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 NFkappaB and the unfolded protein response in certain B-cell lymphomas.
journal_name
Genome Bioljournal_title
Genome biologyauthors
Swift S,Tucker A,Vinciotti V,Martin N,Orengo C,Liu X,Kellam Pdoi
10.1186/gb-2004-5-11-r94keywords:
subject
Has Abstractpub_date
2004-01-01 00:00:00pages
R94issue
11eissn
1474-7596issn
1474-760Xpii
gb-2004-5-11-r94journal_volume
5pub_type
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