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The completion of the Human Geneome Project in 2003 ushered in a new era of genomics. It its wake other international projects sought to build on the foundations of the reference genome. The International HapMap Project (HapMap), launched in 2003, set its sights on determining the variability between individuels by genotyping single nucleotide polymorphisms (SNPs) throughout hundreds of human genomes. Upon it's completion in 2005 the project had genotyped 1.6 millions SNPs in 1184 invididuels from 11 different ethnic populations [http://hapmap.ncbi.nlm.nih.gov] \cite{20811451}. For the first time it was possible to map the haplotype structure of the human genome and calculate linkage disequalibrium (LD) between SNPs. Using this information, the genetic variability within a 'gene of interest' could now be captured with a smaller number of 'tag-SNPs', vastly reducing cost and time. *However, it was when commercial microarray providers, Illumina and Affymetrix, designing high-throughput arrays of non-redundant SNPs capturing the genetic variability across the human genome that the the technology was born* - needs work.  More recently the 1000 Genomes Project (1KP) has provided a much finer map of human genetic variation. The combination of genome (7.4x) and deep exome (65.7x) sequencing in over 2500 samples has enabled a more comprehensive catalouge of over 88 million variant sites to be discovered, including rare and structural changes. This has has several important applications, including designing arrays of rarer coding changes ('exome chips') and as a database to exclude pathogenic variants. However, it is the ability impute GWAS datasets with a larger set of variants using 1KP reference hapolotypes that has been a game change \cite{26432245}  . The seminal GWAS was published in 2007 by the Wellcome Trust Case Controlm Consortium (WTCCC) \cite{17554300}. With a series of 3,000 healthy controls and 14,000 combined cases across seven common human disease, the consortium identified 24 novel genetic associations with diabetes (types I & II), coronary artery disease, Crohn's disease, rheumatoid arthritis and bipolar disorder. In order to obtain a sufficiently large case-control series for GWAS, previously independent genetic genetic began to form large consortia and user there combined resources to unearth genetic risk factors for complex human diseases. The era of the GWAS had arrived.