标题: 离群值比例之基因分析
Outlier Proportion Based Gene Expression Analysis.
作者: 刁滢洁
Tiao, Ying-Chieh
陈邻安
Chen, Lin-An
统计学研究所
关键字: 离群值比例;基因分析;Outlier Proportion;Gene Expression Analysis
公开日期: 2009
摘要: 藉由侦测病体样本中的离群值而找出具有影响力的基因已是一种非常新且重要的基因分析方法。透过离群和或是离群平均可以侦测出离群资料中的集中趋势是否有所改变,但是却无法侦测出偏度等其它特征量数。因此,我们希望可以提供一个容易实行且有较高检定力的统计检定,以作为基因分析的另一项替代选择方法。我们将提出离群值比例的观点,以离群值比例的近似分配为基础,发展出一项统计检定。此外,我们也将更进一步地比较离群值比例和离群平均两者的检定力表现。而为了避免估计尾端机率点的密度函数之困难,进而造成检定力较低的缺点,因此我们将采用经验分位数当作切点。
Discovering the influential genes through the detection of outliers in samples of disease group subjects is a very new and important approach for gene expression analysis. The outlier sum or outlier mean technique can detect the shift in central tendency for the outlier data but not other
characteristics such as spreadness or others for the outlier data. It is desired to provide a test that is easy to implement and efficient in power performance as an alternative tool for gene expression analysis. We propose the concept of outlier proportion for developing a test based on asymptotic distribution of this statistics. We further compare it with the outlier mean for their power performances. To avoid the inefficiency in estimating densities at tail quantiles involved in estimation of outlier proportion variance, we further consider applying the empirical quantile as the cutoff point for an
alternative outlier proportion based test which shows satisfactory role in gene expression analysis from the point of power performance.
URI: http://140.113.39.130/cdrfb3/record/nctu/#GT079726502
http://hdl.handle.net/11536/45231
显示于类别:Thesis


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