Introduction to R (Online)
|Audience||Computational skills required||Duration|
|Biologists||None||1.5 or 2-day workshop (~ 9 - 13 hours of trainer-led time)|
This repository has teaching materials for a hands-on Introduction to R workshop taught online. The workshop will introduce participants to the basics of R and RStudio. R is a simple programming environment that enables the effective handling of data, while providing excellent graphical support. RStudio is a tool that provides a user-friendly environment for working with R. These materials are intended to provide both basic R programming knowledge and its application for increasing efficiency for data analysis.
Note for Trainers: Please note that the schedule linked below assumes that learners will spend between 2-3 hours on reading through, and completing exercises from selected lessons between classes. The online component of the workshop focuses on more exercises and discussion/Q & A.
These materials are developed for a trainer-led workshop, but also amenable to self-guided learning.
- R syntax: Understand the different ‘parts of speech’.
- Data types structures in R: Describe the various data types and data structures.
- Data inspection and wrangling: Demonstrate the utilization of functions and indices to inspect and subset data from various data structures.
- Visualizing data: Demonstrate the use of the ggplot2 package to create plots for easy data visualization.
Click here for links to lessons and the suggested schedule
Download the most recent versions of R and RStudio for the appropriate OS using the links below:
All the files used for the above lessons are linked within, but can also be accessed here.
These materials have been developed by members of the teaching team at the Harvard Chan Bioinformatics Core (HBC). These are open access materials distributed under the terms of the Creative Commons Attribution license (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- Some materials used in these lessons were derived from work that is Copyright © Data Carpentry (http://datacarpentry.org/). All Data Carpentry instructional material is made available under the Creative Commons Attribution license (CC BY 4.0).