Global Quantitative Modeling of Chromatin Factor Interactions
Figure 3
Model provided accurate predictor for experimentally validated chromatin factor interactions.
(A) Heatmap visualization of maximum entropy model pair-wise interaction energy scores (upper right) compared with correlation z-scores (lower left); The heatmap is ordered to position positive interactions close to diagonal so positively interacting factors tend to be adjacent to each other. H3K23ac-, H1-, H3-, H4- represent the depletion of these factors respectively. For comparison with interaction scores, correlations were transformed to z-scores by Fisher transformation and rescaled to make standard deviation equal to the standard deviation of pair-wise interaction energy scores. In figure legend, the corresponding correlation (left) and interaction energy score (right) at each z-score level is shown. The interaction energy score prediction is robust to changing bin size in data processing (Figure S2). (B) Precision-recall curves for predicting known interactions. Precision-recall curve shows the performance of using interaction energy score to classify interaction at all thresholds. Precision-recall curve of L1-regularized pair-wise interaction maximum entropy model interaction energy scores (red, solid) is compared to unregularized pair-wise interaction maximum entropy model interaction energy scores (black, solid), Bayesian network bootstrap score (black, dashed), Pearson correlation coefficients (grey, dashed), Partial correlation (grey, solid), and mutual information (grey, dot). Maximum entropy models, Bayesian network model and mutual information are computed on discretized data, while correlation and partial correlation were computed on continuous data without discretization.