HI, Is there a way to report the CI of logFC from topTable in limma? I googled around and it doesn't seem easy to find. I was expecting the option to be in topTable(). Thanks, Timothy [[alternative HTML version deleted]]

Hello Thomas, I am sure senior members of the list will have more to say, here is my $0.02. logFC is the coefficient of the treatment in your model. Assuming that you have a model with only one treatment log Int_g = b0 + b1 * trt b1 = logFC The CI of logFC can be found in the same manner as you would do in normal linear regression, but here instead of usual t(0.975, df) quantile, you should use the moderated t quantile ie t(0.975, df.residual + df.prior) So the 95% CI for logFC will be logFC -+ t(0.975, fit3$df.residual + fit3$df.prior) * fit3$stdev.unscaled * sqrt(fit3$s2.post) Please correct me if I am wrong. Thanks, S. On Thu, Oct 28, 2010 at 7:46 AM, Timothy Wu <2huggie@gmail.com> wrote: > HI, > > Is there a way to report the CI of logFC from topTable in limma? I googled > around and it doesn't seem easy to find. I was expecting the option to be > in > topTable(). > > Thanks, > > Timothy > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > [[alternative HTML version deleted]]

Sunny's CI is exactly right. CIs could be an option in topTable(), but this the first request for them, so the demand doesn't seem enough for now. Best wishes Gordon > Date: Fri, 29 Oct 2010 00:14:39 -0400 > From: Sunny Srivastava <research.baba at="" gmail.com=""> > To: Timothy Wu <2huggie at gmail.com> > Cc: bioconductor <bioconductor at="" stat.math.ethz.ch=""> > Subject: Re: [BioC] limma report logFC confidence interval? > > Hello Thomas, > I am sure senior members of the list will have more to say, here is my > $0.02. > > logFC is the coefficient of the treatment in your model. Assuming that you > have a model with only one treatment > > log Int_g = b0 + b1 * trt > > b1 = logFC > > The CI of logFC can be found in the same manner as you would do in normal > linear regression, but here instead of usual t(0.975, df) quantile, you > should use the moderated t quantile ie t(0.975, df.residual + df.prior) > > So the 95% CI for logFC will be > > logFC -+ t(0.975, fit3$df.residual + fit3$df.prior) * fit3$stdev.unscaled * > sqrt(fit3$s2.post) > > > Please correct me if I am wrong. > > > Thanks, > S. > > On Thu, Oct 28, 2010 at 7:46 AM, Timothy Wu <2huggie at gmail.com> wrote: > >> HI, >> >> Is there a way to report the CI of logFC from topTable in limma? I googled >> around and it doesn't seem easy to find. I was expecting the option to be >> in >> topTable(). >> >> Thanks, >> >> Timothy ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}