## Fundamentals of Statistical Genetics

STA480 (**Undergraduate**) and STA2080
(**Graduate**)

### Winter 2018

### README FIRST

- This
**objective** of this undergraduate and graduate course is to "learn about statistical
methods for genetic analysis, whether to better analyze genetic data, or to pursue research in
methodology."

- The
**intended audience** are
- Undergraduate students: majored in statistics.
- Graduate students: majored in diverse disciplines beyond statistics and biostatistics.
- Others: post-doctoral fellows, analysts and investigators with mathematical statistics training at the undergraduate level.

- "We assume no formal training in genetics, [but] we assume familiarity with elementary
probability, statistical inference and methods".
The
** prerequisite** is
STA303-Methods of Data Analysis or equivalent. Having said that, we try to be as inclusive as possible: we welcome all students who are
interested in statistical genetics
even just out of scientific curiosities.

- The teaching will generally follow the
**textbook** by Laird and Lange:
The Fundamentals of Modern Statistical Genetics
(available via the UofT library), with additional materials from the instructor.

### GENERAL INFORMATION

- Time: Mondays 10am - 1pm.
- Location: TBA

- Instructor: Lei Sun (sun@utstat.toronto.edu)

- Instructor's Office Hour: half hour each before and after each session, i.e. 9:30-10am and 1-1:30pm.

- TA: TBA

- Format of instruction: lectures.

- Evaluation: in-class closed-book exams.

### COURSE SYLLABUS AND LECTURE NOTES

- Lecture notes and all other information will be posted on the UofT
Blackboard.

* Statistical genetics is an important data science research area with direct impact on
population health, and this course provides an INTRODUCTION to its concepts and fundamentals.
We start with an overview of genetic studies to have a general understanding of its goal and
study design. We then introduce the basic genetic terminologies necessary for the ensuing
discussion of the various statistical methods used for analyzing genetic data. The specific
topics include population genetics, principles of inheritance, likelihood for pedigree data,
aggregation, heritability and segregation analyses, map and linkage analysis,
population-based and family-based association studies and genome-wide association studies.
The flow of the content generally follows that of the "The Fundamentals of Modern Statistical
Genetics" by Laird and Lange, and additional materials will be provided. Participating
students do not need formal training in genetics, but they are expected to have statistical
knowledge at the level of STA303 - Methods of Data Analysis or equivalent. *