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The MOBSTER R package for tumour subclonal deconvolution from bulk DNA whole-genome sequencing data

BACKGROUND: The large-scale availability of whole-genome sequencing profiles from bulk DNA sequencing of cancer tissues is fueling the application of evolutionary theory to cancer. From a bulk biopsy, subclonal deconvolution methods are used to determine the composition of cancer subpopulations in t...

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Autores principales: Caravagna, Giulio, Sanguinetti, Guido, Graham, Trevor A., Sottoriva, Andrea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7672894/
https://www.ncbi.nlm.nih.gov/pubmed/33203356
http://dx.doi.org/10.1186/s12859-020-03863-1
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author Caravagna, Giulio
Sanguinetti, Guido
Graham, Trevor A.
Sottoriva, Andrea
author_facet Caravagna, Giulio
Sanguinetti, Guido
Graham, Trevor A.
Sottoriva, Andrea
author_sort Caravagna, Giulio
collection PubMed
description BACKGROUND: The large-scale availability of whole-genome sequencing profiles from bulk DNA sequencing of cancer tissues is fueling the application of evolutionary theory to cancer. From a bulk biopsy, subclonal deconvolution methods are used to determine the composition of cancer subpopulations in the biopsy sample, a fundamental step to determine clonal expansions and their evolutionary trajectories. RESULTS: In a recent work we have developed a new model-based approach to carry out subclonal deconvolution from the site frequency spectrum of somatic mutations. This new method integrates, for the first time, an explicit model for neutral evolutionary forces that participate in clonal expansions; in that work we have also shown that our method improves largely over competing data-driven methods. In this Software paper we present mobster, an open source R package built around our new deconvolution approach, which provides several functions to plot data and fit models, assess their confidence and compute further evolutionary analyses that relate to subclonal deconvolution. CONCLUSIONS: We present the mobster package for tumour subclonal deconvolution from bulk sequencing, the first approach to integrate Machine Learning and Population Genetics which can explicitly model co-existing neutral and positive selection in cancer. We showcase the analysis of two datasets, one simulated and one from a breast cancer patient, and overview all package functionalities.
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spelling pubmed-76728942020-11-19 The MOBSTER R package for tumour subclonal deconvolution from bulk DNA whole-genome sequencing data Caravagna, Giulio Sanguinetti, Guido Graham, Trevor A. Sottoriva, Andrea BMC Bioinformatics Software BACKGROUND: The large-scale availability of whole-genome sequencing profiles from bulk DNA sequencing of cancer tissues is fueling the application of evolutionary theory to cancer. From a bulk biopsy, subclonal deconvolution methods are used to determine the composition of cancer subpopulations in the biopsy sample, a fundamental step to determine clonal expansions and their evolutionary trajectories. RESULTS: In a recent work we have developed a new model-based approach to carry out subclonal deconvolution from the site frequency spectrum of somatic mutations. This new method integrates, for the first time, an explicit model for neutral evolutionary forces that participate in clonal expansions; in that work we have also shown that our method improves largely over competing data-driven methods. In this Software paper we present mobster, an open source R package built around our new deconvolution approach, which provides several functions to plot data and fit models, assess their confidence and compute further evolutionary analyses that relate to subclonal deconvolution. CONCLUSIONS: We present the mobster package for tumour subclonal deconvolution from bulk sequencing, the first approach to integrate Machine Learning and Population Genetics which can explicitly model co-existing neutral and positive selection in cancer. We showcase the analysis of two datasets, one simulated and one from a breast cancer patient, and overview all package functionalities. BioMed Central 2020-11-17 /pmc/articles/PMC7672894/ /pubmed/33203356 http://dx.doi.org/10.1186/s12859-020-03863-1 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.
spellingShingle Software
Caravagna, Giulio
Sanguinetti, Guido
Graham, Trevor A.
Sottoriva, Andrea
The MOBSTER R package for tumour subclonal deconvolution from bulk DNA whole-genome sequencing data
title The MOBSTER R package for tumour subclonal deconvolution from bulk DNA whole-genome sequencing data
title_full The MOBSTER R package for tumour subclonal deconvolution from bulk DNA whole-genome sequencing data
title_fullStr The MOBSTER R package for tumour subclonal deconvolution from bulk DNA whole-genome sequencing data
title_full_unstemmed The MOBSTER R package for tumour subclonal deconvolution from bulk DNA whole-genome sequencing data
title_short The MOBSTER R package for tumour subclonal deconvolution from bulk DNA whole-genome sequencing data
title_sort mobster r package for tumour subclonal deconvolution from bulk dna whole-genome sequencing data
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7672894/
https://www.ncbi.nlm.nih.gov/pubmed/33203356
http://dx.doi.org/10.1186/s12859-020-03863-1
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