Quantitative Methods for Linkage and Associated Studies

Princeton University, Princeton NJ

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Abstract

The goals of this project are to develop improved quantitative methods for analysis of[unreadable] genetic data gathered in family and population studies of complex diseases, and to[unreadable] implement these methods in easy to use computer programs. Such methods are required to[unreadable] unravel the complex genetic basis of common diseases. New methods will be developed for[unreadable] the following tasks: Faster and more memory-efficient multi-point analysis of both[unreadable] qualitative and quantitative traits in arbitrarily large and complex pedigrees; Testing[unreadable] haplotypes for association with disease; Multipoint linkage disequilibrium analysis;[unreadable] SNP-based association studies. New technologies are allowing collection of increasingly[unreadable] large amounts of polymorphism data on common disease samples drawn from both families and[unreadable] populations. The new methods developed for this project will enable efficient use of these[unreadable] data, and will improve researchers' ability to detect true genetic effects on disease[unreadable] susceptibility and to distinguish them from statistical noise. The computer programs will[unreadable] be freely distributed to the broader research community to ensure that the methods are[unreadable] widely and readily applied to real-world problems.