The large scale of this study made cost prohibitive the inclusion of biological replicates for each RI strain across treatment groups. Therefore, assessing the reproducibility of changes in gene expression within a single strain by conventional methods, such as SAM [26], was not possible. We therefore used an alternative approach to identify probe-sets with extreme ethanol expression changes across a minority of strains or smaller but consistent changes across a larger portion of the BXD family. The impact of acute ethanol on transcript abundance was measured using the Significance-score (S-score) algorithm [27], which utilizes individual probe-level data to determine the statistical significance of transcript level differences between a pair of Affymetrix microarrays. We utilized the R implementation of the S-score algorithm [28] to compare microarray expression levels within BXD strains across treatment groups to generate a saline vs ethanol S-score for each probe-set, where a positive S-score indicates up-regulation with ethanol and vice-versa. In the case of the progenitor strains, where biological replicate microarrays were available for each strain in triplicate, S-scores were generated using the SScore function's class label feature.
