※ [本文轉錄自 NCTU-STAT96G 看板] 作者: cyz ( ) 看板: NCTU-STAT96G 標題: 1130演講＠交大統研所 時間: Wed Nov 21 13:25:39 2007 國立交通大學、清華大學 統計學研究所 專題演講 題　目：Evolution of Multiple Hypothesis Testing in Genetic Studies 主講人：蕭朱杏教授 (臺灣大學公共衛生學系) 時　間：96年11月30日(星期五)上午10:40-11:30 (上午10:20-10:40茶會於交大統計所428室舉行) 地　點：交大綜合一館427室 Abstract The recent advancement of biotechnology and the announcement of human genome have made the genetic association studies possible and easier to conduct. It also opens a new era in statistical sciences. The challenge of testing simultaneously a large number of hypotheses in genomics has been receiving considerable attention. It differs from the traditional multiple comparisons performed after a significant overall test. The small sample size, the large number of tests, and the correlation within data have made the issue even more complex. Statisticians have tackled the problem from different angles. Several algorithms focused on selection of ordered p-values via a bottom-up or top-down procedure, possibly under a controlled false discovery rate (FDR); while some recommended a multi-stage procedure using data from different subjects at every stage, or starting with a smaller group of individuals and then augmenting the data in each of the rest stages. Recently, several researchers proposed to replace the standard null normal distribution with other dispersed ones for the statistics under the null or the alternative hypothesis. Alternatively, the use of Bayesian mixture model considers simultaneously the character of classifying the hypotheses and the general dependence among data. In this talk, we will discuss briefly the current development, introduce the Bayesian approach, and highlight some possible directions. (This is a joint work with Yu-Chung Wei and Shu-Hui Wen) 敬 請 公 佈 歡 迎 參 加 --

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