SDFA: a standardized decomposition format and toolkit for efficient analysis of structural variants in large-scale population genomic studies
Structural variants (SVs) contribute significantly to genetic diversity yet present computational challenges during analysis. We introduce SDFA, a standardized decomposition format and toolkit for efficient analysis of SVs in large-scale population genomics. SDFA efficiently stores and retrieves all SV types while providing algorithms for consistent SV merging, memory-efficient annotation, and precise gene feature annotation across large cohorts. SDFA outperforms existing tools, achieving at least 17.64 times faster merging than four tools and 120.93 times faster annotation than three tools, and uniquely handles complex SVs. We validate SDFA on 895,054 SVs from 150,119 individuals in the UK Biobank dataset.
Authors
- Nan Lin (ORCID: https://orcid.org/0000-0002-4418-1355)
- Yangyang Yuan (ORCID: https://orcid.org/0000-0001-9278-9632)
- Bin Tang (ORCID: https://orcid.org/0000-0002-5600-0873)
- Miaoxin Li (ORCID: https://orcid.org/0000-0002-4733-0109)
- Rui Tan (ORCID: https://orcid.org/0000-0002-7795-1141)
- Junhao Liang (ORCID: https://orcid.org/0009-0008-2009-993X)
- Wenjie Peng (ORCID: https://orcid.org/0009-0009-6493-6127)
- Lihang Ye (ORCID: https://orcid.org/0000-0003-3942-0283)
- Liubin Zhang (ORCID: https://orcid.org/0000-0003-2509-4333)
- Yifei Wang (ORCID: https://orcid.org/0000-0002-9918-2865)
- Zhi Liu
- Fang Li (ORCID: https://orcid.org/0000-0001-5456-0255)
- Chao Xue (ORCID: https://orcid.org/0000-0002-6528-3975)
- Hui Jiang (ORCID: https://orcid.org/0000-0002-1475-1222)
Institutions
- Zhejiang Chinese Medical University (CN)
- Ministry of Education of the People's Republic of China (CN)
- Sun Yat-sen University (CN)
- Third Affiliated Hospital of Zhengzhou University (CN)
Publication Details
- Journal
- Genome biology
- Published
- 2025-09-30
- DOI
- https://doi.org/10.1186/s13059-025-03730-3
- Primary Topic
- Genomics and Rare Diseases
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Basic and Applied Basic Research Foundation of Guangdong Province