Definition and research guide
This page combines a MeSH definition, publication statistics and selected research abstracts. It is a starting point for reading the literature, not a medical textbook or a systematic evidence review.
Content available: 4 complete abstracts (660 words), 10 references. Full article text is not stored or reproduced here; follow the PMID, DOI or PMC links to read the original sources and their access terms.
Definition
A sequencing protocol that drives nucleic acids (DNA or RNA) in an electric field through nanopores allowing single molecule sequence analysis.
Definition: NLM Medical Subject Headings (MeSH) scope note (Public domain (U.S. National Library of Medicine); attribution requested). View the MeSH record.
Also known as: Nanopore Sequencings; Sequencing, Nanopore.
Where it fits in the MeSH classification
- Broader topics
- Sequence Analysis
Related concepts
- Nanopores
Research landscape
PubMed indexes 1,703 records tagged with the MeSH heading “Nanopore Sequencing” (counts retrieved 2026-10-29). 1,647 of them (96.7%) were published from 2020 onward, and the busiest period so far is 2020 onward with 1,647 records.
Reviews account for 87 records (5.1%) and meta-analyses for 2. Randomized controlled trials number 1 (0.1%) as a share of all records on the topic. Randomized trials make up only a small share of this literature, so much of what is known comes from laboratory, observational or descriptive work.
Show the data
| Period | Records |
|---|---|
| through 1999 | 0 |
| 2000-2009 | 0 |
| 2010-2019 | 68 |
| 2020 onward | 1,647 |
Publication-type chart data
| Type | Records | Share |
|---|---|---|
| Reviews | 87 | 5.1% |
| Meta-analyses | 2 | 0.1% |
| Randomized controlled trials | 1 | 0.1% |
Method: PubMed query "Nanopore Sequencing"[MeSH Terms] with publication-type and date filters, retrieved 2026-10-29.
Reading the evidence in genetics and genomics
Genetic findings vary widely in strength. A variant linked to a condition in one study may not replicate in other ancestries, and most common variants have small effects that are meaningful only in aggregate. Studies of rare, high-impact variants can support strong causal claims about a gene, while association studies describe statistical links that need functional and independent replication. Check the sample size, the ancestry of participants, whether results were replicated, and whether a laboratory or clinical outcome was actually measured.
Evidence from open-access studies
These open-access studies come from PubMed’s best-match results for this heading (papers whose main topic it is), ranked here by citation count, with one recent addition. Each abstract is reproduced in full under its recorded open licence so that you can read the authors’ own words. They illustrate the literature; they are not a systematic summary of it. Citation counts measure attention, not reliability or clinical benefit.
| Study / authors | Year | Source label / design | Europe PMC citations | Licence / source |
|---|---|---|---|---|
| A signal processing and deep learning framework for methylation detection using Oxford Nanopore sequencing | 2024 | Research article Design not recorded in structured metadata | 89 | cc by PMID 38365920 · DOI · PMC10873387 |
| Flexible and cost-effective genomic surveillance of P. falciparum malaria with targeted nanopore sequencing | 2024 | Research article Design not recorded in structured metadata | 51 | cc by PMID 38360754 · DOI · PMC10869361 |
| Demultiplexing and barcode-specific adaptive sampling for nanopore direct RNA sequencing | 2025 | Research article Design not recorded in structured metadata | 35 | cc by PMID 40258808 · DOI · PMC12012114 |
| High-quality metagenome assembly from nanopore reads with nanoMDBG | 2026 | Research article Design not recorded in structured metadata | 10 | cc by PMID 41792155 · DOI · PMC13087279 |
A signal processing and deep learning framework for methylation detection using Oxford Nanopore sequencing [1]
Abstract reading summary — source excerpts
- Opening excerpt
- Oxford Nanopore sequencing can detect DNA methylations from ionic current signal of single molecules, offering a unique advantage over conventional methods.
