Dear List, I suddenly understood that had happened and just thought I would let you know. ordinary.t has two columns; > ordinary.t[1:3,] (Intercept) specificstageA 117_at 34.92382 1.7682627 1552264_a_at 39.52028 -1.5384353 1552277_a_at 23.21122 -1.6098082 so I made the mistake to plot both of these at the same time. Sorry to take up your time, and thanks for your replys! Best, Boel ----- Original Message ----- From: Wolfgang Huber <huber@ebi.ac.uk> Date: Friday, July 25, 2008 5:11 pm Subject: Re: [BioC] Link to picture: Comparison of diff. t-statistics, Limma and rowttests To: Boel Brynedal <boel.brynedal at="" ki.se=""> Cc: bioconductor at stat.math.ethz.ch > > Dear Boel > > How does the "pairs" plot look like for the matrix with rows = genes, > columns = three different ways of computing t? > > Can you single out the data for one particular gene where you get a > bigdifference (e.g. where ordinary.t is so large) and trace back > how the > computations in lmFit produce that result? > > Best wishes > Wolfgang > > ------------------------------------------------------------------ > Wolfgang Huber EBI/EMBL Cambridge UK http://www.ebi.ac.uk/huber > > > 25/07/2008 12:19 Boel Brynedal scripsit > > Dear List, > > > > Thank you (Wolfgang and Paolo) for telling me the attachment did > not get > > through. This is a link to the picture: > > http://picasaweb.google.se/Boelbubblan/Statistics/photo > > > > Cheers, > > Boel > > > > --~*~**~***~*~***~**~*~-- > > Boel Brynedal, MSc, PhD student > > Karolinska Institutet > > Department of Clinical neuroscience > > > > > > ----- Original Message ----- > > From: Boel Brynedal <boel.brynedal at="" ki.se=""> > > Date: Friday, July 25, 2008 9:33 am > > Subject: Comparison of diff. t-statistics, Limma and rowttests > > To: bioconductor at stat.math.ethz.ch > > > >> Dear List, > >> > >> I have affy hgu133plus2 arrays from individuals with disease, in > two>> different stages of the disease. I've earlier used rowttests > and FDR > >> correction. Now I was playing around with limma to see what I > could do > >> (added different covariates etc) but also investigated the most > simple>> setting, comparing the two different stages directly using > Limma. The > >> first thing that struck me was that limma "finds" only half the > amount>> of significantly diff expressed genes. So I started to > look at the > >> t-statistics from limma. Then I stumbled across this: when I do a > >> qq-plot of the ordinary t-statistics they are far from normally > >> distributed, and actually totally strange. See attached plot > comparing>> the ordinary t, the moderate t (both from Limma) as > well as t- > >> statisticsfrom rowttests ("Diff_tStatistics_Limma.jpg"). > >> > >> Am I doing something completely wrong? The assumption of equal > >> variancetaken using ordinary t could not create this, could it? > >> Please help me > >> figure out what's wrong here, I'm hoping I've done some stupid > >> mistake.What else could explain this? Thank you. > >> > >> Best wishes, > >> Boel > >> > >> My code and sessionInfo: > >> > >> # eset is a filtered, gcrma normalized ExpressionSet with ~10 > 000 > >> probesets, 24 arrays. > >> library(limma) > >> library(Biobase) > >> library(genefilter) > >> specific<-factor(c(rep("stageA",10),rep("stageB",14)), > >> levels=c("stageB","stageA")) > >> design<-model.matrix(~specific) > >> fit<-lmFit(eset,design) > >> Fit<-eBayes(fit) > >> > >> ordinary.t <- fit3$coef / fit3$stdev.unscaled / fit3$sigma > >> moderate.t<-Fit$t[,2] > >> rowttests.t<-rowttests(eset,fac=specific) > >> > >> par(mfrow=c(1,3)) > >> qqnorm(ordinary.t,main="fit ordinary.t") > >> qqnorm(moderate.t, main=" Fit moderate.t") > >> qqnorm(rowttests.t[,1], main= "rowttests.t") > >> dev2bitmap("Diff_tStatistics_Limma.jpg",type="jpeg", height = 5, > >> width = > >> 15, res = 75) > >> > >>> sessionInfo() > >> R version 2.7.1 (2008-06-23) > >> x86_64-unknown-linux-gnu > >> > >> locale: > >> ... > >> > >> attached base packages: > >> [1] splines tools stats graphics grDevices utils > >> datasets[8] methods base > >> > >> other attached packages: > >> [1] genefilter_1.20.0 survival_2.34-1 Biobase_2.0.1 > limma_2.14.5>> > >> loaded via a namespace (and not attached): > >> [1] annotate_1.18.0 AnnotationDbi_1.2.2 DBI_0.2-4 > >> [4] RSQLite_0.6-9 > >> > >> --~*~**~***~*~***~**~*~-- > >> Boel Brynedal, MSc, PhD student > >> Karolinska Institutet > >> Department of Clinical neuroscience > >> > >> > > > > _______________________________________________ > > Bioconductor mailing list > > Bioconductor at stat.math.ethz.ch > > https://stat.ethz.ch/mailman/listinfo/bioconductor > > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor