SH Guan, L Bonnett and J Brettschneider
Using gene subsets in the assessment of microarray data quality for time course experiments
Abstract: The application of established microarray data quality measures to time course experiments potentially gives misleading information. In particular, genuine biological variation my be misinterpreted as technical artifact. We suggest tailoring standard methods to time course data by restricting the assessment to subsets of genes selected on the basis of the experiment. The method is tested on two different kinds of experimental data sets, one from a developmental process and one from a circadian process. It shows that, with these modifications, quality assessment for microarray data can be tuned to appropriately address the special situation of time course experiments.
Keywords: quality control, microarrays, time course data, Affymetrix chips, relative log expression, normalized unscaled standard errors.