- Closing excerpt
- In summary, DeepMod2 is an open-source tool that enables fast and accurate DNA methylation detection from whole-genome or adaptive sequencing data on a diverse range of flowcell types.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (199 words)
Oxford Nanopore sequencing can detect DNA methylations from ionic current signal of single molecules, offering a unique advantage over conventional methods. Additionally, adaptive sampling, a software-controlled enrichment method for targeted sequencing, allows reduced representation methylation sequencing that can be applied to CpG islands or imprinted regions. Here we present DeepMod2, a comprehensive deep-learning framework for methylation detection using ionic current signal from Nanopore sequencing. DeepMod2 implements both a bidirectional long short-term memory (BiLSTM) model and a Transformer model and can analyze POD5 and FAST5 signal files generated on R9 and R10 flowcells. Additionally, DeepMod2 can run efficiently on central processing unit (CPU) through model pruning and can infer epihaplotypes or haplotype-specific methylation calls from phased reads. We use multiple publicly available and newly generated datasets to evaluate the performance of DeepMod2 under varying scenarios. DeepMod2 has comparable performance to Guppy and Dorado, which are the current state-of-the-art methods from Oxford Nanopore Technologies that remain closed-source. Moreover, we show a high correlation (r = 0.96) between reduced representation and whole-genome Nanopore sequencing. In summary, DeepMod2 is an open-source tool that enables fast and accurate DNA methylation detection from whole-genome or adaptive sequencing data on a diverse range of flowcell types.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 38365920 · DOI · PMC10873387
Flexible and cost-effective genomic surveillance of P. falciparum malaria with targeted nanopore sequencing [2]
Abstract reading summary — source excerpts
- Opening excerpt
- Genomic surveillance of Plasmodium falciparum malaria can provide policy-relevant information about antimalarial drug resistance, diagnostic test failure, and the evolution of vaccine targets.
- Closing excerpt
- falciparum within-sample diversity and to detect deletions underlying rapid diagnostic test failure.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (163 words)
Genomic surveillance of Plasmodium falciparum malaria can provide policy-relevant information about antimalarial drug resistance, diagnostic test failure, and the evolution of vaccine targets. Yet the large and low complexity genome of P. falciparum complicates the development of genomic methods, while resource constraints in malaria endemic regions can limit their deployment. Here, we demonstrate an approach for targeted nanopore sequencing of P. falciparum from dried blood spots (DBS) that enables cost-effective genomic surveillance of malaria in low-resource settings. We release software that facilitates flexible design of amplicon sequencing panels and use this software to design two target panels for P. falciparum. The panels generate 3-4 kbp reads for eight and sixteen targets respectively, covering key drug-resistance associated genes, diagnostic test antigens, polymorphic markers and the vaccine target csp. We validate our approach on mock and field samples, demonstrating robust sequencing coverage, accurate variant calls within coding sequences, the ability to explore P. falciparum within-sample diversity and to detect deletions underlying rapid diagnostic test failure.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 38360754 · DOI · PMC10869361
Demultiplexing and barcode-specific adaptive sampling for nanopore direct RNA sequencing [3]
Abstract reading summary — source excerpts
- Opening excerpt
- Nanopore direct RNA sequencing (dRNA-seq) enables unique insights into RNA biology.
- Closing excerpt
- In summary, WarpDemuX represents a broadly applicable, high-performance, economical multiplexing solution for dRNA-seq, facilitating advanced (epi-) transcriptomic research.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (149 words)
Nanopore direct RNA sequencing (dRNA-seq) enables unique insights into RNA biology. However, applications are currently limited by the lack of accurate and cost-effective sample multiplexing. Here we introduce WarpDemuX, an ultra-fast and highly accurate adapter-barcoding and demultiplexing approach for dRNA-seq with SQK-RNA002 and SQK-RNA004 chemistries. WarpDemuX enhances speed and accuracy by fast processing of the raw nanopore signal, use of a light-weight machine-learning algorithm and design of optimized barcode sets. We demonstrate its utility by performing rapid phenotypic profiling of different SARS-CoV-2 viruses through multiplexed sequencing of longitudinal samples on a single flowcell, identifying systematic differences in transcript abundance and poly(A) tail lengths during infection. Additionally, integrating WarpDemuX into sequencing control software enables real-time enrichment of target molecules through barcode-specific adaptive sampling, which we demonstrate by enriching low abundance viral RNA. In summary, WarpDemuX represents a broadly applicable, high-performance, economical multiplexing solution for dRNA-seq, facilitating advanced (epi-) transcriptomic research.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 40258808 · DOI · PMC12012114
High-quality metagenome assembly from nanopore reads with nanoMDBG [4]
Abstract reading summary — source excerpts
- Opening excerpt
- Third-generation long-read sequencing technologies, significantly improve metagenome assemblies.
