In vitro medication signatures were matched with addiction-rf signatures from the transcriptome-wide association analyses (conducted using S-MultiXcan)25,62 via multi-level meta-regression. We computed weighted (by its proportion of heritability explained (h2MULTI-XCAN)) Pearson correlations between transcriptome-wide brain associations and in vitro L1000 compound signatures using the metafor package in R65. We treated each L1000 compound as a fixed effect incorporating the effect size (rweighted) and sampling variability (se2r_weighted) from all signatures of a compound (e.g., across all time points, cell lines, doses). Analyses included brain region as a random effect to estimate tissue specific heterogeneity. Only genes that were Bonferroni significant in the S-PrediXcan(transcriptome-wide correction = .05/14,389 = 3.48e-06) were entered into the model. We only report those perturbagens that were associated after Bonferroni correction (perturbagen correction = .05/3,897 = 1.28e-05).
