Hello, I'm analysing a set of expression data that were processed (normalized) in Rosetta Resolver version 4. I've exported the data into R to run linear model + anova with 3 factors. In Resolver expression values can be zero or negative - about 4 percent of the probesets in my data set. I'd like to work with log2 transformed intensities, so I was wondering if there's anything speaking against shifting intensities, so that the minimal intensity is e.g. 1. The actual minimmal value is -106 and the maximum is about 14000. I'm happy to receive suggestions or comments, +regards, Arne -- Arne Muller, Ph.D. Toxicogenomics, Aventis Pharma arne dot muller domain=aventis com

Hi Arne There are several approaches: 1) create a positive lower threshold below which you do not believe anything is being expressed. Some people use 1, others use 50, but essentially you do not "shift" your distribtion, you simply re-set all values below a threshold to that threshold 2) perform a linear shift of the distribution - essentially, one takes the lowest value and adds this to every value in the distribution. 3) perform a slightly more intelligent shift - I believe there are some functions in the R library vsn, but I have never used them. These result in an avoidance of zero or negative values (I think) 4) perform kooperberg background correction, which is available in the limma package. This is a published method which estimates low expression values from negative numbers using some kind of Bayesian magic ;-) Thanks Mick -----Original Message----- From: Arne.Muller@aventis.com [mailto:Arne.Muller@aventis.com] Sent: 10 June 2004 10:25 To: bioconductor@stat.math.ethz.ch Subject: [BioC] negative expression values Hello, I'm analysing a set of expression data that were processed (normalized) in Rosetta Resolver version 4. I've exported the data into R to run linear model + anova with 3 factors. In Resolver expression values can be zero or negative - about 4 percent of the probesets in my data set. I'd like to work with log2 transformed intensities, so I was wondering if there's anything speaking against shifting intensities, so that the minimal intensity is e.g. 1. The actual minimmal value is -106 and the maximum is about 14000. I'm happy to receive suggestions or comments, +regards, Arne -- Arne Muller, Ph.D. Toxicogenomics, Aventis Pharma arne dot muller domain=aventis com _______________________________________________ Bioconductor mailing list Bioconductor@stat.math.ethz.ch https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor

Hi Michael, thanks for your reply, please see my comments below. -- Arne Muller, Ph.D. Toxicogenomics, Aventis Pharma arne dot muller domain=aventis com > -----Original Message----- > From: michael watson (IAH-C) [mailto:michael.watson@bbsrc.ac.uk] > Sent: 10 June 2004 11:46 > To: Muller, Arne PH/FR; bioconductor@stat.math.ethz.ch > Subject: RE: [BioC] negative expression values > > > Hi Arne > > There are several approaches: > > 1) create a positive lower threshold below which you do not believe > anything is being expressed. Some people use 1, others use 50, but > essentially you do not "shift" your distribtion, you simply re-set all > values below a threshold to that threshold I think I'll go for this one, and choose a cutoff of 1. > 2) perform a linear shift of the distribution - essentially, one takes > the lowest value and adds this to every value in the distribution. This was actually meant with "shift" intensities. > 3) perform a slightly more intelligent shift - I believe > there are some > functions in the R library vsn, but I have never used them. These > result in an avoidance of zero or negative values (I think) > > 4) perform kooperberg background correction, which is available in the > limma package. This is a published method which estimates low > expression values from negative numbers using some kind of Bayesian > magic ;-) 3 and 4 are probably approrpiate, but I'd like to stay as close to the original Resolver data as possible (and Resolver already performs a de-trending based on the variance, i.e. something like vsn does). One purpose of my analysis is to reproduce some anova results from Resolver. kind regards, Arne > Thanks > Mick > > -----Original Message----- > From: Arne.Muller@aventis.com [mailto:Arne.Muller@aventis.com] > Sent: 10 June 2004 10:25 > To: bioconductor@stat.math.ethz.ch > Subject: [BioC] negative expression values > > > Hello, > > I'm analysing a set of expression data that were processed > (normalized) > in Rosetta Resolver version 4. I've exported the data into R to run > linear model + anova with 3 factors. > > In Resolver expression values can be zero or negative - about > 4 percent > of the probesets in my data set. > > I'd like to work with log2 transformed intensities, so I was wondering > if there's anything speaking against shifting intensities, so that the > minimal intensity is e.g. 1. The actual minimmal value is -106 and the > maximum is about 14000. > > I'm happy to receive suggestions or comments, > > +regards, > > Arne > > -- > Arne Muller, Ph.D. > Toxicogenomics, Aventis Pharma > arne dot muller domain=aventis com > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor >

Hi Arne I quite often use the "set negative to one" approach, however, for the record I must say there is a problem with this, as setting one value of a ratio to 1 can result in very skewed ratios at low intensity levels e.g. if Cy5=24 and Cy3=1, then my ratio is 24, which suggests a SERIOUS amount of upregulation, when in effect the gene is probably "switched off" in both channels. It is important to be aware of this problem Regards Mick -----Original Message----- From: Arne.Muller@aventis.com [mailto:Arne.Muller@aventis.com] Sent: 10 June 2004 11:15 To: michael watson (IAH-C); bioconductor@stat.math.ethz.ch Subject: RE: [BioC] negative expression values Hi Michael, thanks for your reply, please see my comments below. -- Arne Muller, Ph.D. Toxicogenomics, Aventis Pharma arne dot muller domain=aventis com > -----Original Message----- > From: michael watson (IAH-C) [mailto:michael.watson@bbsrc.ac.uk] > Sent: 10 June 2004 11:46 > To: Muller, Arne PH/FR; bioconductor@stat.math.ethz.ch > Subject: RE: [BioC] negative expression values > > > Hi Arne > > There are several approaches: > > 1) create a positive lower threshold below which you do not believe > anything is being expressed. Some people use 1, others use 50, but > essentially you do not "shift" your distribtion, you simply re-set all > values below a threshold to that threshold I think I'll go for this one, and choose a cutoff of 1. > 2) perform a linear shift of the distribution - essentially, one takes > the lowest value and adds this to every value in the distribution. This was actually meant with "shift" intensities. > 3) perform a slightly more intelligent shift - I believe > there are some > functions in the R library vsn, but I have never used them. These > result in an avoidance of zero or negative values (I think) > > 4) perform kooperberg background correction, which is available in the > limma package. This is a published method which estimates low > expression values from negative numbers using some kind of Bayesian > magic ;-) 3 and 4 are probably approrpiate, but I'd like to stay as close to the original Resolver data as possible (and Resolver already performs a de-trending based on the variance, i.e. something like vsn does). One purpose of my analysis is to reproduce some anova results from Resolver. kind regards, Arne > Thanks > Mick > > -----Original Message----- > From: Arne.Muller@aventis.com [mailto:Arne.Muller@aventis.com] > Sent: 10 June 2004 10:25 > To: bioconductor@stat.math.ethz.ch > Subject: [BioC] negative expression values > > > Hello, > > I'm analysing a set of expression data that were processed > (normalized) > in Rosetta Resolver version 4. I've exported the data into R to run > linear model + anova with 3 factors. > > In Resolver expression values can be zero or negative - about > 4 percent > of the probesets in my data set. > > I'd like to work with log2 transformed intensities, so I was wondering > if there's anything speaking against shifting intensities, so that the > minimal intensity is e.g. 1. The actual minimmal value is -106 and the > maximum is about 14000. > > I'm happy to receive suggestions or comments, > > +regards, > > Arne > > -- > Arne Muller, Ph.D. > Toxicogenomics, Aventis Pharma > arne dot muller domain=aventis com > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor >