Although genome wide association studies (GWAS) have considerably advanced our knowledge of the genetics of complex traits, they fail to account for the bulk of the overall heritability [1]. Structural variation, including copy number variants (CNVs), may account for some of the missing heritability, but a comprehensive study of the contribution of these variants to complex traits genetics is generally lacking. One of the main challenges of integrating CNVs into GWAS is the reliability of their assay, but improvements in genotyping platforms and the development of algorithms for the analysis of CNVs increasingly facilitate the investigation of the role of CNVs in disease susceptibility [2]. Given the effect of adjacent CNVs on SNP intensity data, early SNP arrays were designed with the consequence that assays from many CNV loci were excluded, but a newer generation of arrays have been implemented that combine SNP assays and copy number probes optimized for copy-number measurement for target regions of known CNVs [3]. New algorithms are also facilitating higher resolution maps of common CNVs (those that segregate at an allele frequency >5%).
