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Updated: Sep 6, 2025
Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
Published on: July 27, 2021
Random field modeling of multi-trait multi-locus association for detecting methylation quantitative trait loci
Chen Lyu1,2, Manyan Huang1, Nianjun Liu1
1Department of Epidemiology and Biostatistics, Indiana University Bloomington, Bloomington, IN 47405, USA.
Motivation:
CpG sites within the same genomic region often share similar methylation patterns and tend to be co-regulated by multiple genetic variants that may interact with one another.
Results:
We propose a multi-trait methylation random field (multi-MRF) method to evaluate the joint association between a set of CpG sites and a set of genetic variants. The proposed method has several advantages. First, it is a multi-trait method that allows flexible correlation structures between neighboring CpG sites (e.g. distance-based correlation). Second, it is also a multi-locus method that integrates the effect of multiple common and rare genetic variants. Third, it models the methylation traits with a beta distribution to characterize their bimodal and interval properties. Through simulations, we demonstrated that the proposed method had improved power over some existing methods under various disease scenarios. We further illustrated the proposed method via an application to a study of congenital heart defects (CHDs) with 83 cardiac tissue samples. Our results suggested that gene BACE2, a methylation quantitative trait locus (QTL) candidate, colocalized with expression QTLs in artery tibial and harbored genetic variants with nominal significant associations in two genome-wide association studies of CHD.
Availability And Implementation:
https://github.com/chenlyu2656/Multi-MRF.
Supplementary Information:
Supplementary data are available at Bioinformatics online.
