How do you keep HDR students motivated, particularly those whose research has stalled as they can’t get into the field or lab? A common suggestion is to keep them busy processing data ready for publications or learning some new data analysis techniques. But what if the software you need for this requires a license tied to the RMIT campus and/or access though MyDesktop is too slow? You could use free software alternatives, but they are hard to use and require learning advanced coding skills – right? – Wrong!
In this session Professor Oliver Jones, (School of Science), demonstrated how he has encouraged both his PhD students, and himself, to use the lockdown period to develop new skills in data analysis and visualisation using the R programming language. Oliver discussed how the problem solving and self-teaching skills this project required led to a great learning experience for the group. Oliver and his students have new capabilities that will enhance their future research, and which have already led to new collaborations”.
The video below is an edited version of the webinar conducted by Professor Oliver Jones, questions and technical glitches removed.
Sample of COVID19 data processed using R
Here’s the code Oliver used in the presentation:
Resources Recommended by Oliver Jones
How to Install R
- Nice clear instructions on how to Install R on windows, Apple etc – https://www.datacamp.com/community/tutorials/installing-R-windows-mac-ubuntu
- The datacamp website also has a lot of great courses on R – https://www.datacamp.com/search?q=R
ggplot2 (this is the basic package to make the graphs)
- Getting started with ggplot 2 Free book at https://ggplot2-book.org/introduction.html
- Example and background – https://monashdatafluency.github.io/r-intro-2/plotting-with-ggplot2.html
- Drag and Drop GUI Visualization in R – https://towardsdatascience.com/tableau-esque-drag-and-drop-gui-visualization-in-r-901ee9f2fe3f
3D plots with Rayshader
- https://www.tylermw.com/3d-ggplots-with-rayshader/
- https://www.rayshader.com/reference/plot_gg.html
- https://rdrr.io/github/tylermorganwall/rayshader/man/render_movie.html (I used this code for the rotating movie)
- https://rstudio.com/resources/rstudioconf-2020/3d-ggplots-with-rayshader/ (talk by the author)
gganimate
- https://gganimate.com/
- https://www.youtube.com/watch?v=adelgqOlZwE (video example. It uses House price data but you can adapt this).
- Stackoverflow (post questions on code and see answers others have given) https://stackoverflow.com/
3D Printing
- This is the paper I mentioned in the talk
https://pubs.acs.org/doi/abs/10.1021/acs.jchemed.7b00533 (see also https://sites.rmit.edu.au/sister/2019/04/08/open-classrooms-episode-4-oliver-jones/)
MZmine 2
- An open-source software for mass-spectrometry data processing, – http://mzmine.github.io/
Bioconductor
- R package for mass spectrometry and proteomics data analysis – https://bioconductor.org/packages/devel/workflows/vignettes/proteomics/inst/doc/proteomics.html
Additional Resources:
- Teaching Labs Online
- R project – R is a language and environment for statistical computing and graphics.
- Learning Statistics with R: A tutorial for psychology students and other beginners (Open Textbook)
- Answering Questions with Data: Introductory Statistics for Psychology Students (Open Textbook & accompanying material)
- Spectragryph – Optical spectroscopy processing software for UV-VIS, NIR, FTIR, Raman, fluorescence, LIBS, XRF data. Capable of opening multiple vendors and file formats. Free for private and academic use. Compatible with Windows. Could be run on Mac or Linux using a Windows virtual box or emulator such as Wine/WineBottler.
- OERs @RMIT
If you adopt an open textbook for your course, please make sure you let the library know so they can list you as a textbook hero, learn more about being a textbook hero here. Contact library support if you need assistance with finding/using OERs: open.library@rmit.edu.au
