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Gattaca: Base-Pair Resolution Mutation Tracking for Somatic Evolution Studies using Agent-based Models.
Schenck, Ryan O; Brosula, Gabriel; West, Jeffrey; Leedham, Simon; Shibata, Darryl; Anderson, Alexander R A.
Afiliação
  • Schenck RO; Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612, USA.
  • Brosula G; Wellcome Centre for Human Genetics, University of Oxford, Oxford OX37BN, United Kingdom.
  • West J; Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612, USA.
  • Leedham S; Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612, USA.
  • Shibata D; Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612, USA.
  • Anderson ARA; Department of Pathology, University of Southern California, Keck School of Medicine, Los Angeles, CA 90033, USA.
Mol Biol Evol ; 39(4)2022 04 11.
Article em En | MEDLINE | ID: mdl-35298641
Research over the past two decades has made substantial inroads into our understanding of somatic mutations. Recently, these studies have focused on understanding their presence in homeostatic tissue. In parallel, agent-based mechanistic models have emerged as an important tool for understanding somatic mutation in tissue; yet no common methodology currently exists to provide base-pair resolution data for these models. Here, we present Gattaca as the first method for introducing and tracking somatic mutations at the base-pair resolution within agent-based models that typically lack nuclei. With nuclei that incorporate human reference genomes, mutational context, and sequence coverage/error information, Gattaca is able to realistically evolve sequence data, facilitating comparisons between in silico cell tissue modeling with experimental human somatic mutation data. This user-friendly method, incorporated into each in silico cell, allows us to fully capture somatic mutation spectra and evolution.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Genoma Humano / Neoplasias Limite: Humans Idioma: En Revista: Mol Biol Evol Assunto da revista: BIOLOGIA MOLECULAR Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Genoma Humano / Neoplasias Limite: Humans Idioma: En Revista: Mol Biol Evol Assunto da revista: BIOLOGIA MOLECULAR Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos