# Course Overview

## Welcome to the R Introductory Series!

### 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

The course will include a series of eight lessons taught in 1-hour blocks over four weeks. Lessons will be on Tuesdays and Thursdays at 1 pm. Each lesson will be followed by an optional 1-hour 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

### Introduction to R and RStudio

This lesson will serve as a general introduction to R and RStudio. Attendees will explore the RStudio interactive development environment (IDE) and learn to create R projects and scripts, navigate between directories, use functions, and obtain help.

### The Basics of R Programming

In this lesson, attendees will learn the most basic features of the R programming language including:

- R syntax
- Creating R objects
- Data types
- Using mathematical operations
- Using comparison operators
- Creating, subsetting, and modifying vectors

### R Data Structures: Introducing Data Frames

This lesson will introduce data structures with a focus on data frames. Attendees will learn how to import, summarize, and explore data stored in data frames.

### Data Frames and Data Wrangling (part 1)

This lesson will introduce data wrangling with R. Attendees will learn to filter data using base R and tidyverse (dplyr) functionality.

### Data Frames and Data Wrangling (part 2)

In this lesson, attendees will learn how to transform, summarize, and reshape data using functions from the tidyverse.

### Introduction to Data Visualization with R (part 1)

This lesson will introduce prominent ways to visualize data with R. The majority of the lesson will be devoted to learning how to create publishable figures using the ggplot2 package.

### Introduction to Data Visualization with R (Part 2)

In this lesson, attendees will continue learning how to plot publishable figures with ggplot2.

### Introduction to Bioconductor and report generation with R

This lesson will be divided into two parts. Part 1 will introduce Bioconductor, an R package repository for the analysis of biological data. Part 2 will introduce RMarkdown and Quarto for report generation with R.

## 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.

DNAnexus Accounts

If you are not taking the live iteration of this course and you are following this documentation on your own, you do not need a DNAnexus account. DNAnexus is only accessible to course registrants during class times.

Video Recordings

Video recordings of BTEP Coding Club events can be found in the BTEP Video Archive 24-48 hours following any given event.