[BioC] SAM in R and normalization question

[Jane Fridlyand]

Hi,

I just recently saw R-function to compute Q-values given unadjusted
p-values on John Storey web page:

http://www.stat.berkeley.edu/~storey/qvalue/index.html

I have not tried it myself.


My question concerns normalization discussion on which I have been reading
in recent postings. Does anyone have suggestion of what would work for
2-color arrays with common reference design (and the "truth" for the
reference is known -- special case of measuring copy number rather than
expression) where  majority of the genome is rearranged (i.e. majority of
the spots "change"). Assumption of equal fraction of "ups" and "downs" may
not be made either. Generally simple global median normalization works
just fine but not here. I have been hitting my head off the the wall for
the past 3 weeks after encountering three datasets in the row with
significant proportion of tumors looking like normalization failed because
of global genomic instability (majority of clones show change) but can't
come up with a good normalization idea here rather than change the
post-normalization analysis approach. No internal controls are possible
here.  Has anybody encountered situation like that with 2-color gene
expression chips?  I have 3 replicates for each  spot but they are located
right next to each other.

Thanks you very much

Jane