Heart disease, diabetes and other complex diseases involve genes that combine with lifestyle and environmental factors to increase disease susceptibility. To find the genetic factors that influence disease outcomes, researchers have begun using haplotypes – sets of closely linked genetic variants inherited together as a unit. However, the use of haplotypes introduces its own complexities, including uncertainty in haplotype measurement, handling of rare haplotypes and the optimal length of haplotypes to examine. By incorporating the genetic relatedness of haplotypes into statistical estimation, Kelly Burkett hopes to address these points to more effectively predict the effects of haplotypes on disease outcomes. The methods will not only enable researchers to identify genetic risk factors but also the connections between genetic and non-genetic factors, such as lifestyle, environmental and occupational risks. The identification of such risk factors is hoped to eventually lead to improved disease treatment and prevention by highlighting new drug targets and lifestyle modifications for those with increased disease susceptibility.