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 A. Kocher; Zhengyuan Xia; Pak Chung Sham; Jun S. Liu; Junwen Wang

doi:10.1186/s13059-017-1177-3

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 A. Kocher, Zhengyuan Xia, Pak Chung Sham, Jun S. Liu, Junwen Wang

Research output: Contribution to journal › Article › peer-review

20 Scopus citations

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 language	English (US)
Article number	52
Journal	Genome biology
Volume	18
Issue number	1
DOIs	https://doi.org/10.1186/s13059-017-1177-3
State	Published - Mar 16 2017

Keywords

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

ASJC Scopus subject areas

Ecology, Evolution, Behavior and Systematics
Genetics
Cell Biology

Access to Document

10.1186/s13059-017-1177-3

Cite this

Li, M. J., Li, M., Liu, Z., Yan, B., Pan, Z., Huang, D., Liang, Q., Ying, D., Xu, F., Yao, H., Wang, P., Kocher, J. P. A., Xia, Z., Sham, P. C., Liu, J. S., & Wang, J. (2017). Cepip: Context-dependent epigenomic weighting for prioritization of regulatory variants and disease-associated genes. Genome biology, 18(1), Article 52. https://doi.org/10.1186/s13059-017-1177-3

@article{759cc032de864d7e87e2b127397c5331,

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

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.",

keywords = "Cell type-specific, Disease-susceptible gene, Epigenome, Regulatory variant, Variant prioritization",

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

note = "Publisher Copyright: {\textcopyright} 2017 The Author(s).",

year = "2017",

month = mar,

day = "16",

doi = "10.1186/s13059-017-1177-3",

language = "English (US)",

volume = "18",

journal = "Genome biology",

issn = "1474-7596",

publisher = "BioMed Central",

number = "1",

}

TY - JOUR

T1 - Cepip

T2 - Context-dependent epigenomic weighting for prioritization of regulatory variants and disease-associated genes

AU - Li, Mulin Jun

AU - Li, Miaoxin

AU - Liu, Zipeng

AU - Yan, Bin

AU - Pan, Zhicheng

AU - Huang, Dandan

AU - Liang, Qian

AU - Ying, Dingge

AU - Xu, Feng

AU - Yao, Hongcheng

AU - Wang, Panwen

AU - Kocher, Jean Pierre A.

AU - Xia, Zhengyuan

AU - Sham, Pak Chung

AU - Liu, Jun S.

AU - Wang, Junwen

PY - 2017/3/16

Y1 - 2017/3/16

N2 - 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.

AB - 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.

KW - Cell type-specific

KW - Disease-susceptible gene

KW - Epigenome

KW - Regulatory variant

KW - Variant prioritization

UR - http://www.scopus.com/inward/record.url?scp=85015699072&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85015699072&partnerID=8YFLogxK

U2 - 10.1186/s13059-017-1177-3

DO - 10.1186/s13059-017-1177-3

M3 - Article

C2 - 28302177

AN - SCOPUS:85015699072

SN - 1474-7596

VL - 18

JO - Genome biology

JF - Genome biology

IS - 1

M1 - 52

ER -

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

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this