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Accurate quantification of copy-number aberrations and whole-genome duplications in multi-sample tumor sequencing data

Copy-number aberrations (CNAs) and whole-genome duplications (WGDs) are frequent somatic mutations in cancer but their quantification from DNA sequencing of bulk tumor samples is challenging. Standard methods for CNA inference analyze tumor samples individually; however, DNA sequencing of multiple s...

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Autores principales: Zaccaria, Simone, Raphael, Benjamin J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7468132/
https://www.ncbi.nlm.nih.gov/pubmed/32879317
http://dx.doi.org/10.1038/s41467-020-17967-y
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author Zaccaria, Simone
Raphael, Benjamin J.
author_facet Zaccaria, Simone
Raphael, Benjamin J.
author_sort Zaccaria, Simone
collection PubMed
description Copy-number aberrations (CNAs) and whole-genome duplications (WGDs) are frequent somatic mutations in cancer but their quantification from DNA sequencing of bulk tumor samples is challenging. Standard methods for CNA inference analyze tumor samples individually; however, DNA sequencing of multiple samples from a cancer patient has recently become more common. We introduce HATCHet (Holistic Allele-specific Tumor Copy-number Heterogeneity), an algorithm that infers allele- and clone-specific CNAs and WGDs jointly across multiple tumor samples from the same patient. We show that HATCHet outperforms current state-of-the-art methods on multi-sample DNA sequencing data that we simulate using MASCoTE (Multiple Allele-specific Simulation of Copy-number Tumor Evolution). Applying HATCHet to 84 tumor samples from 14 prostate and pancreas cancer patients, we identify subclonal CNAs and WGDs that are more plausible than previously published analyses and more consistent with somatic single-nucleotide variants (SNVs) and small indels in the same samples.
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spelling pubmed-74681322020-09-16 Accurate quantification of copy-number aberrations and whole-genome duplications in multi-sample tumor sequencing data Zaccaria, Simone Raphael, Benjamin J. Nat Commun Article Copy-number aberrations (CNAs) and whole-genome duplications (WGDs) are frequent somatic mutations in cancer but their quantification from DNA sequencing of bulk tumor samples is challenging. Standard methods for CNA inference analyze tumor samples individually; however, DNA sequencing of multiple samples from a cancer patient has recently become more common. We introduce HATCHet (Holistic Allele-specific Tumor Copy-number Heterogeneity), an algorithm that infers allele- and clone-specific CNAs and WGDs jointly across multiple tumor samples from the same patient. We show that HATCHet outperforms current state-of-the-art methods on multi-sample DNA sequencing data that we simulate using MASCoTE (Multiple Allele-specific Simulation of Copy-number Tumor Evolution). Applying HATCHet to 84 tumor samples from 14 prostate and pancreas cancer patients, we identify subclonal CNAs and WGDs that are more plausible than previously published analyses and more consistent with somatic single-nucleotide variants (SNVs) and small indels in the same samples. Nature Publishing Group UK 2020-09-02 /pmc/articles/PMC7468132/ /pubmed/32879317 http://dx.doi.org/10.1038/s41467-020-17967-y Text en © The Author(s) 2020 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Zaccaria, Simone
Raphael, Benjamin J.
Accurate quantification of copy-number aberrations and whole-genome duplications in multi-sample tumor sequencing data
title Accurate quantification of copy-number aberrations and whole-genome duplications in multi-sample tumor sequencing data
title_full Accurate quantification of copy-number aberrations and whole-genome duplications in multi-sample tumor sequencing data
title_fullStr Accurate quantification of copy-number aberrations and whole-genome duplications in multi-sample tumor sequencing data
title_full_unstemmed Accurate quantification of copy-number aberrations and whole-genome duplications in multi-sample tumor sequencing data
title_short Accurate quantification of copy-number aberrations and whole-genome duplications in multi-sample tumor sequencing data
title_sort accurate quantification of copy-number aberrations and whole-genome duplications in multi-sample tumor sequencing data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7468132/
https://www.ncbi.nlm.nih.gov/pubmed/32879317
http://dx.doi.org/10.1038/s41467-020-17967-y
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