Hello, I have a 2-colour microarray experiment with a complex design. I would like to visualise the estimated coefficients and associated error with the most significant genes that come out as result of LIMMA (lmfit, contrasts.fit, eBayes). I thought that it should be stdev.unscaled, but this seems to be the same for all the genes, which I don't think makes much sense. What is an appropriate way to calculate the estimated error associated with a coefficient? Many thanks Dan -- ************************************************************** Daniel Brewer, Ph.D. Institute of Cancer Research Molecular Carcinogenesis Email: daniel.brewer at icr.ac.uk ************************************************************** The Institute of Cancer Research: Royal Cancer Hospital, a charitable Company Limited by Guarantee, Registered in England under Company No. 534147 with its Registered Office at 123 Old Brompton Road, London SW7 3RP. This e-mail message is confidential and for use by the a...{{dropped:2}}

Dear Dan, stdev.unscaled needs to be scaled by the residual standard error for each gene (hence the name), so to get standard errors for the coefficients you need: se.coef <- sqrt(fit$s2.post) * fit$stdev.unscaled The moderated t-statistics are just fit$coef / se.coef. Best wishes Gordon > Date: Thu, 13 May 2010 16:28:36 +0100 > From: Daniel Brewer <daniel.brewer at="" icr.ac.uk=""> > To: Bioconductor mailing list <bioconductor at="" stat.math.ethz.ch=""> > Subject: [BioC] LIMMA: Suitable measure of error from result object. > stdev.unscaled? > > Hello, > > I have a 2-colour microarray experiment with a complex design. I would > like to visualise the estimated coefficients and associated error with > the most significant genes that come out as result of LIMMA (lmfit, > contrasts.fit, eBayes). I thought that it should be stdev.unscaled, but > this seems to be the same for all the genes, which I don't think makes > much sense. What is an appropriate way to calculate the estimated error > associated with a coefficient? > > Many thanks > > Dan > > -- > ************************************************************** > Daniel Brewer, Ph.D. > > Institute of Cancer Research > Molecular Carcinogenesis > Email: daniel.brewer at icr.ac.uk > ************************************************************** ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}