This application was developed with Nature Methods as described in this editorial and this blog entry. Nature methods also dedicated a Points of View and a Points of Significance column to box plots. We hope that you find the BoxPlotR useful and we welcome suggestions for additional features by our users. We would like to thank everyone who has made constructive suggestions so far. We will document the addition of new features in the News tab.
This application allows users to generate customized box plots in a number of variants based on their data. A data matrix can be uploaded as a file or pasted into the application. Basic box plots are generated based on the data and can be modified to include additional information. Additional features become available when checking that option. Information about sample sizes can be represented by the width of each box where the widths are proportional to the square roots of the number of observations n. Notches can be added to the boxes. These are defined as +/-1.58*IQR/sqrt(n) which gives roughly 95% confidence that two medians are different. It is also possible to define the whiskers based on the ideas of Spear and Tukey. Additional options of data visualization (violin and bean plots) reveal more information about the underlying data distribution. Plots can be labeled, customized (colors, dimensions, orientation) and exported as eps, pdf and svg files.
R Development Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna (2013)
RStudio and Inc. shiny: Web Application Framework for R. R package version 0.5.0 (2013)
Adler, D. vioplot: Violin plot. R package version 0.2 (2005)
Eklund, A. beeswarm: The bee swarm plot, an alternative to stripchart. R package version 0.1.5 (2012)
Kampstra, P. Beanplot: A Boxplot Alternative for Visual Comparison of Distributions. Journal of Statistical Software, Code Snippets 28(1). 1-9 (2008)
Neuwirth, E. RColorBrewer: ColorBrewer palettes. R package version 1.0-5. (2011)
Hadley Wickham and Lisa Stryjewski: 40 years of boxplots
Kristin Potter: Methods for Presenting Statistical Information: The Box Plot
What do the box plots show, explain colours if used.Download box plot data as .CSV file
Upgrade to R version 3.1 and shiny-server 1.2
The user can now choose the color of the data points. There is also an additional option for data point display: data points can now be randomly jittered. A small bug in label display was fixed. Log scales can now be used.
A: For EPS files make sure to 'ungroup' all objects so they can be edited independently. In Adobe Illustrator you will also need to use the 'release compound path' command. For PDF files you should 'release clipping mask'. SVG import appears to have problems in Adobe Illustrator and Corel Draw and should be avoided. EPS, PDF and SVG import all work with Inkscape http://www.inkscape.org/.
A: Please download the virtual machine from http://tyerslab.bio.ed.ac.uk/download/shiny.boxplot.7z (1.1GB). Unzip the file using 7zip or equivalent. The virtual machine is available in the open virtualization format (OVF) and you can use this file with vbox and vmware player. One easy way to use the server is to set the virtual host network environment to NAT. After importing the virtual machine you can start the server and login as user shiny with password pk635153Y6jx89r. On the command line use the command ifconfg and record the IP address of the virtual server. Now going back to the virtual host network environment change the advanced settings of the NAT and activate port forwarding for the guest network ip address (shiny server) using port 80 to the host ip address using for example port 8080. Now you should be able to access the shiny server in a browser on port 127.0.0.1:8080 or your localhost:8080. If you are not familiar with the software packages there are detailed examples for vbox and vmware.