRNA expression analysis

Gordon K Smyth smyth at wehi.EDU.AU
Wed Jun 26 06:11:32 CEST 2013


Are there only 2 biological units in your experiment?  (One for treatment 
and one for control?)  Or do you have multiple biological units in each 
group?  Surely it must be the latter but, if so, your model does not take 
this into account.

What questions do you want to test?


On Tue, 25 Jun 2013, Charles Determan Jr wrote:

> Gordon,
> I apologize for not being more definitive with my description.  Your
> initial definition is my intention, consecutive measurements on the same
> biological units.  I will look over the comments in the link you provided.
> Thank you for your insight, I appreciate any further thoughts you may have.
> Regards,
> Charles
> On Tue, Jun 25, 2013 at 6:57 PM, Gordon K Smyth <smyth at wehi.edu.au> wrote:
>> Dear Charles,
>> The term "repeated measures" describes a situation in which repeated
>> measurements are made on the same biological unit.  Hence the repeated
>> measurements are correlated.  It is not clear from the brief information
>> you give whether this is the case, or whether the different time points
>> derive from independent biological samples.
>> The model you give might or might not be correct, depending on the
>> experimental units and the hypotheses that you plan to test.  For most
>> experiments it is not the right approach, for reasons that I have pointed
>> out elsewhere:
>> https://www.stat.math.ethz.ch/**pipermail/bioconductor/2013-**
>> June/053297.html<https://www.stat.math.ethz.ch/pipermail/bioconductor/2013-June/053297.html>
>> Best wishes
>> Gordon
>>  Date: Mon, 24 Jun 2013 15:08:48 -0500
>>> From: Charles Determan Jr <deter088 at umn.edu>
>>> To: bioconductor at r-project.org
>>> Subject: [BioC] Repeated Measures mRNA expression analysis
>>> Greetings,
>>> I need to analyze data collected from an RNA-seq experiment.  This 
>>> consists of comparing two groups (control vs. treatment) and repeated 
>>> sampling (1 hour, 2 hours, 3 hours).  If this were a univariate 
>>> problem I know I would use a 2-way rmANOVA analysis but this is 
>>> RNA-seq and I have thousands of variables.  I am very familiar with 
>>> multiple packages for RNA differential expression analysis (e.g. 
>>> DESeq2, edgeR, limma, etc.) but I have been unable to figure out what 
>>> the most appropriate way to analyze such data in this circumstance. 
>>> The closest answer I can find within the DESeq2 and edgeR manuals 
>>> (limma is somewhat confusing to me) is to place to main treatment of 
>>> interest at the end of the design formula, for example:
>>> design(dds) <- formula(~ time + treatment)
>>> Is this what is considered the appropriate way to address repeated
>>> measures
>>> in mRNA expression experiments?  Any thoughts are appreciated.
>>> Regards,
>>> --
>>> Charles Determan
>>> Integrated Biosciences PhD Candidate
>>> University of Minnesota
> -- 
> Charles Determan
> Integrated Biosciences PhD Candidate
> University of Minnesota

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