SVvalidation: A long-read-based validation method for genomic structural variation

Yan Zheng, Xuequn Shang

科研成果: 期刊稿件文章同行评审

1 引用 (Scopus)

摘要

Although various methods have been developed to detect structural variations (SVs) in genomic sequences, few are used to validate these results. Several commonly used SV callers produce many false positive SVs, and existing validation methods are not accurate enough. Therefore, a highly efficient and accurate validation method is essential. In response, we propose SVvalidation-a new method that uses long-read sequencing data for validating SVs with higher accuracy and efficiency. Compared to existing methods, SVvalidation performs better in validating SVs in repeat regions and can determine the homozygosity or heterozygosity of an SV. Additionally, SVvalidation offers the highest recall, precision, and F1-score (improving by 7-16%) across all datasets. Moreover, SVvalidation is suitable for different types of SVs. The program is available at https://github.com/ nwpuzhengyan/SVvalidation.

源语言英语
文章编号e0291741
期刊PLoS ONE
19
1 January
DOI
出版状态已出版 - 1月 2024

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