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SigsPack, a package for cancer mutational signatures
BACKGROUND: Mutational signatures are specific patterns of somatic mutations introduced into the genome by oncogenic processes. Several mutational signatures have been identified and quantified from multiple cancer studies, and some of them have been linked to known oncogenic processes. Identificati...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6720940/ https://www.ncbi.nlm.nih.gov/pubmed/31477009 http://dx.doi.org/10.1186/s12859-019-3043-7 |
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author | Schumann, Franziska Blanc, Eric Messerschmidt, Clemens Blankenstein, Thomas Busse, Antonia Beule, Dieter |
author_facet | Schumann, Franziska Blanc, Eric Messerschmidt, Clemens Blankenstein, Thomas Busse, Antonia Beule, Dieter |
author_sort | Schumann, Franziska |
collection | PubMed |
description | BACKGROUND: Mutational signatures are specific patterns of somatic mutations introduced into the genome by oncogenic processes. Several mutational signatures have been identified and quantified from multiple cancer studies, and some of them have been linked to known oncogenic processes. Identification of the processes contributing to mutations observed in a sample is potentially informative to understand the cancer etiology. RESULTS: We present here SigsPack, a Bioconductor package to estimate a sample’s exposure to mutational processes described by a set of mutational signatures. The package also provides functions to estimate stability of these exposures, using bootstrapping. The performance of exposure and exposure stability estimations have been validated using synthetic and real data. Finally, the package provides tools to normalize the mutation frequencies with respect to the tri-nucleotide contents of the regions probed in the experiment. The importance of this effect is illustrated in an example. CONCLUSION: SigsPack provides a complete set of tools for individual sample exposure estimation, and for mutation catalogue & mutational signatures normalization. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-3043-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6720940 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-67209402019-09-06 SigsPack, a package for cancer mutational signatures Schumann, Franziska Blanc, Eric Messerschmidt, Clemens Blankenstein, Thomas Busse, Antonia Beule, Dieter BMC Bioinformatics Software BACKGROUND: Mutational signatures are specific patterns of somatic mutations introduced into the genome by oncogenic processes. Several mutational signatures have been identified and quantified from multiple cancer studies, and some of them have been linked to known oncogenic processes. Identification of the processes contributing to mutations observed in a sample is potentially informative to understand the cancer etiology. RESULTS: We present here SigsPack, a Bioconductor package to estimate a sample’s exposure to mutational processes described by a set of mutational signatures. The package also provides functions to estimate stability of these exposures, using bootstrapping. The performance of exposure and exposure stability estimations have been validated using synthetic and real data. Finally, the package provides tools to normalize the mutation frequencies with respect to the tri-nucleotide contents of the regions probed in the experiment. The importance of this effect is illustrated in an example. CONCLUSION: SigsPack provides a complete set of tools for individual sample exposure estimation, and for mutation catalogue & mutational signatures normalization. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-3043-7) contains supplementary material, which is available to authorized users. BioMed Central 2019-09-02 /pmc/articles/PMC6720940/ /pubmed/31477009 http://dx.doi.org/10.1186/s12859-019-3043-7 Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Software Schumann, Franziska Blanc, Eric Messerschmidt, Clemens Blankenstein, Thomas Busse, Antonia Beule, Dieter SigsPack, a package for cancer mutational signatures |
title | SigsPack, a package for cancer mutational signatures |
title_full | SigsPack, a package for cancer mutational signatures |
title_fullStr | SigsPack, a package for cancer mutational signatures |
title_full_unstemmed | SigsPack, a package for cancer mutational signatures |
title_short | SigsPack, a package for cancer mutational signatures |
title_sort | sigspack, a package for cancer mutational signatures |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6720940/ https://www.ncbi.nlm.nih.gov/pubmed/31477009 http://dx.doi.org/10.1186/s12859-019-3043-7 |
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