Figure 1.

Example of noise in microarray visualization. Four views of the same data displayed in different ways. (a-c) show a traditional display using different cutoff values. Note that in (a) variation in the highly over and under expressed regions cannot be seen due to saturation, while in (c) variation in the highly expressed regions can be seen, but variation near zero cannot. (d) uses our rank-based visualization method. In this rank-based view (d), the experiment with the lowest expression for each gene is colored black, the experiment with the highest expression is colored white, and the other experiments interpolate between in grayscale. Using this method, users can see the overall pattern of variation in the data, which makes it clear that heterogeneity in the traditional view is mostly the result of noise. (Data from [26])