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※ [本文轉錄自 NCTU-STAT96G 看板] 作者: pael (就是喜歡) 看板: NCTU-STAT96G 標題: [轉錄]演講公告 時間: Thu Oct 11 21:47:15 2007 ※ [本文轉錄自 NTHU_STAT96 看板] 作者: allen1985 (我要低調 拯救形象) 看板: NTHU_STAT96 標題: 演講公告 時間: Tue Oct 2 16:52:09 2007 清華大學、交通大學 統 計 學 研 究 所 專 題 演 講 題 目: The Effects of Population Stratification and Misclassification in Studies of Gene-Environment Interactions 主講人: 鄭光甫教授 (中國醫藥大學生物統計中心) 時 間: 96年10月12日(星期五)10:40 - 11:30 (上午10:20-10:40茶會於統計所821室舉行) 地 點: 清大綜合三館837室 Abstract Population stratification (confounding by ethnicity) and misclassification of genotype may cause the usual tests in case-control studies producing spurious gene-disease associations. To control for the resulting bias, several powerful approaches have been proposed using unlinked markers. However, the effects of population stratification and misclassification of genotype and environmental exposure in studies of gene-environment interactions are still not clear. In this paper, we quantify the effects of population stratification and misclassification in case-control and case-only studies under general conditions. We also present two conditions under which the effect of population stratification and/or misclassification does not exist in case-control or case-only studies of gene-environment interactions. The two conditions are: (1) genotype and environmental exposure are conditionally independent given stratification variable, and (2) environmental exposure and stratification variable are conditionally independent given genotype. We conducted a simulation study, using parameter values from real examples, to compare the performance of different tests for gene-environment interactions. Our results show that under the given simulation conditions, case-only approach for studying gene-environment interactions is the most powerful method, which is not only insensitive to population stratification and misclassification but also has the best performance in power. 敬請公佈 歡迎參加 -- ※ 發信站: 批踢踢實業坊(ptt.cc) ◆ From: 125.226.160.158
pael:借轉,謝謝! 10/11 21:46
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mangogogo:借轉 謝謝^^~ 10/11 22:01
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