Genome-wide association studies have greatly progressed understanding the genetic basis of disease over the past decade. These studies have typically used common single nucleotide polymorphisms (SNPs) on SNP chips. However they are unable to assess the contribution of complex copy number variation (CNV) to disease. This type of variation occurs when segments of genomic DNA from hundreds of base pairs to hundreds of kilobase pairs in length are deleted or duplicated in the human genome. However CNV can only be adequately genotyped by using read-depth approaches on whole genome sequences generated using high throughput approaches (such as Illumina). The aim of this project is to conduct a GWAS for CNV in gout using >3,000 whole genome sequences generated using an Illumina X10 facility. The project will require skills in bioinformatics, including a background in R code. Undergraduate experience in genetics and statistics would be beneficial, but not essential.