In this project we will use Artificial Intelligence (AI) tools with whole-genome sequencing (WGS) data to: 1) Identify novel gene-phenotype associations 2) Use genetic data to predict phenotypes In genetic studies, traditionally a GWAS approach has been used, where each genetic variant is moulded separately in relation to its effect on a phenotype. With AI methods, many genetic variants can be investigated jointly, which allows for detection of non-linear and non-additive effects. In this project we will test the performance of different traditional ML and AI methods in relation to a large set of quantitative phenotypes but also in relation to simulated phenotypes