Introduction to R and the tidyverse

Welcome! In this 3-session workshop, we use real-world human RNA-seq data to introduce R data manipulation and visualization. Participants will get hands-on experience with coding in R and be introduced to tools in the R tidyverse. You do not need any prior experience in R or coding!

Materials

• Entire workshop

Each lesson

• 0: Setup and installation
• 1: Intro to R and RStudio
• 2: Data manipulation in dplyr and tidyr
• 3: Data visualization in ggplot

Instructor

Kim Dill-McFarland, PhD is a Senior Bioinformatician in the Div of Allergy and Infectious Diseases at the U of Washington. She received her PhD in microbiology from the U of Wisconsin-Madison. Kim now leads a team of bioinformaticians who use sequencing and other high-throughput techniques to research how the human immune system responds to diseases like tuberculosis, asthma, and COVID. Kim has been coding in R for more than 10 years and taught bioinformatics as an Instructor at the U of British Columbia as well as for the Carpentries and RLadies.

Additional resources

Local groups

• Rladies Seattle Not just for ladies! A pro-actively inclusive R community with both in-person and online workshops, hangouts, etc.
• Seattle useR Group

General R

• R cheatsheets also available in RStudio under Help > Cheatsheets
• The Carpentries for workshops on R, python, command line, git, and more! Introductory through intermediate content.
• EDUCE for R workshops using microbial ecology data. Intro R, tidyverse, reproducible research, and statistics.
• TidyTuesday A weekly plotting challenge
• R code club Dr. Pat Schloss opened his lab’s coding club to remote participation.

RNA-seq data analysis

• SEAsnake for processing fastq sequences to counts data used in this workshop
  • Software at https://github.com/BIGslu/SEAsnake
• limma for linear modeling (Chapter 15: RNA-Seq Data)
  • voom weights for correcting for sample and gene quality
• dream for paired sample designs
• kimma for flexible model design

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