Evidence map›Paper›PMID 39353864›Full record

ArticleGenomics, proteomics & bioinformatics2024

MethylGenotyper: Accurate Estimation of SNP Genotypes and Genetic Relatedness from DNA Methylation Data.

Yi Jiang, Minghan Qu, Minghui Jiang, Xuan Jiang, Shane Fernandez, Tenielle Porter, Simon M Laws, Colin L Masters, Huan Guo, Shanshan Cheng and 1 more

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PubMed Full text at PMC Publisher
In one paragraph

Article in Genomics, proteomics & bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Yi JiangMinistry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.ORCID 0000-0002-1196-0280
Minghan QuMinistry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.ORCID 0009-0003-3155-679X
Minghui JiangMinistry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.ORCID 0000-0002-7888-2408
Xuan JiangMinistry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.ORCID 0009-0001-1580-3186
Shane FernandezCentre for Precision Health, Edith Cowan University, Perth, WA 6027, Australia.ORCID 0000-0002-4881-245X
Tenielle PorterCentre for Precision Health, Edith Cowan University, Perth, WA 6027, Australia.ORCID 0000-0002-7887-6622
Simon M LawsCentre for Precision Health, Edith Cowan University, Perth, WA 6027, Australia.ORCID 0000-0002-4355-7082
Colin L MastersThe Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC 3052, Australia.ORCID 0000-0003-3072-7940
Huan GuoMinistry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.ORCID 0000-0002-7838-2585
Shanshan ChengMinistry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.ORCID 0000-0003-2676-7341
Chaolong WangMinistry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.ORCID 0000-0003-3945-1012

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

DNA MethylationGenotypePolymorphism, Single NucleotideAlgorithmsAsian PeopleGenome-Wide Association StudyHumansSoftwareDNA methylationEpigenome-wide association studyGenetic relatednessGenotype callingPopulation structure

Identifiers

PMID39353864
PMCPMC12016561

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.