Plaid models for gene expression data

被引：4

作者：

Lazzeroni, L

Owen, A

机构：

[1] Stanford Univ, Sch Med, Dept Hlth Res & Policy, Div Biostat, Stanford, CA 94305 USA

[2] Stanford Univ, Dept Stat, Stanford, CA 94305 USA

来源：

STATISTICA SINICA | 2002年 / 12卷 / 01期

关键词：

microarrays; SVD; transposable data; unsupervised learning;

D O I：

暂无

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Motivated by genetic expression data, we introduce plaid models. These axe a form of two-sided cluster analysis that allows clusters to overlap. Plaid models also incorporate additive two way ANOVA models within the two-sided clusters. Using these models we find interpretable structure in some yeast expression data, as well as in some nutrition data and some foreign exchange data.

引用

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页码：61 / 86

页数：26

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