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Gattaca: Base-Pair Resolution Mutation Tracking for Somatic Evolution Studies using Agent-based Models
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 som...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9034688/ https://www.ncbi.nlm.nih.gov/pubmed/35298641 http://dx.doi.org/10.1093/molbev/msac058 |
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author | Schenck, Ryan O. Brosula, Gabriel West, Jeffrey Leedham, Simon Shibata, Darryl Anderson, Alexander R.A. |
author_facet | Schenck, Ryan O. Brosula, Gabriel West, Jeffrey Leedham, Simon Shibata, Darryl Anderson, Alexander R.A. |
author_sort | Schenck, Ryan O. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9034688 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-90346882022-04-25 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. Mol Biol Evol Methods 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. Oxford University Press 2022-03-17 /pmc/articles/PMC9034688/ /pubmed/35298641 http://dx.doi.org/10.1093/molbev/msac058 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methods Schenck, Ryan O. Brosula, Gabriel West, Jeffrey Leedham, Simon Shibata, Darryl Anderson, Alexander R.A. Gattaca: Base-Pair Resolution Mutation Tracking for Somatic Evolution Studies using Agent-based Models |
title | Gattaca: Base-Pair Resolution Mutation Tracking for Somatic Evolution Studies using Agent-based Models |
title_full | Gattaca: Base-Pair Resolution Mutation Tracking for Somatic Evolution Studies using Agent-based Models |
title_fullStr | Gattaca: Base-Pair Resolution Mutation Tracking for Somatic Evolution Studies using Agent-based Models |
title_full_unstemmed | Gattaca: Base-Pair Resolution Mutation Tracking for Somatic Evolution Studies using Agent-based Models |
title_short | Gattaca: Base-Pair Resolution Mutation Tracking for Somatic Evolution Studies using Agent-based Models |
title_sort | gattaca: base-pair resolution mutation tracking for somatic evolution studies using agent-based models |
topic | Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9034688/ https://www.ncbi.nlm.nih.gov/pubmed/35298641 http://dx.doi.org/10.1093/molbev/msac058 |
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