ArticleBMC bioinformatics2022
Duet: SNP-assisted structural variant calling and phasing using Oxford nanopore sequencing.
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.
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Who cites it
8 citing papers in PubMed.
- cuteHap: Haplotype-Aware Structural Variant Detection in Phased Long-Read Sequencing Data.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- A Hitchhiker Guide to Structural Variant Calling: A Comprehensive Benchmark Through Different Sequencing Technologies.Biomedicines · 2025Article
- Predicting high-risk clinical missense variants of SMARCB1 in rare neurogenetic disorder schwannomatosis (nerve tumor) through sequence, structure, and molecular dynamics analyses.Neurogenetics · 2025Article
- Simultaneous de novo calling and phasing of genetic variants at chromosome-scale using NanoStrand-seq.Cell discovery · 2024Article
- Mapping crossover events of mouse meiotic recombination by restriction fragment ligation-based Refresh-seq.Cell discovery · 2024Article
- HapKled: a haplotype-aware structural variant calling approach for Oxford nanopore sequencing data.Frontiers in genetics · 2024Article
- In it for the long run: perspectives on exploiting long-read sequencing in livestock for population scale studies of structural variants.Genetics, selection, evolution : GSE · 2023Review
- Characterization of complex structural variation in theFrontiers in pharmacology · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
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 .
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