4.4 Article

Analysis of mutational signatures with yet another package for signature analysis

期刊

GENES CHROMOSOMES & CANCER
卷 60, 期 5, 页码 314-331

出版社

WILEY
DOI: 10.1002/gcc.22918

关键词

biomarker; BRCAness; cancer genomics; mutational signatures; precision oncology; YAPSA

资金

  1. German Cancer Research Center-Heidelberg Center for Personalized Oncology (DKFZ-HIPO)
  2. Molecular Diagnostics Program of the National Center for Tumor Diseases (NCT) in Heidelberg
  3. European Union [824110]
  4. Helmholtz International Graduate School for Cancer Research at the German Cancer Research Center
  5. ProjektDEAL

向作者/读者索取更多资源

YAPSA is a tool for analyzing mutational signatures in tumor genomes, which can improve tumor classification and support therapeutic decisions. It includes features such as correcting triplet content and determining confidence intervals for signature exposures.
Different mutational processes leave characteristic patterns of somatic mutations in the genome that can be identified as mutational signatures. Determining the contributions of mutational signatures to cancer genomes allows not only to reconstruct the etiology of somatic mutations, but can also be used for improved tumor classification and support therapeutic decisions. We here present the R package yet another package for signature analysis (YAPSA) to deconvolute the contributions of mutational signatures to tumor genomes. YAPSA provides in-built collections from the COSMIC and PCAWG SNV signature sets as well as the PCAWG Indel signatures and employs signature-specific cutoffs to increase sensitivity and specificity. Furthermore, YAPSA allows to determine 95% confidence intervals for signature exposures, to perform constrained stratified signature analyses to obtain enrichment and depletion patterns of the identified signatures and, when applied to whole exome sequencing data, to correct for the triplet content of individual target capture kits. With this functionality, YAPSA has proved to be a valuable tool for analysis of mutational signatures in molecular tumor boards in a precision oncology context. YAPSA is available at R/Bioconductor ().

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