Question about best analysis method for a complex array experiment design
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@gordon-smyth
Last seen 9 hours ago
WEHI, Melbourne, Australia
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 ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}
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