Huber et al. [16], employed the model suggested by Rocke and Durbin to design a variance-stabilizing method named VSN. VSN first brings different arrays to the same scale and then transforms the data in such a way that it shows an approximately constant variance across its entire range. This method, like the Log2 transformation, is capable of dealing with very high intensities. In addition, it acts much like a linear transformation for weak intensities. Therefore, it avoids the problem of variance inflation caused by the Log2 method for weakly expressed genes. The values between these two extreme situations are smoothly interpolated by VSN [16].