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
收藏
页码：61 / 86
页数：26
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