thanx Scott!
your suggestions work like a charm ...
and THANX TO ALL who responded to my inquiry. I appreciated ...
steve
________________________________
From: "Ochsner, Scott A"
Cc: bioconductor@stat.math.ethz.ch
Sent: Thursday, July 30, 2009 9:13:43 AM
Subject: RE: [BioC] venn diagram
Steve,
I don't remember exactly where I picked this bit of code up so I apologize for not giving credit. I'm almost sure I got it from looking at the mail archives. It uses the makeIndices function within affycoretools.
>vennDiagram(temp.results)
# make an index of all the probeIds with a TRUE call. As the default for vennCounts() is "both" (and you have implicitly called vennCounts() in your call to vennDiagram()), you need to use "both" in the makeIndices call.
alls<-affycoretools:::makeIndices(temp.results,"both")
>length(which(alls[[3]]==T))
#extract from alls those genes in your venn diagram.
>alls.genes<-lapply(alls,function(x)row.names(temp.results)[x])
or lapply(alls,function(x)fit2$genes$Name[x])
#test to see if the lists of all.genes agree with the venn diagram
>length(alls.genes[[1]])
>length(alls.genes[[2]])
etc...
>alls.genes[[3]]
[1] "1417023_a_at" "1417561_at" "1417580_s_at" "1417867_at"
Hope this helps,
Scott
Scott A. Ochsner, PhD
One Baylor Plaza BCM130, Houston, TX 77030
Voice: (713) 798-6227 Fax: (713) 790-1275
-----Original Message-----
From: bioconductor-bounces@stat.math.ethz.ch [mailto:bioconductor-bounces@stat.math.ethz.ch] On Behalf Of Stephen V. Su
Sent: Thursday, July 30, 2009 1:13 AM
To: bioconductor@stat.math.ethz.ch
Subject: [BioC] venn diagram
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 ....
Your help is greatly appreciated and I thank-you in advance of your considerations
Steve
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