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- Title
Validating clustering for gene expression data.
- Authors
Yeung, K Y; Haynor, D R; Ruzzo, W L
- Abstract
Many clustering algorithms have been proposed for the analysis of gene expression data, but little guidance is available to help choose among them. We provide a systematic framework for assessing the results of clustering algorithms. Clustering algorithms attempt to partition the genes into groups exhibiting similar patterns of variation in expression level. Our methodology is to apply a clustering algorithm to the data from all but one experimental condition. The remaining condition is used to assess the predictive power of the resulting clusters-meaningful clusters should exhibit less variation in the remaining condition than clusters formed by chance.
- Publication
Bioinformatics (Oxford, England), 2001, Vol 17, Issue 4, p309
- ISSN
1367-4803
- Publication type
Journal Article
- DOI
10.1093/bioinformatics/17.4.309