Exon array data were evaluated using a series of quality control steps defined by Affymetrix for uniform hybridization intensity, abnormal background signals, and sample outliers. The data were normalized across all samples for a tissue type on an exon and transcript level (four separate normalizations) per Affymetrix PLIER protocol with a sketch-quantile normalization procedure (Affymetrix Expression Console). This algorithm also removed undetectable signals for the dataset using a screen for signals below a group of antigenomic probesets. Principal component analysis (PCA) was performed to look secondarily to identify sample outliers using Partek Genomics Suite. Individual sample positions on top principal component (PC) axes were exported and the effects postmortem interval (applicable only to brain tissue analyses), age, gender, and sample source/processing day were tested for significance using STATA/IC 10.0. All of the four covariates were deemed to impact the sources of variability on both an exon and transcript level, and were therefore included in subsequent genetic association analyses as covariates in linear regression models. A combined normalization on both brain tissue samples and PBMCs also was performed on both the
