Using network analysis in the study of chromatin 3D structure has proved to be a powerful and useful
approach. In order to determine which factors bound to DNA might play a role in establishing these 3D
chromatin structure, the concept of chromatin assortativity (ChAs) was introduced. ChAs measures to what
extent one specific ...»»»»
Using network analysis in the study of chromatin 3D structure has proved to be a powerful and useful
approach. In order to determine which factors bound to DNA might play a role in establishing these 3D
chromatin structure, the concept of chromatin assortativity (ChAs) was introduced. ChAs measures to what
extent one specific feature of a chromatin fragment (node in the network) is shared by the nodes that interact
preferentially with it. If one feature is localized in some specific region, it suggests that this feature might be
playing a role in mediating genomic contacts in that region.
Here we propose a Local assortativity approach to study a Mouse Embryonic Stem Cell (mESC) Promoter
Capture Hi-C (PCHi-C) chromatin network, studying 78 different chromatin features to get a deeper
biological insight compared to the global assortativity approach already described. We propose a different
method of computing global assortativity by defining subnetworks, and two methods for computing local
assortativity: based on genomic distances (1D) and based on shortest path distance between nodes (3D).^^^^
