DeepHiC: A generative adversarial network for enhancing Hi-C data resolution
Fig 5
Enhancements of DeepHiC in detecting TAD boundaries, using insulation score algorithm.
(a) Graphs of insulation Δ scores derived from different Hi-C data. TAD boundaries are zero-points of insulation Δ scores in ascending intervals. Enlarged photos show that zero-points derived from DeepHiC-enhanced data are closest to those derived from real high-resolution data. (b) Distances from TAD boundaries obtained from downsampled/enhanced data to those obtained from real high-resolution data. Boxplots show that distances of DeepHiC-enhanced data are significantly smaller than others (***: p-value < 1×10−20, *: p-value < 0.05,Wilcoxon rank-sum test). The whiskers are 5 and 95 percentiles. (c) The distribution of the overlaps between TADs in downsampled/enhanced data and those in real high-resolution data. Higher proportion of high Jaccard indices (y-axis) was obtained with use of DeepHiC-enhanced data. ***: p-value < 1×10−20, **: p-value < 0.001, Mann Whitney U-test. Dash lines in violin plots are quantiles.