TADfit is a multivariate linear regression model for profiling hierarchical chromatin domains on replicate Hi-C data.

ABSTRACT: Topologically associating domains (TADs) are fundamental building blocks of three dimensional genome, and organized into complex hierarchies. Identifying hierarchical TADs on Hi-C data helps to understand the relationship between genome architectures and gene regulation. Herein we propose TADfit, a multivariate linear regression model for profiling hierarchical chromatin domains, which tries to fit the interaction frequencies in Hi-C contact matrix with and without replicates using all-possible hierarchical TADs, and the significant ones can be determined by the regression coefficients obtained with the help of an online learning solver called Follow-The-Regularized-Leader (FTRL). Beyond the existing methods, TADfit has an ability to handle multiple contact matrix replicates and find parti

SUBMITTER: Liu E 

PROVIDER: S-EPMC9209495 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature