Figure 9

Agilent error model. This figure illustrates Agilent's universal error model. The scatterplot shows log fold changes (M) as a function of the mean single channel intensity (A) for a single Agilent processed array. Every log fold change (black point) is matched with a blue point of the same mean intensity level which shows the error in the log fold change as estimated by Agilent's universal error model. For log fold changes that were negative, the error estimate was multiplied by -1 before plotting. These error estimates capture the large global variation that characterizes low intensity genes after Agilent pre-processing. This array is representative of results seen with Agilent arrays.