Evidence map›Paper›PMID 41658019›Full record

ArticleSerican journal of medicine2025

Impact of Nanopore Flow Cell Types on DNA Methylation Detection.

Xianglin Shi, Xiaodong Lu, Xinyue Chen, Shaojun Yu, Rebecca S Arnold, Viraj A Master, Jonathan C Zhao

Abstract read
In one paragraph

Article in Serican journal of medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Fluorescent Analysis of KBiomolecules · 2026
    Article
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

7 authors.

Xianglin ShiDepartment of Urology, Emory University School of Medicine, Atlanta, GA 30322, USA.
Xiaodong LuDepartment of Urology, Emory University School of Medicine, Atlanta, GA 30322, USA.
Xinyue ChenDepartment of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA.
Shaojun YuDepartment of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA.
Rebecca S ArnoldDepartment of Urology, Emory University School of Medicine, Atlanta, GA 30322, USA.
Viraj A MasterDepartment of Urology, Emory University School of Medicine, Atlanta, GA 30322, USA.
Jonathan C ZhaoDepartment of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA.

Funding

Molecular Mechanisms Underlying Luminal- Neuroendocrine TransdifferentiationR01CA286147 · NCI · EMORY UNIVERSITY · PI Jindan Yu, Changsheng Zhao · 2024 to 2026
$2.7M
Comprehensive Analyses of HOXB13-regulated Transcriptional programs critical for Prostate Cancer ProgressionR01CA257446 · NCI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI YU, JINDAN · 2021 to 2025
$2.4M
NCI NIH HHS R01 CA257446NCI NIH HHS R01 CA286147
6 · The paper itself

Abstract

Third-generation sequencing technologies have revolutionized the study of epigenetic characteristics in human diseases, with Oxford Nanopore Technologies (ONT) at the forefront of long-read sequencing. ONT has made rapid improvements in flow cell designs, which greatly increased its sequencing accuracy but, at the same time, led to some projects utilizing different flow cell types, mainly R9 vs. R10, across samples. Whether and how the flow cell types affect genome-wide DNA methylation detection remains incompletely understood. Here, we used both flow cell types to analyze 6 human renal cell carcinoma (RCC) samples and compared the results. While there was a highly significant correlation between 5-methylcytosine (5mC) detected by R9 and R10 flow cells, we also observed substantial differences. R9 flow cells over-estimated 5mC levels at hypomethylated chromatin regions, mostly at promoters, while under-estimated 5mC at hypermethylated chromatin regions, enriched at intronic and intergenic regions. Such deviations in detection were likely caused by substantially lower sequencing accuracy of R9 flow cells, due to its mechanics, especially having problems sequencing homopolymeric DNA elements, such as CpG islands, leading to both higher false-positive and false-negative detections. Interestingly, such systematic errors were largely mitigated by batch-correction software, improving data comparability. In summary, our study reports superior performance of R10 flow cells, leading to much higher accuracy in base sequencing and DNA methylation detection.

Indexed as

DNA methylationNanoporesequencingthird-generation

Identifiers

PMID41658019
PMCPMC12880221

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Registered trials

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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.