Dear Bioconductor mailing list,
I am analysing some tiling, chip-on-chip, two color (one is input and the
other is chromatin),  Agilent data. There are 10 arrays with ~44000
features, scanned with GenePix,  each that represent most of the human
promoters of about 8kb regions, each with one biological replicate giving
the grand total of 20 arrays. I am interested in getting high resolution
peaks, hopefully with p-values. I am trying to use Limma to normalize them
using RMA. However all these arrays have different probes, so in the end I
should end up with ~440,000 different probe values. However Limma treats
these arrays as replicates and I only end up with 44,000 probes. How can I
keep it from doing that? Also, any suggestions about normalization methods
would be greatly appreciated.
Thanks a lot,

-- 
Eugene Bolotin
Ph.D. candidate
Genetics Genomics and Bioinformatics
University of California Riverside

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