Chapter 7: GWAS for complex traits#
For most of the remaining chapters, we will shift gears to focus on complex traits which can be controlled by genetic variation across many different regions of the genome.
In this chapter, we will give an introduction to genome-wide association studies (GWAS), one of the main techniques used to study the genetics of complex traits. In future chapters, we will explore applications downstream of GWAS including trait prediction (using polygenic risk scores) and interpretation (using fine-mapping).
For GWAS and other applications, we’ll generally consider traits in two categories:
Quantitative traits are those for which the phenotype can be described using a numerical value. e.g. height or LDL cholestrol.
Case/control traits are those for which we have just two possible phenotype values to compare (e.g. disease/no disease).
The techniques used for these two cases are similar but slightly different. We will explore both cases in this chapter. GWAS and downstream applications require a good understanding of p-values, and we will spend some time reviewing that concept.