한빛사논문
- 조회1,216
Yoo-Jin Ha1,2, Seungseok Kang 1,2, Jisoo Kim 1, Junhan Kim1, Se-Young Jo 1,2 & Sangwoo Kim 1,2,3
1Translational Genome Informatics Laboratory, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea.
2Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine, Seoul, Republic of Korea.
3POSTECH Biotechnology Center, Pohang University of Science and Technology, Pohang, Republic of Korea.
Corresponding author : Correspondence to Sangwoo Kim.
Abstract
Rapid advances in sequencing and analysis technologies have enabled the accurate detection of diverse forms of genomic variants represented as heterozygous, homozygous and mosaic mutations. However, the best practices for mosaic variant calling remain disorganized owing to the technical and conceptual difficulties faced in evaluation. Here we present our benchmark of 11 feasible mosaic variant detection approaches based on a systematically designed whole-exome-level reference standard that mimics mosaic samples, supported by 354,258 control positive mosaic single-nucleotide variants and insertion-deletion mutations and 33,111,725 control negatives. We identified not only the best practice for mosaic variant detection but also the condition-dependent strengths and weaknesses of the current methods. Furthermore, feature-level evaluation and their combinatorial usage across multiple algorithms direct the way for immediate to prolonged improvements in mosaic variant detection. Our results will guide researchers in selecting suitable calling algorithms and suggest future strategies for developers.
논문정보
- Research article
- 2023년 10월 (BRIC 등록일 2023-10-13)
- 국내 연구진
- 의약학 > 유전 및 유전체의학
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