TopicNet: a framework for measuring transcriptional regulatory network change.

ABSTRACT:

Motivation

Recently, many chromatin immunoprecipitation sequencing experiments have been carried out for a diverse group of transcription factors (TFs) in many different types of human cells. These experiments manifest large-scale and dynamic changes in regulatory network connectivity (i.e. network 'rewiring'), highlighting the different regulatory programs operating in disparate cellular states. However, due to the dense and noisy nature of current regulatory networks, directly comparing the gains and losses of targets of key TFs across cell states is often not informative. Thus, here, we seek an abstracted, low-dimensional representation to understand the main features of network change.

Results

We propose a method called TopicNet that applies latent Dirichlet allocation t

SUBMITTER: Lou S 

PROVIDER: S-EPMC7355251 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature