Finding gene clusters for a replicated time course study.
BACKGROUND
Finding genes that share similar expression patterns across samples is an important question that is frequently asked in high-throughput microarray studies. Traditional clustering algorithms such as K-means clustering and hierarchical clustering base gene clustering directly on the observed measurements and do not take into account the specific experimental design under which the microarray data were collected. A new model-based clustering method, the clustering of regression models method, takes into account the specific design of the microarray study and bases the clustering on how genes are related to sample covariates. It can find useful gene clusters for studies from complicated study designs such as replicated time course studies.


RESULTS
In this paper, we applied the clustering of regression models method to data from a time course study of yeast on two genotypes, wild type and YOX1 mutant, each with two technical replicates, and compared the clustering results with K-means clustering. We identified gene clusters that have similar expression patterns in wild type yeast, two of which were missed by K-means clustering. We further identified gene clusters whose expression patterns were changed in YOX1 mutant yeast compared to wild type yeast.


CONCLUSIONS
The clustering of regression models method can be a valuable tool for identifying genes that are coordinately transcribed by a common mechanism.
Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA. qinl@mskcc.org.
Li-Xuan
LX
Qin
Linda
L
Breeden
Steven G
SG
Self
D000465:Algorithms; D002453:Cell Cycle / Q000235:genetics; D018797:Cell Cycle Proteins / Q000172:deficiency / Q000235:genetics; D016000:Cluster Analysis; D020869:Gene Expression Profiling / Q000379:methods / Q000706:statistics & numerical data*; D015966:Gene Expression Regulation, Fungal; D055786:Gene Knockout Techniques; D005800:Genes, Fungal; D018398:Homeodomain Proteins / Q000235:genetics; D005810:Multigene Family; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods / Q000706:statistics & numerical data*; D010363:Pattern Recognition, Automated; D012044:Regression Analysis; D012097:Repressor Proteins / Q000172:deficiency / Q000235:genetics; D029701:Saccharomyces cerevisiae Proteins / Q000235:genetics; D013997:Time Factors
D018797:Cell Cycle Proteins; D018398:Homeodomain Proteins; D012097:Repressor Proteins; D029701:Saccharomyces cerevisiae Proteins; C080459:Yox1 protein, S cerevisiae