From Modelling to Visualization

S. Biffani
November 20, 2017

Who I am

Quantitative Geneticist in Animal Science

Linear Model

Me & R

  • 1996 SAS

  • 2005 SAS + Python

  • 2009 SAS + Python + R

R studioggplottidyverseshiny

Principal Component Analysis

Principal component analysis (PCA) is a technique used to emphasize variation and bring out strong patterns in a dataset.

It's often used to make data easy to explore and visualize.


The beauty of data visualization

…And if you're navigating a dense information jungle, coming across a beautiful graphic or a lovely data visualization, it's a relief, it's like coming across a clearing in the jungle.

David McCandless - data journalist and information designer

My Example

  • Rabbit Fertility data
  • 19 fertility parameters in individuals classified in HIGH & LOW fertility
  • 91 predictors
pc <- princomp(cor(var1), cor=TRUE, scores=TRUE)