Document Type

Journal Article

Publication Title

Genomics, Proteomics and Bioinformatics

Volume

22

Issue

3

PubMed ID

39353864

Publisher

Oxford Academic

School

Centre for Precision Health / School of Medical and Health Sciences

RAS ID

72562

Funders

National Natural Science Foundation of China (82325044, 82021005) / China Postdoctoral Science Foundation (2021M701318) / Natural Science Fund for Distinguished Young Scholars of Hubei Province, China (2022CFA046) / Fundamental Research Funds for the Central Universities, China (2019kfyXJJS036, 2023BR030) / National Health and Medical Research Council

Grant Number

NHMRC Numbers : GNT1161706, GNT1151854

Comments

Jiang, Y., Qu, M., Jiang, M., Jiang, X., Fernandez, S., Porter, T., ... & Wang, C. (2024). MethylGenotyper: Accurate estimation of SNP genotypes and genetic relatedness from DNA methylation data. Genomics, Proteomics & Bioinformatics, 22(3). https://doi.org/10.1093/gpbjnl/qzae044

Abstract

Epigenome-wide association studies (EWAS) are susceptible to widespread confounding caused by population structure and genetic relatedness. Nevertheless, kinship estimation is challenging in EWAS without genotyping data. Here, we proposed MethylGenotyper, a method that for the first time enables accurate genotyping at thousands of single nucleotide polymorphisms (SNPs) directly from commercial DNA methylation microarrays. We modeled the intensities of methylation probes near SNPs with a mixture of three beta distributions corresponding to different genotypes and estimated parameters with an expectation-maximization algorithm. We conducted extensive simulations to demonstrate the performance of the method. When applying MethylGenotyper to the Infinium EPIC array data of 4662 Chinese samples, we obtained genotypes at 4319 SNPs with a concordance rate of 98.26%, enabling the identification of 255 pairs of close relatedness. Furthermore, we showed that MethylGenotyper allows for the estimation of both population structure and cryptic relatedness among 702 Australians of diverse ancestry. We also implemented MethylGenotyper in a publicly available R package (https://github.com/Yi-Jiang/MethylGenotyper) to facilitate future large-scale EWAS.

DOI

10.1093/gpbjnl/qzae044

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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