htnani / genetic-data-analysis-1

RCC workshop, "Analysis of Genetic Data 1: inferring population structure."

Analysis of Genetic Data 1: Inferring Population Structure

Materials for the RCC workshop, "Analysis of Genetic Data 1: Inferring Population Structure".

Date: Tuesday, Feburary 13, 2018
Time: 2:00 pm to 4:30 pm
Location: Zar Room, John Crerar Library (OpenStreetMap)
Instructor: Peter Carbonetto

Introduction

During this short workshop, we will apply simple numeric techniques to investigate human genetic diversity and population structure from large-scale genetic data sets. We will use popular software tools such as PLINK and ADMIXTURE to prepare and analyze the "raw" genetic data, and we will use R to visualize the results of our analyses. While anyone who is curious about the "genomics revolution" may attend, this workshop is mainly intended to develop practical computing skills for graduate students and other researchers working with genetic data-concepts such as "genotype" and "allele frequency" will not be explained. We will practice "live coding" throughout, so please bring your laptop!

Prerequisites

This workshop assumes participants are already familiar with R and a UNIX-like shell environment. An RCC user account is recommended, but not required-temporary access to the RCC cluster will be available in class. All participants must bring a laptop with a Mac, Linux, or Windows operating system that they have administrative privileges on.

Other information

• This workshop attempts to apply elements of the Software Carpentry approach. See also this article. Please also take a look at the Code of Conduct, and the license information.

• To generate PDFs of the slides from the R Markdown source, run make slides.pdf in the docs directory. For this to work, you will need to to install the rmarkdown package in R, as well as the packages used in slides.Rmd. For more details, see the Makefile.

• See also the instructor notes.

Credits

These materials were developed by Peter Carbonetto at the University of Chicago. Thank you to Matthew Stephens for his support and guidance. Also thanks to David Reich and his lab for making a portion of the Affymetrix Human Origins data set available for public use.