Figure 1.

Visualization of typical non-linear artifacts in microarray data and the GRSN method used to reduce them. A. Visualizing non-linear technical artifacts. Top row – standard log base 2 scatter plots comparing normal sample N3 to normal sample N5 from a clinical study of Fanconi Anemia, (GB dataset). Bottom row – the same data as in the top row, but plotted using M vs. A plots in which M is plotted as a function of A where M = log2(Y) – log2(X) and A = (log2(Y) + log2(X))/2 with X = expression values for sample 1 and Y = expression values for sample 2. The probe set summary methods used are (from left to right): MAS 5.0, RMA, and dChip^®. B. A flow chart showing the basic steps followed by the GRSN algorithm to reduce the type of non-linear artifact shown in A.