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• W129252456 abstract "OF DISSERTATION Genetic Association Testing of Copy Number Variation Copy-number variation (CNV) has been implicated in many complex diseases. It is of great interest to detect and locate such regions through genetic association testings. However, the association testings are complicated by the fact that CNVs usually span multiple markers and thus such markers are correlated to each other. To overcome the di culty, it is desirable to pool information across the markers. In this thesis, we propose a kernel-based method for aggregation of marker-level tests, in which rst we obtain a bunch of p-values through association tests for every marker and then the association test involving CNV is based on the statistic of p-values combinations. In addition, we explore several aspects of its implementation. Since p-values among markers are correlated, it is complicated to obtain the null distribution of test statistics for kernel-base aggregation of marker-level tests. To solve the problem, we develop two proper methods that are both demonstrated to preserve the family-wise error rate of the test procedure -a permutation-based approach and a correlation-base approach. Many implementation aspects of kernel-based method are compared through the empirical power studies in a number of simulations constructed from real data involving a pharmacogenomic study of gemcitabine. In addition, more performance comparisons are shown between permutation-based and correlation-based approach. We also apply those two approaches to the real data. The main contribution of the dissertation is the development of marker-level association testing, a comparable and powerful approach to detect phenotype-associated CNVs. Furthermore, the approach is extended to high dimension setting with high e ciency." @default.
• W129252456 created "2016-06-24" @default.
• W129252456 creator A5017624903 @default.
• W129252456 date "2014-01-01" @default.
• W129252456 modified "2023-09-24" @default.
• W129252456 title "Genetic Association Testing of Copy Number Variation" @default.
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• W129252456 hasPublicationYear "2014" @default.
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