Europe PMC

This website requires cookies, and the limited processing of your personal data in order to function. By using the site you are agreeing to this as outlined in our privacy notice and cookie policy.

Analysis of mutational signatures with yet another package for signature analysis.

Author information

Affiliations

  • 1. Computational Oncology, Molecular Diagnostics Program, National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, Heidelberg, 69120, Germany.
      Authors
    • Hübschmann D 1, 2, 4
    • Jopp-Saile L 1, 2, 3
    • Gu Z 1
    (3 authors)
  • 2. Pattern Recognition and Digital Medicine, Heidelberg Institute of Stem Cell Technology and Experimental Medicine (HI-STEM), Im Neuenheimer Feld 280, Heidelberg, 69120, Germany.
      Authors
    • Hübschmann D 1, 2, 4
    • Jopp-Saile L 1, 2, 3
    • Andresen C 2, 3
    (3 authors)
  • 3. Bioinformatics and Omics Data Analytics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, Heidelberg, 69120, Germany.
      Authors
    • Jopp-Saile L 1, 2, 3
    • Andresen C 2, 3
    • Krämer S 3
    • Schlesner M 3
    (4 authors)
  • 4. German Cancer Consortium (DKTK), Im Neuenheimer Feld 280, Heidelberg, 69120, Germany.
      Authors
    • Hübschmann D 1, 2, 4
    • Heilig CE 4
    • Kreutzfeldt S 4
    • Teleanu V 4
    • Fröhling S 4
    (5 authors)
  • 5. Center for Digital Health, Berlin Institute of Health and Charité - Universitätsmedizin Berlin, Berlin, Germany.
      Authors
    • Eils R 5
    (1 author)

ORCIDs linked to this article

Show all (6)

Genes, Chromosomes & Cancer, 31 Dec 2020, 60(5):314-331
https://doi.org/10.1002/gcc.22918 PMID: 33222322 

Abstract 

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).

Full text links 

Read article at publisher's site: https://doi.org/10.1002/gcc.22918

Read article for free, from open access legal sources, via Unpaywall: https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/gcc.22918Unpaywall

Citations & impact 

Impact metrics

31
Citations
Jump to Citations

Citations of article over time

Alternative metrics

Altmetric item for https://www.altmetric.com/details/94797711
Altmetric
Discover the attention surrounding your research
https://www.altmetric.com/details/94797711

Article citations

Go to all (31) article citations

Similar Articles 

To arrive at the top five similar articles we use a word-weighted algorithm to compare words from the Title and Abstract of each citation.