Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
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Linkage disequilibrium mapping is a process of inferring the disease gene location from observed associations of marker alleles in affected patients and normal controls. In reality, the presence of disease-associated chromosomes in affected population is relatively low (usually 10% or less). Hence, it is a challenge to locate these disease genes on the chromosomes. In this paper, we propose an algorithm known as LinkageTracker for linkage disequilibrium mapping. Comparing with some of the existing work, LinkageTracker is more robust and does not require any population ancestry information. Furthermore our algorithm is shown to find the disease locations more accurately than a closely related existing work, by reducing the average sum-square error by more than half (from 80.71 to 30.83) over one hundred trials. LinkageTracker was also applied to a real dataset of patients affected with haemophilia, and the disease gene locations found were consistent with several studies in genetic prediction.