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双平台联合 SNP 辅助结构变异检测和 Oxford nanopore 测序相位分析

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

机构信息

Department of Computer Science, The University of Hong Kong, Hong Kong, China.

出版信息

BMC Bioinformatics. 2022 Nov 7;23(1):465. doi: 10.1186/s12859-022-05025-x.

Abstract

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 .

摘要

背景

使用长读长 Oxford Nanopore Technologies(ONT)MinION 测序仪进行全基因组测序,为临床应用中的结构变异(SV)检测提供了一种具有成本效益的选择。然而,尽管使用长读长具有优势,但准确的 SV 调用和相位仍然具有挑战性。

结果

我们引入了 Duet,这是一种专门针对使用 ONT 数据进行 SV 调用和相位的 SV 检测工具。该工具利用来自 SV 特征和单核苷酸多态性特征的新颖特征,可以准确地区分 SV 单倍型与虚假信号。在多个测序覆盖率范围为 8×至 40×的 ONT 测序数据集上,Duet 与最先进的工具进行了基准测试。在测序覆盖率为 8×的低水平下,Duet 在 SV 调用、SV 基因分型和 SV 相位方面的性能优于所有其他工具。当测序覆盖率更高(20×至 40×)时,与其他工具的性能相比,SV 相位的 F1 分数进一步提高,而其 SV 基因分型和 SV 调用的性能仍高于其他工具。

结论

Duet 可以使用低覆盖度的 ONT 数据进行准确的 SV 调用、SV 基因分型和 SV 相位,因此非常适用于低覆盖度基因组。当扩展到高覆盖度基因组时,它具有出色的性能,适用于各种临床应用。Duet 是开源的,可在 https://github.com/yekaizhou/duet 获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/276c/9639287/da35953dc279/12859_2022_5025_Fig1_HTML.jpg

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