As mentioned, there are no variance stabilization methods designed for dealing with heterogeneity of variance in kinome microarray data, which are different from DNA microarray data from several aspects. These differences may affect the ability of variance stabilization methods to eliminate heterogeneity of variance in kinome array data. One of these differences is that kinome arrays do not have a statistically large number of within-array replicates like some DNA microarrays (e.g., Illumina arrays). Another is that kinome microarrays—unlike DNA microarrays, which usually contain thousands or tens of thousands of probes—contain only several hundred different peptides [14,17]. In fact, a kinome array is usually designed by selecting a set of functionally related peptides [18]. This functional dependency between phosphorylation activities of peptides on an array may make the overall distribution of kinome array measurements different from treatment to treatment, and this may affect the capability of variance-stabilizing methods to improve the data analysis.