Sample A: Cover Page of Thesis, Project, or Dissertation Proposal

Figure 3.7: Candidate lists fold change differences. Comparing ProbeSet fold changes for candidate list
ProbeSets between the two experiments. For each class of samples in each experiment, ProbeSet values are
calculated by one of the three data-cleansing methods and the mean is found, after which the
Normal:Disease class fold change is calculated. The y-axes are the mean fold-change for the Stearman
experiment and the x-axes are the mean fold-changes for the Bhattacharjee experiment. The line gives the
QR regression slope for the points. A perfect 45 degree slope would indicate that the fold-changes are on
average the same across the experiments, although individual ProbeSets might change, while a shift in the
slope means that there is a consistent bias in the direction that fold changes are seen for one experiment
relative to the other, given a particular method for generating values. Those ProbeSets that show a negative
fold-change in both experiments are shown with a medium blue down arrow, those for which both show a
positive fold change are shown with a dark blue up arrow, and those that have differences in the direction
of fold change are shown as grey circles. Also observable is an exaggerated funneling patterns for DE
ProbeSets in the RMA and dCHIP interpretations of Stearman markers and the Intersecting BaFL DE
ProbeSets, intimating that the more significant the expression pattern the more divergent the actual level of
fold-change becomes across datasets.
Another curious feature is a funnel shape that is most evident in the top graph (RMA). The effect
is more pronounced in the larger, down-regulated group of ProbeSets and reflects the fact that the
larger the change the more likely the two experiments are to disagree as to the extent of that
change, but that the effect is symmetrical: one set is not more likely to consistently have a larger
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