Causal probabilistic Bayesian networks were constructed and used as an alternative approach to delineate potential regulatory mechanisms. In order to establish a causal relationship or dependency between nodes in the network, we constructed a directed probabilistic Bayesian network through the application of brain cis expression (e)SNPs as causal anchors. Because cis eSNPs are in LD with causal variants that affect the expression levels of a neighboring gene or they are the causal variant themselves, they serve as an excellent source of natural perturbation to infer causal relationships among genes and between genes and higher order phenotypes like disease (Chen et al., 2008; Emilsson et al., 2008). We detected a total of 11,318 unique cis eSNPs-transcripts in the three brain regions, at FDR of 10% (Figure S2A), which is the largest number of brain eSNP-transcripts detected to date in a single study (Webster et al., 2009). The methodology to identify cis and trans eSNPs is detailed in Extended Experimental Procedures, while Table S1 lists all cis and trans acting eSNPs detected in the present study at FDR of 10%. There was
