Inferring time series chromatin states for promoter-enhancer pairs based on Hi-C data

Abstract Background Co-localized combinations of histone modifications (“chromatin states”) have been shown to correlate with promoter and enhancer activity. Changes in chromatin states over multiple time points state trajectories”) previously analyzed at enhancers separately. With the advent series Hi-C data it is now possible connect promoters analyze trajectories promoter-enhancer pairs. Results We present TimelessFlex, a framework for investigating pairs based on information. TimelessFlex extends our previous approach Timeless, Bayesian network clustering modification sets feature regions. utilize ATAC-seq measuring open define candidates. developed an expectation-maximization algorithm assign each other interactions jointly cluster their regions into paired trajectories. find clustered showing same activation patterns both sides but stronger trend side. While side remains accessible across series, becomes dynamically more towards gene point. Promoter show strong correlations expression signals, whereas signals get only slightly activation. The code available https://github.com/henriettemiko/TimelessFlex . Conclusions clusters can identify distinct changes time.