To Bioconductor We have used the quantile normalization method in Bioconductor and would like to know if there is consensus (or if not what are the opinions) about whether or not to normalize all experimental conditions and controls together or to analyze each group separately. We have two experimental groups and one control with multiple replicates for each from different animals. The three conditions were run at the same time for each replicate to minimize variability between groups. It seems to us that if we normalize both experimental groups and controls together we will bias the results against ourselves, even if most gene expression levels are unchanged. Thanks Gordon Gordon A. Barr, Ph.D. Professor Of Psychology Hunter College, CUNY 695 Park Avenue New York, New York 10021 212-772-5610 (voice) 212-772-4477 (fax) Senior Research Scientist Developmental Psychobiology NYS Psychiatric Institute Columbia College of Physicians and Surgeons 1051 Riverside Drive New York, New York 10032 212-543-5694 (voice) 212-543-5497 (fax)

Gordon Barr <gab5@columbia.edu> [/91/Mon, Feb 17, 2003 at 12:43:10PM -0500]: > To Bioconductor > > We have used the quantile normalization method in Bioconductor and would > like to know if there is consensus (or if not what are the opinions) about > whether or not to normalize all experimental conditions and controls > together or to analyze each group separately. We have two experimental > groups and one control with multiple replicates for each from different > animals. The three conditions were run at the same time for each replicate > to minimize variability between groups. It seems to us that if we normalize > both experimental groups and controls together we will bias the results > against ourselves, even if most gene expression levels are unchanged. > I gather you want to do quantile normalization on all groups separately, ie, normalize towards different cdf (cumulative distribution functions, not cell description files) of probe level intensities. To have an illustrated example (not to assume it is the case in your setting but to see if the technique works under a given situation), consider one set of expressions in one chip is heavily biased upwards (by using more RNA or dye or whatever). If you do normalization per group, all genes within that group will look slightly upregulated against other groups. My feeling is that separate normalization is even worse when the three intensity CDFs have a different skew, so intensities that show on the most skewed group will be stressed in that group. So I'd go for overall normalization if my computational facilities allow so. -- Johannes Hüsing There is something fascinating about science. One gets hannes@ruhrau.de such wholesale returns of conjecture from such a trifling investment of fact. Mark Twain

i dont know about a concensus but... if you look at how different replicate arrays can be (see Figure 2 here http://www.biostat.jhsph.edu/~ririzarr/papers/affy1.pdf), it seems impossible to argue that over-all differences in intensities are due to biological variation as opposed to obsucuring variation. to me, this means that in general, we are left with no choice but to assume that, over-all, genes behave similarly across conditions and normalize everything together. an alternative would be to use control genes, but past attempts seemed to have failed. On Mon, 17 Feb 2003, Gordon Barr wrote: > To Bioconductor > > We have used the quantile normalization method in Bioconductor and would > like to know if there is consensus (or if not what are the opinions) about > whether or not to normalize all experimental conditions and controls > together or to analyze each group separately. We have two experimental > groups and one control with multiple replicates for each from different > animals. The three conditions were run at the same time for each replicate > to minimize variability between groups. It seems to us that if we normalize > both experimental groups and controls together we will bias the results > against ourselves, even if most gene expression levels are unchanged. > > Thanks > > > Gordon > > > > Gordon A. Barr, Ph.D. > Professor Of Psychology > Hunter College, CUNY > 695 Park Avenue > New York, New York 10021 > 212-772-5610 (voice) > 212-772-4477 (fax) > > Senior Research Scientist > Developmental Psychobiology > NYS Psychiatric Institute > Columbia College of Physicians and Surgeons > 1051 Riverside Drive > New York, New York 10032 > 212-543-5694 (voice) > 212-543-5497 (fax) > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > http://www.stat.math.ethz.ch/mailman/listinfo/bioconductor >