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Visualizing tumor evolution with the fishplot package for R
BACKGROUND: Massively-parallel sequencing at depth is now enabling tumor heterogeneity and evolution to be characterized in unprecedented detail. Tracking these changes in clonal architecture often provides insight into therapeutic response and resistance. In complex cases involving multiple timepoi...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5100182/ https://www.ncbi.nlm.nih.gov/pubmed/27821060 http://dx.doi.org/10.1186/s12864-016-3195-z |
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author | Miller, Christopher A. McMichael, Joshua Dang, Ha X. Maher, Christopher A. Ding, Li Ley, Timothy J. Mardis, Elaine R. Wilson, Richard K. |
author_facet | Miller, Christopher A. McMichael, Joshua Dang, Ha X. Maher, Christopher A. Ding, Li Ley, Timothy J. Mardis, Elaine R. Wilson, Richard K. |
author_sort | Miller, Christopher A. |
collection | PubMed |
description | BACKGROUND: Massively-parallel sequencing at depth is now enabling tumor heterogeneity and evolution to be characterized in unprecedented detail. Tracking these changes in clonal architecture often provides insight into therapeutic response and resistance. In complex cases involving multiple timepoints, standard visualizations, such as scatterplots, can be difficult to interpret. Current data visualization methods are also typically manual and laborious, and often only approximate subclonal fractions. RESULTS: We have developed an R package that accurately and intuitively displays changes in clonal structure over time. It requires simple input data and produces illustrative and easy-to-interpret graphs suitable for diagnosis, presentation, and publication. CONCLUSIONS: The simplicity, power, and flexibility of this tool make it valuable for visualizing tumor evolution, and it has potential utility in both research and clinical settings. The fishplot package is available at https://github.com/chrisamiller/fishplot. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-3195-z) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5100182 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-51001822016-11-08 Visualizing tumor evolution with the fishplot package for R Miller, Christopher A. McMichael, Joshua Dang, Ha X. Maher, Christopher A. Ding, Li Ley, Timothy J. Mardis, Elaine R. Wilson, Richard K. BMC Genomics Software BACKGROUND: Massively-parallel sequencing at depth is now enabling tumor heterogeneity and evolution to be characterized in unprecedented detail. Tracking these changes in clonal architecture often provides insight into therapeutic response and resistance. In complex cases involving multiple timepoints, standard visualizations, such as scatterplots, can be difficult to interpret. Current data visualization methods are also typically manual and laborious, and often only approximate subclonal fractions. RESULTS: We have developed an R package that accurately and intuitively displays changes in clonal structure over time. It requires simple input data and produces illustrative and easy-to-interpret graphs suitable for diagnosis, presentation, and publication. CONCLUSIONS: The simplicity, power, and flexibility of this tool make it valuable for visualizing tumor evolution, and it has potential utility in both research and clinical settings. The fishplot package is available at https://github.com/chrisamiller/fishplot. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-3195-z) contains supplementary material, which is available to authorized users. BioMed Central 2016-11-07 /pmc/articles/PMC5100182/ /pubmed/27821060 http://dx.doi.org/10.1186/s12864-016-3195-z Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Software Miller, Christopher A. McMichael, Joshua Dang, Ha X. Maher, Christopher A. Ding, Li Ley, Timothy J. Mardis, Elaine R. Wilson, Richard K. Visualizing tumor evolution with the fishplot package for R |
title | Visualizing tumor evolution with the fishplot package for R |
title_full | Visualizing tumor evolution with the fishplot package for R |
title_fullStr | Visualizing tumor evolution with the fishplot package for R |
title_full_unstemmed | Visualizing tumor evolution with the fishplot package for R |
title_short | Visualizing tumor evolution with the fishplot package for R |
title_sort | visualizing tumor evolution with the fishplot package for r |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5100182/ https://www.ncbi.nlm.nih.gov/pubmed/27821060 http://dx.doi.org/10.1186/s12864-016-3195-z |
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