Figure 2.

Normalization and analysis of array quality metrics shows a color heatmap of the distances between arrays. The color scale is chosen to cover the range of distances encountered in the dataset. Patterns in this plot can indicate clustering of the arrays either because of intended biological or unintended experimental factors (batch effects). The distance d_ab between two arrays a and b is computed as the mean absolute difference (L₁-distance) between the data of the arrays (using the data from all probes without filtering). In formula, d_ab = mean | M_ai - M_bi |, where M_ai is the value of the i-th probe on the a-th array. Outlier detection was performed by looking for arrays for which the sum of the distances to all other arrays, S_a = Σ_b d_ab was exceptionally large. 12 such arrays were detected, and they are marked by an asterisk, ^*.