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Improving cellular phylogenies through the integrated use of mutation order and optimality principles
The study of tumor evolution is being revolutionalized by single-cell sequencing technologies that survey the somatic variation of cancer cells. In these endeavors, reliable inference of the evolutionary relationship of single cells is a key step. However, single-cell sequences contain many errors a...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10432911/ https://www.ncbi.nlm.nih.gov/pubmed/37602230 http://dx.doi.org/10.1016/j.csbj.2023.07.018 |
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author | Miura, Sayaka Dolker, Tenzin Sanderford, Maxwell Kumar, Sudhir |
author_facet | Miura, Sayaka Dolker, Tenzin Sanderford, Maxwell Kumar, Sudhir |
author_sort | Miura, Sayaka |
collection | PubMed |
description | The study of tumor evolution is being revolutionalized by single-cell sequencing technologies that survey the somatic variation of cancer cells. In these endeavors, reliable inference of the evolutionary relationship of single cells is a key step. However, single-cell sequences contain many errors and missing bases, which necessitate advancing standard molecular phylogenetics approaches for applications in analyzing these datasets. We have developed a computational approach that integratively applies standard phylogenetic optimality principles and patterns of co-occurrence of sequence variations to produce more expansive and accurate cellular phylogenies from single-cell sequence datasets. We found the new approach to also perform well for CRISPR/Cas9 genome editing datasets, suggesting that it can be useful for various applications. We apply the new approach to some empirical datasets to showcase its use for reconstructing recurrent mutations and mutational reversals as well as for phylodynamics analysis to infer metastatic cell migrations between tumors. |
format | Online Article Text |
id | pubmed-10432911 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-104329112023-08-18 Improving cellular phylogenies through the integrated use of mutation order and optimality principles Miura, Sayaka Dolker, Tenzin Sanderford, Maxwell Kumar, Sudhir Comput Struct Biotechnol J Research Article The study of tumor evolution is being revolutionalized by single-cell sequencing technologies that survey the somatic variation of cancer cells. In these endeavors, reliable inference of the evolutionary relationship of single cells is a key step. However, single-cell sequences contain many errors and missing bases, which necessitate advancing standard molecular phylogenetics approaches for applications in analyzing these datasets. We have developed a computational approach that integratively applies standard phylogenetic optimality principles and patterns of co-occurrence of sequence variations to produce more expansive and accurate cellular phylogenies from single-cell sequence datasets. We found the new approach to also perform well for CRISPR/Cas9 genome editing datasets, suggesting that it can be useful for various applications. We apply the new approach to some empirical datasets to showcase its use for reconstructing recurrent mutations and mutational reversals as well as for phylodynamics analysis to infer metastatic cell migrations between tumors. Research Network of Computational and Structural Biotechnology 2023-08-02 /pmc/articles/PMC10432911/ /pubmed/37602230 http://dx.doi.org/10.1016/j.csbj.2023.07.018 Text en © 2023 The Authors 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 | Research Article Miura, Sayaka Dolker, Tenzin Sanderford, Maxwell Kumar, Sudhir Improving cellular phylogenies through the integrated use of mutation order and optimality principles |
title | Improving cellular phylogenies through the integrated use of mutation order and optimality principles |
title_full | Improving cellular phylogenies through the integrated use of mutation order and optimality principles |
title_fullStr | Improving cellular phylogenies through the integrated use of mutation order and optimality principles |
title_full_unstemmed | Improving cellular phylogenies through the integrated use of mutation order and optimality principles |
title_short | Improving cellular phylogenies through the integrated use of mutation order and optimality principles |
title_sort | improving cellular phylogenies through the integrated use of mutation order and optimality principles |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10432911/ https://www.ncbi.nlm.nih.gov/pubmed/37602230 http://dx.doi.org/10.1016/j.csbj.2023.07.018 |
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