Charles Determan Jr | 26 Jun 05:19 2013
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Re: Repeated Measures mRNA expression analysis

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@...> 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@...>
>> To: bioconductor@...
>> 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
>>
>
> ______________________________**______________________________**__________
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