English  |  正體中文  |  简体中文  |  Post-Print筆數 : 11 |  Items with full text/Total items : 88866/118573 (75%)
Visitors : 23563039      Online Users : 331
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/115381


    Title: 運用核糖核酸測序實驗資料以偵測有差異表現量之基因
    Authors: 薛慧敏
    Contributors: 統計學系
    Keywords: 錯誤發現率;負二項分配;過度離散;擬概似函數;核糖核酸測序實驗;基因差異性檢定
    Differential expression analysis;false discovery rate;Negative-Binomial;over-dispersion;pseudo likelihood estimation;RNA-Seq
    Date: 2014
    Issue Date: 2017-12-25 15:18:00 (UTC+8)
    Abstract: 已知核糖核酸測序實驗(RNA-Seq)較微陣列實驗(microarray)具備多項優勢,如可避免雜交過程所帶來的雜訊,故準確度較高,以及不受序列為已知的需求限制等。預期隨著實驗成本逐漸降低,核糖核酸測序實驗將逐漸受到歡迎並且被廣泛運用。本研究將針對運用該類實驗資料以偵測顯著差異基因的問題提出統計分析方法。已知所獲得的基因資料為計數型態(count data),在考慮其過度離散(over-dispersion)性質下,我們將以負二項(Negative Binomial)分配來配適資料。為了降低計算難度,將採用最大擬概似函數(maximum pseudo likelihood)估計法。在基因的差異顯著性檢定上,我們則採用外顯類組(phenotypic group)均數差之Wald檢定統計量。本研究透過電腦模擬以驗證所提出的方法,並且運用此方法在數組實際資料上以評估其實用性。
    Recently, the RNA-Seq experiment is developed for a high-throughput DNA sequencing method for mapping and quantifying the transcriptomes. The gene expression level obtained from a RNA-Seq experiment is of the count data type and is often fitted by a Negative-Binomial distribution to account for the over-dispersion. To identify the differentially expressed genes with a binary phenotypic response, we aim to develop a statistical test for comparing the means of two Negative-Binomial distributions. To ease the computational complexity, a maximum pseudo likelihood estimation (MPLE) is considered and the corresponding Wald’s test statistic is subsequently employed. Simulation studies are performed to justify the adequacy of the proposed test in comparison with existing methods. The applicability of the proposed method is demonstrated via the data analysis of some real example data sets.
    Relation: 執行起迄:2014/08/01~2015/08/31
    103-2118-M-004-004
    Data Type: report
    Appears in Collections:[統計學系] 國科會研究計畫

    Files in This Item:

    File Description SizeFormat
    103-2118-M-004-004.pdf4435KbAdobe PDF97View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback