cuteFC: regenotyping structural variants through an accurate and efficient force-calling method

Long-read sequencing technologies have great potential for the comprehensive discovery of structural variations (SVs). However, accurate genotype assignment for SVs remains challenging due to unavoidable sequencing errors, limited coverage, and the complexity of SVs. Herein, we propose cuteFC, which employs self-adaptive clustering along with a multiallele-aware clustering to achieve accurate SV regenotyping through a force-calling approach. cuteFC also applies a Genome Position Scanner algorithm to improve its application efficiency. Benchmarking evaluations demonstrate that cuteFC outperforms state-of-the-art methods with 2-5% higher F1 scores and constructs a higher-quality genomic atlas with minimal computational resources. cuteFC is available at https://github.com/Meltpinkg/cuteFC and https://zenodo.org/records/14671406 .

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Publication Details

Journal
Genome biology
Published
2025-06-13
DOI
https://doi.org/10.1186/s13059-025-03642-2
Citations
14
Primary Topic
RNA Research and Splicing
Type
article
Field-Weighted Citation Impact
10.48

Funders

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article

cuteFC: regenotyping structural variants through an accurate and efficient force-calling method

Zhendong Zhang, Ruibang Luo, Tao Jiang, Shuqi Cao et al.
14 citations
Genome biology
RNA Research and Splicing
10.48
article

cuteFC: regenotyping structural variants through an accurate and efficient force-calling method

Zhendong Zhang, Ruibang Luo, Tao Jiang, Shuqi Cao, Yadong Wang, Yadong Liu, Guohua Wang, Bo Liu
article en
14 citations

Abstract

Long-read sequencing technologies have great potential for the comprehensive discovery of structural variations (SVs). However, accurate genotype assignment for SVs remains challenging due to unavoidable sequencing errors, limited coverage, and the complexity of SVs. Herein, we propose cuteFC, which employs self-adaptive clustering along with a multiallele-aware clustering to achieve accurate SV regenotyping through a force-calling approach. cuteFC also applies a Genome Position Scanner algorithm to improve its application efficiency. Benchmarking evaluations demonstrate that cuteFC outperforms state-of-the-art methods with 2-5% higher F1 scores and constructs a higher-quality genomic atlas with minimal computational resources. cuteFC is available at https://github.com/Meltpinkg/cuteFC and https://zenodo.org/records/14671406 .

Genome biologyVol. 26(1)
Harbin Institute of Technology (CN), University of Hong Kong (HK)
Heilongjiang Postdoctoral Science Foundation, National Natural Science Foundation of China, China Postdoctoral Science Foundation, Harbin Institute of Technology, National Key Research and Development Program of China
Openalex Percentile: Top 1%
RNA Research and Splicing
10.48
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cuteFC: regenotyping structural variants through an accurate and efficient force-calling method — Zhendong Zhang, Ruibang Luo, et al. · Genome biology (2025) | TGRS Research Map | TGRS