Introduction to R Workshop

Welcome to the Introduction to R Workshop by the Nevada Bioinformatics Center with support from the NV INBRE Data Science Core. This workshop is designed to get you started with R programming for data analysis and statistics.

Workshop Overview

This hands-on workshop introduces participants to the R programming language and RStudio development environment. You'll learn essential skills for data manipulation and exploration using R's powerful tools and packages.

Learning Objectives

By the end of this workshop, you will be able to:

• Install and navigate R and RStudio
• Understand fundamental R concepts and data structures
• Import, explore, and manipulate data using base R and tidyverse packages
• Wrangle and reshape data using dplyr and tidyr (e.g., (filtering, joining, pivoting, recoding)
• Organize and manage R projects effectively

Workshop Materials

Module 0: Installation and Setup

File: 00_Installation.md | HTML Version

• Installing R and RStudio
• Understanding the RStudio interface
• Setting up projects and organizing files
• Installing R packages
• Console vs. script workflows

Module 1: Working with Data in R

File: 01_Data.md | HTML Version

• R fundamentals and syntax
• Data structures (vectors, data frames, lists)
• Working with built-in datasets
• Basic data exploration and manipulation
• Creating reproducible workflows

Module 2: Packages for Data Transformation

File: 02_Packages.md | HTML Version

• Introduction to R packages and the tidyverse
• Data manipulation with dplyr
• Data reshaping with tidyr

Workshop Structure

Introduction-R-Workshop/
├── 00_Installation.Rmd          # Setup and installation guide
├── 01_Data.Rmd                  # Working with data in R
└── 02_Packages.Rmd              # Data transformation packages

Getting Started

Prerequisites

• No prior programming experience required

During the Workshop

1. Open the HTML versions of each module for easier reading
2. Follow along with the instructor using the R Markdown (.Rmd) files
3. Practice with the provided examples and exercises
4. Ask questions - learning is collaborative!

Sample Data

This workshop uses several datasets for hands-on practice:

• Built-in R datasets: mtcars, iris, and others
• Workshop dataset: subset_FFQ.csv - A sample food frequency questionnaire dataset

Required Software

• R (version 4.0 or higher) - Download from CRAN
• RStudio - Download from RStudio

Key R Packages

The workshop covers installation and use of:

• tidyverse - A collection of data science packages
  • dplyr - Data manipulation
  • tidyr - Data tidying and reshaping
  • many more

Why Learn R?

Reproducible Analysis

Create scripts that document your entire analysis process, making your work transparent and easy to replicate.

Powerful and Flexible

Access to thousands of packages for everything from basic statistics to machine learning, with specialized tools for various fields.

Excellent Graphics

Create publication-quality visualizations with fine-grained control over every aspect of your plots.

Free and Open Source

No licensing fees, with a supportive community and transparent development process.

Getting Help

During the Workshop

• Ask questions anytime
• Work with your neighbors
• Use the RStudio Help panel (?function_name)

After the Workshop

• R Documentation
• RStudio Cheat Sheets
• R for Data Science - Excellent online book
• Stack Overflow - Programming questions
• RStudio Community - Friendly R community

Contact

Nevada Bioinformatics Center

• Website: Nevada Bioinformatics Center
• For questions about this workshop or future training opportunities

Acknowledgment

This training was developed with support from a grant from the National Institute of General Medical Sciences (GM103440) from the National Institutes of Health.

License

This workshop content is provided for educational purposes only and not to be used for any other purposes.

Happy coding with R! 🎉