A Sticky Multinomial Mixture Model of Strand-Coordinated Mutational Processes in Cancer
Summary: The characterization of mutational processes in terms of their signatures of activity relies mostly on the assumption that mutations in a given cancer genome are independent of one another. Recently, it was discovered that certain segments of mutations, termed processive groups, occur on th...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2020-03-01
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| Series: | iScience |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004220300845 |
| _version_ | 1817987183229796352 |
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| author | Itay Sason Damian Wojtowicz Welles Robinson Mark D.M. Leiserson Teresa M. Przytycka Roded Sharan |
| author_facet | Itay Sason Damian Wojtowicz Welles Robinson Mark D.M. Leiserson Teresa M. Przytycka Roded Sharan |
| author_sort | Itay Sason |
| collection | DOAJ |
| description | Summary: The characterization of mutational processes in terms of their signatures of activity relies mostly on the assumption that mutations in a given cancer genome are independent of one another. Recently, it was discovered that certain segments of mutations, termed processive groups, occur on the same DNA strand and are generated by a single process or signature. Here we provide a first probabilistic model of mutational signatures that accounts for their observed stickiness and strand coordination. The model conditions on the observed strand for each mutation and allows the same signature to generate a run of mutations. It can both use known signatures or learn new ones. We show that this model provides a more accurate description of the properties of mutagenic processes than independent-mutation achieving substantially higher likelihood on held-out data. We apply this model to characterize the processivity of mutagenic processes across multiple types of cancer. : Quantitative Genetics; Bioinformatics; Cancer Subject Areas: Quantitative Genetics, Bioinformatics, Cancer |
| first_indexed | 2024-04-14T00:18:39Z |
| format | Article |
| id | doaj.art-f95ea27101a0422bb3e8d2f70d46b2af |
| institution | Directory Open Access Journal |
| issn | 2589-0042 |
| language | English |
| last_indexed | 2024-04-14T00:18:39Z |
| publishDate | 2020-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | iScience |
| spelling | doaj.art-f95ea27101a0422bb3e8d2f70d46b2af2022-12-22T02:23:03ZengElsevieriScience2589-00422020-03-01233A Sticky Multinomial Mixture Model of Strand-Coordinated Mutational Processes in CancerItay Sason0Damian Wojtowicz1Welles Robinson2Mark D.M. Leiserson3Teresa M. Przytycka4Roded Sharan5Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, IsraelNational Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, USACenter for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USACenter for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USANational Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, USABlavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel; Corresponding authorSummary: The characterization of mutational processes in terms of their signatures of activity relies mostly on the assumption that mutations in a given cancer genome are independent of one another. Recently, it was discovered that certain segments of mutations, termed processive groups, occur on the same DNA strand and are generated by a single process or signature. Here we provide a first probabilistic model of mutational signatures that accounts for their observed stickiness and strand coordination. The model conditions on the observed strand for each mutation and allows the same signature to generate a run of mutations. It can both use known signatures or learn new ones. We show that this model provides a more accurate description of the properties of mutagenic processes than independent-mutation achieving substantially higher likelihood on held-out data. We apply this model to characterize the processivity of mutagenic processes across multiple types of cancer. : Quantitative Genetics; Bioinformatics; Cancer Subject Areas: Quantitative Genetics, Bioinformatics, Cancerhttp://www.sciencedirect.com/science/article/pii/S2589004220300845 |
| spellingShingle | Itay Sason Damian Wojtowicz Welles Robinson Mark D.M. Leiserson Teresa M. Przytycka Roded Sharan A Sticky Multinomial Mixture Model of Strand-Coordinated Mutational Processes in Cancer iScience |
| title | A Sticky Multinomial Mixture Model of Strand-Coordinated Mutational Processes in Cancer |
| title_full | A Sticky Multinomial Mixture Model of Strand-Coordinated Mutational Processes in Cancer |
| title_fullStr | A Sticky Multinomial Mixture Model of Strand-Coordinated Mutational Processes in Cancer |
| title_full_unstemmed | A Sticky Multinomial Mixture Model of Strand-Coordinated Mutational Processes in Cancer |
| title_short | A Sticky Multinomial Mixture Model of Strand-Coordinated Mutational Processes in Cancer |
| title_sort | sticky multinomial mixture model of strand coordinated mutational processes in cancer |
| url | http://www.sciencedirect.com/science/article/pii/S2589004220300845 |
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