Correcting the loss of cell-cycle synchrony in clustering analysis of microarray data using weights.
BACKGROUND
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)(t(2)/C(2))]--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.
Duan
Fenghai
F
Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT 06520-8034, USA.
Zhang
Heping
H
D000465:Algorithms; D001683:Biological Clocks / Q000502:physiology; D002453:Cell Cycle / Q000502:physiology*; D016000:Cluster Analysis; D020869:Gene Expression Profiling / Q000379:methods*; D015966:Gene Expression Regulation, Fungal / Q000502:physiology; D008957:Models, Genetic; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D012441:Saccharomyces cerevisiae / Q000166:cytology* / Q000502:physiology*; D029701:Saccharomyces cerevisiae Proteins / Q000235:genetics / Q000378:metabolism; D012680:Sensitivity and Specificity; D013997:Time Factors
D029701:Saccharomyces cerevisiae Proteins