Visualizing tumor evolution with the fishplot package for R.
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.



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.



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 .
McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, 63108, USA. c.a.miller@wustl.edu.|Department of Medicine, Division of Genomics and Bioinformatics, Washington University School of Medicine, St. Louis, MO, 63108, USA. c.a.miller@wustl.edu.
Christopher A
CA
Miller
McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, 63108, USA.
Joshua
J
McMichael
McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, 63108, USA.|Department of Medicine, Division of Oncology, Washington University School of Medicine, St. Louis, MO, 63108, USA.
Ha X
HX
Dang
McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, 63108, USA.|Department of Medicine, Division of Oncology, Washington University School of Medicine, St. Louis, MO, 63108, USA.
Christopher A
CA
Maher
McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, 63108, USA.|Department of Medicine, Division of Oncology, Washington University School of Medicine, St. Louis, MO, 63108, USA.
Li
L
Ding
McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, 63108, USA.|Department of Medicine, Division of Oncology, Washington University School of Medicine, St. Louis, MO, 63108, USA.
Timothy J
TJ
Ley
McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, 63108, USA.|Department of Medicine, Division of Oncology, Washington University School of Medicine, St. Louis, MO, 63108, USA.|Department of Genetics, Washington University School of Medicine, St. Louis, MO, 63108, USA.
Elaine R
ER
Mardis
McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, 63108, USA.|Department of Medicine, Division of Genomics and Bioinformatics, Washington University School of Medicine, St. Louis, MO, 63108, USA.|Department of Medicine, Division of Oncology, Washington University School of Medicine, St. Louis, MO, 63108, USA.|Department of Genetics, Washington University School of Medicine, St. Louis, MO, 63108, USA.
Richard K
RK
Wilson
D063646:Carcinogenesis; D023281:Genomics / Q000379:methods; D008954:Models, Biological; D012984:Software; D064878:Web Browser