De novo mutational signature discovery in tumor genomes using SparseSignatures.

Cancer is the result of mutagenic processes that can be inferred from tumor genomes by analyzing rate spectra of point mutations, or "mutational signatures". Here we present SparseSignatures, a novel framework to extract signatures from somatic point mutation data. Our approach incorporate...

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Autores principales:	Avantika Lal, Keli Liu, Robert Tibshirani, Arend Sidow, Daniele Ramazzotti
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/ed06227f6ba944be9baaed2c108694e4
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id	oai:doaj.org-article:ed06227f6ba944be9baaed2c108694e4
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spelling	oai:doaj.org-article:ed06227f6ba944be9baaed2c108694e42021-11-25T05:40:34ZDe novo mutational signature discovery in tumor genomes using SparseSignatures.1553-734X1553-735810.1371/journal.pcbi.1009119https://doaj.org/article/ed06227f6ba944be9baaed2c108694e42021-06-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009119https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Cancer is the result of mutagenic processes that can be inferred from tumor genomes by analyzing rate spectra of point mutations, or "mutational signatures". Here we present SparseSignatures, a novel framework to extract signatures from somatic point mutation data. Our approach incorporates a user-specified background signature, employs regularization to reduce noise in non-background signatures, uses cross-validation to identify the number of signatures, and is scalable to large datasets. We show that SparseSignatures outperforms current state-of-the-art methods on simulated data using a variety of standard metrics. We then apply SparseSignatures to whole genome sequences of pancreatic and breast tumors, discovering well-differentiated signatures that are linked to known mutagenic mechanisms and are strongly associated with patient clinical features.Avantika LalKeli LiuRobert TibshiraniArend SidowDaniele RamazzottiPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 6, p e1009119 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Avantika Lal Keli Liu Robert Tibshirani Arend Sidow Daniele Ramazzotti De novo mutational signature discovery in tumor genomes using SparseSignatures.
description	Cancer is the result of mutagenic processes that can be inferred from tumor genomes by analyzing rate spectra of point mutations, or "mutational signatures". Here we present SparseSignatures, a novel framework to extract signatures from somatic point mutation data. Our approach incorporates a user-specified background signature, employs regularization to reduce noise in non-background signatures, uses cross-validation to identify the number of signatures, and is scalable to large datasets. We show that SparseSignatures outperforms current state-of-the-art methods on simulated data using a variety of standard metrics. We then apply SparseSignatures to whole genome sequences of pancreatic and breast tumors, discovering well-differentiated signatures that are linked to known mutagenic mechanisms and are strongly associated with patient clinical features.
format	article
author	Avantika Lal Keli Liu Robert Tibshirani Arend Sidow Daniele Ramazzotti
author_facet	Avantika Lal Keli Liu Robert Tibshirani Arend Sidow Daniele Ramazzotti
author_sort	Avantika Lal
title	De novo mutational signature discovery in tumor genomes using SparseSignatures.
title_short	De novo mutational signature discovery in tumor genomes using SparseSignatures.
title_full	De novo mutational signature discovery in tumor genomes using SparseSignatures.
title_fullStr	De novo mutational signature discovery in tumor genomes using SparseSignatures.
title_full_unstemmed	De novo mutational signature discovery in tumor genomes using SparseSignatures.
title_sort	de novo mutational signature discovery in tumor genomes using sparsesignatures.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/ed06227f6ba944be9baaed2c108694e4
work_keys_str_mv	AT avantikalal denovomutationalsignaturediscoveryintumorgenomesusingsparsesignatures AT keliliu denovomutationalsignaturediscoveryintumorgenomesusingsparsesignatures AT roberttibshirani denovomutationalsignaturediscoveryintumorgenomesusingsparsesignatures AT arendsidow denovomutationalsignaturediscoveryintumorgenomesusingsparsesignatures AT danieleramazzotti denovomutationalsignaturediscoveryintumorgenomesusingsparsesignatures
_version_	1718414553475186688

De novo mutational signature discovery in tumor genomes using SparseSignatures.

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