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Visualizing tumor evolution with the fishplot package for R

delete2016-11-07
delete131
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OA
AI
C
Christopher A. Miller *
J
Joshua F. McMichael
H
Ha X. Dang
C
Christopher A. Maher
李丁 cover
李丁 (Li Ding)
T
Timothy J. Ley
E
Elaine R. Mardis
R
Richard K. Wilson
DOI:10.1186/s12864-016-3195-zdelete
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Abstract

Abstract

En 中文
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.
Keywords:
CLONAL EVOLUTION
CANCER
AI Summary

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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

BMC Genomics cover
BMC Genomics
IF:
3.7
Papers:
1.9W
Citations:
5.2W

Organization

W
washington university (wustl)
Scholars:
5.5W
Papers: 4.5W
Citations: 70