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

Yan Zheng, Xuequn Shang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

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.

Original languageEnglish
Article numbere0291741
JournalPLoS ONE
Volume19
Issue number1 January
DOIs
StatePublished - Jan 2024

Fingerprint

Dive into the research topics of 'SVvalidation: A long-read-based validation method for genomic structural variation'. Together they form a unique fingerprint.

Cite this