Course Description
Methods for analysis of genetic data, with an emphasis on gene mapping. Topics include quantitative genetics, covariance between relatives, estimation of genetic parameters, detection of genetic linkage in crosses and natural populations, association mapping, and QTL mapping. Emphasis on fitting models, estimating parameters, and making inferences based on genetic data.
Athena Title
STATIST GENETICS
Prerequisite
(STAT 6220 or STAT 4230/6230 or STAT 6315 or STAT 6320 or STAT 6420) and STAT 4510/6510
Semester Course Offered
Offered spring
Grading System
A - F (Traditional)
Course Objectives
Students will learn methods for statistical analysis of genetic data. The primary goal is to teach students to think statistically and mathematically in analyzing the relationship between genotypic variation and phenotypic variation. The emphasis is on taking a biological problem, translating it into a mathematical one via an appropriate set of assumptions, devising an appropriate hypothesis test and test statistics, and analyzing the results. Students will learn this thought process and gain experience in implementing many types of genetic data analysis, both by hand and by computer.
Topical Outline
Topics include basics of population genetics, quantitative genetics and partition of genetic variance, coancestry coefficients and covariance between relatives, detection of genetic linkage in crosses and in natural populations, numerical methods for estimation of genetic parameters, linkage disequilibrium, the transmission-disequilibrium test, case-control tests, genome-wide association studies, single-QTL mapping, interval QTL mapping, QTL mapping in natural populations, and expression QTLs.