Computational method for reducing variance with Affymetrix microarrays

摘要

BackgroundAffymetrix microarrays are used by many laboratories to generate gene expression profiles. Generally, only large differences (> 1.7-fold) between conditions have been reported. Computational methods to reduce inter-array variability might be of value when attempting to detect smaller differences. We examined whether inter-array variability could be reduced by using data based on the Affymetrix algorithm for pairwise comparisons between arrays (ratio method) rather than data based on the algorithm for analysis of individual arrays (signal method). Six HG-U95A arrays that probed mRNA from young (21–31 yr old) human muscle were compared with six arrays that probed mRNA from older (62–77 yr old) muscle.