ArticleNature communications2024
MethPhaser: methylation-based long-read haplotype phasing of human genomes.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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The trial behind it
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Who cites it
18 citing papers in PubMed.
- asms: finding allele-specific methylation in human genomes without phasing.NAR genomics and bioinformatics · 2026Article
- DNA Methylation as a Programmable Information Layer: From Molecular Marks to Disease State Engineering.International journal of molecular sciences · 2026Review
- From Spatial Epigenomes to Clinical Diagnostics: Integrative Methylomics Across Scales and Modalities.International journal of molecular sciences · 2026Review
- Advances in haplotype phasing and genotype imputation.Nature reviews. Genetics · 2026Review
- GREGoR: accelerating genomics for rare diseases.Nature · 2025Article
- Computational analysis of DNA methylation from long-read sequencing.Nature reviews. Genetics · 2025Review
- NANOME: A Nextflow pipeline for haplotype-aware allele-specific consensus DNA methylation detection by nanopore long-read sequencing.bioRxiv : the preprint server for biology · 2025Article
- Haplotypic resolution of the challenging genomic regions of MHC and KIR using a combination of targeted sequencing and a novel assembly pipeline.Nucleic acids research · 2025Article
- Prospective, multicenter validation of a platform for rapid molecular profiling of central nervous system tumors.Nature medicine · 2025Article
- Near-complete Middle Eastern genomes refine autozygosity and enhance disease-causing and population-specific variant discovery.Nature genetics · 2025Article
- Unraveling the hidden complexity of cancer through long-read sequencing.Genome research · 2025Review
- Evolution of genome-wide methylation profiling technologies.Genome research · 2025Review
- A Hitchhiker's Guide to long-read genomic analysis.Genome research · 2025Review
- Profiling the epigenome using long-read sequencing.Nature genetics · 2025Review
- Expanding Upon Genomics in Rare Diseases: Epigenomic Insights.International journal of molecular sciences · 2024Review
- GREGoR: Accelerating Genomics for Rare Diseases.ArXiv · 2024Article
- Unveiling microbial diversity: harnessing long-read sequencing technology.Nature methods · 2024Review
- HapKled: a haplotype-aware structural variant calling approach for Oxford nanopore sequencing data.Frontiers in genetics · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
The assignment of variants across haplotypes, phasing, is crucial for predicting the consequences, interaction, and inheritance of mutations and is a key step in improving our understanding of phenotype and disease. However, phasing is limited by read length and stretches of homozygosity along the genome. To overcome this limitation, we designed MethPhaser, a method that utilizes methylation signals from Oxford Nanopore Technologies to extend Single Nucleotide Variation (SNV)-based phasing. We demonstrate that haplotype-specific methylations extensively exist in Human genomes and the advent of long-read technologies enabled direct report of methylation signals. For ONT R9 and R10 cell line data, we increase the phase length N50 by 78%-151% at a phasing accuracy of 83.4-98.7% To assess the impact of tissue purity and random methylation signals due to inactivation, we also applied MethPhaser on blood samples from 4 patients, still showing improvements over SNV-only phasing. MethPhaser further improves phasing across HLA and multiple other medically relevant genes, improving our understanding of how mutations interact across multiple phenotypes. The concept of MethPhaser can also be extended to non-human diploid genomes. MethPhaser is available at https://github.com/treangenlab/methphaser .
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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.