Skip to main content
Advertisement

< Back to Article

DLoopCaller: A deep learning approach for predicting genome-wide chromatin loops by integrating accessible chromatin landscapes

Fig 6

Comparison of chromatin loops among cell types.

(a) Distance distribution of DLoopCaller identified chromatin loops from Hi-C contact maps by using CTCF ChIA-PET data after training on GM12878, H1-ESC, and K562 (replicate1) separately. (b) APA plots of identified chromatin loops in GM12878, H1-ESC, and K562 (replicate1). (c) Venn diagram of DLoopCaller identified chromatin loops determined by CTCF ChIA-PET experiments in GM12878, H1-ESC and K562 (replicate1). (d) The proportion of CTCF ChIA-PET interactions types for H1-ESC and K562. The proportion of identified chromatin loops types using CTCF ChIA-PET data after training for H1-ESC and K562 (replicate1).

Fig 6

doi: https://doi.org/10.1371/journal.pcbi.1010572.g006