A key aspect of ProCAT is the two-parameter approach for reducing spatial nonuniformity. Several factors can affect the performance of ProCAT's normalization. First, ProCAT normalizes the signal of a spot according to the signal distribution in its local neighborhood. It diminishes the signal intensity if the spot is located in a high signal neighborhood, while compensating the intensity if it is in a low signal neighborhood. This approach is based on the assumption that signal intensities across the slide share the same distribution, and it holds true if and only if the regional variations observed on the slide are due to technical artifacts and not from real biological differences. Since proteins are printed in a random order on most of the current protein microarrays, it is unlikely a particular region of the slide will gain high intensities as a result of biologically relevant reasons. Second, the size of the neighborhood window can also largely affect the performance of the normalization. Small window sizes tend to add biases to signals and diminish all local variations, whereas large window sizes increase the computational burden and tend to preserve local variations. We found that the optimal window size of ProCAT is 9 for protein-protein interactions; this figure corresponds to approximately four blocks on the chip and is used as the default. Other window sizes can also be chosen to fit various shapes of spatial artifacts.