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Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor
Mutational signature analysis is commonly performed in cancer genomic studies. Here, we present SigProfilerExtractor, an automated tool for de novo extraction of mutational signatures, and benchmark it against another 13 bioinformatics tools by using 34 scenarios encompassing 2,500 simulated signatu...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9646490/ https://www.ncbi.nlm.nih.gov/pubmed/36388765 http://dx.doi.org/10.1016/j.xgen.2022.100179 |
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author | Islam, S.M. Ashiqul Díaz-Gay, Marcos Wu, Yang Barnes, Mark Vangara, Raviteja Bergstrom, Erik N. He, Yudou Vella, Mike Wang, Jingwei Teague, Jon W. Clapham, Peter Moody, Sarah Senkin, Sergey Li, Yun Rose Riva, Laura Zhang, Tongwu Gruber, Andreas J. Steele, Christopher D. Otlu, Burçak Khandekar, Azhar Abbasi, Ammal Humphreys, Laura Syulyukina, Natalia Brady, Samuel W. Alexandrov, Boian S. Pillay, Nischalan Zhang, Jinghui Adams, David J. Martincorena, Iñigo Wedge, David C. Landi, Maria Teresa Brennan, Paul Stratton, Michael R. Rozen, Steven G. Alexandrov, Ludmil B. |
author_facet | Islam, S.M. Ashiqul Díaz-Gay, Marcos Wu, Yang Barnes, Mark Vangara, Raviteja Bergstrom, Erik N. He, Yudou Vella, Mike Wang, Jingwei Teague, Jon W. Clapham, Peter Moody, Sarah Senkin, Sergey Li, Yun Rose Riva, Laura Zhang, Tongwu Gruber, Andreas J. Steele, Christopher D. Otlu, Burçak Khandekar, Azhar Abbasi, Ammal Humphreys, Laura Syulyukina, Natalia Brady, Samuel W. Alexandrov, Boian S. Pillay, Nischalan Zhang, Jinghui Adams, David J. Martincorena, Iñigo Wedge, David C. Landi, Maria Teresa Brennan, Paul Stratton, Michael R. Rozen, Steven G. Alexandrov, Ludmil B. |
author_sort | Islam, S.M. Ashiqul |
collection | PubMed |
description | Mutational signature analysis is commonly performed in cancer genomic studies. Here, we present SigProfilerExtractor, an automated tool for de novo extraction of mutational signatures, and benchmark it against another 13 bioinformatics tools by using 34 scenarios encompassing 2,500 simulated signatures found in 60,000 synthetic genomes and 20,000 synthetic exomes. For simulations with 5% noise, reflecting high-quality datasets, SigProfilerExtractor outperforms other approaches by elucidating between 20% and 50% more true-positive signatures while yielding 5-fold less false-positive signatures. Applying SigProfilerExtractor to 4,643 whole-genome- and 19,184 whole-exome-sequenced cancers reveals four novel signatures. Two of the signatures are confirmed in independent cohorts, and one of these signatures is associated with tobacco smoking. In summary, this report provides a reference tool for analysis of mutational signatures, a comprehensive benchmarking of bioinformatics tools for extracting signatures, and several novel mutational signatures, including one putatively attributed to direct tobacco smoking mutagenesis in bladder tissues. |
format | Online Article Text |
id | pubmed-9646490 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-96464902022-11-14 Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor Islam, S.M. Ashiqul Díaz-Gay, Marcos Wu, Yang Barnes, Mark Vangara, Raviteja Bergstrom, Erik N. He, Yudou Vella, Mike Wang, Jingwei Teague, Jon W. Clapham, Peter Moody, Sarah Senkin, Sergey Li, Yun Rose Riva, Laura Zhang, Tongwu Gruber, Andreas J. Steele, Christopher D. Otlu, Burçak Khandekar, Azhar Abbasi, Ammal Humphreys, Laura Syulyukina, Natalia Brady, Samuel W. Alexandrov, Boian S. Pillay, Nischalan Zhang, Jinghui Adams, David J. Martincorena, Iñigo Wedge, David C. Landi, Maria Teresa Brennan, Paul Stratton, Michael R. Rozen, Steven G. Alexandrov, Ludmil B. Cell Genom Technology Mutational signature analysis is commonly performed in cancer genomic studies. Here, we present SigProfilerExtractor, an automated tool for de novo extraction of mutational signatures, and benchmark it against another 13 bioinformatics tools by using 34 scenarios encompassing 2,500 simulated signatures found in 60,000 synthetic genomes and 20,000 synthetic exomes. For simulations with 5% noise, reflecting high-quality datasets, SigProfilerExtractor outperforms other approaches by elucidating between 20% and 50% more true-positive signatures while yielding 5-fold less false-positive signatures. Applying SigProfilerExtractor to 4,643 whole-genome- and 19,184 whole-exome-sequenced cancers reveals four novel signatures. Two of the signatures are confirmed in independent cohorts, and one of these signatures is associated with tobacco smoking. In summary, this report provides a reference tool for analysis of mutational signatures, a comprehensive benchmarking of bioinformatics tools for extracting signatures, and several novel mutational signatures, including one putatively attributed to direct tobacco smoking mutagenesis in bladder tissues. Elsevier 2022-09-23 /pmc/articles/PMC9646490/ /pubmed/36388765 http://dx.doi.org/10.1016/j.xgen.2022.100179 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Technology Islam, S.M. Ashiqul Díaz-Gay, Marcos Wu, Yang Barnes, Mark Vangara, Raviteja Bergstrom, Erik N. He, Yudou Vella, Mike Wang, Jingwei Teague, Jon W. Clapham, Peter Moody, Sarah Senkin, Sergey Li, Yun Rose Riva, Laura Zhang, Tongwu Gruber, Andreas J. Steele, Christopher D. Otlu, Burçak Khandekar, Azhar Abbasi, Ammal Humphreys, Laura Syulyukina, Natalia Brady, Samuel W. Alexandrov, Boian S. Pillay, Nischalan Zhang, Jinghui Adams, David J. Martincorena, Iñigo Wedge, David C. Landi, Maria Teresa Brennan, Paul Stratton, Michael R. Rozen, Steven G. Alexandrov, Ludmil B. Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor |
title | Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor |
title_full | Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor |
title_fullStr | Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor |
title_full_unstemmed | Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor |
title_short | Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor |
title_sort | uncovering novel mutational signatures by de novo extraction with sigprofilerextractor |
topic | Technology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9646490/ https://www.ncbi.nlm.nih.gov/pubmed/36388765 http://dx.doi.org/10.1016/j.xgen.2022.100179 |
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