title: Robust test method for time-course microarray experiments.
abstract: BACKGROUND
  In a time-course microarray experiment, the expression level for each gene is observed across a number of time-points in order to characterize the temporal trajectories of the gene-expression profiles. For many of these experiments, the scientific aim is the identification of genes for which the trajectories depend on an experimental or phenotypic factor. There is an extensive recent body of literature on statistical methodology for addressing this analytical problem. Most of the existing methods are based on estimating the time-course trajectories using parametric or non-parametric mean regression methods. The sensitivity of these regression methods to outliers, an issue that is well documented in the statistical literature, should be of concern when analyzing microarray data.
  
  
  RESULTS
  In this paper, we propose a robust testing method for identifying genes whose expression time profiles depend on a factor. Furthermore, we propose a multiple testing procedure to adjust for multiplicity.
  
  
  CONCLUSIONS
  Through an extensive simulation study, we will illustrate the performance of our method. Finally, we will report the results from applying our method to a case study and discussing potential extensions.
authors.affiliation: Biostatistics and Bioinformatics Center, Samsung Cancer Research Institute, Samsung Medical Center, Seoul 137-710, Republic of Korea. insuk.sohn@samsung.com
authors.forename: Insuk
authors.initials: I
authors.lastname: Sohn
authors.forename: Kouros
authors.initials: K
authors.lastname: Owzar
authors.forename: Stephen L
authors.initials: SL
authors.lastname: George
authors.forename: Sujong
authors.initials: S
authors.lastname: Kim
authors.forename: Sin-Ho
authors.initials: SH
authors.lastname: Jung
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D000818:Animals; D001172:Arthritis, Rheumatoid / Q000235:genetics; D017173:Caenorhabditis elegans / Q000235:genetics; D003198:Computer Simulation; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D008875:Middle Aged; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D012044:Regression Analysis; D013997:Time Factors; D055815:Young Adult