Name: Analysis of Genetic Data 1: Inferring Population Structure
Start: 2023-02-07T14:00:00-06:00
End: 2023-02-07T16:00:00-06:00
Location: John Crerar Library - Kathleen A. Zar Room

Analysis of Genetic Data 1: Inferring Population Structure

Research Computing Center

John Crerar Library - Kathleen A. Zar Room

In this short workshop, we will apply basic numerical techniques such as principal components analysis (PCA) to investigate human genetic diversity and population structure from large-scale genetic data sets. We will investigate how genetic data sets are represented in computer files, and we will use command-line programs such as PLINK to prepare the “raw” genetic data for analysis. We will use R to perform the statistical analysis and visualize the results. The aim workshop is mainly intended to develop practical computing skills for researchers working with genetic data, including the use of simple command-line programs to inspect and manipulate the data files. Please be aware that concepts in genetics research (e.g., “genotype”, “allele frequency”) will not be explained.

Objectives: Workshop participants will: (1) work through the steps of a basic population structure analysis in human genetics, starting with the “raw” source data, and ending with a visualization of population structure estimated from the genetic data; (2) understand how genetic data sets are commonly represented in computer files; (3) use command-line tools such as PLINK to inspect and process genetic data; (4) use R to compute principal components from genetic data; and (5) learn through “live coding.”

Level: Intermediate.

Duration: 2 hours

Prerequisites: This hands-on workshop assumes participants are already familiar with R and a UNIX-like shell environment. An RCC user account is not required, but recommended.

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Analysis of Genetic Data 1: Inferring Population Structure

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Analysis of Genetic Data 1: Inferring Population Structure

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