- Closing excerpt
- Critically, the latest ONT technology can now produce comparable MAG construction results as those obtained using PacBio HiFi at the same sequencing depth.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (149 words)
Third-generation long-read sequencing technologies, significantly improve metagenome assemblies. Highly accurate PacBio HiFi reads can yield hundreds of near-complete metagenome-assembled genomes (MAGs) from a single sample. Recently, the accuracy of the more cost-effective Oxford Nanopore Technologies (ONT) platform has increased to a per-base error rate of 1-2%. However, current metagenome assemblers are optimized for HiFi and do not scale to the large data sets that ONT enables. We present nanoMDBG, an evolution of metaMDBG, which supports the latest ONT reads through an error correction pre-processing step in minimizer-space. Across a range of ONT datasets, including a large 400 Gbp soil sample, nanoMDBG reconstructs up to twice as many high-quality MAGs as the next best ONT assembler, metaFlye, while requiring a third of the CPU time and memory. Critically, the latest ONT technology can now produce comparable MAG construction results as those obtained using PacBio HiFi at the same sequencing depth.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 41792155 · DOI · PMC13087279
Key reviews and meta-analyses
The most cited review-type papers among PubMed’s best-match results for this heading, listed with bibliographic details only. Follow the links for the full text and access terms.
- Research article Opportunities and challenges in long-read sequencing data analysis [5]
- Research article Nanopore sequencing technology, bioinformatics and applications [6]
- Research article Third-Generation Sequencing in the Clinical Laboratory: Exploring the Advantages and Challenges of Nanopore Sequencing [7]
- Research article Nanopore sequencing technology and tools for genome assembly: computational analysis of the current state, bottlenecks and future directions [8]
- Research article Recent advances in the detection of base modifications using the Nanopore sequencer [9]
- Research article Computational methods for RNA modification detection from nanopore direct RNA sequencing data [10]
References
- Ahsan MU, Gouru A, Chan J, Zhou W, Wang K. A signal processing and deep learning framework for methylation detection using Oxford Nanopore sequencing. . 2024. PMID 38365920 · DOI · PMC10873387
- de Cesare M, Mwenda M, Jeffreys AE, Chirwa J, Drakeley C, Schneider K, et al.. Flexible and cost-effective genomic surveillance of P. falciparum malaria with targeted nanopore sequencing. . 2024. PMID 38360754 · DOI · PMC10869361
- van der Toorn W, Bohn P, Liu-Wei W, Olguin-Nava M, Gribling-Burrer AS, Smyth RP, et al.. Demultiplexing and barcode-specific adaptive sampling for nanopore direct RNA sequencing. . 2025. PMID 40258808 · DOI · PMC12012114
- Benoit G, James R, Raguideau S, Alabone G, Goodall T, Chikhi R, et al.. High-quality metagenome assembly from nanopore reads with nanoMDBG. . 2026. PMID 41792155 · DOI · PMC13087279
- Amarasinghe SL, Su S, Dong X, Zappia L, Ritchie ME, Gouil Q. Opportunities and challenges in long-read sequencing data analysis. Genome Biol. 2020. PMID 32033565 · DOI · PMC7006217
- Wang Y, Zhao Y, Bollas A, Wang Y, Au KF. Nanopore sequencing technology, bioinformatics and applications. Nat Biotechnol. 2021. PMID 34750572 · DOI · PMC8988251
- Petersen LM, Martin IW, Moschetti WE, Kershaw CM, Tsongalis GJ. Third-Generation Sequencing in the Clinical Laboratory: Exploring the Advantages and Challenges of Nanopore Sequencing. J Clin Microbiol. 2019. PMID 31619531 · DOI · PMC6935936
- Senol Cali D, Kim JS, Ghose S, Alkan C, Mutlu O. Nanopore sequencing technology and tools for genome assembly: computational analysis of the current state, bottlenecks and future directions. Brief Bioinform. 2019. PMID 29617724 · DOI · PMC6781587
- Xu L, Seki M. Recent advances in the detection of base modifications using the Nanopore sequencer. J Hum Genet. 2020. PMID 31602005 · DOI · PMC7087776
- Furlan M, Delgado-Tejedor A, Mulroney L, Pelizzola M, Novoa EM, Leonardi T. Computational methods for RNA modification detection from nanopore direct RNA sequencing data. RNA Biol. 2021. PMID 34559589 · DOI · PMC8677041
About this article
- Sources
- NLM Medical Subject Headings (definition, synonyms); NCBI PubMed (counts, identifiers); Europe PMC (open-access abstracts and citation counts).
- Verification
- Every reference was resolved against PubMed on 2026-10-31; title, year and DOI matched.
- Review state
- automated source verified; no human expert review has been recorded yet.
- Version
- 1, last updated 2026-10-29.
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Evidence strength
EvidenceHelix's computed view of the study designs behind this topic: how common meta-analyses, randomized trials and reviews are, how recent the literature is, and a plain-language reading. It describes the design mix of the literature. It is not a quality appraisal of any study, and it is not medical advice.