Hi I have performed print-tip loess normalisation followed by quantile normalisation in limma. I have then converted the resulting MAList object back to an RGList object using RG.MA(). I now want to extract the single channel intensities from this normalised RGList object to create *new* RGList objects which represent comparisons between samples that were not made on the arrays directly. However, as RG.MA gives me log2(intensity) back rather than raw intensity, I presume I need to un-log this data before sending it down my normal analysis pipeline of RGList -> MAList -> lmFit(MAList) -> eBayes() -> topTable() ?? Thanks Mick

Mick, Is there no way to do this with an appropriate contrast matrix? That seems a safer/more appropriate way of using your two-channel data. Sean On Oct 1, 2004, at 7:35 AM, michael watson (IAH-C) wrote: > Hi > > I have performed print-tip loess normalisation followed by quantile > normalisation in limma. I have then converted the resulting MAList > object back to an RGList object using RG.MA(). I now want to extract > the single channel intensities from this normalised RGList object to > create *new* RGList objects which represent comparisons between samples > that were not made on the arrays directly. > > However, as RG.MA gives me log2(intensity) back rather than raw > intensity, I presume I need to un-log this data before sending it down > my normal analysis pipeline of RGList -> MAList -> lmFit(MAList) -> > eBayes() -> topTable() ?? > > Thanks > Mick > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor

On Oct 1, 2004, at 8:50 AM, michael watson (IAH-C) wrote: > You tell me, contrast matrices are a black art when it comes to > complicated experiments. > > What I have are two conditions, +ve and -ve, and a control. The design > of the experiment is rather odd. I have arrays that are: > > -ve / +ve > -ve / +ve > -ve / +ve > Etc > Etc > -ve / Control > > What I want are: > > -ve / Control > -ve / Control > Etc > +ve / Control > +ve / Control > Etc > > I figured that by using the methods decsribe in limma, I could subtract > the single channel intensity data, and completely re-arrange the > experiment such that all of my -ve and +ve values have the control as > the denominator. > > I have no idea if this kind of complex re-arrangement can be done with > a > contrast matrix. > Perhaps others will help us out also, but it seems to me that you have a common reference design, with -ve being the common reference? If so, then you can refer to the limma user guide for direct guidance. Following the procedure for making the design matrix in the Guide, you will end up with a design matrix with two columns: positive and Control. The Control coefficient is Control/-ve. The +ve coefficient is looking at +ve/-ve. If you want -ve/Control and +ve/Control, you can specify the contrast matrix as: makeContrasts(1-Control,positive-Control,levels=design) This is untested, and I'm no expert, but does it give you what you want? Sean

I'm not sure I told you enough about the experimental design to get this right, so if we want to explore this using contrast matrices, I better add the little detail that might make things more complicated. Although I can assume all my negative samples are replicates of the same thing, I can't assume that all my positive samples are. It's a *very* strange experiment, but I have 8 +ve phenotype samples and they are NOT replicates of one another. So I actually have a factor with nine levels (the 8 +ve phenotypes and the control) all against a common reference, which is the -ve phenotype. To complicate things further, sometimes the -ve is labelled Cy5, sometimes Cy3, and only two of the +ve phenotypes have replication, in the form of a single dye-flip. This is why I really wanted to extract the single channels and then construct "dummy" microarray experiments ;-) -----Original Message----- From: Sean Davis [mailto:sdavis2@mail.nih.gov] Sent: 01 October 2004 14:08 To: michael watson (IAH-C) Cc: Bioconductor Subject: Re: [BioC] Extracting Single Channel Intensities in limma On Oct 1, 2004, at 8:50 AM, michael watson (IAH-C) wrote: > You tell me, contrast matrices are a black art when it comes to > complicated experiments. > > What I have are two conditions, +ve and -ve, and a control. The > design of the experiment is rather odd. I have arrays that are: > > -ve / +ve > -ve / +ve > -ve / +ve > Etc > Etc > -ve / Control > > What I want are: > > -ve / Control > -ve / Control > Etc > +ve / Control > +ve / Control > Etc > > I figured that by using the methods decsribe in limma, I could > subtract the single channel intensity data, and completely re- arrange > the experiment such that all of my -ve and +ve values have the control > as the denominator. > > I have no idea if this kind of complex re-arrangement can be done with > a > contrast matrix. > Perhaps others will help us out also, but it seems to me that you have a common reference design, with -ve being the common reference? If so, then you can refer to the limma user guide for direct guidance. Following the procedure for making the design matrix in the Guide, you will end up with a design matrix with two columns: positive and Control. The Control coefficient is Control/-ve. The +ve coefficient is looking at +ve/-ve. If you want -ve/Control and +ve/Control, you can specify the contrast matrix as: makeContrasts(1-Control,positive-Control,levels=design) This is untested, and I'm no expert, but does it give you what you want? Sean