Cepip: Context-dependent epigenomic weighting for prioritization of regulatory variants and disease-associated genes

Mulin Jun Li, Miaoxin Li, Zipeng Liu, Bin Yan, Zhicheng Pan, Dandan Huang, Qian Liang, Dingge Ying, Feng Xu, Hongcheng Yao, Panwen Wang, Jean-Pierre Kocher, Zhengyuan Xia, Pak Chung Sham, Jun S. Liu, Junwen Wang

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

It remains challenging to predict regulatory variants in particular tissues or cell types due to highly context-specific gene regulation. By connecting large-scale epigenomic profiles to expression quantitative trait loci (eQTLs) in a wide range of human tissues/cell types, we identify critical chromatin features that predict variant regulatory potential. We present cepip, a joint likelihood framework, for estimating a variant's regulatory probability in a context-dependent manner. Our method exhibits significant GWAS signal enrichment and is superior to existing cell type-specific methods. Furthermore, using phenotypically relevant epigenomes to weight the GWAS single-nucleotide polymorphisms, we improve the statistical power of the gene-based association test.

Original languageEnglish (US)
Article number52
JournalGenome Biology
Volume18
Issue number1
DOIs
StatePublished - Mar 16 2017

Fingerprint

prioritization
Epigenomics
epigenetics
Genome-Wide Association Study
gene
Genes
polymorphism
genes
Quantitative Trait Loci
cells
single nucleotide polymorphism
Chromatin
Single Nucleotide Polymorphism
chromatin
quantitative trait loci
Joints
Weights and Measures
methodology
method
tissue

Keywords

  • Cell type-specific
  • Disease-susceptible gene
  • Epigenome
  • Regulatory variant
  • Variant prioritization

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Genetics
  • Cell Biology

Cite this

Cepip : Context-dependent epigenomic weighting for prioritization of regulatory variants and disease-associated genes. / Li, Mulin Jun; Li, Miaoxin; Liu, Zipeng; Yan, Bin; Pan, Zhicheng; Huang, Dandan; Liang, Qian; Ying, Dingge; Xu, Feng; Yao, Hongcheng; Wang, Panwen; Kocher, Jean-Pierre; Xia, Zhengyuan; Sham, Pak Chung; Liu, Jun S.; Wang, Junwen.

In: Genome Biology, Vol. 18, No. 1, 52, 16.03.2017.

Research output: Contribution to journalArticle

Li, MJ, Li, M, Liu, Z, Yan, B, Pan, Z, Huang, D, Liang, Q, Ying, D, Xu, F, Yao, H, Wang, P, Kocher, J-P, Xia, Z, Sham, PC, Liu, JS & Wang, J 2017, 'Cepip: Context-dependent epigenomic weighting for prioritization of regulatory variants and disease-associated genes', Genome Biology, vol. 18, no. 1, 52. https://doi.org/10.1186/s13059-017-1177-3
Li, Mulin Jun ; Li, Miaoxin ; Liu, Zipeng ; Yan, Bin ; Pan, Zhicheng ; Huang, Dandan ; Liang, Qian ; Ying, Dingge ; Xu, Feng ; Yao, Hongcheng ; Wang, Panwen ; Kocher, Jean-Pierre ; Xia, Zhengyuan ; Sham, Pak Chung ; Liu, Jun S. ; Wang, Junwen. / Cepip : Context-dependent epigenomic weighting for prioritization of regulatory variants and disease-associated genes. In: Genome Biology. 2017 ; Vol. 18, No. 1.
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