RMA verse GCRMA, low intensity
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@matthew-hannah-621
Last seen 9.7 years ago
Fangxin, You might want to experiment with eset <- justGCRMA(fast=F) as the fast version sets signals (or BGs?) that are close to BG to a constant value (search the lists for a better (correct) definition) which may give some bias for low signal values. However, you will still have differences in the BG correction of the 3 methods (MAS,RMA,GCRMA) that will give differences when signal is close to BG whatever you do. You can easily see this by plotting the expression values for a single chip for MAS,RMA,GCRMA,GCRMA(fast=T) against each other. I was then going to suggest looking for significant differences between the different timepoints, because much of the low intensity stuff is non-significant, presumably because it is variable between arrays. However, you have no replica so this is not possible. Maybe, depending on what times you have, split the times to form pairs or triplicates of arrays that you could test against the other arrays. To try and identify all genes that cycle in potentially complex ways is alot to expect without replication. If you had replica, most of these 'cycling' genes that vary between normalizations would probably be eliminated as noise. BTW - justGCRMA(fast=F) is incredably slow. HTH, Matt
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