Repository logo
 

A graphical model approach visualizes regulatory relationships between genome-wide transcription factor binding profiles.

Published version
Peer-reviewed

Loading...
Thumbnail Image

Type

Article

Change log

Authors

Ng, Felicia SL 
Ruau, David 
Wernisch, Lorenz 
Göttgens, Berthold 

Abstract

Integrated analysis of multiple genome-wide transcription factor (TF)-binding profiles will be vital to advance our understanding of the global impact of TF binding. However, existing methods for measuring similarity in large numbers of chromatin immunoprecipitation assays with sequencing (ChIP-seq), such as correlation, mutual information or enrichment analysis, are limited in their ability to display functionally relevant TF relationships. In this study, we propose the use of graphical models to determine conditional independence between TFs and showed that network visualization provides a promising alternative to distinguish 'direct' versus 'indirect' TF interactions. We applied four algorithms to measure 'direct' dependence to a compendium of 367 mouse haematopoietic TF ChIP-seq samples and obtained a consensus network known as a 'TF association network' where edges in the network corresponded to likely causal pairwise relationships between TFs. The 'TF association network' illustrates the role of TFs in developmental pathways, is reminiscent of combinatorial TF regulation, corresponds to known protein-protein interactions and indicates substantial TF-binding reorganization in leukemic cell types. With the rapid increase in TF ChIP-Seq data sets, the approach presented here will be a powerful tool to study transcriptional programmes across a wide range of biological systems.

Description

Keywords

ChIP-seq, haematopoiesis, network, transcriptional regulation, Algorithms, Animals, Binding Sites, Cells, Cultured, Chromatin Immunoprecipitation, Computational Biology, Computer Graphics, Gene Expression Regulation, Genome, Hematopoietic Stem Cells, Leukemia, Mice, Models, Statistical, Protein Binding, Transcription Factors

Journal Title

Brief Bioinform

Conference Name

Journal ISSN

1467-5463
1477-4054

Volume Title

Publisher

Oxford University Press (OUP)
Sponsorship
Leukaemia & Lymphoma Research (12029)
Biotechnology and Biological Sciences Research Council (BB/I00050X/1)
Cancer Research Uk (None)
Wellcome Trust (097922/Z/11/Z)
Medical Research Council (MC_PC_12009)
Bloodwise, the Biotechnology and Biological Sciences Research Council, the Leukaemia and Lymphoma Society, Cancer Research UK, the National Institute for Health Research Cambridge Biomedical Research Centre, and the Wellcome Trust and MRC Cambridge Institute for Medical Research and Wellcome Trust—Medical Research Council Cambridge Stem Cell Institute; Yousef Jameel scholarship awarded by the Cambridge Commonwealth, European and International Trust (to F.S.L.N.).