Diametrical clustering is a software that explicitly identifies anti-correlated clusters of genes. Our algorithm proceeds by iteratively (i) re-partitioning the genes and (ii) computing the dominant singular vector of each gene cluster; each singular vector serving as the prototype of a ‘diametric’ cluster. We empirically show the effectiveness of the algorithm in identifying diametrical or anti-correlated clusters. Testing the algorithm on yeast cell cycle data, fibroblast gene expression data, and DNA microarray data from yeast mutants reveals that opposed cellular pathways can be discovered with this method.
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I. S. Dhillon, E. M. Marcotte, U. Roshan,
“Diametrical Clustering for identifying anti- correlated gene clusters“,
Bioinformatics, 19, pp 1612-1619, 2003