Using R and GitHub: reproducibility in research

Note on version control (git)

Please install Git before installing R Studio. This allows seamless integration between the two programs because R Studio looks for Git on your computer, but Git does not look for R Studio. In the past, installation in the opposite order has been known to create issues. If you already installed R Studio and Git, but do not see the Git Tab in R Studio then you can follow this support page to troubleshoot.

Learning new tools (how to learn how to do things in R).

• GitHub (for tracking and documenting your work)
• RMarkdown (to easily build webpages and pdfs with or without R code)
• Beamer (pdf slides that blow away Powerpoint presentations)
• Regular Expressions (find-and-replace on steroids)
• LaTeX (for type-setting equations and improving your slides)
• Git (version control)

UoC.Git.2018-11-27

• info

• Github

• Rstudio

• Reports

• Websites

Get Tickets

[eventbight link coming soon here]

General Information

Statistical software that are also programming languages, such as R, are excellent tools for conducting analyses of biological data. However, many users are not taking full advantage of their capabilities. This workshop is an introduction to some of the resources that are available to R users that have been developed and implemented in the larger programming community. No prior knowledge of R will be necessary, but this workshop will not be an introduction to R basics. Instead, we will focus on using R Studio and Github to easily sync your data and analyses online. Within this workshop we will explore how to maximize reproducibility, collaborate internationally on statistical analyses, present data summaries, data management, and the promotion of open science

Who: The course is aimed at R beginners and novice to intermediate analysts. You do not need to have previous knowledge of R.

Where: [coming soon]

Requirements: Participants should bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) with administrative privileges. If you want to work along during tutorial, you must have both Git, R and RStudio installed on your own computer (See below for instructions). However, you are still welcome to attend because all examples will be presented via slides in the classroom and on github.

Contact: Please contact anthony.davidson@canberra.edu.au for more information.

Schedule

I have developed this course from an program hosted on github from https://afilazzola.github.io

#input timetable from csv here....

Software

Please install Git before installing R Studio. This allows seamless integration between the two programs because R Studio looks for Git on your computer, but Git does not look for R Studio. In the past, installation in the opposite order has been known to create issues. If you already installed R Studio and Git, but do not see the Git Tab in R Studio then you can follow this support page to troubleshoot.

Git

Git is a version control system that lets you track who made changes to what when and has options for easily updating a shared or public version of your code on github.com. You will need a supported web browser (current versions of Chrome, Firefox or Safari, or Internet Explorer version 9 or above).

You will need an account at github.com for parts of the Git lesson. Basic GitHub accounts are free and premium accounts are free to students. We encourage you to create a GitHub account if you don’t have one already. Please consider what personal information you’d like to reveal. For example, you may want to review these instructions for keeping your email address private provided at GitHub.

Information on how to install Git for each OS is provided by Software Carpentry and can be found here

R

R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio.

Other workshops

If you are interested in undertaking courses like this I am currently based in Australia and enjoy developing and working alongside njoyed this workshop and were interested in learning more, I also run a workshop on R-basics and Introduction to Generalized Linear Modelling (GLM) found here. I also have a short introduction on using Functions in R.

You can find similar style workshops, usually that are longer and go into more detail, with Software Carpentry. They have teachers available globally and cover all forms of programming beyond R.