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Once the data are normalized, one uses only the genes that you are interested in - whether because the others are from a different species, or for any other reason that can be stated a priori without reference to the data at hand. --Naomi At 04:45 PM 6/6/2007, Maurice Melancon wrote: >Hello, > >I worked with a single-colour multi-species array. The dataset had limited >options for transformation but disparately needed it, and vsn fit the bill >nicely. I was advised to include all non-empty spots in the normalization, >even those that I am certain show hybridization due to non-target binding, >because all spots contain useful information. To qualify for a spot being >'present' or 'absent', the creators of the array used the criteria of >intensity above 2 SD of empty spots as their criteria. This has proven to >be far too liberal for my purposes, considering the nature of the array, and >considering that while the dataset was in desparate need of scaling, the >empty spots have little to no hybridization and thus the criteria for >dropping spots prior to normalization or anything else is lax (imho). > >With vsn dataset in hand, the consensus seems to be among my collaborators >to count only those spots that meet a certain criteria based upon the vsn >data as present, and to test only those for differential expression. One >then calculates FDR based upon this subset of the data. Is this fair? Can >you ignore spots used in normalization because you know them to be >unreliable probes? Or must this subset be eliminated prior to >transformation? > >This is along a similar line to something posted earlier, where someone >asked if it was allowable to normalize only a subset of the spots on an >array, and to me the bigger question is how to fairly exclude spots that you >are not interested in. > >With thanks, > >Maurice > > [[alternative HTML version deleted]] > >_______________________________________________ >Bioconductor mailing list >Bioconductor at stat.math.ethz.ch >https://stat.ethz.ch/mailman/listinfo/bioconductor >Search the archives: >http://news.gmane.org/gmane.science.biology.informatics.conductor Naomi S. Altman 814-865-3791 (voice) Associate Professor Dept. of Statistics 814-863-7114 (fax) Penn State University 814-865-1348 (Statistics) University Park, PA 16802-2111