PreciseTAD: a transfer learning framework for 3D domain boundary prediction at base-pair resolution.

ABSTRACT:

Motivation

Chromosome conformation capture technologies (Hi-C) revealed extensive DNA folding into discrete 3D domains, such as Topologically Associating Domains and chromatin loops. The correct binding of CTCF and cohesin at domain boundaries is integral in maintaining the proper structure and function of these 3D domains. 3D domains have been mapped at the resolutions of 1 kilobase and above. However, it has not been possible to define their boundaries at the resolution of boundary-forming proteins.

Results

To predict domain boundaries at base-pair resolution, we developed preciseTAD, an optimized transfer learning framework trained on high-resolution genome annotation data. In contrast to current TAD/loop callers, preciseTAD-predicted boundaries are strongly supported by

SUBMITTER: Stilianoudakis SC 

PROVIDER: S-EPMC8756196 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature