Statistical analysis of a small set of time-ordered gene expression data using linear splines.
BACKGROUND
Recently, the temporal response of genes to changes in their environment has been investigated using cDNA microarray technology by measuring the gene expression levels at a small number of time points. Conventional techniques for time series analysis are not suitable for such a short series of time-ordered data. The analysis of gene expression data has therefore usually been limited to a fold-change analysis, instead of a systematic statistical approach.


METHODS
We use the maximum likelihood method together with Akaike's Information Criterion to fit linear splines to a small set of time-ordered gene expression data in order to infer statistically meaningful information from the measurements. The significance of measured gene expression data is assessed using Student's t-test.


RESULTS
Previous gene expression measurements of the cyanobacterium Synechocystis sp. PCC6803 were reanalyzed using linear splines. The temporal response was identified of many genes that had been missed by a fold-change analysis. Based on our statistical analysis, we found that about four gene expression measurements or more are needed at each time point.
De Hoon
M J L
MJ
Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639, Japan. mdehoon@ims.u-tokyo.ac.jp
Imoto
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S
Miyano
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D000465:Algorithms; D016000:Cluster Analysis; D000458:Cyanobacteria / Q000145:classification / Q000235:genetics*; D004269:DNA, Bacterial / Q000235:genetics; D020869:Gene Expression Profiling / Q000379:methods*; D005786:Gene Expression Regulation / Q000235:genetics*; D016013:Likelihood Functions; D016014:Linear Models; D008957:Models, Genetic; D015233:Models, Statistical; D015203:Reproducibility of Results; D018401:Sample Size; D012680:Sensitivity and Specificity; D016415:Sequence Alignment / Q000379:methods; D017422:Sequence Analysis, DNA / Q000379:methods*; D013045:Species Specificity; D013269:Stochastic Processes; D013997:Time Factors
D004269:DNA, Bacterial