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    Title: 核糖核酸測序實驗資料的維度縮減在基因集分析的運用
    Other Titles: Dimension Reduction in the Rna-Seq Data: Application to the Gene Set Analysis
    Authors: 薛慧敏
    Contributors: 統計學系
    Date: 2013
    Issue Date: 2015-07-28 17:14:40 (UTC+8)
    Abstract: 近來核糖核酸測序實驗(RNA-Seq)逐漸受到歡迎,本計晝主要研究目的為核糖 核酸測序實驗資料的特定基因集分析(gene set analysis)。針對大型資料(big data),維 度縮減(dimension reduction)為重要的工作,我們將運用適當的維度縮減方法在統計 分析中。我們考慮由Cook與Weisberg於1991年所提出的分段平均變異估計法 (Sliced average variance estimation, SAVE),該方法已被證明在多元常態分配中有好 的理論性質。但由於核醣核酸測序實驗產生的資料本質為計數型態,一般多以卜瓦 松(Poisson)或負二項(Negative Binomial)分佈來配適其表現量,在此計晝中,我們將 尋求適當的轉換方法,期望將原始資料轉換成服從多元常態分配。特定基因集資料 經過轉換後,則可進行維度縮減。針對二元型態的外顯因子,透過經縮減的資料, 我們將計算該基因集的最大接受者操作特徵函數之完整或部分線下面積(AUC, pAUC),以此來評估該基因集與外顯因子的相關程度。我們將運用我們的方法在實 際資料上,以判斷其實用性。另外也將透過電腦模擬以驗證該方法。
    Relation: 計畫編號NSC102-2118-M004-006
    Data Type: report
    Appears in Collections:[Department of Statistics] NSC Projects

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