Welcome to the website. This is a portfolio consists of notes in STAT494 (statistical genetics).
Statistical Genetics is a subject and field of study investigating how variation in genome associates people’s research of interests by statistical methods.
Here is an excerpt from the book <An Introduction to Statistical Genetic Data Analysis> (Mills, Barban, et.al (2020)) describing genetics data analysis background for us:
“Human genetic research is now relevant beyond biology, epidemiology, and the medical sciences, with applications in such fields as psychology, psychiatry, statistics, demography, sociology, and economics. With advances in computing power, the availability of data, and new techniques, it is now possible to integrate large-scale molecular genetic information into research across a broad range of topics.”
Through this portfolio, we will explore a tiny subfield of statistical genetics:Genome wide association studies (GWAS). It is one of the most popular statistical tools. The method investigates a type of genetic variants, called SNP (single-nucleotide polymorphism), and its associations with the trait of interest. The trait can be either binary (for example, if a person is affected by a disease), or quantitative (for example, body weight/ height).
In chapter 1, we will learn the context of Genome-wide association studies, and its basics. In chapter 2, we will explore the effect of population, ancestry and how that related to GWAS application and analysis.