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Analysis of mutational signatures with yet another package for signature analysis

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...

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Hauptverfasser: Hübschmann, Daniel (VerfasserIn) , Jopp-Saile, Lea (VerfasserIn) , Andresen, Carolin (VerfasserIn) , Krämer, Stephen (VerfasserIn) , Gu, Zuguang (VerfasserIn) , Heilig, Christoph E. (VerfasserIn) , Kreutzfeldt, Simon (VerfasserIn) , Teleanu, Maria-Veronica (VerfasserIn) , Fröhling, Stefan (VerfasserIn) , Eils, Roland (VerfasserIn) , Schlesner, Matthias (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: May 2021
In: Genes, chromosomes & cancer
Year: 2021, Jahrgang: 60, Heft: 5, Pages: 314-331
ISSN:1098-2264
DOI:10.1002/gcc.22918
Online-Zugang:Verlag, kostenfrei, Volltext: https://doi.org/10.1002/gcc.22918
Verlag, kostenfrei, Volltext: https://onlinelibrary.wiley.com/doi/abs/10.1002/gcc.22918
Volltext
Verfasserangaben:Daniel Hübschmann, Lea Jopp-Saile, Carolin Andresen, Stephen Krämer, Zuguang Gu, Christoph E. Heilig, Simon Kreutzfeldt, Veronica Teleanu, Stefan Fröhling, Roland Eils, Matthias Schlesner
Beschreibung
Zusammenfassung: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 (http://bioconductor.org/packages/3.12/bioc/html/YAPSA.html).
Beschreibung:Online veröffentlicht: 22. November 2020
Gesehen am 26.10.2023
Beschreibung:Online Resource
ISSN:1098-2264
DOI:10.1002/gcc.22918

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