hello, If we have many samples to be compared in an microarray experiment, for example, tissueType1 tissueType2 tissueType3 age1 4 4 4 age2 4 4 4 age3 4 4 4 each kind of sample has 4 biological replicates, primary interest are differential expression among different age groups and among different tissueTypes. We usually use common reference design. I am wondering if I can use self-self hybridization design, in which two identical samples are labeled with different dyes and hybridized to the same slide. maybe I don't need to worry about dye bias by using log- intensity A-value for each spot, and use limma analyze like, MA<-normalizeWithinArrays(RG, method="none") MA<-normalizeBetweenArrays(MA, method="Aq") convert MA to exprSet, then replace M-value in exprSet with A-value, then use the new exprSet to get significant genes using limma. I only know self-self experiment to be used to show imbalance in red and green intensity, but I never found it to be used to do real experiment. I think there must be some reasons that self-self hybridization is not appropriate. Could anyone explain it, Thanks in advance! Ren [[alternative HTML version deleted]]

On Mar 29, 2005, at 2:46 PM, Na, Ren wrote: > hello, > > If we have many samples to be compared in an microarray experiment, > for example, > > tissueType1 tissueType2 tissueType3 > age1 4 4 4 > age2 4 4 4 > age3 4 4 4 > each kind of sample has 4 biological replicates, primary interest are > differential > expression among different age groups and among different tissueTypes. > We usually > use common reference design. I am wondering if I can use self-self > hybridization design, > in which two identical samples are labeled with different dyes and > hybridized to the > same slide. maybe I don't need to worry about dye bias by using > log-intensity A-value > for each spot, and use limma analyze like, > MA<-normalizeWithinArrays(RG, method="none") > MA<-normalizeBetweenArrays(MA, method="Aq") > convert MA to exprSet, then replace M-value in exprSet with A-value, > then use the new > exprSet to get significant genes using limma. I only know self-self > experiment to be > used to show imbalance in red and green intensity, but I never found > it to be used to > do real experiment. I think there must be some reasons that self- self > hybridization is > not appropriate. > Could anyone explain it, Thanks in advance! > These are some useful links for thinking about factorial designs. Note that the limma user guide also contains examples of factorial design. http://www.bioconductor.org/workshops/Heidelberg02/exp-design.pdf http://www.maths.adelaide.edu.au/people/psolomon/Designsingle.pdf http://www.microarrays.med.uni-goettingen.de/landgrebe_et_al2004b.pdf In practice, a direct design can cut the variance in half when comparing two samples on two arrays via a common reference versus the same two samples on a single array, so they can be very useful. The dye bias is a real phenomenon, so needs to be accounted for in the design of the experiment (dye swaps). Sean