The results are similar for datasets that differ greatly. The IFN data, presented in the most detail, was from an experiment that examined the effects of interferon treatment on human PBMC in vitro [16], and used the HGU133A GeneChip®. The vitamin A data compared RNA extracted from liver tissue from Sprague-Dawley rats fed vitamin A deficient or sufficient diets [15,21], and used the relatively old RGU34A GeneChip®, designed with much less sequence data and informatics. The smoking data are from a large study examining differences in bronchial epithelia extracted from human subjects [22], and also used HGU133A GeneChip®; the variability within each group in the smoking dataset is much greater than in the others. The Pearson correlation between samples from subjects within each of the two groups in the smoking data were 0.87 and 0.89, compared to an average Pearson correlation >0.97 for samples within each group for the IFN data. In all three cases, representing different generations of GeneChip®, different species, different laboratories and different amounts of intra-group variability, our approach achieved the primary goal of improving FDR while minimizing the removal of very significant probe sets (p ≤ 0.001) and retaining those probe sets turned on or off.
