Hi all, I have a question about RMA's background adjustment. The data I'm working with is from a custom Affy PM-only array, and I used RMA before the analysis. The PI now wants an estimate of how many of the probes/probes sets are "present" or above background, to compare with some cDNA arrays that have the same samples on them. I normally use Affy's mas5calls algorithm, but I can't here because it's a PM-only array. I was looking at RMA's background adjustment step, and while I understand generally that it's a model based approach using only PM data for each array separately, I'm unsure as to what assumptions go into it and how the biology of these samples may affect it. The help file for bg.adjust (the internal function used) says: "Assumes PMs are a convolution of normal and exponentional. So we observe X+Y where X is backround and Y is signal. bg.adjust returns E[Y|X+Y, Y>0] as our backround corrected PM. bg.parameters provides adhoc estimates of the parameters of the normal and exponential distributions. " My questions: 1. How might this model be affected if almost all of the probes are expressed in the sample? The model was developed using the standard Affy spike-in and serial dilution data sets, but I'm pretty sure that those samples used did not have nearly all of the transcripts on the array in them (typical percent present for Affy's whole genome arrays are 40-60%). The custom array I'm using is for a particular tissue, and the same samples on a similar cDNA array have >99% of the spots above background. If I use the empty features around each PM as an estimate of background for the Affy array, then ~95 of PM probes have signals greater than the empty features. I'm worried that if all of the probe sets are expressed, then RMA's background correction will actually be subtracting off real signal instead of additive background. Any thoughts? 2. In my analysis of the cDNA arrays, I decided not to subtract background at all, because almost all the spots were above the background estimate. Am I justified in using this rationale for the Affy arrays and skipping the background correction step? The custom Affy array was based on the clones from the cDNA arrays, plus other clones from the same tissue. There is good reason to believe that just about all of the transcripts on the Affy array are expressed in the samples we're analyzing. Thanks for any help, Jenny Jenny Drnevich, Ph.D. Functional Genomics Bioinformatics Specialist W.M. Keck Center for Comparative and Functional Genomics Roy J. Carver Biotechnology Center University of Illinois, Urbana-Champaign 330 ERML 1201 W. Gregory Dr. Urbana, IL 61801 USA ph: 217-244-7355 fax: 217-265-5066 e-mail: drnevich at uiuc.edu