ArticleNucleic acids research2019
coMethDMR: accurate identification of co-methylated and differentially methylated regions in epigenome-wide association studies with continuous phenotypes.
Article in Nucleic acids research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 4 of them syntheses that pooled it.
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Who cites it
23 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- The aging epigenome: integrative analyses reveal intersection with Alzheimer's disease.GeroScience · 2026Pooled it
- Cross-tissue analysis of blood and brain epigenome-wide association studies in Alzheimer's disease.Nature communications · 2022Pooled it
- Sex-specific DNA methylation differences in Alzheimer's disease pathology.Acta neuropathologica communications · 2021Pooled it
- Epigenome-wide meta-analysis of DNA methylation differences in prefrontal cortex implicates the immune processes in Alzheimer's disease.Nature communications · 2020Pooled it
- From aging to Alzheimer's disease: concordant brain DNA methylation changes in late life.Genome medicine · 2026Article
- ReMeDy: A Flexible Statistical Framework For Region-based Detection of DNA Methylation Dysregulation.bioRxiv : the preprint server for biology · 2026Article
- DNA methylation signatures of frailty beyond age: a longitudinal study of female and male mice.bioRxiv : the preprint server for biology · 2025Article
- Using blood methylomes to predict response to amisulpride in the first-episode psychosis in the OPTiMiSE cohort.Translational psychiatry · 2025Article
- Blood DNA methylation signature for incident dementia: Evidence from longitudinal cohorts.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Critical evaluation of the reliability of DNA methylation probes on the Illumina MethylationEPIC v1.0 BeadChip microarrays.Epigenetics · 2024Article
- Article
- A novel principal component based method for identifying differentially methylated regions in Illumina Infinium MethylationEPIC BeadChip data.Epigenetics · 2023Article
- Multi-ancestry epigenome-wide analyses identify methylated sites associated with aortic augmentation index in TOPMed MESA.Scientific reports · 2023Article
- Critical evaluation of the reliability of DNA methylation probes on the Illumina MethylationEPIC BeadChip microarrays.Research square · 2023Article
- UHRF1/DNMT1-MZF1 axis-modulated intragenic site-specific CpGI methylation confers divergent expression and opposing functions ofActa pharmaceutica Sinica. B · 2023Article
- An evaluation of the genome-wide false positive rates of common methods for identifying differentially methylated regions using illumina methylation arrays.Epigenetics · 2022Article
- Aclust2.0: a revamped unsupervised R tool for Infinium methylation beadchips data analyses.Bioinformatics (Oxford, England) · 2022Article
- Article
- CpG Site-Specific Methylation-Modulated Divergent Expression ofFrontiers in oncology · 2022Article
- MethylSPWNet and MethylCapsNet: Biologically Motivated Organization of DNAm Neural Networks, Inspired by Capsule Networks.NPJ systems biology and applications · 2021Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Recent technology has made it possible to measure DNA methylation profiles in a cost-effective and comprehensive genome-wide manner using array-based technology for epigenome-wide association studies. However, identifying differentially methylated regions (DMRs) remains a challenging task because of the complexities in DNA methylation data. Supervised methods typically focus on the regions that contain consecutive highly significantly differentially methylated CpGs in the genome, but may lack power for detecting small but consistent changes when few CpGs pass stringent significance threshold after multiple comparison. Unsupervised methods group CpGs based on genomic annotations first and then test them against phenotype, but may lack specificity because the regional boundaries of methylation are often not well defined. We present coMethDMR, a flexible, powerful, and accurate tool for identifying DMRs. Instead of testing all CpGs within a genomic region, coMethDMR carries out an additional step that selects co-methylated sub-regions first. Next, coMethDMR tests association between methylation levels within the sub-region and phenotype via a random coefficient mixed effects model that models both variations between CpG sites within the region and differential methylation simultaneously. coMethDMR offers well-controlled Type I error rate, improved specificity, focused testing of targeted genomic regions, and is available as an open-source R package.
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Registered trials
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 Socratic graph.