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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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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. |
format | Online Article Text |
id | pubmed-7468132 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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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