Thanks for the suggestions,
one option i was thinking was to center the universal channel and sample channels by normalising the medians of each column of the matrix on each channel. But I don't know if it is appropriate to do a loess after this?
Does the quantile option actually do this?
Peter
At 06:59 PM 7/28/2004, you wrote:
At 06:02 AM 29/07/2004, Peter Wilkinson wrote:I would like to know some alternative to normalization for 2 channel experiments against universal, where samples may have been hybridized in seperate batches where the universal RNA has changed lot (should not have happened but it did). What is the same between the batches is that what looks like up-regulated compared to the universal iis upr-egulated, and what is down-regulated looks down-regulated. The difference is that the down-regulated (and not in the up), so so much more down-regulated in one of the batches. It looks like to be that the universal has more mRNA abundance in one batch over the other.
Gquantile won't help because it doesn't change the M-values. (It is intended for use with single channel analyses.) You could try 'quantile' or 'scale' normalization (not both) but there are no magic bullets in a situation like this. If you use 'scale normalization, you should always do within-array normalization first. If you use 'quantile' normalization, the within-array normalization step is optional.
Gordon
so ...
I have samples that can be divided into 2 classes: 0,1, and within each class I have samples that have been run at different times. I would like to treat my universal channel uniformly across all samples (assuming that my universal changed lot), and then adjust the Sample (Red) channel to that.
is the normalizeBetweenArrays with the method="Gquantile" option the right option for this?
What is the complete work-flow for this case? And after I have normalized within the Arrays, can I go on to scale option for normalizing between arrays.
Peter
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