Welcome to the Swimmer Plot App

Summary:

This web application allows you to graph a swimmer plot to visualize individual or patient trajectories and events over time. A swimmer plot is a graphical display where a horizontal bar is drawn for each individual or patient to represent follow-up time and events (e.g. progression, adverse event) are marked using various symbols. These graphs are commonly used to illustrate patient trajectories in cancer clinical trials. The user uploads a dataset according to the specifications provided, and a swimmer plot will be created automatically.

Detail and Uses:

The plots and summary statistics provided in this app can be downloaded and used for publications, presentations, or simply for internal reference. This app will take your formatted data and automatically create high quality graphs. The user has the ability to select stylistic choices including axis and plot titles, and download quality.

Disclaimer:

We do not take responsibility for any misuse or misinterpretation of this application or the results produced.

References

Jonathan McPherson, Alan Dipert and Barbara Borges (2021). shiny: Web Application Framework for R. R package version 1.7.1. https://CRAN.R-project.org/package=shiny

Winston Chang (2021). shinythemes: Themes for Shiny. R package version 1.2.0. https://CRAN.R-project.org/package=shinythemes

Carson Sievert and Joe Cheng (2021). bslib: Custom "Bootstrap" "Sass" Themes for "shiny" and "rmarkdown". R package version 0.3.1.https://CRAN.R-project.org/package=bslib

Wickham et al., (2019). Welcome to the tidyverse. Journal of Open Source Software, 4(43), 1686, https://doi.org/10.21105/joss.01686

H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016.

Hadley Wickham, Romain François, Lionel Henry and Kirill Müller (2021). dplyr: A Grammar of Data Manipulation. R package version 1.0.7. https://CRAN.R-project.org/package=dplyr

Hadley Wickham (2011). The Split-Apply-Combine Strategy for Data Analysis. Journal of Statistical Software, 40(1), 1-29. URL http://www.jstatsoft.org/v40/i01/.

Wickham H, Bryan J (2022). _readxl: Read Excel Files_. R package version 1.4.1, <https://CRAN.R-project.org/package=readxl>.

R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.

Developed by
Gonghao Liu, Aijin Wang

Accepted format for upload data include csv, xlsx, and xls.

Description of Columns
ID Variable:

This variable is the ID of each participant patient, which will be used as a unique identifier.

Event Variable:

This variable is the event in the plot, represented by markers.

Time Variable:

This variable is the time associated with each event, which can be measured by day, month, and year.

Group Variable:

This variable is a group identifier (the color to differentiate the groups of patients).

Below is a sample data set that satisfies the above criteria. This data can be downloaded and used as a sample for visualization.