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SUITOR: Selecting the number of mutational signatures through cross-validation
For de novo mutational signature analysis, the critical first step is to decide how many signatures should be expected in a cancer genomics study. An incorrect number could mislead downstream analyses. Here we present SUITOR (Selecting the nUmber of mutatIonal signaTures thrOugh cRoss-validation), a...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9009674/ https://www.ncbi.nlm.nih.gov/pubmed/35377867 http://dx.doi.org/10.1371/journal.pcbi.1009309 |
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author | Lee, Donghyuk Wang, Difei Yang, Xiaohong R. Shi, Jianxin Landi, Maria Teresa Zhu, Bin |
author_facet | Lee, Donghyuk Wang, Difei Yang, Xiaohong R. Shi, Jianxin Landi, Maria Teresa Zhu, Bin |
author_sort | Lee, Donghyuk |
collection | PubMed |
description | For de novo mutational signature analysis, the critical first step is to decide how many signatures should be expected in a cancer genomics study. An incorrect number could mislead downstream analyses. Here we present SUITOR (Selecting the nUmber of mutatIonal signaTures thrOugh cRoss-validation), an unsupervised cross-validation method that requires little assumptions and no numerical approximations to select the optimal number of signatures without overfitting the data. In vitro studies and in silico simulations demonstrated that SUITOR can correctly identify signatures, some of which were missed by other widely used methods. Applied to 2,540 whole-genome sequenced tumors across 22 cancer types, SUITOR selected signatures with the smallest prediction errors and almost all signatures of breast cancer selected by SUITOR were validated in an independent breast cancer study. SUITOR is a powerful tool to select the optimal number of mutational signatures, facilitating downstream analyses with etiological or therapeutic importance. |
format | Online Article Text |
id | pubmed-9009674 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-90096742022-04-15 SUITOR: Selecting the number of mutational signatures through cross-validation Lee, Donghyuk Wang, Difei Yang, Xiaohong R. Shi, Jianxin Landi, Maria Teresa Zhu, Bin PLoS Comput Biol Research Article For de novo mutational signature analysis, the critical first step is to decide how many signatures should be expected in a cancer genomics study. An incorrect number could mislead downstream analyses. Here we present SUITOR (Selecting the nUmber of mutatIonal signaTures thrOugh cRoss-validation), an unsupervised cross-validation method that requires little assumptions and no numerical approximations to select the optimal number of signatures without overfitting the data. In vitro studies and in silico simulations demonstrated that SUITOR can correctly identify signatures, some of which were missed by other widely used methods. Applied to 2,540 whole-genome sequenced tumors across 22 cancer types, SUITOR selected signatures with the smallest prediction errors and almost all signatures of breast cancer selected by SUITOR were validated in an independent breast cancer study. SUITOR is a powerful tool to select the optimal number of mutational signatures, facilitating downstream analyses with etiological or therapeutic importance. Public Library of Science 2022-04-04 /pmc/articles/PMC9009674/ /pubmed/35377867 http://dx.doi.org/10.1371/journal.pcbi.1009309 Text en https://creativecommons.org/publicdomain/zero/1.0/This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication. |
spellingShingle | Research Article Lee, Donghyuk Wang, Difei Yang, Xiaohong R. Shi, Jianxin Landi, Maria Teresa Zhu, Bin SUITOR: Selecting the number of mutational signatures through cross-validation |
title | SUITOR: Selecting the number of mutational signatures through cross-validation |
title_full | SUITOR: Selecting the number of mutational signatures through cross-validation |
title_fullStr | SUITOR: Selecting the number of mutational signatures through cross-validation |
title_full_unstemmed | SUITOR: Selecting the number of mutational signatures through cross-validation |
title_short | SUITOR: Selecting the number of mutational signatures through cross-validation |
title_sort | suitor: selecting the number of mutational signatures through cross-validation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9009674/ https://www.ncbi.nlm.nih.gov/pubmed/35377867 http://dx.doi.org/10.1371/journal.pcbi.1009309 |
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