optimalTAD: annotation of topologically associating domains based on chromatin marks enrichment

In many eukaryotes, chromosomes are organized as strings of spatially segregated Topologically Associating Domains (TADs), characterized by a substantially increased frequency of interactions within them. Boundaries of TADs are highly enriched in histone acetylation chromatin marks and occupied binding sites of architectural proteins, highlighting the functional role of TADs in the regulation of gene expression. While many computational approaches have been developed for TAD identification, it remains challenging because of their nested structure, resulting in weakly overlapping sets of TADs at different scales. Here, we propose a novel algorithm optimalTAD for identifying the optimal set of TADs based on epigenetic marks enrichment. Assuming that the most dramatic enrichment corresponds to the best annotation of TAD boundaries, our algorithm optimizes TAD calling parameters by maximizing the difference in chromatin mark levels between TADs and their boundaries. Using this algorithm, we annotated TADs in multiple publicly available fruit fly and mammalian Hi-C datasets and identified a set of epigenetic marks that are best suited for TAD prediction. Through the analysis of diverse organisms and cell types with distinct underlying principles of TAD organization, we have shown that optimalTAD is a universal tool suitable for studying TAD structure, functions, and properties unique to specific cell types and organisms. optimalTAD is freely available at GitHub: . Key Points ### Competing Interest Statement The authors have declared no competing interest.