Method published in Genome Research is designed to increase the accuracy of mapping by admixture linkage disequilibrium.
Researchers developed a novel computation method that they say is designed to better identify genomic regions harboring disease-susceptibility genes.
The approach uses mapping by admixture linkage disequilibrium (MALD). It looks for patterns of variation that are over-represented in groups with increased susceptibility to a particular disorder.
In the current study, scientists developed a new technique for MALD called expected mutual information. “Our novel approach extends previous methods by incorporating knowledge on population admixture, drawing a more precise picture of the mosaic of ancestries along an individual’s genome,” explains primary author, Sivan Bercovici from Technion-Israel Institute of Technology.
The scientists anticipate that this new method may lead to significant advances in the ability to isolate the genetic determinants of common diseases. “The convergence of the novel computational technologies provided in this manuscript with analysis and knowledge of the population genetic architecture of special populations of interest should greatly facilitate design and implementation of genome-wide mapping of susceptibility loci for clinical phenotypes of general importance in human health and disease,” explains coauthor Karl Skorecki, M.D, also from Technion-Israel Institute of Technology.
Besides investigators from Technion-Israel Institute of Technology, the study included researchers from Washington University. The paper was published in the March 18 edition of Genome Research.
