ArticleNucleic acids research2016
MethylAction: detecting differentially methylated regions that distinguish biological subtypes.
Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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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.
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.
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Who cites it
12 citing papers in PubMed.
- DNA methylation site loss for plasticity-led novel trait genetic fixation.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Differentiation in the human urothelia is defined by distinct alternative polyadenylation.Cell reports · 2026Article
- Integrative mapping of the dog epigenome: Reference annotation for comparative intertissue and cross-species studies.Science advances · 2023Article
- Computational challenges in detection of cancer using cell-free DNA methylation.Computational and structural biotechnology journal · 2022Review
- Ten Years of EWAS.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2021Review
- Whole-Genome Differentially Hydroxymethylated DNA Regions among Twins Discordant for Cardiovascular Death.Genes · 2021Article
- DNA Methylation Changes in the Sperm of Captive-Reared Fish: A Route to Epigenetic Introgression in Wild Populations.Molecular biology and evolution · 2019Article
- Genome-wide analysis of epigenetic dynamics across human developmental stages and tissues.BMC genomics · 2019Article
- Data showing atherosclerosis-associated differentially methylated regions are often at enhancers.Data in brief · 2019Article
- Epigenetic Targeting of Adipocytes Inhibits High-Grade Serous Ovarian Cancer Cell Migration and Invasion.Molecular cancer research : MCR · 2018Article
- Interplay between maternal Slc6a4 mutation and prenatal stress: a possible mechanism for autistic behavior development.Scientific reports · 2017Article
- Goldmine integrates information placing genomic ranges into meaningful biological contexts.Nucleic acids research · 2016Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
DNA methylation differences capture substantial information about the molecular and gene-regulatory states among biological subtypes. Enrichment-based next generation sequencing methods such as MBD-isolated genome sequencing (MiGS) and MeDIP-seq are appealing for studying DNA methylation genome-wide in order to distinguish between biological subtypes. However, current analytic tools do not provide optimal features for analyzing three-group or larger study designs. MethylAction addresses this need by detecting all possible patterns of statistically significant hyper- and hypo- methylation in comparisons involving any number of groups. Crucially, significance is established at the level of differentially methylated regions (DMRs), and bootstrapping determines false discovery rates (FDRs) associated with each pattern. We demonstrate this functionality in a four-group comparison among benign prostate and three clinical subtypes of prostate cancer and show that the bootstrap FDRs are highly useful in selecting the most robust patterns of DMRs. Compared to existing tools that are limited to two-group comparisons, MethylAction detects more DMRs with strong differential methylation measurements confirmed by whole genome bisulfite sequencing and offers a better balance between precision and recall in cross-cohort comparisons. MethylAction is available as an R package at http://jeffbhasin.github.io/methylaction.
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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 OpenQuestion graph.