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  • 學位論文

親本-子代三元體家庭之穩健多變量相關檢定

Robust Multivariate Association Test Using Parent-Offspring Triad Families

指導教授 : 戴政
共同指導教授 : 張淑惠
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摘要


為了特徵化一個複雜疾病的遺傳機制,在以家庭為基礎的遺傳研究中,通常會收集多個相關的數量性狀,進行一個假定的基因與多性狀間之多變量相關性分析,來搜尋潛在的疾病基因。雖然這種多變量相關檢定方法相較於單變量相關檢定方法具有較佳的檢定力表現,但是當研究所探討的基因之遺傳模式(或稱作基因顯性程度)設定錯誤時,這些多變量相關檢定方法會遭遇到統計檢定力降低之風險。本論文的主要目的為利用親本-子代三元體家庭資料來發展一個穩健多變量相關檢定,首先將在隱性、可累加或顯性遺傳模式下建立最適多變量計分檢定,再以這些最適檢定來建立一個最大值型態的穩健多變量相關檢定。在模擬研究中,以本論文所提出的方法和現有的多變量方法進行型I錯誤率與檢定力之比較,模擬結果證實穩健多變量相關檢定在所有可能的遺傳模式下,確實表現出檢定力之穩健性。在實例分析中,以一個實際資料來說明本論文所提出的方法之應用性,分析結果顯示當處理多數量性狀時,穩健多變量相關檢定確實較穩健單變量相關檢定更具有檢定能力。

並列摘要


For characterizing the genetic mechanism of a complex disease multiple correlated quantitative traits are usually collected in a genetic study. On the basis of familial data, several multivariate tests have been proposed to investigate the association between the underlying disease genes and the multiple traits. Although these association tests may have better power performance than those univariate association tests, they suffer from loss of testing power when the genetic model (mode of inheritance) of the putative gene is misspecified. In this thesis we aim to develop a robust multivariate association test using parent-offspring triad data. We will first establish the optimal multivariate score test for the recessive, additive or dominant genetic model, based on these optimal tests a maximum-type robust multivariate association test is then proposed. Simulations are conducted to compare our proposed method with the existing multivariate methods on type I error rates and testing powers. The results show that the proposed robust test does manifest the robustness in testing power over all plausible genetic models. A practical data set is also applied to demonstrate the applicability of our proposed approach. The results suggest that the robust multivariate association test is more powerful than robust univariate association test when dealing with multiple quantitative traits.

參考文獻


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