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Simulation of heterogeneous tumour genomes with HeteroGenesis and in silico whole exome sequencing
SUMMARY: Tumour evolution results in progressive cancer phenotypes such as metastatic spread and treatment resistance. To better treat cancers, we must characterize tumour evolution and the genetic events that confer progressive phenotypes. This is facilitated by high coverage genome or exome sequen...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6691334/ https://www.ncbi.nlm.nih.gov/pubmed/30615054 http://dx.doi.org/10.1093/bioinformatics/bty1063 |
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author | Tanner, Georgette Westhead, David R Droop, Alastair Stead, Lucy F |
author_facet | Tanner, Georgette Westhead, David R Droop, Alastair Stead, Lucy F |
author_sort | Tanner, Georgette |
collection | PubMed |
description | SUMMARY: Tumour evolution results in progressive cancer phenotypes such as metastatic spread and treatment resistance. To better treat cancers, we must characterize tumour evolution and the genetic events that confer progressive phenotypes. This is facilitated by high coverage genome or exome sequencing. However, the best approach by which, or indeed whether, these data can be used to accurately model and interpret underlying evolutionary dynamics is yet to be confirmed. Establishing this requires sequencing data from appropriately heterogeneous tumours in which the exact trajectory and combination of events occurring throughout its evolution are known. We therefore developed HeteroGenesis: a tool to generate realistically evolved tumour genomes, which can be sequenced using weighted-Wessim (w-Wessim), an in silico exome sequencing tool that we have adapted from previous methods. HeteroGenesis simulates more complex and realistic heterogeneous tumour genomes than existing methods, can model different evolutionary dynamics, and enables the creation of multi-region and longitudinal data. AVAILABILITY AND IMPLEMENTATION: HeteroGenesis and w-Wessim are freely available under the GNU General Public Licence from https://github.com/GeorgetteTanner, implemented in Python and supported on linux and MS Windows. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-6691334 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-66913342019-08-16 Simulation of heterogeneous tumour genomes with HeteroGenesis and in silico whole exome sequencing Tanner, Georgette Westhead, David R Droop, Alastair Stead, Lucy F Bioinformatics Applications Notes SUMMARY: Tumour evolution results in progressive cancer phenotypes such as metastatic spread and treatment resistance. To better treat cancers, we must characterize tumour evolution and the genetic events that confer progressive phenotypes. This is facilitated by high coverage genome or exome sequencing. However, the best approach by which, or indeed whether, these data can be used to accurately model and interpret underlying evolutionary dynamics is yet to be confirmed. Establishing this requires sequencing data from appropriately heterogeneous tumours in which the exact trajectory and combination of events occurring throughout its evolution are known. We therefore developed HeteroGenesis: a tool to generate realistically evolved tumour genomes, which can be sequenced using weighted-Wessim (w-Wessim), an in silico exome sequencing tool that we have adapted from previous methods. HeteroGenesis simulates more complex and realistic heterogeneous tumour genomes than existing methods, can model different evolutionary dynamics, and enables the creation of multi-region and longitudinal data. AVAILABILITY AND IMPLEMENTATION: HeteroGenesis and w-Wessim are freely available under the GNU General Public Licence from https://github.com/GeorgetteTanner, implemented in Python and supported on linux and MS Windows. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2019-08-15 2019-01-04 /pmc/articles/PMC6691334/ /pubmed/30615054 http://dx.doi.org/10.1093/bioinformatics/bty1063 Text en © The Author(s) 2019. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Tanner, Georgette Westhead, David R Droop, Alastair Stead, Lucy F Simulation of heterogeneous tumour genomes with HeteroGenesis and in silico whole exome sequencing |
title | Simulation of heterogeneous tumour genomes with HeteroGenesis and in silico whole exome sequencing |
title_full | Simulation of heterogeneous tumour genomes with HeteroGenesis and in silico whole exome sequencing |
title_fullStr | Simulation of heterogeneous tumour genomes with HeteroGenesis and in silico whole exome sequencing |
title_full_unstemmed | Simulation of heterogeneous tumour genomes with HeteroGenesis and in silico whole exome sequencing |
title_short | Simulation of heterogeneous tumour genomes with HeteroGenesis and in silico whole exome sequencing |
title_sort | simulation of heterogeneous tumour genomes with heterogenesis and in silico whole exome sequencing |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6691334/ https://www.ncbi.nlm.nih.gov/pubmed/30615054 http://dx.doi.org/10.1093/bioinformatics/bty1063 |
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