Dear Group, I have a question regarding the Volcano-plots which can be obtained after an analysis using the linear models in the limma package. In some cases I see a strange tailing phenomena in the Volcano-plot (x=M and y=eb$lods). I think this is a mathematical "artefact" and would appreciate if someone could explain this to me. This tailing looks like an inversed "normal distribution plot", and where I by inversed mean an up-side-down distribution plot with the lowest eb$lods values at M=0. The image is available as a pdf file at http://biobase.biotech.kth.se/~valtteri/R/VolcanoPlot.pdf What I noticed is that the features in this tail have their s2.post values equal to 0.0663 in the object obtained using the ebayes function of the limma package. In the image provided I have coloured all features with s2.post=0.0663 in red. Some background on the analysis I did: R version: 1.8.0 Limma version: 1.2.8 The data is background subtracted, filtered and normalised data from 5 slides with 30 000 features (no duplicates), stored in a numeric matrix, Ms fit <- lm.series(Ms, design=c(1,1,1,1,1)) eb <- ebayes(fit) M <- fit$coef # to get the M values plot(M, eb$lods) # to give the volcano-plot I'd really appreciate if someone could explain strange (?) behaviour to me. Thanks! best regards, Valtteri Contact information: Valtteri Wirta Department of Biotechnology, KTH AlbaNova University Center S - 10691 Stockholm, Sweden Visiting address: Roslagstullsbacken 21, B3 Phone: +46 8 5537 8344(office) Phone: +46 733 386 341 (gsm) Fax: +46 8 5537 8481 Email: valtteri@biotech.kth.se Web: www.biotech.kth.se/molbio

At 07:54 PM 6/11/2003, Valtteri Wirta wrote: >Dear Group, > >I have a question regarding the Volcano-plots which can be obtained after >an analysis using the linear models in the limma package. > >In some cases I see a strange tailing phenomena in the Volcano-plot (x=M >and y=eb$lods). I think this is a mathematical "artefact" and would >appreciate if someone could explain this to me. >This tailing looks like an inversed "normal distribution plot", and where >I by inversed mean an up-side-down distribution plot with the lowest >eb$lods values at M=0. >The image is available as a pdf file at >http://biobase.biotech.kth.se/~valtteri/R/VolcanoPlot.pdf > >What I noticed is that the features in this tail have their s2.post values >equal to 0.0663 in the object obtained using the ebayes function of the >limma package. In the image provided I have coloured all features with >s2.post=0.0663 in red. These genes have no degrees of freedom to estimate a standard deviation, presumably because 4 out of the 5 arrays have missing values for those genes. So the posterior standard deviation for those genes is set to the estimated prior standard deviation. So the t- and B-statistics for those genes are a function of the M-value only. So you see the mathematical pattern in the plot. Gordon >Some background on the analysis I did: >R version: 1.8.0 >Limma version: 1.2.8 >The data is background subtracted, filtered and normalised data from 5 >slides with 30 000 features (no duplicates), stored in a numeric matrix, Ms >fit <- lm.series(Ms, design=c(1,1,1,1,1)) >eb <- ebayes(fit) >M <- fit$coef # to get the M values >plot(M, eb$lods) # to give the volcano-plot > >I'd really appreciate if someone could explain strange (?) behaviour to me. > >Thanks! > >best regards, >Valtteri > > > > > > >Contact information: > >Valtteri Wirta >Department of Biotechnology, KTH >AlbaNova University Center >S - 10691 Stockholm, Sweden > >Visiting address: Roslagstullsbacken 21, B3 >Phone: +46 8 5537 8344(office) >Phone: +46 733 386 341 (gsm) >Fax: +46 8 5537 8481 >Email: valtteri@biotech.kth.se >Web: www.biotech.kth.se/molbio