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

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

2022
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Overview
Background Whole 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. Results We 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. Conclusion Duet 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 .