Introduction to Bioinformatics and Computational Genomics

Week 9R

Everything after this point is statistics on tables. R is how the field does that, and it runs in your browser.

Questions this week answers

  • Almost everything in R is a vector. Why does that matter?
  • What is aes() doing that ggplot() is not?
  • How do you get a package you do not have?

By the end of this week you can

  • Create vectors and data frames and subset them
  • Read a tab-separated file into a data frame
  • Produce a plot with ggplot2 and say what aes() is doing
0 of 3 done

  1. What R is

    A free software environment for statistical computing and graphics. RStudio is the IDE most people use with it. Here, R itself is compiled to WebAssembly and runs in the browser tab, with no install.

    1 / 3

What should survive this week

  • Rows are observations and columns are variables. Every table in this course is a data frame, including the count table in week 10 and the OTU table in week 12.
  • ggplot() takes the data; aes() maps its columns onto visual properties. That mapping is the join between your table and what appears on screen.
  • install.packages() then library(). Here both run against WebAssembly builds of CRAN and Bioconductor, in your own browser tab.