Dear listers, I would like to reduce my array dataset by IQR filtering. However, I have a paired design (I have samples from the same subject before and after a treatment). I was wondering whether IQR filtering on the normalized data as such would be recommended for such paired design, or whether it would be better to first calculate the treatment effect (after - before) for each gene in each individual followed by IQR filtering. I am asking because in our intervention studies the between-subject effect is normally larger than the within-subject (treatment) effect. As a result, I am afraid that I introduce a 'bias' in retaining genes that vary highly between individuals, whereas genes responding to the treatment (the relevant ones) are discarded. I checked this on a sample dataset; if I retain the 50% most variable genes by IQR filtering I do find an overlap of only ~85% between the two approaches (7133 genes of the 8426 genes that are retained in both approaches; approach 1 is IQR filtering directly on normalized data; approach 2 is subtract AFTER minus BEFORE followed by IQR filtering). So any suggestion on how to optimally filter a paired dataset would be appreciated. Regards, Guido --------------------------------------------------------- Guido Hooiveld, PhD Nutrition, Metabolism & Genomics Group Division of Human Nutrition Wageningen University Biotechnion, Bomenweg 2 NL-6703 HD Wageningen the Netherlands tel: (+)31 317 485788 fax: (+)31 317 483342 email: guido.hooiveld@wur.nl internet: http://nutrigene.4t.com http://scholar.google.com/citations?user=qFHaMnoAAAAJ http://www.researcherid.com/rid/F-4912-2010 [[alternative HTML version deleted]]