Improving cellular phylogenies through the integrated use of mutation order and optimality principles.

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 th

SUBMITTER: Miura S 

PROVIDER: S-EPMC10432911 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature