when correcting for multiple testing. More importantly, there are no significant differences between the performances of the single gene and composite feature classifiers in the merged setting (Tables S17-S20).

Hence, we can also reject the hypothesis that the lack of performance difference is due to the sizes of the employed training sets.

[c|c|c]{} & CV-opt features & 50 best features\

merged

& ![**Classification results for merged and paired setting**. In the merged setting one Affymetrix data set is set aside as test and the remaining four Affymetrix data sets are merged into a single data set. This is repeated until every one of the five data sets acted as a test set. [**Top row:**]{} Results for the merged setting. The red lines indicate the median. [**Bottom row:**]{} Only the five Affymetrix data sets were used in the paired setting.[]{data-label="fig:boxplot_pw_vs_merged"}](Plots/Dotplot_Experiment_08_AFFYmerged.pdf "fig:"){width="3in"} & ![**Classification results for merged and paired setting**. In the merged setting one Affymetrix data set is set aside as test and the remaining four Affymetrix data sets are merged into a single data set. This is repeated until every one of the five data sets acted as a test set. [**Top row:**]{} Results for the merged setting. The red 