Integrative construction of regulatory region networks in 127 human reference epigenomes by matrix factorization

Dianbo Liu, Jose Davila-Velderrain, Zhizhuo Zhang, Manolis Kellis (Lead / Corresponding author)

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Abstract

Despite large experimental and computational efforts aiming to dissect the mechanisms underlying disease risk, mapping cis-regulatory elements to target genes remains a challenge. Here, we introduce a matrix factorization framework to integrate physical and functional interaction data of genomic segments. The framework was used to predict a regulatory network of chromatin interaction edges linking more than 20 000 promoters and 1.8 million enhancers across 127 human reference epigenomes, including edges that are present in any of the input datasets. Our network integrates functional evidence of correlated activity patterns from epigenomic data and physical evidence of chromatin interactions. An important contribution of this work is the representation of heterogeneous data with different qualities as networks. We show that the unbiased integration of independent data sources suggestive of regulatory interactions produces meaningful associations supported by existing functional and physical evidence, correlating with expected independent biological features.

Original languageEnglish
Pages (from-to)7235-7246
Number of pages12
JournalNucleic Acids Research
Volume47
Issue number14
Early online date2 Jul 2019
DOIs
Publication statusPublished - 22 Aug 2019

Keywords

  • Algorithms
  • Chromatin/genetics
  • Computational Biology/methods
  • Epigenomics/methods
  • Gene Expression Profiling/methods
  • Gene Ontology
  • Gene Regulatory Networks
  • Humans
  • K562 Cells
  • Polymorphism, Single Nucleotide
  • Promoter Regions, Genetic/genetics
  • Protein Interaction Mapping/methods
  • Regulatory Elements, Transcriptional/genetics
  • Reproducibility of Results

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