{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["22(3)"],"submitter":["Jiang Y"],"pubmed_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"],"journal":["Genomics, proteomics & bioinformatics"],"pagination":["qzae044"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12016561"],"repository":["biostudies-literature"],"pubmed_title":["MethylGenotyper: Accurate Estimation of SNP Genotypes and Genetic Relatedness from DNA Methylation Data."],"pmcid":["PMC12016561"],"pubmed_authors":["Jiang Y","Cheng S","Guo H","Wang C","Qu M","Jiang X","Laws SM","Fernandez S","Masters CL","Jiang M","Porter T"],"additional_accession":[]},"is_claimable":false,"name":"MethylGenotyper: Accurate Estimation of SNP Genotypes and Genetic Relatedness from DNA Methylation Data.","description":"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","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Sep","modification":"2026-05-26T14:07:52.31Z","creation":"2026-05-24T03:07:47.931Z"},"accession":"S-EPMC12016561","cross_references":{"pubmed":["39353864"],"doi":["10.1093/gpbjnl/qzae044"]}}