Introduction to R

Description

This four-class course is designed to introduce attendees to R statistical programming and its broad applications. Each two hour session will include brief tutorials interspersed with challenge exercises, and assumes attendees have no prior computer coding experience. At the end of this course, you will be able to use R to import, manipulate, and visualize data. Please see each set of class materials for specific learning objectives.

This repository is adapted from content originally appearing in R for data analysis and visualization of Ecological Data, Copyright (c) Data Carpentry. See links at the bottom of each lesson for specific episodes from Carpentries material that have been modified.

Required software: Software requirements for this course can be found on fredhutch.io's Software page. The HackMD (interactive page used for sharing links and information) for this course is here: https://hackmd.io/@k8hertweck/introR

Schedule

Click on the following links to access materials for each class:

• Class 1: R syntax, assigning objects, using functions
• Class 2: Data types and structures; slicing and subsetting data
• Class 3: Data manipulation with dplyr
• Class 4: Data visualization in ggplot2

Resources

• Each class' materials are described in the R markdown (.Rmd) and markdown (.md) files. The former should be edited to make changes to the material; the latter are automatically formatted to appear in GitHub. The directories for each class are also created for publishing on GitHub.
• The data used for this course are from the National Cancer Institute's Genomic Data Commons. extra/ holds the original data files used for download during the activities, as well as the intermediate data files for each cancer type directly downloaded from NCI-GDC, and the script used to derive them: clinical_data.R.
• exercises/ includes a file for each class representing both the aggregated in-class exercises as well as additional supplemental exercises for practice
• solutions/ includes the solutions for all files in exercises/
• instructors.md includes information for instructors to facilitate teaching each lesson, including additional options if a participant can't install R, RStudio, or tidyverse on their computer.
• hackmdio.md is an archive of the interactive webpage used during lessons
• Information about use of R and RStudio at Fred Hutch is available on the Data Science Wiki