Hello, I'd like to solicit some advice regarding normalization of two-color arrays in which one sample is a reference pool. These arrays may violate the assumption that M~1 for most spots, and thus I am unsure of how best to correct the spatial and intensity biases that crop up in some of our arrays. While it may be possible to achieve some degree of normalization post-transformation, the process of transforming between arrays can mask intensity-effects (especially if the scan intensities or sample qualities differ) as well as spatial effects. Any advice on how to approach this problem would be much appreciated. -oliver- P.S. Thanks for the earlier advice on using OLIN to correct spatial biases. The quality of my (non-reference-based) array data was much improved by this approach.