Journal
GENOME BIOLOGY
Volume 4, Issue 5, Pages -Publisher
BMC
DOI: 10.1186/gb-2003-4-5-r34
Keywords
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Funding
- NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES [U24DK058813] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES [P42ES004908, P30ES006096] Funding Source: NIH RePORTER
- NIDDK NIH HHS [5U24DK058813-02] Funding Source: Medline
- NIEHS NIH HHS [P30 ES006096, P42 ES004908, ES04908-12, 2P30 ES06096-11] Funding Source: Medline
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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.
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