Robust test method for time-course microarray experiments.

BMC Bioinformatics
Insuk SohnSin-Ho Jung

Abstract

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. 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. 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.

References

Mar 7, 2003·Development·John Wang, Stuart K Kim
Nov 25, 2004·PLoS Biology·Graham E J RodwellStuart K Kim
Dec 25, 2004·Biostatistics·Sin-Ho JungStanley Young
Sep 6, 2005·Proceedings of the National Academy of Sciences of the United States of America·John D StoreyRonald W Davis
Oct 4, 2007·Statistical Applications in Genetics and Molecular Biology·Claudia AngeliniMarianna Pensky

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Citations

Mar 14, 2014·Biostatistics·Ana Arribas-Gil, Juan Romo

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Software Mentioned

quantreg
BOOT
PERM
R

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