Much of our present knowledge of the relationship between genotype and disease comes from statistical studies of the correlation between particular genetic variants and the likelihood of a specific disease. Linkage analysis, which tracks the transmission pattern of genetic markers within a pedigree family, has been successful in identifying over one thousand human monogenic disease genes [1]. On the other hand, there has so far been less success with common human diseases, such as hypertension, Alzheimer's, asthma and cancer. Susceptibility to these is affected by multiple genes, as well as environmental factors. The risk from any single genetic variant is low, so that linkage analysis sample sizes are usually too small to provide statistically significant disease/genotype relationships. Association studies, based on analysis of genetic differences, particularly SNPs, between those with and without a disease in a broader population, are more powerful for detecting such low signals. Approximately 10 million human SNPs have so far been identified [2]. Currently, association studies depend on choosing a subset of these which includes those influencing the probability of disease, or that are in linkage
