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.
Text (Publisher draft (refereed))
Available under License Creative Commons Attribution.
Download (1014Kb) | Preview
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.
|School or Research Centre:||Birkbeck Schools and Research Centres > School of Business, Economics & Informatics > Computer Science and Informatics|
|Date Deposited:||27 Jan 2011 16:17|
|Last Modified:||17 Apr 2013 12:33|
Archive Staff Only (login required)