Do you spend too much time re-running analyses? Did you ever have trouble regenerating a figure or result from a previous analysis? This session is for you!
In this workshop, we will explore 10 principles that you can follow to elevate your research to the next level in terms of reproducibility. Equipped with these principles, you and others will spend less time re-running your analyses. We will apply these principles in real time to a toy R project that we will start from scratch. Topics will include R, RStudio, Git/GitHub, R Markdown/Notebooks, Conda/Bioconda, and open research.
In order to get the most out of the hands-on demos, you need to be familiar with R. That being said, the principles are certainly generalizable to other programming languages like Python, so you can still join us to learn the concepts.
Create a GitHub.com account if you don't already have one. If you already have one, confirm that you can log in.
Please have a recent version of R installed (version 3.1.2 or later). You can check your R version by running "R.version.string" at the R console. Install the tidyverse, knitr and rmarkdown R packages using the following command:
install.packages(c("tidyverse", "knitr", "rmarkdown"))
|10 Principles of Reproducible Research: The Hands-on R Edition : 2019-10-24||Burnaby, Bennett Library, Rm 7010, Research Commons||Thursday, October 24, 2019 - 1:00pm to 5:00pm|