Figure 7

Most important features for classification of peak cell-type specificity. A) Difference in average 10-fold crossvalidated ROC-score for each TF SVM classifier after removing all features within a feature group (see Table1), compared to including all features. Y-axis shows the change in ROC-score after removing the corresponding feature for the given TF. Removing peak clustering or peak height gives a decrease in ROC-score for most TFs. B) As (A), but after removing confounding factors from the analysis. Specifically, only the 10% highest and 20% most clustered peaks were used, and peak height and cluster features were removed from the SVM training and test datasets. Only the five TFs that had more than 100 remaining peaks in both the overlapping and the cell-type specific datasets were considered. The importance of features varies for each TF. Distance to TSS seems to be more informative than the binary promoter feature, and removal of the cell-type specific mark for active chromatin (H3K4me3) gives the highest performance penalty overall.