APSC 5984/20816 Complex Trait Genomics

Spring 2020


Teaching assistant

Time and Location

Course Description

This course will cover quantitative genetic analysis of complex trait genomics with emphasis on the use of molecular markers spanning the entire genome. We will discuss statistical methodologies for connecting phenotypes with high-dimensional genomic information to better understand polygenic traits from both prediction and inference perspectives. Topics will include genomic relatedness, linkage disequilibrium, population stratification, genomic heritability, missing heritability, genome-wide association study, genomic prediction, causal inference, and statistical learning. We will use examples from the animal, plant, and human genetics literature. Additional topics will be briefly touched upon, including sequence data, gene expression, epigenetics, and bioinformatics. Homework assignments involve hands-on analysis of simulated and real genomic data available in public repositories. The course will use R/Bioconductor software for statistical computing tools.

Learning Objectives

After taking this course, the student will be able to:

Texts and Reading Materials

Lecture slides will be provided on the class website. There will be no required textbook.



Lectures will be delivered using a whiteboard and presentation slides.