Hi-C Filtering and Heatmap Analysis

The interaction matrices were binned using a binsize=50 kb, binstep=5kb, binmode=mean. First, we generated the matrices from the Hi-C interaction data using binstep of 5kb. Second, the self-circularized restriction fragments were filtered by setting the diagonal elements of the matrices to be zero. Third, we removed the rows/cols of the matrices if the sum of elements in the rows/cols were zero. Fourth, we followed the approach in Hnisz et al.⁴¹ to calculate the Z-score matrices of the interaction matrices. We detected and flagged the elements of the interaction matrices if their corresponding Z-score values were greater than 21, which were considered as outlier pixel/interactions. We then took the union of all outlier pixel/interactions across all the interaction matrices and set them to be zero. Fifth, the matrices were balanced according to the KR normalization method⁶⁸ which was similar to the study by Rao et al.⁶⁷. Sixth, we recovered the interaction matrices with binsize=50kb by combining every 10 bins into one bin with binmode=mean. The differential heatmap was the subtraction between the matrices in the two conditions.