Computational methods to elucidate chromatin topological structures using 3D genomic maps

ABSTRACT

The chromosome conformation capture (3C) technique and its variants have been employed to reveal the existence of a hierarchy of structures in three-dimensional (3D) chromosomal architecture, including compartments, topologically associating domains (TADs), sub-TADs and chromatin loops. In this talk, I am going to introduce three methods on deciphering 3D genomic maps: (1) a mixed-scale dense convolutional neural network model (HiCMSD) to enhance low-resolution Hi-C interaction map for deciphering accurate multi-scale topological structures; (2) a generic and efficient method to identify multi-scale topological domains (MSTD), including cis- and trans-interacting regions, from a variety of 3D genomic datasets; (3) a powerful and robust circular trajectory reconstruction tool CIRCLET without specifying a starting cell for resolving cell cycle phases of single cells by considering multi-scale features of chromosomal architectures.