QUANTITATIVE METHODS TO MAP GENES FOR COMPLEX TRAITS

Rockefeller University, New York NY

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Abstract

The long-term goal is to develop novel analytical methods that will enable researchers to find sets of disease genes underlying complex traits. These methods make use of genetic linkage and linkage disequilibrium between markers and nearby disease genes and provide, for example, maximum likelihood estimates for the numbers and positions of disease genes. Results are expected to open the way to identifying susceptibility genes. Once such genes are found, there is hope that knowledge of their structure will lead to a deeper understanding of disease etiology and, thus, to the possibility of ameliorating or curing these traits. The three specific aims are 1) to apply the Ising model of statistical physics to linkage and disequilibrium analysis, 2) to investigate effects of pedigree errors on disequilibrium analysis, and 3) to implement methodology developed under this proposal in computer programs.