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研究生：	莊佳叡 Chuang, Chia-Jui
論文名稱：	以不同統計方法比較生物微晶片資料之研究 On the Evaluation of Different Statistical Procedures for Microarray Data
指導教授：	馬瀰嘉 Ma, Mi-Chia
學位類別：	碩士 Master
系所名稱：	管理學院 - 統計學系 Department of Statistics
論文出版年：	2004
畢業學年度：	92
語文別：	英文
論文頁數：	65
中文關鍵詞：	生物微晶片、核糖雜交、基因表現量、變異數分析、群集分析、因素分析、標準化
外文關鍵詞：	ANOVA, Cluster analysis, Factor analysis, Normalization, Nucleotide Hybridization, Microarray
相關次數：	點閱：153 下載：10
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　　目前生物微晶片（microarray）發展相當迅速，但卻沒有出現一套統一的資料分析模式，本研究主要探討兩個方向：首先是介紹兩種常見到的生物微晶片實驗方式（雙螢光染色法、酵素呈色法），所獲得之基因表現量資料的不同，其次是利用統計方法對基因分群，目前已提出的方法有因素分析法和群集分析法。本文提出利用變異數分析方法來對基因分群，其優點為(1)不論基因數量多大都可以分析；(2)不會像因素分析資料多一些基因或少一些基因就改變分群結果；(3)不會因兩基因表現完全相同，使得因素負荷幾乎為0；(4)不像群集分析由樹形圖不易歸納哪些基因是同一群。接著對不同分群方法的優缺點以一組實際資料來做比較，最後利用模擬生成不同型態的資料並以誤判率比較不同分群方法下各群分類的不正確率，並且在各種情況下討論不同統計方法的使用時機。

　　The development of microarray is very fast at the time being, but a unified data analysis mode does not exist. This research is to study grouping of genes. The first thing is to introduce the two experiments of microarray (one is fluorescence, and
another is colormetry) and another thing is how to use statistics to group genes.
　　Presently, the factor analysis and cluster analysis are usually used to group genes. In this thesis, analysis of variance (ANOVA) is proposed to group genes. The advantages are: (1) It can be analyzed no matter how large the genes set is. (2) The amount
of the gene will not affect the result just as factor analysis does. (3) It will not cause the factor loading to be zero because of the two same gene presentations. (4) It is not like the cluster
analysis that is difficult to obtain the grouping result of the genes by dendrogam.
　　Next, the advantage and defect of different grouping methods are compared by a real data. Then, different ways are simulated to generate data, and then the incorrectness are compared among the different grouping methods by rate of erroneous judgment.
Finally, we discuss the usage opportunity of different statistic methods in every different situations.

Chapter 1 ..........................................1
1.1 Introduction ................................1
1.2 Microarray ...................................2
1.3 Motivation ...................................3
1.4 Structure ....................................4
Chapter 2 Microarray Principles and Literatures .....6
2.1 Fluorescence Criterion ......................6
2.2 Normalization of Fluorescence Criterion .....7
2.3 Colorimetry Criterion .......................8
2.4 Normalization of Colorimetry Criterion ......11
Chapter 3 Statistical Procedures .................12
3.1 Gene Expression ............................12
3.2 Factor Analysis ............................14
3.2.1 Factor Analysis Techniques ...............15
3.2.2 Example of 11 Genes (using data matrix A
model) ...............................15
3.2.3 Example of 11 Genes (using data matrix B
model) ................................16
3.2.4 Rotation ...............................18
3.2.5 Comments ...............................20
3.3 Cluster Analysis ............................21
3.3.1 Hierarchical Clustering ...............21
3.3.2 Nonhierarchical Clustering ..............23
3.3.3 Example of 11 Genes (using data matrix A
model) ................................24
3.3.4 Example of 11 Genes (using data matrix B
model) .................................25
3.3.5 Comments ...............................26
3.4 Analysis of Variance (ANOVA) .............27
Chapter 4 Analysis Result and Simulation ...........31
4.1 Analysis Result ............................31
4.1.1 Factor Analysis ..........................31
4.1.2 Cluster Analysis .........................33
4.1.3 ANOVA ...................................35
4.2 Simulation ................................37
4.3 Comment .................................40
Chapter 5 Conclusion ..........................42
References .......................................44
Appendix 1 Interaction Plot of 11 Genes .........45
Appendix 2 Compute the large dimension of data matrix
.................................................47
Appendix 3 The result of factor analysis .........51
Appendix 4 The result of cluster analysis ........55
Appendix 5 The result of ANOVA ...................59
Appendix 6 Parameters ...........................63
                                    

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damage-inducible gene gadd45 in xeroderma pigmentosum C cells
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校外：2004-06-16公開

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