Microarray data were analyzed using R and Microsoft Excel. Each tissue was analyzed separately. Quality assessment of the data using Bioconductor array QualityMetrics package 21 resulted in the removal of 7 outliers: amygdala 16 (feno-treated) and 31 (beza-treated); PFC 6 (tesa-treated) and 36 (feno-treated); and liver 11 (beza-treated), 27 (tesa-treated) and 36 (feno-treated). Liver 11 and 36, amygdala 16 and 31, and PFC 6 and 36 were on a faulty beadchip. Variance stabilization transformation and quantile normalization were used to pre-process the data using the Bioconductor Lumi package 14. Groups being compared were normalized together, i.e., saline and beza, saline and tesa, and saline and feno. Lastly, outlier values for each gene within a group were removed using Grubbs’ test (p<0.05). After data processing, the total number of unique genes reliably expressed (i.e., detection p < 0.05 and detected on at least 80% of the samples) in each tissue region for each treatment is provided (Table 1).
