Figure 4

Sampling of learning and test set and selection of marker genes. Depicted is one fold in the ten-fold resampling procedure. From the original data set comprising n cases and p genes, ~70% of the cases are randomly selected for the learning set L _i and ~30% cases for the test set T _i . On the learning set L _i with unpermuted class labels, the signal-to-noise weight for each gene and each class is computed as illustrated for class B. The class labels are then randomly permuted 1,000 times and the signal-to-noise weights (for each gene and each class) are recomputed for each permutation to assess the significance of the weights for the unpermuted learning set. Both the learning and the test set are filtered to contain only those genes that are significantly differently expressed in the learning set.