Introduction

MOTIVATION: Chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing (ChIP-Seq) measures the genome-wide occupancy of transcription factors in vivo. Different combinations of DNA-binding protein occupancies may result in a gene being expressed in different tissues or at different developmental stages. To fully understand the functions of genes, it is essential to develop probabilistic models on multiple ChIP-Seq profiles to decipher the combinatorial regulatory mechanisms by multiple transcription factors. RESULTS: In this work, we describe a probabilistic model (SignalSpider) to decipher the combinatorial binding events of multiple transcription factors. Comparing with similar existing methods, we found SignalSpider performs better in clustering promoter and enhancer regions. Notably, SignalSpider can learn higher-order combinatorial patterns from multiple ChIP-Seq profiles. We have applied SignalSpider on the normalized ChIP-Seq profiles from the ENCODE consortium and learned model instances. We observed different higher-order enrichment and depletion patterns across sets of proteins. Those clustering patterns are supported by Gene Ontology (GO) enrichment, evolutionary conservation and chromatin interaction enrichment, offering biological insights for further focused studies. We also proposed a specific enrichment map visualization method to reveal the genome-wide transcription factor combinatorial patterns from the models built, which extend our existing fine-scale knowledge on gene regulation to a genome-wide level. AVAILABILITY AND IMPLEMENTATION: The matrix-algebra-optimized executables and source codes are available at the authors' websites: http://www.cs.toronto.edu/∼wkc/SignalSpider.

Publications

  1. SignalSpider: probabilistic pattern discovery on multiple normalized ChIP-Seq signal profiles.
    Cite this
    Wong KC, Li Y, Peng C, Zhang Z, 2015-01-01 - Bioinformatics (Oxford, England)

Credits

  1. Ka-Chun Wong
    Developer

    Department of Computer Science and Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Canada

  2. Yue Li
    Developer

    Department of Computer Science and Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Canada

  3. Chengbin Peng
    Developer

    Department of Computer Science and Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Canada

  4. Zhaolei Zhang
    Investigator

    Department of Computer Science and Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Canada

Community Ratings

UsabilityEfficiencyReliabilityRated By
0 user
Sign in to rate
Summary
AccessionBT006844
Tool TypeApplication
Category
PlatformsLinux/Unix
Technologies
User InterfaceTerminal Command Line
Download Count0
Country/RegionCanada
Submitted ByZhaolei Zhang