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 Schools and Departments > School of Business, Economics & Informatics > Computer Science and Information Systems |
| 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: | 02 Jul 2020 12:08 |
| URI: | http://eprints.bbk.ac.uk/id/eprint/2991 |
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