Evidence map›Paper›PMID 42349238›Full record

ArticleComputational biology and chemistry2026

Comparison of nanopore sequencing, MethylationEPIC array, and EM-Seq for DNA methylation detection.

Steven Brooks, Melissa Robins, Hongyu Gao, Xuhong Yu, Kwangsik Nho, Andrew Saykin, Yunlong Liu, Gang Peng

Abstract readComparative Study
In one paragraph

Article in Computational biology and chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Steven BrooksDepartment of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
Melissa RobinsDepartment of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
Hongyu GaoDepartment of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
Xuhong YuDepartment of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
Kwangsik NhoDepartment of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
Andrew SaykinDepartment of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
Yunlong LiuDepartment of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA. Electronic address: yunliu@iu.edu.
Gang PengDepartment of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA. Electronic address: gangpeng@iu.edu.

Funding

Project 1U19AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI MONICA G. RIVERA-MINDT · 2016 to 2026
$226.7M
Subject CollectionU10AA008401 · NIAAA · SUNY DOWNSTATE MEDICAL CENTER · PI JAY Arnold TISCHFIELD · 1989 to 2026
$162.7M
Peripheral and Central Biomarkers of Alzheimer's Disease in Diverse CohortsU19AG074879 · NIA · MAYO CLINIC JACKSONVILLE · PI Minerva Maria Carrasquillo, NILUFER ERTEKIN-TANER · 2023 to 2026
$42.0M
MVP Data Integration into the ADSP Phenotype Harmonization ConsortiumU24AG074855 · NIA · VANDERBILT UNIVERSITY MEDICAL CENTER · PI CUCCARO, MICHAEL L, HOHMAN, TIMOTHY J · 2021 to 2025
$37.5M
Research Education ComponentP30AG010133 · NIA · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI SAYKIN, ANDREW J · 1991 to 2020
$37.3M
Research Education ComponentP30AG072976 · NIA · INDIANA UNIVERSITY INDIANAPOLIS · PI ANDREW J SAYKIN · 2021 to 2026
$24.1M
Ultrascale Machine Learning to Empower Discovery in Alzheimers Disease BiobanksU01AG068057 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Christos Davatzikos, Heng Huang · 2020 to 2026
$20.7M
KBASE2: Korean Brain Aging Study, Longitudinal Endophenotypes and Systems BiologyU01AG072177 · NIA · INDIANA UNIVERSITY INDIANAPOLIS · PI LEE, DONG YOUNG, NHO, KWANGSIK TIMOTHY · 2021 to 2025
$11.2M
Memory Circuitry in MCI and Early Alzheimer’s Disease Prodrome: Molecular DriversR01AG019771 · NIA · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI SAYKIN, ANDREW J · 2001 to 2021
$6.9M
Leveraging Neuroimaging Biomarkers to Understand the Role of Social Networks in Alzheimer's DiseaseR01AG057739 · NIA · TRUSTEES OF INDIANA UNIVERSITY · PI APOSTOLOVA, LIANA G, PERRY, BREA LOUISE · 2018 to 2022
$3.5M
Cognitive Aging, Alzheimers disease, and Cancer-related Cognitive DeclineR01AG068193 · NIA · GEORGETOWN UNIVERSITY · PI MANDELBLATT, JEANNE, SAYKIN, ANDREW J · 2020 to 2023
$2.8M
Training Grant on Alzheimer's Disease and ADRD at Indiana UniversityT32AG071444 · NIA · INDIANA UNIVERSITY INDIANAPOLIS · PI GARY E. LANDRETH, Bruce T Lamb · 2021 to 2026
$2.8M
NHGRI NIH HHS R25 HG012325NIAAA NIH HHS U10 AA008401NIA NIH HHS P30 AG010133NIA NIH HHS P30 AG072976NIA NIH HHS R01 AG019771NIA NIH HHS R01 AG057739NIA NIH HHS R01 AG068193NIA NIH HHS R01 AG092591NIA NIH HHS T32 AG071444NIA NIH HHS U01 AG068057NIA NIH HHS U01 AG072177NIA NIH HHS U19 AG024904NIA NIH HHS U19 AG074879NIA NIH HHS U24 AG074855NLM NIH HHS R01 LM013463
6 · The paper itself

Abstract

DNA methylation is an important biological process in epigenetics, and many methods have been developed to profile DNA methylation. Recent studies have employed Oxford Nanopore long-read sequencing for DNA methylation detection, presenting an alternative to the widely utilized Infinium arrays and short-read methods. In this study, we evaluate the performance of Nanopore sequencing in DNA methylation detection by comparing it to Illumina's MethylationEPIC microarray (EPIC) and Enzymatic Methyl-Sequencing (EM-Seq). The initial comparison was between Nanopore and the EPIC array using blood samples (n = 4). Among the ∼850,000 CpG sites covered by both methods, we observed high concordance (Pearson correlation coefficient, r ≥ 0.94 across all four samples). After downsampling Nanopore data from an average coverage of 26.4 reads per site to 10 reads per site, the correlation in CpG methylation remained high (r ≥ 0.93). When comparing Nanopore and EM-Seq using brain tissue samples (n = 4), lower correlation of CpG methylation (r: 0.79-0.88) was detected between Nanopore and EM-Seq, which can be attributed to biased and reduced coverage of hypomethylated CpG sites by EM-Seq. We also investigated additional features of Nanopore sequencing, such as native DNA sequencing that can differentiate 5mC and 5hmC, as well as haplotype phasing. Overall, the Nanopore platform exhibited a high degree of concordance with the EPIC array and provided more uniform genomic coverage than EM-Seq. This study provides insights for researchers in selecting appropriate DNA methylation detection methods, considering factors such as cost, DNA input, and the complexity of downstream analysis.

Indexed as

DNA MethylationNanoporesNanopore SequencingOligonucleotide Array Sequence AnalysisSequence Analysis, DNACpG IslandsHumans5mC/5hmCDNA methylationEM-SeqHaplotype phasingLong-read sequencingNanopore

Identifiers

PMID42349238
PMCPMC13356952

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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.