Journal Article

Correcting the loss of cell-cycle synchrony in clustering analysis of microarray data using weights

Fenghai Duan and Heping Zhang

in Bioinformatics

Volume 20, issue 11, pages 1766-1771
Published in print July 2004 | ISSN: 1367-4803
Published online May 2004 | e-ISSN: 1460-2059 | DOI: https://dx.doi.org/10.1093/bioinformatics/bth169
Correcting the loss of cell-cycle synchrony in clustering analysis of microarray data using weights

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Motivation: Due to the existence of the loss of synchrony in cell-cycle data sets, standard clustering methods (e.g. k-means), which group open reading frames (ORFs) based on similar expression levels, are deficient unless the temporal pattern of the expression levels of the ORFs is taken into account.

Methods: We propose to improve the performance of the k-means method by assigning a decreasing weight on its variable level and evaluating the ‘weighted k-means’ on a yeast cell-cycle data set. Protein complexes from a public website are used as biological benchmarks. To compare the k-means clusters with the structures of the protein complexes, we measure the agreement between these two ways of clustering via the adjusted Rand index.

Results: Our results show the time-decreasing weight function—exp[−(1/2)(t2/C2)—]which we assign to the variable level of k-means, generally increases the agreement between protein complexes and k-means clusters when C is near the length of two cell cycles.

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Subjects: Bioinformatics and Computational Biology

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