【論】Cope,2004,A benchmark of Affymetricx GeneChip～

Leslie M. Cope, Rafael A. Irizarry, Harris A. Jaffee, Zhijin Wu and Terence P. Speed
A benchmark for Affymetrix GeneChip expression measures
Bioinformatics. 2004 Feb 12;20(3):323-31.
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・Affymetrix社製GeneChipのデータ生成法を比較し、各方法の特性を明らかにする。結果はDilution studyとSpike-in studyのBenchmark dataとして応用する。
・データ
1.The dilution study by GeneLogic
2.The spike-in study by Affymetrix
・解析ソフト
1.Affymetrix software
2.R + Bioconductor
・データ生成法
1.MAS5.0
2.dChip
3.RMA(robust multi-array analysis)
4.RMA(Not multi-array)
5.RMA(Not robust)
6.RMA(MM as PM)
・評価法（グラフ）
1.MA plot
2.Variance across replicates plot
3.Sensitivity of expression ratios to total quantity of RNA plot
4.Observed expression versus nominal expression plots
5.ROC curves
6.Observed fold-change versus nominal fold-change plots
7.Predicted variability plot
・実験
その1.データ生成法1～4を比較
その2.データ生成法4～6を比較

・ROCとは「Receiver Operator Charasteristic (ROC) curves offer a graphical representation of both specificity and sensitivity for such a rule. ROC curves are created by plotting the true positive (TP) rate (sensitivity) against false positive (FP) rate (1-specificity) obtained at each possible threshold value.」
・目的「This is because our aim is the comparison of bias and variance of measurement processes, not algorithms for the specific task of identifying defferential expression.」

・キーワードである「Dilution study」と「Spike-in study」が、何のことやらわからん。

《チェック論文》
・Irizarry,R.A., Bolstad, B.M., Collin,F., Cope,L.M., Hobbs,B. and Speed,T.P. (2003b) Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Res., 31, e15.
・Workman,C., Jensen,L.J., Jarmer,H., Berka,R., Gautier,L., Nielsen,H.B., Saxild,H., Nielsen,C., Brunak,S. and Knudsen,S. (2002) A new non-linear normalization method for reducing variability in DNA microarray experiments. Genome Biol., 3, research 0048.