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Genome Biol. 2003;4(5):R34. Epub 2003 Apr 25.

Clustering gene-expression data with repeated measurements.

Author information

1
Department of Microbiology, University of Washington, Seattle, WA 98195, USA. kayee@u.washington.edu

Abstract

Clustering is a common methodology for the analysis of array data, and many research laboratories are generating array data with repeated measurements. We evaluated several clustering algorithms that incorporate repeated measurements, and show that algorithms that take advantage of repeated measurements yield more accurate and more stable clusters. In particular, we show that the infinite mixture model-based approach with a built-in error model produces superior results.

PMID:
12734014
PMCID:
PMC156590
DOI:
10.1186/gb-2003-4-5-r34
[Indexed for MEDLINE]
Free PMC Article

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