Chapter 12 A fast, furious overview of the tidyverse

Basically want to highlight why it can be so useful for bioinformatic data (and also some of the limitations with really large data sets).

(But, once you have whittled bams and vcfs down to things like GWAS results and tables of theta values, they dplyr is totally up for the job.)

A really key concept here is going to be the relational data model (e.g. tidy data) and how it is so much better for handling data.

A superpowerful example of this is provided by tidytree which allows one to convert from phylo objects to a tidy object: Shoot! that is so much easier to look at! This is a great example of how a single approach to manipulating data works so well for other things that have traditionally not been manipulated that way (and as a conseqence have been completely opaque for a long time to most people.)

Cool. I should definitely have a chapter on tidy trees and ggtree.

What I really want to stress is that the syntax of the tidyverse is such that it makes programming a relaxing and enjoying experience.