Structure of the differential diagnostic decision tree. Gene discovery and class prediction were performed following the illustrated decision tree. At each level, the dataset was filtered to remove genes that showed minimal variation in their level of expression between the genetic subtype (class) under evaluation and all subtypes that fall below it in the decision tree (nonclass). Numbers at the right represent the number of probe sets that pass the variance filter at each level. The cases assigned to a diagnostic subgroup are removed prior to progressing to the next level in the algorithm. Cases that pass through the entire decision tree without being assigned to a class are classified as “other.”