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研究生：	廖姿淇 Liao, Tzu-chi
論文名稱：	微陣列資料之品質評估 Post-chip quality assessment for cDNA microarray data
指導教授：	詹世煌 Chan, Shih-Huang
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：	2007
畢業學年度：	95
語文別：	英文
論文頁數：	36
中文關鍵詞：	微陣列、MA-plot 、品質指標、晶片品質
外文關鍵詞：	quality index, microarray, array quality, MA-plot
相關次數：	點閱：57 下載：1
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查詢本校圖書館目錄查詢臺灣博碩士論文知識加值系統勘誤回報

隨著cDNA 微陣列生物科技的進步，人們可同時獲取數千個基因表現值。然而晶片製作過程中，品質易受系統性實驗誤差影響，進而降低資料準確性。近年來，微陣列晶片品質控管益受重視。本研究透過觀察M-A plot之函數關係，提出晶片品質衡量指標β1、σR'/σG'以及ρR'G'。若晶片計算之σR'/σG'高於標準值或ρR'G'低於標準值，則認定該晶片品質不佳。模擬及實際資料分析結果顯示，指標能有效區別晶片間的品質。進一步，由Roche and Durbin (2002) 所提出基因表現模型加以推導，得到控制晶片品質的重要因子σ2ηT、σ2ηC以及σ2ηS，實驗過程中設法降低σ2ηT、σ2ηC以及提高σ2ηS可有效改善晶片品質。

With the prominent advance of microarray technology, people can observe thousands of gene expressed values simultaneously. To have valid results, quality control on array data becomes a necessary and important step before analysis is performed. In this thesis, motivated by the M-A plot of Dudoit et al. (2002), quality indexes, β1、σR'/σG'and ρR'G'are proposed to assess the array quality. Simulation study shows that σR'/σG'and ρR'G'both have large influence on array quality. In practice, theses arrays with high σR'/σG'and low ρR'G'could be considered as outliers and be excluded from further analysis. Through the two color model suggested by Rocke and Durbin (2001), we find out that σ2ηT and σ2ηC, the multiplicative error terms unique to control and treatment group, affect σR'/σG'and ρR'G'the most, and hence the gene expressed value. People can improve the quality of microarray data by controlling σ2ηT and σ2ηC.

FIGURES.....................................................................................................................II
TABLES..................................................................................................................... III
CHAPTER ONE ..........................................................................................................1
INTRODUCTION........................................................................................................1
CHAPTER TWO .........................................................................................................3
QUALITY MEASURES FOR MICROARRAY DATA ...........................................3
2.1 QUALITY MEASURES AVAILABLE IN THE LITERATURE.............................................3
2.2 M-A PLOT .............................................................................................................5
2.3 RELATIONSHIP BETWEEN σR′/σG′、R G ρ ′ ′ AND LINEAR EFFECT β 1.................7
2.4 CURVILINEAR EFFECT β2
..................................................................................13
CHAPTER THREE...................................................................................................14
SIMULATION STUDY.............................................................................................14
3.1 LINEAR SETTING ..................................................................................................14
3.2 CURVILINEAR SETTING ........................................................................................16
3.3 SIMULATION RESULTS..........................................................................................17
3.3.1 Results for linear setting .............................................................................17
3.3.2 Results for curvilinear setting.....................................................................20
3.3.3 Effect of normalization................................................................................24
CHAPTER FOUR......................................................................................................27
EXAMPLES ...............................................................................................................27
4.1 MICROARRAY DATA.............................................................................................27
4.2 RESULTS FOR DATA ANALYSIS ..............................................................................28
CHAPTER FIVE .......................................................................................................32
CONCLUSION ..........................................................................................................32
REFERENCE.............................................................................................................35
                                    

1. Jones, L., Goldstein, D. R., et al. (2006). Assessment of the relationship between pre-chip and post-chip quality measures for Affymetrix GeneChip expression data. BMC Bioinformatics, 7:211.

2. Brettschneider, J., Collin, F., Bolstad, B. M., and Speed, T. P. (2006). Quality assessment for short oligonucleotide microarray data. Submitted to Technometrics.

3. Petri, A., Fleckner, J., and Matthiessen, M. W. (2004). Array-A-Lizer: A serial DNA microarray quality analyzer. BMC bioinformatics, 5:12.

4. Buness, A., Huber, W., et al. (2005). arrayMagic: two-colour cDNA microarray quality control and preprocessing. Bioinformatics, 21(4), 554-556.

5. Dudoit, S., Yang, Y. H., Speed, T. P., and Callow, M. J. (2002). Statistical Methods for Identifying Differentially Expressed Gene in Replicated cDNA Microarray Experiments. Statistica Sinica, 12, 111-139.

6. Rocke, D. M. and Durbin, B. (2001). A model for measurement error for gene expression arrays. Journal of Computational Biology, 8, 6, 577-569.

7. Li, C., Wong, W. H. (2001a). Model-based analysis of oligonucleotide arrays: Expression index computation and outlier detection. Proceedings of the National Academy of Science, 98, 31-36.

8. Li, C., Wong, W. H. (2001b). Model-based analysis of oligonucleotide arrays: Model validation, design issues and standard error applications, Genome Biology, 2, 1-11.

9. Gautier, L., el al. (2004). affy-Analysis of Affymetrix Genechip data at the probe level. Bioinformatics, 20, 307-315.

10. Hubbell, E., el al. (2002). Robust estimators for expression analysis, Bioinformatics, 18, 1585-1592.

校內：2008-08-13公開
校外：2008-08-13公開

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