HBI: a hierarchical Bayesian interaction model to estimate cell-type-specific methylation quantitative trait loci incorporating priors from cell-sorted bisulfite sequencing data

Abstract Methylation quantitative trait loci (meQTLs) quantify the effects of genetic variants on DNA methylation levels. However, most published studies utilize bulk methylation datasets composed of different cell types and limit our understanding of cell-type-specific methylation regulation. We pr...

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Main Authors: Youshu Cheng, Biao Cai, Hongyu Li, Xinyu Zhang, Gypsyamber D’Souza, Sadeep Shrestha, Andrew Edmonds, Jacquelyn Meyers, Margaret Fischl, Seble Kassaye, Kathryn Anastos, Mardge Cohen, Bradley E. Aouizerat, Ke Xu, Hongyu Zhao
Format: Article
Language:English
Published: BMC 2024-10-01
Series:Genome Biology
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Online Access:https://doi.org/10.1186/s13059-024-03411-7
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author Youshu Cheng
Biao Cai
Hongyu Li
Xinyu Zhang
Gypsyamber D’Souza
Sadeep Shrestha
Andrew Edmonds
Jacquelyn Meyers
Margaret Fischl
Seble Kassaye
Kathryn Anastos
Mardge Cohen
Bradley E. Aouizerat
Ke Xu
Hongyu Zhao
author_facet Youshu Cheng
Biao Cai
Hongyu Li
Xinyu Zhang
Gypsyamber D’Souza
Sadeep Shrestha
Andrew Edmonds
Jacquelyn Meyers
Margaret Fischl
Seble Kassaye
Kathryn Anastos
Mardge Cohen
Bradley E. Aouizerat
Ke Xu
Hongyu Zhao
author_sort Youshu Cheng
collection DOAJ
description Abstract Methylation quantitative trait loci (meQTLs) quantify the effects of genetic variants on DNA methylation levels. However, most published studies utilize bulk methylation datasets composed of different cell types and limit our understanding of cell-type-specific methylation regulation. We propose a hierarchical Bayesian interaction (HBI) model to infer cell-type-specific meQTLs, which integrates a large-scale bulk methylation data and a small-scale cell-type-specific methylation data. Through simulations, we show that HBI enhances the estimation of cell-type-specific meQTLs. In real data analyses, we demonstrate that HBI can further improve the functional annotation of genetic variants and identify biologically relevant cell types for complex traits.
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id doaj-art-c6b0a2734db1434f9dcd7daf066bd2c6
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issn 1474-760X
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publishDate 2024-10-01
publisher BMC
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series Genome Biology
spelling doaj-art-c6b0a2734db1434f9dcd7daf066bd2c62025-08-20T02:17:47ZengBMCGenome Biology1474-760X2024-10-0125112710.1186/s13059-024-03411-7HBI: a hierarchical Bayesian interaction model to estimate cell-type-specific methylation quantitative trait loci incorporating priors from cell-sorted bisulfite sequencing dataYoushu Cheng0Biao Cai1Hongyu Li2Xinyu Zhang3Gypsyamber D’Souza4Sadeep Shrestha5Andrew Edmonds6Jacquelyn Meyers7Margaret Fischl8Seble Kassaye9Kathryn Anastos10Mardge Cohen11Bradley E. Aouizerat12Ke Xu13Hongyu Zhao14Department of Biostatistics, Yale School of Public HealthDepartment of Biostatistics, Yale School of Public HealthDepartment of Biostatistics, Yale School of Public HealthVA Connecticut Healthcare SystemDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public HealthDepartment of Epidemiology, School of Public Health, University of Alabama at BirminghamThe University of North Carolina at Chapel HillDepartment of Psychiatry, SUNY Downstate Health Sciences University School of MedicineDepartment of Medicine, University of Miami School of MedicineDivision of Infectious Diseases and Tropical Medicine, Georgetown UniversityDepartment of Medicine, Albert Einstein College of MedicineHektoen Institute for Medical ResearchBluestone Center for Clinical Research, College of Dentistry, New York UniversityVA Connecticut Healthcare SystemDepartment of Biostatistics, Yale School of Public HealthAbstract Methylation quantitative trait loci (meQTLs) quantify the effects of genetic variants on DNA methylation levels. However, most published studies utilize bulk methylation datasets composed of different cell types and limit our understanding of cell-type-specific methylation regulation. We propose a hierarchical Bayesian interaction (HBI) model to infer cell-type-specific meQTLs, which integrates a large-scale bulk methylation data and a small-scale cell-type-specific methylation data. Through simulations, we show that HBI enhances the estimation of cell-type-specific meQTLs. In real data analyses, we demonstrate that HBI can further improve the functional annotation of genetic variants and identify biologically relevant cell types for complex traits.https://doi.org/10.1186/s13059-024-03411-7Methylation quantitative trait lociCell-type-specific DNA methylationhierarchical Bayesian interaction modelCell-sorted methylation sequencing dataColocalization
spellingShingle Youshu Cheng
Biao Cai
Hongyu Li
Xinyu Zhang
Gypsyamber D’Souza
Sadeep Shrestha
Andrew Edmonds
Jacquelyn Meyers
Margaret Fischl
Seble Kassaye
Kathryn Anastos
Mardge Cohen
Bradley E. Aouizerat
Ke Xu
Hongyu Zhao
HBI: a hierarchical Bayesian interaction model to estimate cell-type-specific methylation quantitative trait loci incorporating priors from cell-sorted bisulfite sequencing data
Genome Biology
Methylation quantitative trait loci
Cell-type-specific DNA methylation
hierarchical Bayesian interaction model
Cell-sorted methylation sequencing data
Colocalization
title HBI: a hierarchical Bayesian interaction model to estimate cell-type-specific methylation quantitative trait loci incorporating priors from cell-sorted bisulfite sequencing data
title_full HBI: a hierarchical Bayesian interaction model to estimate cell-type-specific methylation quantitative trait loci incorporating priors from cell-sorted bisulfite sequencing data
title_fullStr HBI: a hierarchical Bayesian interaction model to estimate cell-type-specific methylation quantitative trait loci incorporating priors from cell-sorted bisulfite sequencing data
title_full_unstemmed HBI: a hierarchical Bayesian interaction model to estimate cell-type-specific methylation quantitative trait loci incorporating priors from cell-sorted bisulfite sequencing data
title_short HBI: a hierarchical Bayesian interaction model to estimate cell-type-specific methylation quantitative trait loci incorporating priors from cell-sorted bisulfite sequencing data
title_sort hbi a hierarchical bayesian interaction model to estimate cell type specific methylation quantitative trait loci incorporating priors from cell sorted bisulfite sequencing data
topic Methylation quantitative trait loci
Cell-type-specific DNA methylation
hierarchical Bayesian interaction model
Cell-sorted methylation sequencing data
Colocalization
url https://doi.org/10.1186/s13059-024-03411-7
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