title: Statistical tests for identifying differentially expressed genes in time-course microarray experiments.
abstract: BACKGROUND
  Microarray technology allows the monitoring of expression levels for thousands of genes simultaneously. In time-course experiments in which gene expression is monitored over time, we are interested in testing gene expression profiles for different experimental groups. However, no sophisticated analytic methods have yet been proposed to handle time-course experiment data.
  
  
  RESULTS
  We propose a statistical test procedure based on the ANOVA model to identify genes that have different gene expression profiles among experimental groups in time-course experiments. Especially, we propose a permutation test which does not require the normality assumption. For this test, we use residuals from the ANOVA model only with time-effects. Using this test, we detect genes that have different gene expression profiles among experimental groups. The proposed model is illustrated using cDNA microarrays of 3840 genes obtained in an experiment to search for changes in gene expression profiles during neuronal differentiation of cortical stem cells.
authors.affiliation: Department of Statistics, Seoul National University, Seoul, Korea. tspark@stats.snu.ac.kr
authors.forename: Taesung
authors.initials: T
authors.lastname: Park
authors.forename: Sung-Gon
authors.initials: SG
authors.lastname: Yi
authors.forename: Seungmook
authors.initials: S
authors.lastname: Lee
authors.forename: Seung Yeoun
authors.initials: SY
authors.lastname: Lee
authors.forename: Dong-Hyun
authors.initials: DH
authors.lastname: Yoo
authors.forename: Jun-Ik
authors.initials: JI
authors.lastname: Ahn
authors.forename: Yong-Sung
authors.initials: YS
authors.lastname: Lee
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D000818:Animals; D001483:Base Sequence; D002454:Cell Differentiation / Q000235:genetics; D002540:Cerebral Cortex / Q000166:cytology / Q000254:growth & development; D016000:Cluster Analysis; D020869:Gene Expression Profiling / Q000379:methods*; D018507:Gene Expression Regulation, Developmental / Q000235:genetics*; D008957:Models, Genetic; D015233:Models, Statistical; D008969:Molecular Sequence Data; D009419:Nerve Tissue Proteins / Q000235:genetics; D009474:Neurons / Q000166:cytology / Q000502:physiology; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D051381:Rats; D016415:Sequence Alignment / Q000379:methods*; D013234:Stem Cells / Q000166:cytology / Q000502:physiology
chemical_list: D009419:Nerve Tissue Proteins