한빛사논문
- 조회271
Hu Jin 1,2, Doga C. Gulhan 1,2, Benedikt Geiger 1, Daniel Ben-Isvy 1, David Geng 1, Viktor Ljungström 1 & Peter J. Park 1,*
1Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
2These authors contributed equally: Hu Jin, Doga C. Gulhan.
*Corresponding author: correspondence to Peter J. Park
Abstract
Mutational signature analysis is a recent computational approach for interpreting somatic mutations in the genome. Its application to cancer data has enhanced our understanding of mutational forces driving tumorigenesis and demonstrated its potential to inform prognosis and treatment decisions. However, methodological challenges remain for discovering new signatures and assigning proper weights to existing signatures, thereby hindering broader clinical applications. Here we present Mutational Signature Calculator (MuSiCal), a rigorous analytical framework with algorithms that solve major problems in the standard workflow. Our simulation studies demonstrate that MuSiCal outperforms state-of-the-art algorithms for both signature discovery and assignment. By reanalyzing more than 2,700 cancer genomes, we provide an improved catalog of signatures and their assignments, discover nine indel signatures absent in the current catalog, resolve long-standing issues with the ambiguous ‘flat’ signatures and give insights into signatures with unknown etiologies. We expect MuSiCal and the improved catalog to be a step towards establishing best practices for mutational signature analysis.
논문정보
- Research article
- 2024년 02월 (BRIC 등록일 2024-02-26)
- 국외 연구진
- 의약학 > 유전 및 유전체의학
댓글 작성 로그인
팝업 닫기관련 링크
관련분야 연구자보기
소속기관 논문보기
관련분야 논문보기
해당논문 저자보기
