Hi, I'm hoping someone can give me a little guidance for an unusual normalization need. I have 9 affy human ST arrays that have varying amounts of RNA, so I can't use the standard quantile normalizaton approach. The wet lab process that involved the polya spike-ins was done in such a way as to ensure the same amount of the polya spike-ins on each array. These probesets are:
Probe.Set.ID mRna...Description total_probes category 7893306 AFFX-Bs-thr_st, polya_spike 1160 control->affx 7894584 AFFX-Bs-lys_st, polya_spike 567 control->affx 7894611 AFFX-Bs-dap_st, polya_spike 1189 control->affx 7895139 AFFX-Bs-phe_st, polya_spike 844 control->affx I have done this successfully before using the 3' IVT yeast arrays, but on those there were many more probesets, so I just ran expresso without the quantile normalization step, and then did a weighted cyclic loess using the polya-spike-ins. I see from the total_probes counts for these 4 probesets on the human ST array that maybe I could use a weighted quantile normalization where I set the weights = 0 for all the probes except the polya_spike probes. So my thought would be to do a RmaBackgroundCorrection() on all probes, then a weighted QuantileNormalization() step, then followed with a RmaPlm() call, as is done in Mark Robinson's doEverything() functions (which I use all the time). If such an approach is advisable, would someone point out to me how to identify the polya_spike probes, so I could then do some weighted QuantileNormalization() or, if that's not possible, maybe a cyclic loess step? Thanks very much for any help or pointers, Dick ******************************************************************************* Richard P. Beyer, Ph.D. University of Washington Tel.:(206) 616 7378 Env. & Occ. Health Sci. , Box 354695 Fax: (206) 685 4696 4225 Roosevelt Way NE, # 100 Seattle, WA 98105-6099 http://depts.washington.edu/ceeh/members_fc_IEHSFC.html http://staff.washington.edu/dbeyer ******************************************************************************* -- When reporting problems on aroma.affymetrix, make sure 1) to run the latest version of the package, 2) to report the output of sessionInfo() and traceback(), and 3) to post a complete code example. You received this message because you are subscribed to the Google Groups "aroma.affymetrix" group with website http://www.aroma-project.org/. To post to this group, send email to aroma-affymetrix@googlegroups.com To unsubscribe and other options, go to http://www.aroma-project.org/forum/
