ArticleBMC bioinformatics2016
MethPat: a tool for the analysis and visualisation of complex methylation patterns obtained by massively parallel sequencing.
Article in BMC bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 24 citations in OpenAlex.
- DNA methylation patterns re-establish during clonal expansion restoring cell-to-cell epialleles heterogeneity.Biology direct · 2026Article
- Methylation heterogeneity of the AQP1 promoter as a candidate prognostic biomarker in cholangiocarcinoma.Scientific reports · 2026Article
- MUC1 promoter methylation pattern diversity and its association with TET3 expression and prognosis in cholangiocarcinoma.Scientific reports · 2025Article
- Locus-level L1 DNA methylation profiling reveals the epigenetic and transcriptional interplay between L1s and their integration sites.Cell genomics · 2024Article
- Pivotal role for S-nitrosylation of DNA methyltransferase 3B in epigenetic regulation of tumorigenesis.Nature communications · 2023Article
- Methylscaper: an R/Shiny app for joint visualization of DNA methylation and nucleosome occupancy in single-molecule and single-cell data.Bioinformatics (Oxford, England) · 2021Article
- MethPanel: a parallel pipeline and interactive analysis tool for multiplex bisulphite PCR sequencing to assess DNA methylation biomarker panels for disease detection.Bioinformatics (Oxford, England) · 2021Article
- Epigenetic Distribution of Recombinant Plant Chromosome Fragments in a Human-International journal of molecular sciences · 2021Article
- Tracing and tracking epiallele families in complex DNA populations.NAR genomics and bioinformatics · 2020Article
- Quantitative comparison of within-sample heterogeneity scores for DNA methylation data.Nucleic acids research · 2020Article
- Characterization of human telomerase reverse transcriptase promoter methylation and transcription factor binding in differentiated thyroid cancer cell lines.Genes, chromosomes & cancer · 2019Article
- EPIC-TABSAT: analysis tool for targeted bisulfite sequencing experiments and array-based methylation studies.Nucleic acids research · 2019Article
- A Novel Computational Method for Detecting DNA Methylation Sites with DNA Sequence Information and Physicochemical Properties.International journal of molecular sciences · 2018Article
- Detecting rare asymmetrically methylated cytosines and decoding methylation patterns in the honeybee genome.Royal Society open science · 2017Article
- Association of Tissue-Specific DNA Methylation Alterations with α-Thalassemia Southeast Asian Deletion.Genetics & epigenetics · 2017Article
- ampliMethProfiler: a pipeline for the analysis of CpG methylation profiles of targeted deep bisulfite sequenced amplicons.BMC bioinformatics · 2016Article
- Exemplary multiplex bisulfite amplicon data used to demonstrate the utility of Methpat.GigaScience · 2015Article
Corrections and comments
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Authors and funding
12 authors at 8 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDNA methylation at a gene promoter region has the potential to regulate gene transcription. Patterns of methylation over multiple CpG sites in a region are often complex and cell type specific, with the region showing multiple allelic patterns in a sample. This complexity is commonly obscured when DNA methylation data is summarised as an average percentage value for each CpG site (or aggregated across CpG sites). True representation of methylation patterns can only be fully characterised by clonal analysis. Deep sequencing provides the ability to investigate clonal DNA methylation patterns in unprecedented detail and scale, enabling the proper characterisation of the heterogeneity of methylation patterns. However, the sheer amount and complexity of sequencing data requires new synoptic approaches to visualise the distribution of allelic patterns.
resultsWe have developed a new analysis and visualisation software tool "Methpat", that extracts and displays clonal DNA methylation patterns from massively parallel sequencing data aligned using Bismark. Methpat was used to analyse multiplex bisulfite amplicon sequencing on a range of CpG island targets across a panel of human cell lines and primary tissues. Methpat was able to represent the clonal diversity of epialleles analysed at specific gene promoter regions. We also used Methpat to describe epiallelic DNA methylation within the mitochondrial genome.
conclusionsMethpat can summarise and visualise epiallelic DNA methylation results from targeted amplicon, massively parallel sequencing of bisulfite converted DNA in a compact and interpretable format. Unlike currently available tools, Methpat can visualise the diversity of epiallelic DNA methylation patterns in a sample.
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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.