This is an introductory R course intended for learners with no prior coding experience. It was initially put together the goal of helping introduce wet-lab researchers affected by university shutdowns during the spring of 2020 to learn the basics of programming in R, and borrows heavily from a class taught to NYU summer research students.

Table of Contents

  1. Intro R Course, Workshop 1: Introduction
    - downloading and installing R and Rstudio
    - learning your way around Rstudio
    - packages
    - simple math in R
  2. Intro R Course, Workshop 2: Variables, Types, and Functions
    - variables
    - types
    - basic functions
  3. Intro R Course, Workshop 3: Vectors
    - creating vectors (lists of things)
    - consecutive sequences of numbers
    - math with vectors
    - pulling specific elements out of vectors
    - vector types
  4. Intro R Course, Workshop 4: Missing values and Logical operations
    - creating, storing, and working with missing values
    - logical (boolean) types
    - using logical types to select data of interest
    - operations with logical data types
  5. Intro R Course, Workshop 5: Dataframes
    - formatting data for analysis and reading excel data into R dataframes
    - selecting rows and columns of interest
    - adding columns to dataframes
    - exporting data from R
    - performing operations on individual columns of data
  6. Intro R Course, Workshop 6: Plotting (with ggplot2)
    - plotting with base R
    - introduction to ggplot
    - combining multiple data representations in ggplot
    - changing the appearance of plots
    - organizing data according to “tidy” principles
    - easy, reproducible paper figures with ggplot
  7. Intro R Course, Workshop 7: Summarizing data and doing basic stats
    - subsetting data
    - summarizing your data
    - splitting data by categories to calculate stats
    - ttests, anova, linear models
    - resources for learning to do statistics in R
  8. Intro R Course, Workshop 8: Basics of programming, and simulation in biology (Part I)
    - conditional statements
    - simulating biological data (intro)
    - random number generation
    - writing your own functions
  9. Intro R Course, Workshop 9: Basics of programming, and simulation in biology (Part II)
    - simulating biological data (continued)
    - testing functions
    - loops
    - using simulations to plan experiments
    - additional resources