Instructor notes for the R Workshop in Rio Based on Software Carpentry
In this workshop, we will cover basics of using R, git and Github for analysis of collaboration with biological data. R is an open source statistical programming language, which allows users to perform standard as well as customized statistical analyses. Git is a piece of software for version control, allowing users to document changes made to R code and revert to old versions if necessary. Github is a website that allows collaboration between several researchers, sharing all the components of a project: data, code, outputs and manuscripts.
By the end of this workshop, participants will be able to:
- Organize data for import into R
- Use R to analyze and visualize data
- Write R functions to automate analyses
- Use version control (git) to track changes to their work
- Use Github to share their project with collaborators.
- Install git
- Install R
- Install Rstudio
- optional bring a dataset that you are analyzing!
The workshop will include teaching sessions as well as interactive sessions in which participants may practice applying methods to their own data or to sample datasets. Thus, it would be beneficial for participants to bring data they are currently analyzing.
As a prerequisite for the workshop, all participants should create a GitHub profile (github.com) if needed, and install Git on their computers. This will allow us to immediately start sharing course notes at the start of the workshop.
Topics covered will include:
- Organizing and formatting data for use in analyses
- Data import and export to and from R
- Performing basic analyses on data
- Visualizing data using different types of plots
- Writing functions to perform tasks that are repeated multiple times
- using reproducible documents (knitr)
- Adding and commiting files
- Ignoring files
- Resolving merge conflicts
- Writing for the web
- forking
- pull requests
- licences
abs/master