Abstract:
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Family-based association methods have shown great promise in detecting genetic factors for human diseases during the past decade. Yet, the successes have been restricted largely to simple Mendelian cases, because complex diseases such as diabetes, asthma, etc., usually involve multiple, interacting genetic determinants, which can be distributed widely across our genome. Current genome scans for the susceptibility loci of complex diseases, involving hundreds of markers, usually carry out up to thousands of marker-wise tests, which fail to detect the possible interactions among the disease genes, and the significance is also difficult to establish, due to the moderate sample size and the effects from multiple comparisons. In this paper, we propose a haplotype-based statistic, haplotype transmission association (HTA), which can be proven a measure of the amount of linkage/linkage disequilibrium information contributed by each marker. Using screening based on the properties of HTA, a large set of candidate markers can be reduced to a small set of "important" ones. The resulting marker set is more informative, and further detailed studies carried out on it will be more cost-efficient.
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