Hi Jim, Thanks for taking the time to answer my query. Unfortunately my beginner skills do not allow me to modify the code of a package. I did find my way around by subsetting the "fit" object and plotting just the genes of interest with genas, which gave me a very nice view of what is happening within the subgroup of interest. In doing so, I came across another issue that I wasn't able to solve. When I plot the Venn diagram of those contrasts of interest vennDiagram((decideTests (fit.contrast[,c (5, 10, 14, 17, 19)], adjust.method = "none", method="separate", p.value=0.05)), include=c("up","down"), counts.col=c("red","green"))

Dear Christian, I think the 894 probes in your Venn diagram intersect are either up in all 5 contrasts or down in all 5 contrasts while the 1081 from the intersect of the topTable()s are either up or down in all 5 contrasts. Important difference and common pitfall... :-) Have you tried include = "both" in vennDiagram()? Cheers, - axel On Wed, Oct 16, 2013 at 12:30 PM, Christian De Santis < christian.desantis@stir.ac.uk> wrote: > Hi Jim, > > Thanks for taking the time to answer my query. Unfortunately my beginner > skills do not allow me to modify the code of a package. I did find my way > around by subsetting the "fit" object and plotting just the genes of > interest with genas, which gave me a very nice view of what is happening > within the subgroup of interest. In doing so, I came across another issue > that I wasn't able to solve. > > When I plot the Venn diagram of those contrasts of interest > > vennDiagram((decideTests (fit.contrast[,c (5, 10, 14, 17, 19)], > adjust.method = "none", method="separate", p.value=0.05)), > include=c("up","down"), counts.col=c("red","green")) > > From the above I get 894 genes at the intersection of the 5 groups. My > rationale is that I could isolate this group of probes by selecting the > common unique probenames. > > The function decideTests (method="separate") should be the equivalent of > topTable on individual coefficients and should give the same probes if > adjust.method is the same (Vignette, decideTests). Therefore: > > contrast.5 <- topTable(fit.contrast, adjust.method="none", coef=5, > number=20000, p.value = 0.05) > contrast.10 <- topTable(fit.contrast, adjust.method="none", coef=10, > number=20000, p.value = 0.05) > contrast.14 <- topTable(fit.contrast, adjust.method="none", coef=14, > number=20000, p.value = 0.05) > contrast.17 <- topTable(fit.contrast, adjust.method="none", coef=17, > number=20000, p.value = 0.05) > contrast.19 <- topTable(fit.contrast, adjust.method="none", coef=19, > number=20000, p.value = 0.05) > probes <- Reduce(intersect, list(contrast.5$ProbeName, > contrast.10$ProbeName, contrast.14$ProbeName, contrast.17$ProbeName, > contrast.19$ProbeName)) > > However this returns me a list of 1081 probes, not 894! I don’t understand > where I am doing this wrong. > > Any help is very appreciated. > > Regards, > Christian > > > sessionInfo() > R version 3.0.1 (2013-05-16) > Platform: i386-w64-mingw32/i386 (32-bit) > > locale: > [1] LC_COLLATE=English_United Kingdom.1252 LC_CTYPE=English_United > Kingdom.1252 LC_MONETARY=English_United Kingdom.1252 > [4] LC_NUMERIC=C LC_TIME=English_United > Kingdom.1252 > > attached base packages: > [1] grid stats graphics grDevices utils datasets methods > base > > other attached packages: > [1] ellipse_0.3-8 limma_3.16.7 > > loaded via a namespace (and not attached): > [1] bitops_1.0-6 tools_3.0.1 > > > -----Original Message----- > From: James W. MacDonald [mailto:jmacdon@uw.edu] > Sent: 15 October 2013 16:05 > To: Christian De Santis > Cc: bioconductor@r-project.org > Subject: Re: [BioC] Modify plot - genas function from LIMMA > > Hi Christian, > > The short answer is no. The longer answer is 'of course you can!'. And > thus is the nature of Open Source projects. > > The only argument to genas() that pertains to plots is whether or not you > want one. The remaining code is all 'hard coded' within the function, so > you are unable to effect any changes on the results by adding extra > arguments to the function call. > > However, you have access to the code, and can simply check it out of the > subversion repository, or if that sounds daunting you can always just > download the source package and work with that. > > And then all you have to do (easy for me to say) is modify genas() to your > liking, and then install your modified package. > > An alternative would be to make a really good argument to Gordon Smyth for > what you want to do, and hope that he buys your argument, and is motivated > enough to make the changes for you. > > Best, > > Jim > > > > On Tuesday, October 15, 2013 10:49:21 AM, Christian De Santis wrote: > > Hi everyone, > > > > I am using the function genas from the Limma package to calculate the > logFC correlation between some contrasts. > > > > genas(fit.contrast, coef = c(2,3), chooseMethod = "Fpval", plot = > > TRUE) > > > > I have isolated the list of DE probes in common between the contrasts of > interest and I would like to visualize these probes on the plots with a > different colour. Is there a way to do this directly on the plot generated > by genas? I am quite stuck on trying to enter the options of the plot > argument and impose these parameters. Any help would be very appreciated. > Thanks in advance. > > > > Regards, > > Christian > > > > > > -- > James W. MacDonald, M.S. > Biostatistician > University of Washington > Environmental and Occupational Health Sciences > 4225 Roosevelt Way NE, # 100 > Seattle WA 98105-6099 > > > > -- > The University of Stirling has been ranked in the top 12 of UK > universities for graduate employment*. > 94% of our 2012 graduates were in work and/or further study within six > months of graduation. > *The Telegraph > The University of Stirling is a charity registered in Scotland, number SC > 011159. > > _______________________________________________ > Bioconductor mailing list > Bioconductor@r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor -- Axel Klenk Research Informatician Information Management Drug Discovery Actelion Pharmaceuticals Ltd. • Gewerbestrasse 16 • CH-4123 Allschwil • Switzerland G12.O1.R10 VOIP 92 63 67 • phone +41 61 565 63 67 axel.klenk@actelion.com • www.actelion.com Address for visitors: Hegenheimermattweg 91 -- The information of this email and in any file transmitted with it is strictly confidential and may be legally privileged. 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