Evidence map›Paper›PMID 36344913›Full record

ArticleBMC bioinformatics2022

Duet: SNP-assisted structural variant calling and phasing using Oxford nanopore sequencing.

Yekai Zhou, Amy Wing-Sze Leung, Syed Shakeel Ahmed, Tak-Wah Lam, Ruibang Luo

Abstract read
In one paragraph

Article in BMC bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. cuteHap: Haplotype-Aware Structural Variant Detection in Phased Long-Read Sequencing Data.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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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

5 authors.

Yekai Zhou *Department of Computer Science, The University of Hong Kong, Hong Kong, China.
Amy Wing-Sze Leung *Department of Computer Science, The University of Hong Kong, Hong Kong, China.
Syed Shakeel AhmedDepartment of Computer Science, The University of Hong Kong, Hong Kong, China.
Tak-Wah LamDepartment of Computer Science, The University of Hong Kong, Hong Kong, China.
Ruibang LuoDepartment of Computer Science, The University of Hong Kong, Hong Kong, China. rbluo@cs.hku.hk.ORCID http://orcid.org/0000-0001-9711-6533

Funding

General Program of the Shenzhen Municipal Government JCYJ20210324134405015Hong Kong Research Grants Council grants GRF 17113721
6 · The paper itself

Abstract

backgroundWhole genome sequencing using the long-read Oxford Nanopore Technologies (ONT) MinION sequencer provides a cost-effective option for structural variant (SV) detection in clinical applications. Despite the advantage of using long reads, however, accurate SV calling and phasing are still challenging.

resultsWe introduce Duet, an SV detection tool optimized for SV calling and phasing using ONT data. The tool uses novel features integrated from both SV signatures and single-nucleotide polymorphism signatures, which can accurately distinguish SV haplotype from a false signal. Duet was benchmarked against state-of-the-art tools on multiple ONT sequencing datasets of sequencing coverage ranging from 8× to 40×. At low sequencing coverage of 8×, Duet performs better than all other tools in SV calling, SV genotyping and SV phasing. When the sequencing coverage is higher (20× to 40×), the F1-score for SV phasing is further improved in comparison to the performance of other tools, while its performance of SV genotyping and SV calling remains higher than other tools.

conclusionDuet can perform accurate SV calling, SV genotyping and SV phasing using low-coverage ONT data, making it very useful for low-coverage genomes. It has great performance when scaled to high-coverage genomes, which is adaptable to various clinical applications. Duet is open source and is available at https://github.com/yekaizhou/duet .

Indexed as

Nanopore SequencingPolymorphism, Single NucleotideHigh-Throughput Nucleotide SequencingSequence Analysis, DNAWhole Genome SequencingOxford Nanopore SequencingSNP callingStructural variant (SV) callingSV genotypingSV phasing

Identifiers

PMID36344913
PMCPMC9639287

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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.