【論】Thomas,2001,An efficient and robust statistica～

Jeffrey G.Thomas, James M.Olson, Stephen J.Tapscott, and Lue Ping Zhao,
An Efficient and Robust Statistical Modeling Approach to Discover Differentially Expressed Genes Using Genomic Expression Profiles
Genome Research Vol.11, Issue 7, 1227-1236, July 2001
[PDF]

・マイクロアレイの発現量データに基づく遺伝子抽出法の提案。教師付き学習法。Z-scoreにより遺伝子をランキング。
・データ：Leukemia data (27 ALL/11 AML) [Golub]
・結果：有意水準1％の条件下で、グループ間で発現量に差があると判定された141遺伝子を抽出（1と2）。
1.ALLよりAMLの方が高い発現量の遺伝子
2.AMLよりALLの方が高い発現量の遺伝子
3.AMLサンプル中、TPO（Thrombopoietin）に関連した遺伝子
4.AMLサンプル中、予後（生/死）間で異なる発現量の遺伝子
・比較法：t-tests, Wilcoxon rank sum statistics

・問題点「Cluster analysis is not a sensitive method for this type of study because it focuses on group similarities, not differences within each individual gene. Furthermore, clustering algorithms such as those listed above are also unable to take advantage of preexisting knowledge of the data, such as the sample groupings.」
・特性「This methodology makes no distributional assumptions about the data and accounts for high false-positive error rate resulting from multiple comparisons.」
・方法「In this work, we calculated the significance value (i.e., P-value) for each probe set using a modified Bonferroni's correction as proposed by Hochberg (Hochberg 1988) (see Methods for details).」
・特長「In contrast, the estimating equation technique we used to calculate Z-scores does not require any distributional assumptions or homogeneity of variances (see Methods for details).」
・方法「We propose a regression model for the expression level of the jth gene in the kth sample:
　Y_jk = δ_k + λ_k(a_j + b_jx_k) + ε_jk (1)
in which (a_j, b_j) are gene-specific regression coefficients, (δ_k,λ_k) are the sample-specific additive and multiplicative heterogeneity factors, respectively, and ε_jk is a random variable reflecting variation due to sources other than the one identified by the known covariate and the systematic heterogeneity between samples.」