biostudies-literatureJin HNHGRI NIH HHSNCI NIH HHS541-552https://www.ebi.ac.uk/biostudies/studies/S-EPMC10937379biostudies-literatureUnknown56(3)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 cancerNature geneticsAccurate and sensitive mutational signature analysis with MuSiCal.PMC10937379T32 HG002295R01 CA269805Park PJGeng DJin HBen-Isvy DGeiger BLjungstrom VGulhan DCfalseAccurate and sensitive mutational signature analysis with MuSiCal.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 cancer2024-01-01T00:00:00Z2024 Mar2026-07-14T20:56:47.514Z2026-06-24T03:06:26.234ZS-EPMC109373793836103410.1038/s41588-024-01659-0