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Improving cellular phylogenies through the integrated use of mutation order and optimality principles
Dolker, Tenzin Sanderford, Maxwell
Dolker, Tenzin
Sanderford, Maxwell
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Journal article
Date
2023-08-07
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Biology
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https://doi.org/10.1016/j.csbj.2023.07.018
Abstract
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.
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Sayaka Miura, Tenzin Dolker, Maxwell Sanderford, Sudhir Kumar, Improving cellular phylogenies through the integrated use of mutation order and optimality principles, Computational and Structural Biotechnology Journal, Volume 21, 2023, Pages 3894-3903, ISSN 2001-0370, https://doi.org/10.1016/j.csbj.2023.07.018.
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Elsevier
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Computational and Structural Biotechnology Journal (CSBJ), Vol. 21
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