Instructor(s): Jinliang Yang
Number of Credit Hours: 3
Cross-listings: None
Prerequisites: AGRO 815A, 815B, and 815D, AGRO/ASCI 931, and STAT 802 or equivalent, or permission of the instructor.
Description: The goal of this course is to apply biometrical methods to connect the phenotypic traits with high-dimensional genomic data. After this class, students will have a better understanding of polygenic traits for both prediction (or plant breeding) and inference (for gene mapping) purposes.
Learning Outcomes/Course Objectives
Students in AGRO 932 will learn to process next-generation sequencing data and calculate statistics (i.e., Theta and Fst) to measure population differentiation, calculate breeding population means and variances, understand the best linear unbiased prediction and apply it to conduct genome-wide association study and genomic selection. Additionally, students will have the opportunity to provide relevant background information about the research objectives, to practice data visualization, and to appropriately judge others’ work and give useful feedback.