Journal article
Analysis of factorial time-course microarrays with application to a clinical study of burn injury
Abstract
Time-course microarray experiments are capable of capturing dynamic gene expression profiles. It is important to study how these dynamic profiles depend on the multiple factors that characterize the experimental condition under which the time course is observed. Analytic methods are needed to simultaneously handle the time course and factorial structure in the data. We developed a method to evaluate factor effects by pooling information across …
Authors
Zhou B; Xu W; Herndon D; Tompkins R; Davis R; Xiao W; Wong H; Toner M; Warren HS; Schoenfeld DA
Journal
Proceedings of the National Academy of Sciences of the United States of America, Vol. 107, No. 22, pp. 9923–9928
Publisher
Proceedings of the National Academy of Sciences
Publication Date
June 2010
DOI
10.1073/pnas.1002757107
ISSN
0027-8424
Associated Experts
Fields of Research (FoR)
Medical Subject Headings (MeSH)
AdultAge FactorsAnalysis of VarianceBurnsChildChild, PreschoolCross-Sectional StudiesData Interpretation, StatisticalDatabases, GeneticFemaleGene Expression ProfilingGenes, ImmunoglobulinGenes, MitochondrialHumansInfantLongitudinal StudiesMaleMiddle AgedModels, StatisticalOligonucleotide Array Sequence AnalysisPrognosisSoftwareTime Factors