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dc.contributor.author Sohn, I
dc.contributor.author Owzar, K
dc.contributor.author George, SL
dc.contributor.author Kim, S
dc.contributor.author Jung, SH
dc.coverage.spatial England
dc.date.accessioned 2011-06-21T17:27:56Z
dc.date.issued 2010-07-22
dc.identifier http://www.ncbi.nlm.nih.gov/pubmed/20649954
dc.identifier 1471-2105-11-391
dc.identifier.citation BMC Bioinformatics, 2010, 11 pp. 391 - ?
dc.identifier.uri http://hdl.handle.net/10161/4334
dc.description.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.
dc.format.extent 391 - ?
dc.language ENG
dc.language.iso en_US en_US
dc.relation.ispartof BMC Bioinformatics
dc.relation.isversionof 10.1186/1471-2105-11-391
dc.subject Adult
dc.subject Aged
dc.subject Aged, 80 and over
dc.subject Algorithms
dc.subject Animals
dc.subject Arthritis, Rheumatoid
dc.subject Caenorhabditis elegans
dc.subject Computer Simulation
dc.subject Gene Expression Profiling
dc.subject Humans
dc.subject Middle Aged
dc.subject Oligonucleotide Array Sequence Analysis
dc.subject Regression Analysis
dc.subject Time Factors
dc.subject Young Adult
dc.title Robust test method for time-course microarray experiments.
dc.title.alternative en_US
dc.type Journal Article
dc.description.version Version of Record en_US
duke.date.pubdate 2010-7-22 en_US
duke.description.endpage 391 en_US
duke.description.issue en_US
duke.description.startpage 391 en_US
duke.description.volume 11 en_US
dc.relation.journal Bmc Bioinformatics en_US
pubs.author-url http://www.ncbi.nlm.nih.gov/pubmed/20649954
pubs.organisational-group /Duke
pubs.organisational-group /Duke/School of Medicine
pubs.organisational-group /Duke/School of Medicine/Basic Science Departments
pubs.organisational-group /Duke/School of Medicine/Basic Science Departments/Biostatistics & Bioinformatics
pubs.organisational-group /Duke/School of Medicine/Institutes and Centers
pubs.organisational-group /Duke/School of Medicine/Institutes and Centers/Duke Cancer Institute
pubs.publication-status Published online
pubs.volume 11
dc.identifier.eissn 1471-2105

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