Programming Resources: R

Learn R in the R Studio console!

This is an introduction to R programming class from the UCSF Library. It assumes no prior experience with R programming.

This covers similar concepts to "Introduction to R Programming" with additional topics such as data visualization and machine learning.

This is a hands-on workshop that covers how to use ggplot2 for common visualizations using the R programming language. It is not an introductory R programming workshop.

In this workshop, we will use R to perform some common statistical analyses. Although this is not an introduction to R programming or statistics, this workshop is ideal for those who are just starting to use R for data analysis.

In this workshop, we will provide a brief review of the concepts underlying power and sample size analysis. Following this, we will use R for hands-on programming practice with power and sample size calculations for several different types of analyses, including parametric and nonparametric tests using both analytical and simulation approaches.

This is a hands-on workshop that covers how to describe single variables and test for relationships between two variables using the R programming language. It is not an introductory R programming workshop.

This is a 2-part hands-on workshop that covers how to build common regression models (logistic & linear regression, survival analysis) using the R programming language, and how to visualize the results. It is not an introductory R programming workshop.

In this workshop, we will use R to analyze DNA variants from Variant Call Format files to identify those likely to have a functional impact. It is intended for those with intermediate R programming skills.

This workshop is intended for individuals who are already comfortable with R programming and who are interested in learning to use R for standard RNA-Seq analyses. We will take you through a complete RNA-Seq workflow using R Bioconductor packages.

In this workshop, we will demonstrate how to process and analyze single cell RNA-seq data using R Bioconductor packages, focusing primarily on Seurat. It is intended for those with intermediate R programming skills who are familiar with the biological concepts of single cell RNA-seq.

In this course, you will learn how to write your own R packages. We will start by demonstrating the basic steps of developing and publishing an R package. You will then have time to practice adding new features and getting packages ready for submission to CRAN.

R4DS teaches you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it.

A delightful series of tutorials introducing statistics in R with fun illustrations and activities.