On Thu, Jul 30, 2009 at 2:13 AM, Stephen V. Su <svs8@yahoo.com> wrote:

> To whom this may concern:
>
>     I must first apologize for not being a bioinformaticist and really only
> "pretend" to know how to use R to analyze microarray.  But i do understand
> the concepts of Limma and when to apply it.  I think it is a really
> powerful way to analyze matrix data.  So, if you don't mind, I would like to
> ask you a question regarding Venn Diagrams.  I have generated a
> RMA-processed expression set for 3 different conditions (each condition has
> a minimum of 8 CEL files- Affy 0.5 genome rat chip), fed it through limma to
> create a statistical computation of all the genes that are differentially
> expressed and created a venn Diagram to depict the results.  A general input
> functions of what i just wrote is depicted here:
>
>
> > fit <- lmFit(x, design)
>
> > cont.matrix <- makeContrasts(x3Dvsinvivo = x3D - invivo,
> + x3Dvsx2D = x3D - x2D,
> + x2Dvsinvivo = x2D - invivo, levels = design)
> > fit2 <- contrasts.fit(fit, cont.matrix)
> > fit2 <- eBayes(fit2)
> > results <- decideTests(fit2)
> > vennDiagram(results)
>
> My question is:  How do I extract out the genes that reside in each of the
> quadrant in the Venn diagram?  Is there a way for me to say, retrieve the
> 108 genes that are unique to condition A, 98 genes unique to condition B and
> C, and so on ....


Hi, Steve.  The answer is in the help system.  If you read the help for
decideTests, you will see that the value from a call to decideTests is an
object of class "TestResults".  Doing help("TestResults-class") will tell
you that an object of class "TestResults" can be treated like a matrix.  It
also has a few methods, one of which is the summary method.  So, try:

summary(result)

Does that help?

Sean

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