ReviewBriefings in bioinformatics2018
A survey of the approaches for identifying differential methylation using bisulfite sequencing data.
Review in Briefings in bioinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
What it found
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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.
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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
37 citing papers in PubMed.
- SOPA and SIMPA: normalized single-sample integrated multiomics pathway analysis of tumor heterogeneity in solid cancers.Briefings in bioinformatics · 2026Article
- Uncovering alterations in cancer epigenetics via trans-dimensional Markov chain Monte Carlo and hidden Markov models.Journal of the Royal Statistical Society. Series C, Applied statistics · 2026Article
- cyberDMR: accurate and robust identification of differentially methylated regions from WGS-derived methylomes.BMC biology · 2026Article
- KDM5C and KDM5D influence DNA methylation in adult mouse liver.Biology of sex differences · 2026Article
- Benchmarking of methods to analyse data derived from GBS-MeDIP.BMC bioinformatics · 2026Article
- Methylome differences among barley inbreds and their association with genomic, transcriptomic, and phenotypic variation.Journal of experimental botany · 2026Article
- ReMeDy: A Flexible Statistical Framework For Region-based Detection of DNA Methylation Dysregulation.bioRxiv : the preprint server for biology · 2026Article
- Methods for analysing wildlife DNA methylation data.Conservation physiology · 2026Article
- OpTiles: an R package for adaptive tiling and methylation variability profiling.Bioinformatics (Oxford, England) · 2025Article
- Evaluation of Illumina and Oxford Nanopore Sequencing for the Study of DNA Methylation in Alzheimer's Disease and Frontotemporal Dementia.International journal of molecular sciences · 2025Review
- Data-Driven Identification of Early Cancer-Associated Genes via Penalized Trans-Dimensional Hidden Markov Models.Biomolecules · 2025Article
- MethyLasso: a segmentation approach to analyze DNA methylation patterns and identify differentially methylated regions from whole-genome datasets.Nucleic acids research · 2024Article
- Identifying Differential Methylation in Cancer Epigenetics via a Bayesian Functional Regression Model.Biomolecules · 2024Article
- Molecular Regulation of Fetal Brain Development in Inbred and Congenic Mouse Strains Differing in Longevity.Genes · 2024Article
- HBCR_DMR: A Hybrid Method Based on Beta-Binomial Bayesian Hierarchical Model and Combination of Ranking Method to Detect Differential Methylation Regions in Bisulfite Sequencing Data.Journal of personalized medicine · 2024Article
- Isogenic Human-Induced Pluripotent Stem-Cell-Derived Cardiomyocytes Reveal Activation of Wnt Signaling Pathways Underlying Intrinsic Cardiac Abnormalities in Rett Syndrome.International journal of molecular sciences · 2022Article
- Computational Analysis of High-Dimensional DNA Methylation Data for Cancer Prognosis.Journal of computational biology : a journal of computational molecular cell biology · 2022Review
- DNA methylation-based predictors of health: applications and statistical considerations.Nature reviews. Genetics · 2022Review
- Calling differentially methylated regions from whole genome bisulphite sequencing with DMRcate.Nucleic acids research · 2021Article
- Abnormal expression and methylation of PRR34-AS1 are associated with adverse outcomes in acute myeloid leukemia.Cancer medicine · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
DNA methylation is an important epigenetic mechanism that plays a crucial role in cellular regulatory systems. Recent advancements in sequencing technologies now enable us to generate high-throughput methylation data and to measure methylation up to single-base resolution. This wealth of data does not come without challenges, and one of the key challenges in DNA methylation studies is to identify the significant differences in the methylation levels of the base pairs across distinct biological conditions. Several computational methods have been developed to identify differential methylation using bisulfite sequencing data; however, there is no clear consensus among existing approaches. A comprehensive survey of these approaches would be of great benefit to potential users and researchers to get a complete picture of the available resources. In this article, we present a detailed survey of 22 such approaches focusing on their underlying statistical models, primary features, key advantages and major limitations. Importantly, the intrinsic drawbacks of the approaches pointed out in this survey could potentially be addressed by future research.
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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.