Abstract
Recent experimental and computational efforts provided large datasets describing 3-dimensional organization of mouse and human genomes and showed the interconnection between expression profile, epigenetic state, and spatial interactions of loci. These interconnections were utilized to infer spatial organization of chromatin, including enhancer-promoter contacts, from 1-dimensional epigenetic marks. Here we showed that predictive power of some of these algorithms is overestimated due to peculiar properties of biological data. We proposed an alternative approach, which allowed obtaining high-quality predictions of chromatin interactions using information on gene expression and CTCF-binding alone. Using multiple metrics, we confirmed that our algorithm could efficiently predict 3-dimensional architecture of both normal and rearranged genomes.