Why Did We Do It?

It does not always have to be pretty. That was the motto in Sticks little development run. Sticks was developed as a way to visualize protein dynamic simulations and static protein structures in R without having to use third-party software.


Getting Sticks To Work For You

Sticks runs by decomposing 3 different data frames to make 3D images at discrete time points. It then knits these images together to form a GIF. All of this can be run in R.

For entering data into the XDATA, YDATA, and ZDATA portions of the function use the below graphic as a template for the data frames.

Figure 1. Example matrix for the inputs for a single dimension.

The descending axis on the left represents the time points in the simulation. The top axis reflects the amino acids in the protein sequence. The data between these two axes represent the coordinate for the particular amino acid at the particular time point, in the axis chosen. In total to run Sticks you must just run a clean function to get your data into this format for three individual data frames (1 per x, y, and z). Then plug them in and push run. After running the software, you will be greeted by a delightful gif like the one below.

Figure 2. GIF generated by Sticks to represent proteins dynamics.


How To Find It And Where To Use It

This software can be useful when working on computers or computational resources without biochemical modelling software. It also opens up operation on devices without the chops to run the visualization software.

For anyone looking to work with Sticks please visit the Sticks page on the UCalgary Github. STICKs Github Page


R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL

Karline Soetaert (2019). plot3D: Plotting Multi-Dimensional Data. R package version 1.3.

Yihui Xie (2013). animation: An R Package for Creating Animations and Demonstrating Statistical Methods. Journal of Statistical Software, 53(1), 1-27. URL