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Consensus clustering and functional interpretation of gene-expression data

Swift, S. and Tucker, A. and Vinciotti, V. and Martin, Nigel and Orengo, C.A. and Liu, X. and Kellam, P. (2004) Consensus clustering and functional interpretation of gene-expression data. Genome Biology 5 (11), ISSN 1465-6906.

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Abstract

Microarray analysis using clustering algorithms can suffer from lack of inter-method consistency in assigning related gene-expression profiles to clusters. Obtaining a consensus set of clusters from a number of clustering methods should improve confidence in gene-expression analysis. Here we introduce consensus clustering, which provides such an advantage. When coupled with a statistically based gene functional analysis, our method allowed the identification of novel genes regulated by NFκB and the unfolded protein response in certain B-cell lymphomas.

Metadata

Item Type: Article
School: Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
Research Centres and Institutes: Structural Molecular Biology, Institute of (ISMB), Birkbeck Knowledge Lab
Depositing User: Administrator
Date Deposited: 27 Jan 2011 16:17
Last Modified: 24 Jul 2025 04:21
URI: https://eprints.bbk.ac.uk/id/eprint/2991

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