Course Overview

Welcome to the R Introductory Series 2023

A series of introductory lessons in R for scientists.

This course will include a series of lessons for individuals new to R or with limited R experience. The purpose of this course is to introduce the foundational skills necessary to begin to analyze and visualize data in R. This course is not designed for those with intermediate R experience and is not tailored to any one specific type of analysis.

Course Expectations / Learning Objectives

The course will include a series of eight lessons taught in one to one hour and 15 minute blocks over four weeks. Lessons will be on Mondays and Wednesdays at 1 pm. Each lesson will be followed by an optional 45 minute help session. Content has been adapted from material provided by Data Carpentry Intro to R and RStudio for Genomics (Link to the license) as well as R for Data Science.

Content Organization

Learning R - The Basics

Here, we will introduce R and RStudio. Learners will explore the RStudio interactive development environment (IDE) and begin to use functions and assign objects. By the end of this section, learners should understand how to work within the RStudio environment to create R projects and R scripts, navigate between directories, use functions, obtain help, and work with basic objects such as vectors.

Data frames and Data Wrangling

Here, we will learn how to store and work with tabular data in R. Learners will become acquainted with the basics of data frame manipulation including importing, cleaning, transforming, and exporting data. For data wrangling, the focus will be on the R tidyverse collection of packages.

Data Visualization with GGplot2

In this section, we will learn how to create publishable figures using the R (ggplot2) package. This includes an introduction to mapping and aesthetics, building plots iteratively, and improving plot readability. Additional packages for colors, themes, and statistics integration will be demonstrated.

Bioconductor and Rmarkdown

Here, we will review major concepts taught in the first three sectinos. We will explore R Markdown functionality, to help learners generate shareable, professional, and reproducible data analysis reports. We will also introduce Bioconductor, including how to install and search for packages and how to get help.

Required Course Materials

To participate in this class you will need your government-issued computer and a reliable internet connection. You do not need to download or install any software to participate in the class. However, at the end of the class, we will provide instruction on installing R and R Studio on your local machine.

This class will be taught on the DNAnexus platform. Every learner will need to create a DNAnexus account.