[BioC] Question about best analysis method for a complex array experiment design

[Gordon K Smyth]

Dear Agnes,

> Date: Wed, 08 Jan 2014 11:45:41 +0100
> From: Agnes Paquet <paquet at ipmc.cnrs.fr>
> To: bioconductor at r-project.org
> Subject: [BioC] Question about best analysis method for a complex
> 	array expriment design
>
> Dear List,
>
> I need to analyze an experiment with a design more complex than usual
> for our facility, and I am not sure about the best way to analyze this
> dataset. I would really appreciate your advice on whether the method I
> am planning to use is correct, or if there is a better way to analyze
> this data.
>
> The experiment design is the following:
> We have 10 patients, and we are using one-color Agilent arrays. Each
> patient performed a physical test twice: once without anything added,
> and once taking a drug during the test. Samples are collected before and
> after the physical test, for a total of 4 samples by patients. The drug
> was administered randomly during the first or second test.
>
> Here is the top of my target file:
>
> Patient.ID	TimePoint	Drug	TestOrder	Drug.Included.In.Test
> Pt1	Before	no	test1	control
> Pt1	After	no	test1	control
> Pt1	Before	no	test2	test
> Pt1	After	yes	test2	test
> Pt2	Before	no	test2	control
> Pt2	After	no	test2	control
> Pt2	Before	no	test1	test
> Pt2	After	yes	test1	test
>
> We are interested in finding:
> - DE genes related to physical test only
> - DE genes related to the addition of the drug only
> - Genes differentially regulated by the drug during the physical test
>
> I usually use limma for differential analysis, so following the limma
> user?s guide, I was planning to use a design with blocks of size 4 for
> patients, and a variable with 4 levels combining Drug.Included.In.Test
> and TimePoint.
>
> Is this approach correct?

Yes.

> I read in the user?s guide patient information could also be modeled as
> random effect using the duplicateCorrelation function. Would this method
> be more appropriate?

Would not give an advantage here (balanced design and only two 
patients).

> Is there a better way to model the data, that would estimate the
> physical test effect and the drug effect directly?

No.

Best wishes
Gordon

> Thank you very much for your help,
>
> Agnes

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