【論】Baldi,2001,A Bayesian framework for the analys～

Pierre Baldi and Anthony D.Long
A Bayesian framework for the analysis of microarray expression data: regularized t-test and statistical inferences of gene changes
Bioinformatics Vol.17 no.6 2001 Pages 509-519
[PDF][Web Site]

・ベイズ統計のマイクロアレイ解析への応用。
・1.Bayesian approach 2.simple fold approach 3.straight t-test　を比較。
・紹介されている処理はR用のソフトウェア、Cyber-Tで利用可能（http://visitor.ics.uci.edu/genex/cybert/）。

・問題点「Current methods are unsatisfactory due to the lack of a systematic framework that can accommodate noise, variability, and low replication often typical of microarray data.」
・目的「Our goal here is to develop a general Bayesian statistical framework for the analysis of array data.」
・アレイデータ解析の三段階「Gene expression array data can be analyzed on at least three levels of increasing complexity. First, the level of single genes, where one seeks to establish whether each gene in isolation behaves differently in a control versus a treatment situation. The second level considers gene combinations, where clusters of genes are analyzed in terms of common functionalities, interactions, co-regulation, and so forth. The third level attempts to infer the underlying regulatory regions and gene/protein networks that ultimately are responsible for the patterns observed.」
・ベイズの定理「Bayes theorem: P(M|D) = P(D|M)P(M)/P(D), where P(D|M) is the data likelihood and P(M) is the prior probability capturing any background information one may have.」

・"ベイズ統計"の何たるかがわかってないので、全く歯が立たない。